[A research on real-time ventricular QRS classification methods for single-chip-microcomputers].

PubMed

Peng, L; Yang, Z; Li, L; Chen, H; Chen, E; Lin, J

1997-05-01

Ventricular QRS classification is key technique of ventricular arrhythmias detection in single-chip-microcomputer based dynamic electrocardiogram real-time analyser. This paper adopts morphological feature vector including QRS amplitude, interval information to reveal QRS morphology. After studying the distribution of QRS morphology feature vector of MIT/BIH DB ventricular arrhythmia files, we use morphological feature vector cluster to classify multi-morphology QRS. Based on the method, morphological feature parameters changing method which is suitable to catch occasional ventricular arrhythmias is presented. Clinical experiments verify missed ventricular arrhythmia is less than 1% by this method.

Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions

DOE PAGES

Vesselinova, Neda; Alexandrov, Boian; Wall, Michael E.

2016-11-08

We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation: initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time coursesmore » in three different bacterial species: Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability.« less

Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions

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

Vesselinova, Neda; Alexandrov, Boian; Wall, Michael E.

We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation: initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time coursesmore » in three different bacterial species: Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability.« less

Automating the generation of finite element dynamical cores with Firedrake

NASA Astrophysics Data System (ADS)

Ham, David; Mitchell, Lawrence; Homolya, Miklós; Luporini, Fabio; Gibson, Thomas; Kelly, Paul; Cotter, Colin; Lange, Michael; Kramer, Stephan; Shipton, Jemma; Yamazaki, Hiroe; Paganini, Alberto; Kärnä, Tuomas

2017-04-01

The development of a dynamical core is an increasingly complex software engineering undertaking. As the equations become more complete, the discretisations more sophisticated and the hardware acquires ever more fine-grained parallelism and deeper memory hierarchies, the problem of building, testing and modifying dynamical cores becomes increasingly complex. Here we present Firedrake, a code generation system for the finite element method with specialist features designed to support the creation of geoscientific models. Using Firedrake, the dynamical core developer writes the partial differential equations in weak form in a high level mathematical notation. Appropriate function spaces are chosen and time stepping loops written at the same high level. When the programme is run, Firedrake generates high performance C code for the resulting numerics which are executed in parallel. Models in Firedrake typically take a tiny fraction of the lines of code required by traditional hand-coding techniques. They support more sophisticated numerics than are easily achieved by hand, and the resulting code is frequently higher performance. Critically, debugging, modifying and extending a model written in Firedrake is vastly easier than by traditional methods due to the small, highly mathematical code base. Firedrake supports a wide range of key features for dynamical core creation: A vast range of discretisations, including both continuous and discontinuous spaces and mimetic (C-grid-like) elements which optimally represent force balances in geophysical flows. High aspect ratio layered meshes suitable for ocean and atmosphere domains. Curved elements for high accuracy representations of the sphere. Support for non-finite element operators, such as parametrisations. Access to PETSc, a world-leading library of programmable linear and nonlinear solvers. High performance adjoint models generated automatically by symbolically reasoning about the forward model. This poster will present the key features of the Firedrake system, as well as those of Gusto, an atmospheric dynamical core, and Thetis, a coastal ocean model, both of which are written in Firedrake.

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles.

PubMed

Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F; Perez, Danny

2017-10-21

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles

NASA Astrophysics Data System (ADS)

Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F.; Perez, Danny

2017-10-01

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Overview of the solar dynamic ground test demonstration program

NASA Technical Reports Server (NTRS)

Shaltens, Richard K.; Boyle, Robert V.

1993-01-01

The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the availability of SD technologies in a simulated space environment at the NASA Lewis Research Center (LeRC) vacuum facility. An aerospace industry/ government team is working together to design, fabricate, build, and test a complete SD system. This paper reviews the goals and status of the SD GTD program. A description of the SD system includes key design features of the system, subsystems, and components as reported at the Critical Design Review (CDR).

Simulations of Long-Term Community Dynamics in Coral Reefs - How Perturbations Shape Trajectories

PubMed Central

Kubicek, Andreas; Muhando, Christopher; Reuter, Hauke

2012-01-01

Tropical coral reefs feature extraordinary biodiversity and high productivity rates in oligotrophic waters. Due to increasing frequencies of perturbations – anthropogenic and natural – many reefs are under threat. Such perturbations often have devastating effects on these unique ecosystems and especially if they occur simultaneously and amplify each other's impact, they might trigger a phase shift and create irreversible conditions. We developed a generic, spatially explicit, individual-based model in which competition drives the dynamics of a virtual benthic reef community – comprised of scleractinian corals and algae – under different environmental settings. Higher system properties, like population dynamics or community composition arise through self-organization as emergent properties. The model was parameterized for a typical coral reef site at Zanzibar, Tanzania and features coral bleaching and physical disturbance regimes as major sources of perturbations. Our results show that various types and modes (intensities and frequencies) of perturbations create diverse outcomes and that the switch from high diversity to single species dominance can be evoked by small changes in a key parameter. Here we extend the understanding of coral reef resilience and the identification of key processes, drivers and respective thresholds, responsible for changes in local situations. One future goal is to provide a tool which may aid decision making processes in management of coral reefs. PMID:23209397

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling

NASA Astrophysics Data System (ADS)

Leandro, J.; Schumann, A.; Pfister, A.

2016-04-01

Some of the major challenges in modelling rainfall-runoff in urbanised areas are the complex interaction between the sewer system and the overland surface, and the spatial heterogeneity of the urban key features. The former requires the sewer network and the system of surface flow paths to be solved simultaneously. The latter is still an unresolved issue because the heterogeneity of runoff formation requires high detailed information and includes a large variety of feature specific rainfall-runoff dynamics. This paper discloses a methodology for considering the variability of building types and the spatial heterogeneity of land surfaces. The former is achieved by developing a specific conceptual rainfall-runoff model and the latter by defining a fully distributed approach for infiltration processes in urban areas with limited storage capacity dependent on OpenStreetMaps (OSM). The model complexity is increased stepwise by adding components to an existing 2D overland flow model. The different steps are defined as modelling levels. The methodology is applied in a German case study. Results highlight that: (a) spatial heterogeneity of urban features has a medium to high impact on the estimated overland flood-depths, (b) the addition of multiple urban features have a higher cumulative effect due to the dynamic effects simulated by the model, (c) connecting the runoff from buildings to the sewer contributes to the non-linear effects observed on the overland flood-depths, and (d) OSM data is useful in identifying pounding areas (for which infiltration plays a decisive role) and permeable natural surface flow paths (which delay the flood propagation).

Patterns In Contingencies: The Interlocking of Formal and Informal Political Institutions in Contemporary Argentina

ERIC Educational Resources Information Center

Llamazares, Ivan

2005-01-01

This article explores how the interlocking of formal and informal political institutions has affected the dynamics and performance of the Argentine democracy. Key institutional features of the Argentine political system have been a competitive form of federalism, loosely structured and political parties that are not ideologically unified,…

Space Station: Key to the Future.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Washington, DC.

The possible applications, advantages and features of an advanced space station to be developed are considered in a non-technical manner in this booklet. Some of the areas of application considered include the following: the detection of large scale dynamic earth processes such as changes in snow pack, crops, and air pollution levels; the…

Acceleration-Augmented LQG Control of an Active Magnetic Bearing

NASA Technical Reports Server (NTRS)

Feeley, Joseph J.

1993-01-01

A linear-quadratic-gaussian (LQG) regulator controller design for an acceleration-augmented active magnetic bearing (AMB) is outlined. Acceleration augmentation is a key feature in providing improved dynamic performance of the controller. The optimal control formulation provides a convenient method of trading-off fast transient response and force attenuation as control objectives.

The relationship between two fast/slow analysis techniques for bursting oscillations

PubMed Central

Teka, Wondimu; Tabak, Joël; Bertram, Richard

2012-01-01

Bursting oscillations in excitable systems reflect multi-timescale dynamics. These oscillations have often been studied in mathematical models by splitting the equations into fast and slow subsystems. Typically, one treats the slow variables as parameters of the fast subsystem and studies the bifurcation structure of this subsystem. This has key features such as a z-curve (stationary branch) and a Hopf bifurcation that gives rise to a branch of periodic spiking solutions. In models of bursting in pituitary cells, we have recently used a different approach that focuses on the dynamics of the slow subsystem. Characteristic features of this approach are folded node singularities and a critical manifold. In this article, we investigate the relationships between the key structures of the two analysis techniques. We find that the z-curve and Hopf bifurcation of the two-fast/one-slow decomposition are closely related to the voltage nullcline and folded node singularity of the one-fast/two-slow decomposition, respectively. They become identical in the double singular limit in which voltage is infinitely fast and calcium is infinitely slow. PMID:23278052

Chaotic Dynamics of Linguistic-Like Processes at the Syntactical and Semantic Levels: in the Pursuit of a Multifractal Attractor

NASA Astrophysics Data System (ADS)

Nicolis, John S.; Katsikas, Anastassis A.

Collective parameters such as the Zipf's law-like statistics, the Transinformation, the Block Entropy and the Markovian character are compared for natural, genetic, musical and artificially generated long texts from generating partitions (alphabets) on homogeneous as well as on multifractal chaotic maps. It appears that minimal requirements for a language at the syntactical level such as memory, selectivity of few keywords and broken symmetry in one dimension (polarity) are more or less met by dynamically iterating simple maps or flows e.g. very simple chaotic hardware. The same selectivity is observed at the semantic level where the aim refers to partitioning a set of enviromental impinging stimuli onto coexisting attractors-categories. Under the regime of pattern recognition and classification, few key features of a pattern or few categories claim the lion's share of the information stored in this pattern and practically, only these key features are persistently scanned by the cognitive processor. A multifractal attractor model can in principle explain this high selectivity, both at the syntactical and the semantic levels.

Effects of the dynamic modification of stationary phases by sorbates in gas chromatography: The possibility of separating enantiomers in achiral systems

NASA Astrophysics Data System (ADS)

Zenkevich, I. G.; Pavlovskii, A. A.

2016-10-01

It is shown that the gas chromatographic separation of enantiomers on columns with achiral nonpolar stationary phases is principally possible as a result of the dynamic modification of stationary phases by sorbates under analysis. It is found that a number of key characteristic features is intrinsic to such separation: it can be only partial, it does not occur for all chromatographic columns, and it is observed only for some compounds and only within narrow ranges of quantities of sorbates that are close to the limits of mass overload of chromatographic systems. These characteristic features are illustrated by the examples of separating (1 R,5 R)-(+)- and (1 S,5 S)-(-)-α-pinenes on a WCOT column with an RTX-5 phase. The main characteristic feature of the separation of enantiomers as a result of the dynamic modification of stationary phases is the nonconformity of peaks in chromatograms with two individual enantiomers, compared to other ways and means for their separation; the first eluting peak belongs to the enantiomer that predominates in a mixture irrespective of its configuration, while the second peak corresponds to the racemic mixture of enantiomers; i.e., the ratio of peak areas in chromatograms does not correspond to the actual ratio of enantiomers in samples under analysis and is strongly distorted as a result of their incomplete separation. It is concluded that the separation of racemic mixtures in achiral systems is fundamentally impossible under any conditions, and this is one of the key criteria of the validity of the considered concept as a whole.

Structural and functional adaptations of the mammalian nuclear envelope to meet the meiotic requirements.

PubMed

Link, Jana; Jahn, Daniel; Alsheimer, Manfred

2015-01-01

Numerous studies in the past years provided definite evidence that the nuclear envelope is much more than just a simple barrier. It rather constitutes a multifunctional platform combining structural and dynamic features to fulfill many fundamental functions such as chromatin organization, regulation of transcription, signaling, but also structural duties like maintaining general nuclear architecture and shape. One additional and, without doubt, highly impressive aspect is the recently identified key function of selected nuclear envelope components in driving meiotic chromosome dynamics, which in turn is essential for accurate recombination and segregation of the homologous chromosomes. Here, we summarize the recent work identifying new key players in meiotic telomere attachment and movement and discuss the latest advances in our understanding of the actual function of the meiotic nuclear envelope.

Incorporation of National Universities in Korea: Dynamic Forces, Key Features, and Challenges

ERIC Educational Resources Information Center

Rhee, Byung-Shik

2007-01-01

Education reform has become more popular than ever, and the incorporation of public institutions of higher education is one such reform. Eventually, Korea will see its national universities being incorporated. The legislature passed a law on March 7, 2007 that requires a new national university to be established as a National University…

Adaptive Role Playing Games: An Immersive Approach for Problem Based Learning

ERIC Educational Resources Information Center

Sancho, Pilar; Moreno-Ger, Pablo; Fuentes-Fernandez, Ruben; Fernandez-Manjon, Baltasar

2009-01-01

In this paper we present a general framework, called NUCLEO, for the application of socio-constructive educational approaches in higher education. The underlying pedagogical approach relies on an adaptation model in order to improve group dynamics, as this has been identified as one of the key features in the success of collaborative learning…

Dynamic Key Management Schemes for Secure Group Access Control Using Hierarchical Clustering in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Tsaur, Woei-Jiunn; Pai, Haw-Tyng

2008-11-01

The applications of group computing and communication motivate the requirement to provide group access control in mobile ad hoc networks (MANETs). The operation in MANETs' groups performs a decentralized manner and accommodated membership dynamically. Moreover, due to lack of centralized control, MANETs' groups are inherently insecure and vulnerable to attacks from both within and outside the groups. Such features make access control more challenging in MANETs. Recently, several researchers have proposed group access control mechanisms in MANETs based on a variety of threshold signatures. However, these mechanisms cannot actually satisfy MANETs' dynamic environments. This is because the threshold-based mechanisms cannot be achieved when the number of members is not up to the threshold value. Hence, by combining the efficient elliptic curve cryptosystem, self-certified public key cryptosystem and secure filter technique, we construct dynamic key management schemes based on hierarchical clustering for securing group access control in MANETs. Specifically, the proposed schemes can constantly accomplish secure group access control only by renewing the secure filters of few cluster heads, when a cluster head joins or leaves a cross-cluster. In such a new way, we can find that the proposed group access control scheme can be very effective for securing practical applications in MANETs.

Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

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

Huang, Renke; Jin, Shuangshuang; Chen, Yousu

This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

Sediment features at the grounding zone and beneath Ekström Ice Shelf, East Antarctica, imaged using on-ice vibroseis.

NASA Astrophysics Data System (ADS)

Smith, Emma C.; Eisen, Olaf; Hofstede, Coen; Lambrecht, Astrid; Mayer, Christoph

2017-04-01

The grounding zone, where an ice sheet becomes a floating ice shelf, is known to be a key threshold region for ice flow and stability. A better understanding of ice dynamics and sediment transport across such zones will improve knowledge about contemporary and palaeo ice flow, as well as past ice extent. Here we present a set of seismic reflection profiles crossing the grounding zone and continuing to the shelf edge of Ekström Ice Shelf, East Antarctica. Using an on-ice vibroseis source combined with a snowstreamer we have imaged a range of sub-glacial and sub-shelf sedimentary and geomorphological features; from layered sediment deposits to elongated flow features. The acoustic properties of the features as well as their morphology allow us to draw conclusions as to their material properties and origin. These results will eventually be integrated with numerical models of ice dynamics to quantify past and present interactions between ice and the solid Earth in East Antarctica; leading to a better understanding of future contributions of this region to sea-level rise.

Sex-chromosome turnovers: the hot-potato model.

PubMed

Blaser, Olivier; Neuenschwander, Samuel; Perrin, Nicolas

2014-01-01

Sex-determining systems often undergo high rates of turnover but for reasons that remain largely obscure. Two recent evolutionary models assign key roles, respectively, to sex-antagonistic (SA) mutations occurring on autosomes and to deleterious mutations accumulating on sex chromosomes. These two models capture essential but distinct key features of sex-chromosome evolution; accordingly, they make different predictions and present distinct limitations. Here we show that a combination of features from the two models has the potential to generate endless cycles of sex-chromosome transitions: SA alleles accruing on a chromosome after it has been co-opted for sex induce an arrest of recombination; the ensuing accumulation of deleterious mutations will soon make a new transition ineluctable. The dynamics generated by these interactions share several important features with empirical data, namely, (i) that patterns of heterogamety tend to be conserved during transitions and (ii) that autosomes are not recruited randomly, with some chromosome pairs more likely than others to be co-opted for sex.

On the persistence and coherence of subpolar sea surface temperature and salinity anomalies associated with the Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Zhang, Rong

2017-08-01

This study identifies key features associated with the Atlantic multidecadal variability (AMV) in both observations and a fully coupled climate model, e.g., decadal persistence of monthly mean subpolar North Atlantic (NA) sea surface temperature (SST) and salinity (SSS) anomalies, and high coherence at low frequency among subpolar NA SST/SSS, upper ocean heat/salt content, and the Atlantic Meridional Overturning Circulation (AMOC) fingerprint. These key AMV features, which can be used to distinguish the AMV mechanism, cannot be explained by the slab ocean model results or the red noise process but are consistent with the ocean dynamics mechanism. This study also shows that at low frequency, the correlation and regression between net surface heat flux and SST anomalies are key indicators of the relative roles of oceanic versus atmospheric forcing in SST anomalies. The oceanic forcing plays a dominant role in the subpolar NA SST anomalies associated with the AMV.

Finite element modeling of truss structures with frequency-dependent material damping

NASA Technical Reports Server (NTRS)

Lesieutre, George A.

1991-01-01

A physically motivated modelling technique for structural dynamic analysis that accommodates frequency dependent material damping was developed. Key features of the technique are the introduction of augmenting thermodynamic fields (AFT) to interact with the usual mechanical displacement field, and the treatment of the resulting coupled governing equations using finite element analysis methods. The AFT method is fully compatible with current structural finite element analysis techniques. The method is demonstrated in the dynamic analysis of a 10-bay planar truss structure, a structure representative of those contemplated for use in future space systems.

Update of the 2 Kw Solar Dynamic Ground Test Demonstration Program

NASA Technical Reports Server (NTRS)

Shaltens, Richard K.; Boyle, Robert V.

1994-01-01

The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the operation of a complete 2 kW, SD system in a simulated space environment at a NASA Lewis Research Center (LeRC) thermal-vacuum facility. This paper reviews the goals and status of the SD GTD program. A brief description of the SD system identifying key design features of the system, subsystems, and components is included. An aerospace industry/government team is working together to design, fabricate, assemble, and test a complete SD system.

Evolutionary dynamics of language systems

PubMed Central

Wu, Chieh-Hsi; Hua, Xia; Dunn, Michael; Levinson, Stephen C.; Gray, Russell D.

2017-01-01

Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000–10,000 y, there are suggestions that grammatical structures might retain more signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact. PMID:29073028

Transport in Dynamical Astronomy and Multibody Problems

NASA Astrophysics Data System (ADS)

Dellnitz, Michael; Junge, Oliver; Koon, Wang Sang; Lekien, Francois; Lo, Martin W.; Marsden, Jerrold E.; Padberg, Kathrin; Preis, Robert; Ross, Shane D.; Thiere, Bianca

We combine the techniques of almost invariant sets (using tree structured box elimination and graph partitioning algorithms) with invariant manifold and lobe dynamics techniques. The result is a new computational technique for computing key dynamical features, including almost invariant sets, resonance regions as well as transport rates and bottlenecks between regions in dynamical systems. This methodology can be applied to a variety of multibody problems, including those in molecular modeling, chemical reaction rates and dynamical astronomy. In this paper we focus on problems in dynamical astronomy to illustrate the power of the combination of these different numerical tools and their applicability. In particular, we compute transport rates between two resonance regions for the three-body system consisting of the Sun, Jupiter and a third body (such as an asteroid). These resonance regions are appropriate for certain comets and asteroids.

Colloquium: Non-Markovian dynamics in open quantum systems

NASA Astrophysics Data System (ADS)

Breuer, Heinz-Peter; Laine, Elsi-Mari; Piilo, Jyrki; Vacchini, Bassano

2016-04-01

The dynamical behavior of open quantum systems plays a key role in many applications of quantum mechanics, examples ranging from fundamental problems, such as the environment-induced decay of quantum coherence and relaxation in many-body systems, to applications in condensed matter theory, quantum transport, quantum chemistry, and quantum information. In close analogy to a classical Markovian stochastic process, the interaction of an open quantum system with a noisy environment is often modeled phenomenologically by means of a dynamical semigroup with a corresponding time-independent generator in Lindblad form, which describes a memoryless dynamics of the open system typically leading to an irreversible loss of characteristic quantum features. However, in many applications open systems exhibit pronounced memory effects and a revival of genuine quantum properties such as quantum coherence, correlations, and entanglement. Here recent theoretical results on the rich non-Markovian quantum dynamics of open systems are discussed, paying particular attention to the rigorous mathematical definition, to the physical interpretation and classification, as well as to the quantification of quantum memory effects. The general theory is illustrated by a series of physical examples. The analysis reveals that memory effects of the open system dynamics reflect characteristic features of the environment which opens a new perspective for applications, namely, to exploit a small open system as a quantum probe signifying nontrivial features of the environment it is interacting with. This Colloquium further explores the various physical sources of non-Markovian quantum dynamics, such as structured environmental spectral densities, nonlocal correlations between environmental degrees of freedom, and correlations in the initial system-environment state, in addition to developing schemes for their local detection. Recent experiments addressing the detection, quantification, and control of non-Markovian quantum dynamics are also briefly discussed.

Age structure is critical to the population dynamics and survival of honeybee colonies.

PubMed

Betti, M I; Wahl, L M; Zamir, M

2016-11-01

Age structure is an important feature of the division of labour within honeybee colonies, but its effects on colony dynamics have rarely been explored. We present a model of a honeybee colony that incorporates this key feature, and use this model to explore the effects of both winter and disease on the fate of the colony. The model offers a novel explanation for the frequently observed phenomenon of 'spring dwindle', which emerges as a natural consequence of the age-structured dynamics. Furthermore, the results indicate that a model taking age structure into account markedly affects the predicted timing and severity of disease within a bee colony. The timing of the onset of disease with respect to the changing seasons may also have a substantial impact on the fate of a honeybee colony. Finally, simulations predict that an infection may persist in a honeybee colony over several years, with effects that compound over time. Thus, the ultimate collapse of the colony may be the result of events several years past.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2000-12-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2001-01-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Condition and deterioration rate of precommercial thinning slash at False Island, Alaska.

Treesearch

Michael H. McClellan; Paul E. Hennon; Patrick G. Heuer; Kenneth W. Coffin

2014-01-01

We examined slash from thinning treatments in a 21-year chronosequence of young-growth stands in southeast Alaska to determine the strength and persistence of slash effects on two key features of deer habitat quality: forage availability and deer mobility within thinned areas. We describe the main deterioration processes and their dynamics over time. We measured wood...

A Typology of Agency in New Generation Learning Environments: Emerging Relational, Ecological and New Material Considerations

ERIC Educational Resources Information Center

Charteris, Jennifer; Smardon, Dianne

2018-01-01

The impetus to move to a new generation learning environments places a spotlight on the relational dynamics of classroom spaces. A key feature is the notion of learner agency. A complex notion, learner agency involves both compliance with and resistance to classroom norms and therefore is far more sophisticated than acting in acquiescence to…

Dynamic Assessment and Response to Intervention

PubMed Central

Grigorenko, Elena L.

2013-01-01

This article compares and contrasts the main features of dynamic testing and assessment (DT/A) and response to intervention (RTI). The comparison is carried out along the following lines: (a) historical and empirical roots of both concepts, (b) premises underlying DT/A and RTI, (c) terms used in these concepts, (d) use of these concepts, (e) evidence in support of DT/A and RTI, and (f) expectations associated with each of the concepts. The main outcome of this comparison is a conclusion that both approaches belong to one family of methodologies in psychology and education whose key feature is in blending assessment and intervention in one holistic activity. Because DT/A has been around much longer than RTI, it makes sense for the proponents of RTI to consider both the accomplishments and frustrations that have accumulated in the field of DT/A. PMID:19073895

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Dynamic response of underpasses for high-speed train lines

NASA Astrophysics Data System (ADS)

Vega, J.; Fraile, A.; Alarcon, E.; Hermanns, L.

2012-11-01

Underpasses are common in modern railway lines. Wildlife corridors and drainage conduits often fall into this category of partially buried structures. Their dynamic behavior has received far less attention than that of other structures such as bridges, but their large number makes their study an interesting challenge from the viewpoint of safety and cost savings. Here, we present a complete study of a culvert, including on-site measurements and numerical modeling. The studied structure belongs to the high-speed railway line linking Segovia and Valladolid in Spain. The line was opened to traffic in 2004. On-site measurements were performed for the structure by recording the dynamic response at selected points of the structure during the passage of high-speed trains at speeds ranging between 200 and 300 km/h. The measurements provide not only reference values suitable for model fitting, but also a good insight into the main features of the dynamic behavior of this structure. Finite element techniques were used to model the dynamic behavior of the structure and its key features. Special attention is paid to vertical accelerations, the values of which should be limited to avoid track instability according to Eurocode. This study furthers our understanding of the dynamic response of railway underpasses to train loads.

Radiation characteristics and implosion dynamics of Z-pinch dynamic hohlraums performed on PTS facility

NASA Astrophysics Data System (ADS)

Huang, Xian Bin; Ren, Xiao Dong; Dan, Jia Kun; Wang, Kun Lun; Xu, Qiang; Zhou, Shao Tong; Zhang, Si Qun; Cai, Hong Chun; Li, Jing; Wei, Bing; Ji, Ce; Feng, Shu Ping; Wang, Meng; Xie, Wei Ping; Deng, Jian Jun

2017-09-01

The preliminary experimental results of Z-pinch dynamic hohlraums conducted on the Primary Test Stand (PTS) facility are presented herein. Six different types of dynamic hohlraums were used in order to study the influence of load parameters on radiation characteristics and implosion dynamics, including dynamic hohlraums driven by single and nested arrays with different array parameters and different foams. The PTS facility can deliver a current of 6-8 MA in the peak current and 60-70 ns in the 10%-90% rising time to dynamic hohlraum loads. A set of diagnostics monitor the implosion dynamics of plasmas, the evolution of shock waves in the foam and the axial/radial X-ray radiation, giving the key parameters characterizing the features of dynamic hohlraums, such as the trajectory and related velocity of shock waves, radiation temperature, and so on. The experimental results presented here put our future study on Z-pinch dynamic hohlraums on the PTS facility on a firm basis.

The capability of static and dynamic features to distinguish competent from genuinely expert practitioners in pediatric diagnosis.

PubMed

Loveday, Thomas; Wiggins, Mark W; Searle, Ben J; Festa, Marino; Schell, David

2013-02-01

The authors describe the development of a new, more objective method of distinguishing experienced competent nonexpert from expert practitioners within pediatric intensive care. Expert performance involves the acquisition and use of refined feature-event associations (cues) in the operational environment. Competent non-experts, although experienced, possess rudimentary cue associations in memory. Thus, they cannot respond as efficiently or as reliably as their expert counterparts, particularly when key diagnostic information is unavailable, such as that provided by dynamic cues. This study involved the application of four distinct tasks in which the use of relevant cues could be expected to increase both the accuracy and the efficiency of diagnostic performance. These tasks included both static and dynamic stimuli that were varied systematically. A total of 50 experienced pediatric intensive staff took part in the study. The sample clustered into two levels across the tasks: Participants who performed at a consistently high level throughout the four tasks were labeled experts, and participants who performed at a lower level throughout the tasks were labeled competent nonexperts. The groups differed in their responses to the diagnostic scenarios presented in two of the tasks and their ability to maintain performance in the absence of dynamic features. Experienced pediatricians can be decomposed into two groups on the basis of their capacity to acquire and use cues; these groups differ in their diagnostic accuracy and in their ability to maintain performance in the absence of dynamic features. The tasks may be used to identify practitioners who are failing to acquire expertise at a rate consistent with their experience, position, or training. This information may be used to guide targeted training efforts.

Emulating short-term synaptic dynamics with memristive devices

NASA Astrophysics Data System (ADS)

Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

2016-01-01

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism

PubMed Central

2017-01-01

Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J) and the modal matrix (M-1) arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions. PMID:29267329

Dynamic plasmonic colour display

NASA Astrophysics Data System (ADS)

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-02-01

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications.

Dynamic plasmonic colour display.

PubMed

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-02-24

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications.

Dynamic plasmonic colour display

PubMed Central

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-01-01

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications. PMID:28232722

Dynamics of atmospheres with a non-dilute condensible component

PubMed Central

Ding, Feng

2016-01-01

The diversity of characteristics for the host of recently discovered exoplanets opens up a great deal of fertile new territory for geophysical fluid dynamics, particularly when the fluid flow is coupled to novel thermodynamics, radiative transfer or chemistry. In this paper, we survey one of these new areas—the climate dynamics of atmospheres with a non-dilute condensible component, defined as the situation in which a condensible component of the atmosphere makes up a substantial fraction of the atmospheric mass within some layer. Non-dilute dynamics can occur for a wide range of condensibles, generically applying near both the inner and the outer edges of the conventional habitable zone and in connection with runaway greenhouse phenomena. It also applies in a wide variety of other planetary circumstances. We first present a number of analytical results developing some key features of non-dilute atmospheres, and then show how some of these features are manifest in simulations with a general circulation model adapted to handle non-dilute atmospheres. We find that non-dilute atmospheres have weak horizontal temperature gradients even for rapidly rotating planets, and that their circulations are largely barotropic. The relative humidity of the condensible component tends towards 100% as the atmosphere becomes more non-dilute, which has important implications for runaway greenhouse thresholds. Non-dilute atmospheres exhibit a number of interesting organized convection features, for which there is not yet any adequate theoretical understanding. PMID:27436980

Dynamics of atmospheres with a non-dilute condensible component.

PubMed

Pierrehumbert, Raymond T; Ding, Feng

2016-06-01

The diversity of characteristics for the host of recently discovered exoplanets opens up a great deal of fertile new territory for geophysical fluid dynamics, particularly when the fluid flow is coupled to novel thermodynamics, radiative transfer or chemistry. In this paper, we survey one of these new areas-the climate dynamics of atmospheres with a non-dilute condensible component, defined as the situation in which a condensible component of the atmosphere makes up a substantial fraction of the atmospheric mass within some layer. Non-dilute dynamics can occur for a wide range of condensibles, generically applying near both the inner and the outer edges of the conventional habitable zone and in connection with runaway greenhouse phenomena. It also applies in a wide variety of other planetary circumstances. We first present a number of analytical results developing some key features of non-dilute atmospheres, and then show how some of these features are manifest in simulations with a general circulation model adapted to handle non-dilute atmospheres. We find that non-dilute atmospheres have weak horizontal temperature gradients even for rapidly rotating planets, and that their circulations are largely barotropic. The relative humidity of the condensible component tends towards 100% as the atmosphere becomes more non-dilute, which has important implications for runaway greenhouse thresholds. Non-dilute atmospheres exhibit a number of interesting organized convection features, for which there is not yet any adequate theoretical understanding.

Neo-classical theory of competition or Adam Smith's hand as mathematized ideology

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2001-10-01

Orthodox economic theory (utility maximization, rational agents, efficient markets in equilibrium) is based on arbitrarily postulated, nonempiric notions. The disagreement between economic reality and a key feature of neo-classical economic theory was criticized empirically by Osborne. I show that the orthodox theory is internally self-inconsistent for the very reason suggested by Osborne: lack of invertibility of demand and supply as functions of price to obtain price as functions of supply and demand. The reason for the noninvertibililty arises from nonintegrable excess demand dynamics, a feature of their theory completely ignored by economists.

Spatiotemporal chaos of fractional order logistic equation in nonlinear coupled lattices

NASA Astrophysics Data System (ADS)

Zhang, Ying-Qian; Wang, Xing-Yuan; Liu, Li-Yan; He, Yi; Liu, Jia

2017-11-01

We investigate a new spatiotemporal dynamics with fractional order differential logistic map and spatial nonlinear coupling. The spatial nonlinear coupling features such as the higher percentage of lattices in chaotic behaviors for most of parameters and none periodic windows in bifurcation diagrams are held, which are more suitable for encryptions than the former adjacent coupled map lattices. Besides, the proposed model has new features such as the wider parameter range and wider range of state amplitude for ergodicity, which contributes a wider range of key space when applied in encryptions. The simulations and theoretical analyses are developed in this paper.

Defining the conserved internal architecture of a protein kinase.

PubMed

Kornev, Alexandr P; Taylor, Susan S

2010-03-01

Protein kinases constitute a large protein family of important regulators in all eukaryotic cells. All of the protein kinases have a similar bilobal fold, and their key structural features have been well studied. However, the recent discovery of non-contiguous hydrophobic ensembles inside the protein kinase core shed new light on the internal organization of these molecules. Two hydrophobic "spines" traverse both lobes of the protein kinase molecule, providing a firm but flexible connection between its key elements. The spine model introduces a useful framework for analysis of intramolecular communications, molecular dynamics, and drug design. Published by Elsevier B.V.

A Shellcode Detection Method Based on Full Native API Sequence and Support Vector Machine

NASA Astrophysics Data System (ADS)

Cheng, Yixuan; Fan, Wenqing; Huang, Wei; An, Jing

2017-09-01

Dynamic monitoring the behavior of a program is widely used to discriminate between benign program and malware. It is usually based on the dynamic characteristics of a program, such as API call sequence or API call frequency to judge. The key innovation of this paper is to consider the full Native API sequence and use the support vector machine to detect the shellcode. We also use the Markov chain to extract and digitize Native API sequence features. Our experimental results show that the method proposed in this paper has high accuracy and low detection rate.

Dynamical injections as the source of near geostationary quiet time particle spatial boundaries

NASA Technical Reports Server (NTRS)

Mauk, B. H.; Meng, C. I.

1983-01-01

The question whether the noon-dusk feature is a manifestation of the spatial structures that should arise from quasi-stationary convection is examined. The key consideration here is whether the energy dispersion of the feature can be explained. It is shown that the observed energy dispersion cannot be attributed to the standard stationary convection configurations, either perturbed or unperturbed. It is also demonstrated, using a detailed computer simulation, that the nighttime, double-spiral-shaped injection boundary (used previously to reproduce the fast changing nighttime features) is successful at reproducing the noon-dusk feature by allowing the particles to evolve for periods of 12 to 36 hours after the injection. It is stressed that the portion of the injection boundary responsible for the feature looks very different from the standard convection boundaries configuration. Conclusions are offered concerning the importance of quasi-stationary convection as the mechanism by which the near geostationary regions are populated.

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

PubMed

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-18

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters' influence on performance to provide insights about their optimisation.

Manipulators with flexible links: A simple model and experiments

NASA Technical Reports Server (NTRS)

Shimoyama, Isao; Oppenheim, Irving J.

1989-01-01

A simple dynamic model proposed for flexible links is briefly reviewed and experimental control results are presented for different flexible systems. A simple dynamic model is useful for rapid prototyping of manipulators and their control systems, for possible application to manipulator design decisions, and for real time computation as might be applied in model based or feedforward control. Such a model is proposed, with the further advantage that clear physical arguments and explanations can be associated with its simplifying features and with its resulting analytical properties. The model is mathematically equivalent to Rayleigh's method. Taking the example of planar bending, the approach originates in its choice of two amplitude variables, typically chosen as the link end rotations referenced to the chord (or the tangent) motion of the link. This particular choice is key in establishing the advantageous features of the model, and it was used to support the series of experiments reported.

Emergence of structural patterns out of synchronization in networks with competitive interactions

NASA Astrophysics Data System (ADS)

Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

2011-09-01

Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

Structural studies on choline-carboxylate bio-ionic liquids by x-ray scattering and molecular dynamics.

PubMed

Tanzi, Luana; Ramondo, Fabio; Caminiti, Ruggero; Campetella, Marco; Di Luca, Andrea; Gontrani, Lorenzo

2015-09-21

We report a X-ray diffraction and molecular dynamics study on three choline-based bio-ionic liquids, choline formate, [Ch] [For], choline propanoate, [Ch][Pro], and choline butanoate, [Ch][But]. For the first time, this class of ionic liquids has been investigated by X-ray diffraction. Experimental and theoretical structure factors have been compared for each term of the series. Local structural organization has been obtained from ab initio calculations through static models of isolated ion pairs and dynamic simulations of small portions of liquids through twelve, ten, and nine ion pairs for [Ch][For], [Ch][Pro], and [Ch][But], respectively. All the theoretical models indicate that cations and anions are connected by strong hydrogen bonding and form stable ion pairs in the liquid that are reminiscent of the static ab initio ion pairs. Different structural aspects may affect the radial distribution function, like the local structure of ion pairs and the conformation of choline. When small portions of liquids have been simulated by dynamic quantum chemical methods, some key structural features of the X-ray radial distribution function were well reproduced whereas the classical force fields here applied did not entirely reproduce all the observed structural features.

Structural studies on choline-carboxylate bio-ionic liquids by x-ray scattering and molecular dynamics

NASA Astrophysics Data System (ADS)

Tanzi, Luana; Ramondo, Fabio; Caminiti, Ruggero; Campetella, Marco; Di Luca, Andrea; Gontrani, Lorenzo

2015-09-01

We report a X-ray diffraction and molecular dynamics study on three choline-based bio-ionic liquids, choline formate, [Ch] [For], choline propanoate, [Ch][Pro], and choline butanoate, [Ch][But]. For the first time, this class of ionic liquids has been investigated by X-ray diffraction. Experimental and theoretical structure factors have been compared for each term of the series. Local structural organization has been obtained from ab initio calculations through static models of isolated ion pairs and dynamic simulations of small portions of liquids through twelve, ten, and nine ion pairs for [Ch][For], [Ch][Pro], and [Ch][But], respectively. All the theoretical models indicate that cations and anions are connected by strong hydrogen bonding and form stable ion pairs in the liquid that are reminiscent of the static ab initio ion pairs. Different structural aspects may affect the radial distribution function, like the local structure of ion pairs and the conformation of choline. When small portions of liquids have been simulated by dynamic quantum chemical methods, some key structural features of the X-ray radial distribution function were well reproduced whereas the classical force fields here applied did not entirely reproduce all the observed structural features.

Towards DMD-Based Estimation and Control of Flow Separation using an Array of Surface Pressure Sensors

NASA Astrophysics Data System (ADS)

Deem, Eric; Cattafesta, Louis; Zhang, Hao; Rowley, Clancy

2016-11-01

Closed-loop control of flow separation requires the spatio-temporal states of the flow to be fed back through the controller in real time. Previously, static and dynamic estimation methods have been employed that provide reduced-order model estimates of the POD-coefficients of the flow velocity using surface pressure measurements. However, this requires a "learning" dataset a priori. This approach is effective as long as the dynamics during control do not stray from the learning dataset. Since only a few dynamical features are required for feedback control of flow separation, many of the details provided by full-field snapshots are superfluous. This motivates a state-observation technique that extracts key dynamical features directly from surface pressure, without requiring PIV snapshots. The results of identifying DMD modes of separated flow through an array of surface pressure sensors in real-time are presented. This is accomplished by employing streaming DMD "on the fly" to surface pressure snapshots. These modal characteristics exhibit striking similarities to those extracted from PIV data and the pressure field obtained via solving Poisson's equation. Progress towards closed-loop separation control based on the dynamic modes of surface pressure will be discussed. Supported by AFOSR Grant FA9550-14-1-0289.

A complex systems analysis of stick-slip dynamics of a laboratory fault

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

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Endocannabinoid signaling and memory dynamics: A synaptic perspective.

PubMed

Drumond, Ana; Madeira, Natália; Fonseca, Rosalina

2017-02-01

Memory acquisition is a key brain feature in which our human nature relies on. Memories evolve over time. Initially after learning, memories are labile and sensitive to disruption by the interference of concurrent events. Later on, after consolidation, memories are resistant to disruption. However, reactivation of previously consolidated memories renders them again in an unstable state and therefore susceptible to perturbation. Additionally, and depending on the characteristics of the stimuli, a parallel process may be initiated which ultimately leads to the extinction of the previously acquired response. This dynamic aspect of memory maintenance opens the possibility for an updating of previously acquired memories but it also creates several conceptual challenges. What is the time window for memory updating? What determines whether reconsolidation or extinction is triggered? In this review, we tried to re-examine the relationship between consolidation, reconsolidation and extinction, aiming for a unifying view of memory dynamics. Since cellular models of memory share common principles, we present the evidence that similar rules apply to the maintenance of synaptic plasticity. Recently, a new function of the endocannabinoid (eCB) signaling system has been described for associative forms of synaptic plasticity in amygdala synapses. The eCB system has emerged as a key modulator of memory dynamics by adjusting the outcome to stimuli intensity. We propose a key function of eCB in discriminative forms of learning by restricting associative plasticity in amygdala synapses. Since many neuropsychiatric disorders are associated with a dysregulation in memory dynamics, understanding the rules underlying memory maintenance paves the path to better clinical interventions. Copyright © 2016 Elsevier Inc. All rights reserved.

Age structure is critical to the population dynamics and survival of honeybee colonies

PubMed Central

Betti, M. I.; Wahl, L. M.

2016-01-01

Age structure is an important feature of the division of labour within honeybee colonies, but its effects on colony dynamics have rarely been explored. We present a model of a honeybee colony that incorporates this key feature, and use this model to explore the effects of both winter and disease on the fate of the colony. The model offers a novel explanation for the frequently observed phenomenon of ‘spring dwindle’, which emerges as a natural consequence of the age-structured dynamics. Furthermore, the results indicate that a model taking age structure into account markedly affects the predicted timing and severity of disease within a bee colony. The timing of the onset of disease with respect to the changing seasons may also have a substantial impact on the fate of a honeybee colony. Finally, simulations predict that an infection may persist in a honeybee colony over several years, with effects that compound over time. Thus, the ultimate collapse of the colony may be the result of events several years past. PMID:28018627

Flow dynamics analyses of pathophysiological liver lobules using porous media theory

NASA Astrophysics Data System (ADS)

Hu, Jinrong; Lü, Shouqin; Feng, Shiliang; Long, Mian

2017-08-01

Blood flow inside the liver plays a key role in hepatic functions, and abnormal hemodynamics are highly correlated with liver diseases. To date, the flow field in an elementary building block of the organ, the liver lobule, is difficult to determine experimentally in humans due to its complicated structure, with radially branched microvasculature and the technical difficulties that derive from its geometric constraints. Here we established a set of 3D computational models for a liver lobule using porous media theory and analyzed its flow dynamics in normal, fibrotic, and cirrhotic lobules. Our simulations indicated that those approximations of ordinary flow in portal tracts (PTs) and the central vein, and of porous media flow in the sinusoidal network, were reasonable only for normal or fibrotic lobules. Models modified with high resistance in PTs and collateral vessels inside sinusoids were able to describe the flow features in cirrhotic lobules. Pressures, average velocities, and volume flow rates were profiled and the predictions compared well with experimental data. This study furthered our understanding of the flow dynamics features of liver lobules and the differences among normal, fibrotic, and cirrhotic lobules.

Continuum theory of gene expression waves during vertebrate segmentation.

PubMed

Jörg, David J; Morelli, Luis G; Soroldoni, Daniele; Oates, Andrew C; Jülicher, Frank

2015-09-01

The segmentation of the vertebrate body plan during embryonic development is a rhythmic and sequential process governed by genetic oscillations. These genetic oscillations give rise to traveling waves of gene expression in the segmenting tissue. Here we present a minimal continuum theory of vertebrate segmentation that captures the key principles governing the dynamic patterns of gene expression including the effects of shortening of the oscillating tissue. We show that our theory can quantitatively account for the key features of segmentation observed in zebrafish, in particular the shape of the wave patterns, the period of segmentation and the segment length as a function of time.

Continuum theory of gene expression waves during vertebrate segmentation

PubMed Central

Jörg, David J; Morelli, Luis G; Soroldoni, Daniele; Oates, Andrew C; Jülicher, Frank

2015-01-01

Abstract The segmentation of the vertebrate body plan during embryonic development is a rhythmic and sequential process governed by genetic oscillations. These genetic oscillations give rise to traveling waves of gene expression in the segmenting tissue. Here we present a minimal continuum theory of vertebrate segmentation that captures the key principles governing the dynamic patterns of gene expression including the effects of shortening of the oscillating tissue. We show that our theory can quantitatively account for the key features of segmentation observed in zebrafish, in particular the shape of the wave patterns, the period of segmentation and the segment length as a function of time. PMID:28725158

A Verification System for Distributed Objects with Asynchronous Method Calls

NASA Astrophysics Data System (ADS)

Ahrendt, Wolfgang; Dylla, Maximilian

We present a verification system for Creol, an object-oriented modeling language for concurrent distributed applications. The system is an instance of KeY, a framework for object-oriented software verification, which has so far been applied foremost to sequential Java. Building on KeY characteristic concepts, like dynamic logic, sequent calculus, explicit substitutions, and the taclet rule language, the system presented in this paper addresses functional correctness of Creol models featuring local cooperative thread parallelism and global communication via asynchronous method calls. The calculus heavily operates on communication histories which describe the interfaces of Creol units. Two example scenarios demonstrate the usage of the system.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

Overview of the Solar Dynamic Ground Test Demonstration Program at the NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Shaltens, Richard K.

1995-01-01

The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the availability of SD technologies in a simulated space environment at the NASA Lewis Research Center (LERC) vacuum facility. Data from the SD GTD program will be provided to the joint U.S. and Russian team which is currently designing a 2 kW SD flight demonstration power system. This SD technology has the potential as a future power source for the International Space Station. This paper reviews the goals and status of the SD GTD program. A description of the SD GTD system includes key design features of the system, subsystems and components.

Formations of Tethered Spacecraft as Stable Platforms for Far IR and Sub-mm Astronomy

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.; Hadaegh, Fred Y.; Shao, Michael; Lorenzini, Enrico C.

2004-01-01

In this paper we describe current research in tethered formations for interferometry, and a roadmap to demonstrating the required key technologies via on-ground and in-orbit testing. We propose an integrated kilometer-size tethered spacecraft formation flying concept which enables Far IR and Sub-mm astronomy observations from space. A rather general model is used to predict the dynamics, control, and estimation performance of formations of spacecraft connected by tethers in LEO and deep space. These models include the orbital and tethered formation dynamics, environmental models, and models of the formation estimator/controller/commander. Both centralized and decentralized control/sensing/estimation schemes are possible, and dynamic ranges of interest for sensing/control are described. Key component/subsystem technologies are described which need both ground-based and in-orbit demonstration prior to their utilization in precision space interferometry missions using tethered formations. Defining an orbiting formation as an ensemble of orbiting spacecraft performing a cooperative task, recent work has demonstrated the validity of the tethering the spacecraft to provide both the required formation rigidity and satisfy the formation reconfiguration needs such as interferometer baseline control. In our concept, several vehicles are connected and move along the tether, so that to reposition them the connecting tether links must vary in length. This feature enables variable and precise baseline control while the system spins around the boresight. The control architecture features an interferometer configuration composed of one central combiner spacecraft and two aligned collector spacecraft. The combiner spacecraft acts as the formation leader and is also where the centralized sensing and estimation functions reside. Some of the issues analyzed with the model are: dynamic modes of deformation of the distributed structure, architecture of the formation sensor, and sources of dynamical perturbation that need to be mitigated for precision operation in space. Examples from numerical simulation of an envisioned scenario in heliocentric orbit demonstrate the potential of the concept for space interferometry.

Task-dependent recurrent dynamics in visual cortex

PubMed Central

Tajima, Satohiro; Koida, Kowa; Tajima, Chihiro I; Suzuki, Hideyuki; Aihara, Kazuyuki; Komatsu, Hidehiko

2017-01-01

The capacity for flexible sensory-action association in animals has been related to context-dependent attractor dynamics outside the sensory cortices. Here, we report a line of evidence that flexibly modulated attractor dynamics during task switching are already present in the higher visual cortex in macaque monkeys. With a nonlinear decoding approach, we can extract the particular aspect of the neural population response that reflects the task-induced emergence of bistable attractor dynamics in a neural population, which could be obscured by standard unsupervised dimensionality reductions such as PCA. The dynamical modulation selectively increases the information relevant to task demands, indicating that such modulation is beneficial for perceptual decisions. A computational model that features nonlinear recurrent interaction among neurons with a task-dependent background input replicates the key properties observed in the experimental data. These results suggest that the context-dependent attractor dynamics involving the sensory cortex can underlie flexible perceptual abilities. DOI: http://dx.doi.org/10.7554/eLife.26868.001 PMID:28737487

Seasonally forced disease dynamics explored as switching between attractors

NASA Astrophysics Data System (ADS)

Keeling, Matt J.; Rohani, Pejman; Grenfell, Bryan T.

2001-01-01

Biological phenomena offer a rich diversity of problems that can be understood using mathematical techniques. Three key features common to many biological systems are temporal forcing, stochasticity and nonlinearity. Here, using simple disease models compared to data, we examine how these three factors interact to produce a range of complicated dynamics. The study of disease dynamics has been amongst the most theoretically developed areas of mathematical biology; simple models have been highly successful in explaining the dynamics of a wide variety of diseases. Models of childhood diseases incorporate seasonal variation in contact rates due to the increased mixing during school terms compared to school holidays. This ‘binary’ nature of the seasonal forcing results in dynamics that can be explained as switching between two nonlinear spiral sinks. Finally, we consider the stability of the attractors to understand the interaction between the deterministic dynamics and demographic and environmental stochasticity. Throughout attention is focused on the behaviour of measles, whooping cough and rubella.

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

A multi-machine scaling of halo current rotation

NASA Astrophysics Data System (ADS)

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; Gerhardt, S. P.; Granetz, R. S.; Hender, T. C.; Pautasso, G.; Contributors, JET

2018-01-01

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: (1) the machine-specific minimum current quench time, \

A multi-machine scaling of halo current rotation

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

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

A multi-machine scaling of halo current rotation

DOE PAGES

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; ...

2017-12-12

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

PubMed Central

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612

Validating early stellar encounters as the cause of dynamically hot planetary systems

NASA Astrophysics Data System (ADS)

Kalas, Paul

2017-08-01

One of the key questions concerning exoplanetary systems is why some are dynamically cold, such as TRAPPIST-1, whereas others are dynamically hot, with highly eccentric planets and/or perturbed debris disks. Dynamical theory describes a variety of plausible mechanisms, but few can be empirically tested since the critical dynamical evolution that sets the final planetary architecture is short-lived. One rare system available for testing dynamical upheaval scenarios is the 400 Myr-old Fomalhaut system. In Cycle 22 we coronagraphically studied Fomalhaut C, which is a wide M-dwarf companion to Fomalhaut A, in order to test our prediction that the unresolved, Herschel-detected debris disk around Fomalhaut C may be highly perturbed because of a recent close interaction with Fomalhaut A. Using HST/STIS we discovered a highly asymmetric feature extending northward of Fomalhaut C by 3 that resembles our model of a dynamically hot disk. However, it may be a background galaxy and the definitive test of its physical relationship to Fomalhaut C is to demonstrate common proper motion. Using Keck adaptive optics follow-up observations in J band, we did not detect the feature, and hence follow-up HST observations are the only way to test for common proper motion. Here we request a very small program to revisit Fomalhaut C with STIS in order to validate the initial discovery as a debris disk (1 proper motion between HST epochs). The astrophysical significance is demonstrating that the Fomalhaut system is a valuable case for studying dynamical upheavals via stellar encounters that are inferred to occur in the evolution of many other planetary systems.

Hydration status and diurnal trophic interactions shape microbial community function in desert biocrusts

NASA Astrophysics Data System (ADS)

Kim, Minsu; Or, Dani

2017-12-01

Biological soil crusts (biocrusts) are self-organised thin assemblies of microbes, lichens, and mosses that are ubiquitous in arid regions and serve as important ecological and biogeochemical hotspots. Biocrust ecological function is intricately shaped by strong gradients of water, light, oxygen, and dynamics in the abundance and spatial organisation of the microbial community within a few millimetres of the soil surface. We report a mechanistic model that links the biophysical and chemical processes that shape the functioning of biocrust representative microbial communities that interact trophically and respond dynamically to cycles of hydration, light, and temperature. The model captures key features of carbon and nitrogen cycling within biocrusts, such as microbial activity and distribution (during early stages of biocrust establishment) under diurnal cycles and the associated dynamics of biogeochemical fluxes at different hydration conditions. The study offers new insights into the highly dynamic and localised processes performed by microbial communities within thin desert biocrusts.

Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management

NASA Astrophysics Data System (ADS)

Müller, Felix; Burkhard, Benjamin; Kroll, Franziska

In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the "adaptive cycle". Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.

Scalable Molecular Dynamics with NAMD

PubMed Central

Phillips, James C.; Braun, Rosemary; Wang, Wei; Gumbart, James; Tajkhorshid, Emad; Villa, Elizabeth; Chipot, Christophe; Skeel, Robert D.; Kalé, Laxmikant; Schulten, Klaus

2008-01-01

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This paper, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Next, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, e.g., the Tcl scripting language. Finally, the paper provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. PMID:16222654

Structural studies on choline-carboxylate bio-ionic liquids by x-ray scattering and molecular dynamics

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

Tanzi, Luana; Ramondo, Fabio, E-mail: fabio.ramondo@univaq.it; Caminiti, Ruggero

2015-09-21

We report a X-ray diffraction and molecular dynamics study on three choline-based bio-ionic liquids, choline formate, [Ch] [For], choline propanoate, [Ch][Pro], and choline butanoate, [Ch][But]. For the first time, this class of ionic liquids has been investigated by X-ray diffraction. Experimental and theoretical structure factors have been compared for each term of the series. Local structural organization has been obtained from ab initio calculations through static models of isolated ion pairs and dynamic simulations of small portions of liquids through twelve, ten, and nine ion pairs for [Ch][For], [Ch][Pro], and [Ch][But], respectively. All the theoretical models indicate that cations andmore » anions are connected by strong hydrogen bonding and form stable ion pairs in the liquid that are reminiscent of the static ab initio ion pairs. Different structural aspects may affect the radial distribution function, like the local structure of ion pairs and the conformation of choline. When small portions of liquids have been simulated by dynamic quantum chemical methods, some key structural features of the X-ray radial distribution function were well reproduced whereas the classical force fields here applied did not entirely reproduce all the observed structural features.« less

The change in critical technologies for computational physics

NASA Technical Reports Server (NTRS)

Watson, Val

1990-01-01

It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.

IMAT graphics manual

NASA Technical Reports Server (NTRS)

Stockwell, Alan E.; Cooper, Paul A.

1991-01-01

The Integrated Multidisciplinary Analysis Tool (IMAT) consists of a menu driven executive system coupled with a relational database which links commercial structures, structural dynamics and control codes. The IMAT graphics system, a key element of the software, provides a common interface for storing, retrieving, and displaying graphical information. The IMAT Graphics Manual shows users of commercial analysis codes (MATRIXx, MSC/NASTRAN and I-DEAS) how to use the IMAT graphics system to obtain high quality graphical output using familiar plotting procedures. The manual explains the key features of the IMAT graphics system, illustrates their use with simple step-by-step examples, and provides a reference for users who wish to take advantage of the flexibility of the software to customize their own applications.

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

OT2_wlanger_7: Dynamics of Giant Magnetic Gas Loops and Their Connection to the CMZ in the Galactic Center

NASA Astrophysics Data System (ADS)

Langer, W.

2011-09-01

Understanding the mass transfer and dynamics among the Galactic Center, the disk, and the halo of the Milky Way is fundamental to the study of the evolution of galaxies and star formation. Recently several giant loops of molecular gas (GML) have been found in the Galactic Center from CO maps, which are likely the result of the magnetic Parker instability. There is new evidence of a possible connection between these loops and the Central Molecular Zone as shown in a sparse [CII] sampling made by the Herschel Key Project GOT C+. Here we propose to map various features of the GMLs and the interface region in [CII] with HIFI. We will also map the foot points of the loop, which are thought to be highly shocked regions, in the ortho 110-101 line of water, which is a known shock tracer. With this data we will characterize different ISM components and their flow among these Galactic Center features.

Computing by robust transience: How the fronto-parietal network performs sequential category-based decisions

PubMed Central

Chaisangmongkon, Warasinee; Swaminathan, Sruthi K.; Freedman, David J.; Wang, Xiao-Jing

2017-01-01

Summary Decision making involves dynamic interplay between internal judgements and external perception, which has been investigated in delayed match-to-category (DMC) experiments. Our analysis of neural recordings shows that, during DMC tasks, LIP and PFC neurons demonstrate mixed, time-varying, and heterogeneous selectivity, but previous theoretical work has not established the link between these neural characteristics and population-level computations. We trained a recurrent network model to perform DMC tasks and found that the model can remarkably reproduce key features of neuronal selectivity at the single-neuron and population levels. Analysis of the trained networks elucidates that robust transient trajectories of the neural population are the key driver of sequential categorical decisions. The directions of trajectories are governed by network self-organized connectivity, defining a ‘neural landscape’, consisting of a task-tailored arrangement of slow states and dynamical tunnels. With this model, we can identify functionally-relevant circuit motifs and generalize the framework to solve other categorization tasks. PMID:28334612

The Olfactory Mosaic: Bringing an Olfactory Network Together for Odor Perception.

PubMed

Courtiol, Emmanuelle; Wilson, Donald A

2017-01-01

Olfactory perception and its underlying neural mechanisms are not fixed, but rather vary over time, dependent on various parameters such as state, task, or learning experience. In olfaction, one of the primary sensory areas beyond the olfactory bulb is the piriform cortex. Due to an increasing number of functions attributed to the piriform cortex, it has been argued to be an associative cortex rather than a simple primary sensory cortex. In fact, the piriform cortex plays a key role in creating olfactory percepts, helping to form configural odor objects from the molecular features extracted in the nose. Moreover, its dynamic interactions with other olfactory and nonolfactory areas are also critical in shaping the olfactory percept and resulting behavioral responses. In this brief review, we will describe the key role of the piriform cortex in the larger olfactory perceptual network, some of the many actors of this network, and the importance of the dynamic interactions among the piriform-trans-thalamic and limbic pathways.

Further steps in the modeling of behavioural crowd dynamics, good news for safe handling. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

The recent review paper [4] constitutes a valuable contribution on the understanding, modeling and simulation of crowd dynamics in extreme situations. It provides a very comprehensive revision about the complexity features of the system under consideration, scaling and the consequent justification of the used methods. In particular, macro and microscopic models have so far been used to model crowd dynamics [9] and authors appropriately explain that working at the mesoscale is a good choice to deal with the heterogeneous behaviour of walkers as well as with the difficulty of their deterministic identification. In this way, methods based on the kinetic theory and statistical dynamics are employed, more precisely the so-called kinetic theory for active particles [7]. This approach has successfully been applied in the modeling of several complex dynamics, with recent applications to learning [2,8] that constitutes the key to understand communication and is of great importance in social dynamics and behavioral sciences.

Coherent inflationary dynamics for Bose-Einstein condensates crossing a quantum critical point

NASA Astrophysics Data System (ADS)

Feng, Lei; Clark, Logan W.; Gaj, Anita; Chin, Cheng

2018-03-01

Quantum phase transitions, transitions between many-body ground states, are of extensive interest in research ranging from condensed-matter physics to cosmology1-4. Key features of the phase transitions include a stage with rapidly growing new order, called inflation in cosmology5, followed by the formation of topological defects6-8. How inflation is initiated and evolves into topological defects remains a hot topic of debate. Ultracold atomic gas offers a pristine and tunable platform to investigate quantum critical dynamics9-21. We report the observation of coherent inflationary dynamics across a quantum critical point in driven Bose-Einstein condensates. The inflation manifests in the exponential growth of density waves and populations in well-resolved momentum states. After the inflation stage, extended coherent dynamics is evident in both real and momentum space. We present an intuitive description of the quantum critical dynamics in our system and demonstrate the essential role of phase fluctuations in the formation of topological defects.

Redefining the Speed Limit of Phase Change Memory Revealed by Time-resolved Steep Threshold-Switching Dynamics of AgInSbTe Devices

NASA Astrophysics Data System (ADS)

Shukla, Krishna Dayal; Saxena, Nishant; Durai, Suresh; Manivannan, Anbarasu

2016-11-01

Although phase-change memory (PCM) offers promising features for a ‘universal memory’ owing to high-speed and non-volatility, achieving fast electrical switching remains a key challenge. In this work, a correlation between the rate of applied voltage and the dynamics of threshold-switching is investigated at picosecond-timescale. A distinct characteristic feature of enabling a rapid threshold-switching at a critical voltage known as the threshold voltage as validated by an instantaneous response of steep current rise from an amorphous off to on state is achieved within 250 picoseconds and this is followed by a slower current rise leading to crystallization. Also, we demonstrate that the extraordinary nature of threshold-switching dynamics in AgInSbTe cells is independent to the rate of applied voltage unlike other chalcogenide-based phase change materials exhibiting the voltage dependent transient switching characteristics. Furthermore, numerical solutions of time-dependent conduction process validate the experimental results, which reveal the electronic nature of threshold-switching. These findings of steep threshold-switching of ‘sub-50 ps delay time’, opens up a new way for achieving high-speed non-volatile memory for mainstream computing.

Addressable metasurfaces for dynamic holography and optical information encryption.

PubMed

Li, Jianxiong; Kamin, Simon; Zheng, Guoxing; Neubrech, Frank; Zhang, Shuang; Liu, Na

2018-06-01

Metasurfaces enable manipulation of light propagation at an unprecedented level, benefitting from a number of merits unavailable to conventional optical elements, such as ultracompactness, precise phase and polarization control at deep subwavelength scale, and multifunctionalities. Recent progress in this field has witnessed a plethora of functional metasurfaces, ranging from lenses and vortex beam generation to holography. However, research endeavors have been mainly devoted to static devices, exploiting only a glimpse of opportunities that metasurfaces can offer. We demonstrate a dynamic metasurface platform, which allows independent manipulation of addressable subwavelength pixels at visible frequencies through controlled chemical reactions. In particular, we create dynamic metasurface holograms for advanced optical information processing and encryption. Plasmonic nanorods tailored to exhibit hierarchical reaction kinetics upon hydrogenation/dehydrogenation constitute addressable pixels in multiplexed metasurfaces. The helicity of light, hydrogen, oxygen, and reaction duration serve as multiple keys to encrypt the metasurfaces. One single metasurface can be deciphered into manifold messages with customized keys, featuring a compact data storage scheme as well as a high level of information security. Our work suggests a novel route to protect and transmit classified data, where highly restricted access of information is imposed.

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints. PMID:19003514

Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert

2017-08-01

Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.

Inward open characterization of EmrD transporter with molecular dynamics simulation

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

Tan, Xianwei; Wang, Boxiong, E-mail: boxiong_wang@yahoo.com

EmrD is a member of the multidrug resistance exporter family. Up to now, little is known about the structural dynamics that underline the function of the EmrD protein in inward-facing open state and how the EmrD transits from an occluded state to an inward open state. For the first time the article applied the AT simulation to investigate the membrane transporter protein EmrD, and described the dynamic features of the whole protein, the domain, the helices, and the amino acid residues during an inward-open process from its occluded state. The gradual inward-open process is different from the current model ofmore » rigid-body domain motion in alternating-access mechanism. Simulation results show that the EmrD inward-open conformational fluctuation propagates from a C-terminal domain to an N-terminal domain via the linker region during the transition from its occluded state. The conformational fluctuation of the C-terminal domain is larger than that of the N-terminal domain. In addition, it is observed that the helices exposed to the surrounding membrane show a higher level of flexibility than the other regions, and the protonated E227 plays a key role in the transition from the occluded to the open state. -- Highlights: •This study described the dynamic features of the whole EmrD protein, during an inward-open process from its occluded state. •The EmrD inward-open conformational fluctuation propagates from a C-terminal domain to an N-terminal domain via the linker region during the transition from its occluded state. •The conformational fluctuation of the C-terminal domain is larger than that of the N-terminal domain. •The protonated E227 plays a key role in the transition from the occluded to the open state.« less

Trait-based plant ecology: moving towards a unifying species coexistence theory : Features of the Special Section.

PubMed

Escudero, Adrián; Valladares, Fernando

2016-04-01

Functional traits are the center of recent attempts to unify key ecological theories on species coexistence and assembling in populations and communities. While the plethora of studies on the role of functional traits to explain patterns and dynamics of communities has rendered a complex picture due to the idiosyncrasies of each study system and approach, there is increasing evidence on their actual relevance when aspects such as different spatial scales, intraspecific variability and demography are considered.

Market dynamics and stock price volatility

NASA Astrophysics Data System (ADS)

Li, H.; Rosser, J. B., Jr.

2004-06-01

This paper presents a possible explanation for some of the empirical properties of asset returns within a heterogeneous-agents framework. The model turns out, even if we assume the input fundamental value follows an simple Gaussian distribution lacking both fat tails and volatility dependence, these features can show up in the time series of asset returns. In this model, the profit comparison and switching between heterogeneous play key roles, which build a connection between endogenous market and the emergence of stylized facts.

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

DOE PAGES

Ferguson, Jared O.; Jablonowski, Christiane; Johansen, Hans; ...

2016-11-09

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interactionmore » of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.« less

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

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

Ferguson, Jared O.; Jablonowski, Christiane; Johansen, Hans

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interactionmore » of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.« less

Physical activity classification with dynamic discriminative methods.

PubMed

Ray, Evan L; Sasaki, Jeffer E; Freedson, Patty S; Staudenmayer, John

2018-06-19

A person's physical activity has important health implications, so it is important to be able to measure aspects of physical activity objectively. One approach to doing that is to use data from an accelerometer to classify physical activity according to activity type (e.g., lying down, sitting, standing, or walking) or intensity (e.g., sedentary, light, moderate, or vigorous). This can be formulated as a labeled classification problem, where the model relates a feature vector summarizing the accelerometer signal in a window of time to the activity type or intensity in that window. These data exhibit two key characteristics: (1) the activity classes in different time windows are not independent, and (2) the accelerometer features have moderately high dimension and follow complex distributions. Through a simulation study and applications to three datasets, we demonstrate that a model's classification performance is related to how it addresses these aspects of the data. Dynamic methods that account for temporal dependence achieve better performance than static methods that do not. Generative methods that explicitly model the distribution of the accelerometer signal features do not perform as well as methods that take a discriminative approach to establishing the relationship between the accelerometer signal and the activity class. Specifically, Conditional Random Fields consistently have better performance than commonly employed methods that ignore temporal dependence or attempt to model the accelerometer features. © 2018, The International Biometric Society.

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres

PubMed Central

Ince, Robin A. A.; Jaworska, Katarzyna; Gross, Joachim; Panzeri, Stefano; van Rijsbergen, Nicola J.; Rousselet, Guillaume A.; Schyns, Philippe G.

2016-01-01

A key to understanding visual cognition is to determine “where”, “when”, and “how” brain responses reflect the processing of the specific visual features that modulate categorization behavior—the “what”. The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event. Reverse-correlation methods coupled with information-theoretic analyses revealed that visibility of the eyes influences face detection behavior. The N170 initially reflects coding of the behaviorally relevant eye contralateral to the sensor, followed by a causal communication of the other eye from the other hemisphere. These findings demonstrate that the deceptively simple N170 ERP hides a complex network information processing mechanism involving initial coding and subsequent cross-hemispheric transfer of visual features. PMID:27550865

History-dependent ion transport through conical nanopipettes and the implications in energy conversion dynamics at nanoscale interfaces.

PubMed

Li, Yan; Wang, Dengchao; Kvetny, Maksim M; Brown, Warren; Liu, Juan; Wang, Gangli

2015-01-01

The dynamics of ion transport at nanostructured substrate-solution interfaces play vital roles in high-density energy conversion, stochastic chemical sensing and biosensing, membrane separation, nanofluidics and fundamental nanoelectrochemistry. Further advancements in these applications require a fundamental understanding of ion transport at nanoscale interfaces. The understanding of the dynamic or transient transport, and the key physical process involved, is limited, which contrasts sharply with widely studied steady-state ion transport features at atomic and nanometer scale interfaces. Here we report striking time-dependent ion transport characteristics at nanoscale interfaces in current-potential ( I - V ) measurements and theoretical analyses. First, a unique non-zero I - V cross-point and pinched I - V curves are established as signatures to characterize the dynamics of ion transport through individual conical nanopipettes. Second, ion transport against a concentration gradient is regulated by applied and surface electrical fields. The concept of ion pumping or separation is demonstrated via the selective ion transport against concentration gradients through individual nanopipettes. Third, this dynamic ion transport process under a predefined salinity gradient is discussed in the context of nanoscale energy conversion in supercapacitor type charging-discharging, as well as chemical and electrical energy conversion. The analysis of the emerging current-potential features establishes the urgently needed physical foundation for energy conversion employing ordered nanostructures. The elucidated mechanism and established methodology can be generalized into broadly-defined nanoporous materials and devices for improved energy, separation and sensing applications.

History-dependent ion transport through conical nanopipettes and the implications in energy conversion dynamics at nanoscale interfaces

DOE PAGES

Li, Yan; Wang, Dengchao; Kvetny, Maksim M.; ...

2014-08-20

The dynamics of ion transport at nanostructured substrate–solution interfaces play vital roles in high-density energy conversion, stochastic chemical sensing and biosensing, membrane separation, nanofluidics and fundamental nanoelectrochemistry. Advancements in these applications require a fundamental understanding of ion transport at nanoscale interfaces. The understanding of the dynamic or transient transport, and the key physical process involved, is limited, which contrasts sharply with widely studied steady-state ion transport features at atomic and nanometer scale interfaces. Here we report striking time-dependent ion transport characteristics at nanoscale interfaces in current–potential (I–V) measurements and theoretical analyses. First, a unique non-zero I–V cross-point and pinched I–Vmore » curves are established as signatures to characterize the dynamics of ion transport through individual conical nanopipettes. Moreoever, ion transport against a concentration gradient is regulated by applied and surface electrical fields. The concept of ion pumping or separation is demonstrated via the selective ion transport against concentration gradients through individual nanopipettes. Third, this dynamic ion transport process under a predefined salinity gradient is discussed in the context of nanoscale energy conversion in supercapacitor type charging–discharging, as well as chemical and electrical energy conversion. Our analysis of the emerging current–potential features establishes the urgently needed physical foundation for energy conversion employing ordered nanostructures. The elucidated mechanism and established methodology can be generalized into broadly-defined nanoporous materials and devices for improved energy, separation and sensing applications.« less

Session 6: Dynamic Modeling and Systems Analysis

NASA Technical Reports Server (NTRS)

Csank, Jeffrey; Chapman, Jeffryes; May, Ryan

2013-01-01

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

PubMed Central

Ollivier, Julien F.; Soyer, Orkun S.

2016-01-01

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

Personalized keystroke dynamics for self-powered human--machine interfacing.

PubMed

Chen, Jun; Zhu, Guang; Yang, Jin; Jing, Qingshen; Bai, Peng; Yang, Weiqing; Qi, Xuewei; Su, Yuanjie; Wang, Zhong Lin

2015-01-27

The computer keyboard is one of the most common, reliable, accessible, and effective tools used for human--machine interfacing and information exchange. Although keyboards have been used for hundreds of years for advancing human civilization, studying human behavior by keystroke dynamics using smart keyboards remains a great challenge. Here we report a self-powered, non-mechanical-punching keyboard enabled by contact electrification between human fingers and keys, which converts mechanical stimuli applied to the keyboard into local electronic signals without applying an external power. The intelligent keyboard (IKB) can not only sensitively trigger a wireless alarm system once gentle finger tapping occurs but also trace and record typed content by detecting both the dynamic time intervals between and during the inputting of letters and the force used for each typing action. Such features hold promise for its use as a smart security system that can realize detection, alert, recording, and identification. Moreover, the IKB is able to identify personal characteristics from different individuals, assisted by the behavioral biometric of keystroke dynamics. Furthermore, the IKB can effectively harness typing motions for electricity to charge commercial electronics at arbitrary typing speeds greater than 100 characters per min. Given the above features, the IKB can be potentially applied not only to self-powered electronics but also to artificial intelligence, cyber security, and computer or network access control.

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions.

PubMed

Duan, Lingfeng; Han, Jiwan; Guo, Zilong; Tu, Haifu; Yang, Peng; Zhang, Dong; Fan, Yuan; Chen, Guoxing; Xiong, Lizhong; Dai, Mingqiu; Williams, Kevin; Corke, Fiona; Doonan, John H; Yang, Wanneng

2018-01-01

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.

A finite element analysis of novel vented dental abutment geometries for cement‐retained crown restorations

PubMed Central

Rodriguez, Lucas C.; Saba, Juliana N.; Meyer, Clark A.; Chung, Kwok‐Hung; Wadhwani, Chandur

2016-01-01

Abstract Recent literature indicates that the long‐term success of dental implants is, in part, attributed to how dental crowns are attached to their associated implants. The commonly utilized method for crown attachment – cementation, has been criticized because of recent links between residual cement and peri‐implant disease. Residual cement extrusion from crown‐abutment margins post‐crown seating is a growing concern. This study aimed at (1) identifying key abutment features, which would improve dental cement flow characteristics, and (2) understanding how these features would impact the mechanical stability of the abutment under functional loads. Computational fluid dynamic modeling was used to evaluate cement flow in novel abutment geometries. These models were then evaluated using 3D‐printed surrogate models. Finite element analysis also provided an understanding of how the mechanical stability of these abutments was altered after key features were incorporated into the geometry. The findings demonstrated that the key features involved in improved venting of the abutment during crown seating were (1) addition of vents, (2) diameter of the vents, (3) location of the vents, (4) addition of a plastic screw insert, and (5) thickness of the abutment wall. This study culminated in a novel design for a vented abutment consisting of 8 vents located radially around the abutment neck‐margin plus a plastic insert to guide the cement during seating and provide retrievability to the abutment system.Venting of the dental abutment has been shown to decrease the risk of undetected residual dental cement post‐cement‐retained crown seating. This article will utilize a finite element analysis approach toward optimizing dental abutment designs for improved dental cement venting. Features investigated include (1) addition of vents, (2) diameter of vents, (3) location of vents, (4) addition of plastic screw insert, and (5) thickness of abutment wall. PMID:29744160

A finite element analysis of novel vented dental abutment geometries for cement-retained crown restorations.

PubMed

Rodriguez, Lucas C; Saba, Juliana N; Meyer, Clark A; Chung, Kwok-Hung; Wadhwani, Chandur; Rodrigues, Danieli C

2016-11-01

Recent literature indicates that the long-term success of dental implants is, in part, attributed to how dental crowns are attached to their associated implants. The commonly utilized method for crown attachment - cementation, has been criticized because of recent links between residual cement and peri-implant disease. Residual cement extrusion from crown-abutment margins post-crown seating is a growing concern. This study aimed at (1) identifying key abutment features, which would improve dental cement flow characteristics, and (2) understanding how these features would impact the mechanical stability of the abutment under functional loads. Computational fluid dynamic modeling was used to evaluate cement flow in novel abutment geometries. These models were then evaluated using 3D-printed surrogate models. Finite element analysis also provided an understanding of how the mechanical stability of these abutments was altered after key features were incorporated into the geometry. The findings demonstrated that the key features involved in improved venting of the abutment during crown seating were (1) addition of vents, (2) diameter of the vents, (3) location of the vents, (4) addition of a plastic screw insert, and (5) thickness of the abutment wall. This study culminated in a novel design for a vented abutment consisting of 8 vents located radially around the abutment neck-margin plus a plastic insert to guide the cement during seating and provide retrievability to the abutment system.Venting of the dental abutment has been shown to decrease the risk of undetected residual dental cement post-cement-retained crown seating. This article will utilize a finite element analysis approach toward optimizing dental abutment designs for improved dental cement venting. Features investigated include (1) addition of vents, (2) diameter of vents, (3) location of vents, (4) addition of plastic screw insert, and (5) thickness of abutment wall.

In Pursuit of Analogs for Europa's Dynamics & Potential Habitats

NASA Astrophysics Data System (ADS)

Schmidt, Britney E.; Blankenship, D. D.; Greenbaum, J. S.; Young, D. A.

2010-10-01

Future Europa exploration will seek to characterize the distribution of shallow subsurface water as well as to understand the formation of surface features through dynamic ice-shell processes. Radar sounding will be a critical tool for imaging these features, and should be of primary interest to the astrobiology community for understanding how and where life might arise on Europa. To develop successful instrumentation and data interpretation techniques for exploring Europa, we must leverage analogous terrestrial environments and processes. Airborne ice penetrating radar is now a mature tool in terrestrial studies of Earth's ice sheets, and orbital examples have been successfully deployed at Earth's Moon and Mars. It is a distinct possibility that water within or just below the ice on Europa has played a role in forming some of its dynamic terrain. Observations of rotated blocks and dark floor materials may suggest that brines existed in the near subsurface and enabled the formation of such features. The University of Texas High Capability Airborne Radar Sounder (HiCARS) developed to study Antarctic ice sheet dynamics has been configured to test observation scenarios for Europa. We discuss recent results from the 60 MHz HiCARS system over brine infiltrated Antarctic marine ice as an analog for processes affecting the formation of pits and chaos. Basal melt occurring below terrestrial marine ice is directly analogous to processes that may operate on Europa if the shell is "thin,” and will be similar to processes occurring instead within the ice sheet in the case of a thicker, multi-layer ice sheet where enriched brines may remain liquid within the shell. A key site for further investigation of conductive and "convective” ices is found in the polythermal glaciers in the Arctic, and the case for this exploration will be illuminated.

Engineering the robustness of industrial microbes through synthetic biology.

PubMed

Zhu, Linjiang; Zhu, Yan; Zhang, Yanping; Li, Yin

2012-02-01

Microbial fermentations and bioconversions play a central role in the production of pharmaceuticals, enzymes and chemicals. To meet the demands of industrial production, it is desirable that microbes maintain a maximized carbon flux towards target metabolites regardless of fluctuations in intracellular or extracellular environments. This requires cellular systems that maintain functional stability and dynamic homeostasis in a given physiological state, or manipulate transitions between different physiological states. Stable maintenance or smooth transition can be achieved through engineering of dynamic controllability, modular and hierarchical organization, or functional redundancy, three key features of biological robustness in a cellular system. This review summarizes how synthetic biology can be used to improve the robustness of industrial microbes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Features of CRISPR-Cas Regulation Key to Highly Efficient and Temporally-Specific crRNA Production.

PubMed

Rodic, Andjela; Blagojevic, Bojana; Djordjevic, Magdalena; Severinov, Konstantin; Djordjevic, Marko

2017-01-01

Bacterial immune systems, such as CRISPR-Cas or restriction-modification (R-M) systems, affect bacterial pathogenicity and antibiotic resistance by modulating horizontal gene flow. A model system for CRISPR-Cas regulation, the Type I-E system from Escherichia coli , is silent under standard laboratory conditions and experimentally observing the dynamics of CRISPR-Cas activation is challenging. Two characteristic features of CRISPR-Cas regulation in E. coli are cooperative transcription repression of cas gene and CRISPR array promoters, and fast non-specific degradation of full length CRISPR transcripts (pre-crRNA). In this work, we use computational modeling to understand how these features affect the system expression dynamics. Signaling which leads to CRISPR-Cas activation is currently unknown, so to bypass this step, we here propose a conceptual setup for cas expression activation, where cas genes are put under transcription control typical for a restriction-modification (R-M) system and then introduced into a cell. Known transcription regulation of an R-M system is used as a proxy for currently unknown CRISPR-Cas transcription control, as both systems are characterized by high cooperativity, which is likely related to similar dynamical constraints of their function. We find that the two characteristic CRISPR-Cas control features are responsible for its temporally-specific dynamical response, so that the system makes a steep (switch-like) transition from OFF to ON state with a time-delay controlled by pre-crRNA degradation rate. We furthermore find that cooperative transcription regulation qualitatively leads to a cross-over to a regime where, at higher pre-crRNA processing rates, crRNA generation approaches the limit of an infinitely abrupt system induction. We propose that these dynamical properties are associated with rapid expression of CRISPR-Cas components and efficient protection of bacterial cells against foreign DNA. In terms of synthetic applications, the setup proposed here should allow highly efficient expression of small RNAs in a narrow time interval, with a specified time-delay with respect to the signal onset.

Side-binding proteins modulate actin filament dynamics

PubMed Central

Crevenna, Alvaro H; Arciniega, Marcelino; Dupont, Aurélie; Mizuno, Naoko; Kowalska, Kaja; Lange, Oliver F; Wedlich-Söldner, Roland; Lamb, Don C

2015-01-01

Actin filament dynamics govern many key physiological processes from cell motility to tissue morphogenesis. A central feature of actin dynamics is the capacity of filaments to polymerize and depolymerize at their ends in response to cellular conditions. It is currently thought that filament kinetics can be described by a single rate constant for each end. In this study, using direct visualization of single actin filament elongation, we show that actin polymerization kinetics at both filament ends are strongly influenced by the binding of proteins to the lateral filament surface. We also show that the pointed-end has a non-elongating state that dominates the observed filament kinetic asymmetry. Estimates of flexibility as well as effects on fragmentation and growth suggest that the observed kinetic diversity arises from structural alteration. Tuning elongation kinetics by exploiting the malleability of the filament structure may be a ubiquitous mechanism to generate a rich variety of cellular actin dynamics. DOI: http://dx.doi.org/10.7554/eLife.04599.001 PMID:25706231

A prototypic mathematical model of the human hair cycle.

PubMed

Al-Nuaimi, Yusur; Goodfellow, Marc; Paus, Ralf; Baier, Gerold

2012-10-07

The human hair cycle is a complex, dynamic organ-transformation process during which the hair follicle repetitively progresses from a growth phase (anagen) to a rapid apoptosis-driven involution (catagen) and finally a relative quiescent phase (telogen) before returning to anagen. At present no theory satisfactorily explains the origin of the hair cycle rhythm. Based on experimental evidence we propose a prototypic model that focuses on the dynamics of hair matrix keratinocytes. We argue that a plausible feedback-control structure between two key compartments (matrix keratinocytes and dermal papilla) leads to dynamic instabilities in the population dynamics resulting in rhythmic hair growth. The underlying oscillation consists of an autonomous switching between two quasi-steady states. Additional features of the model, namely bistability and excitability, lead to new hypotheses about the impact of interventions on hair growth. We show how in silico testing may facilitate testing of candidate hair growth modulatory agents in human HF organ culture or in clinical trials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Understanding dynamic friction through spontaneously evolving laboratory earthquakes

PubMed Central

Rubino, V.; Rosakis, A. J.; Lapusta, N.

2017-01-01

Friction plays a key role in how ruptures unzip faults in the Earth’s crust and release waves that cause destructive shaking. Yet dynamic friction evolution is one of the biggest uncertainties in earthquake science. Here we report on novel measurements of evolving local friction during spontaneously developing mini-earthquakes in the laboratory, enabled by our ultrahigh speed full-field imaging technique. The technique captures the evolution of displacements, velocities and stresses of dynamic ruptures, whose rupture speed range from sub-Rayleigh to supershear. The observed friction has complex evolution, featuring initial velocity strengthening followed by substantial velocity weakening. Our measurements are consistent with rate-and-state friction formulations supplemented with flash heating but not with widely used slip-weakening friction laws. This study develops a new approach for measuring local evolution of dynamic friction and has important implications for understanding earthquake hazard since laws governing frictional resistance of faults are vital ingredients in physically-based predictive models of the earthquake source. PMID:28660876

Four-stranded mini microtubules formed by Prosthecobacter BtubAB show dynamic instability.

PubMed

Deng, Xian; Fink, Gero; Bharat, Tanmay A M; He, Shaoda; Kureisaite-Ciziene, Danguole; Löwe, Jan

2017-07-18

Microtubules, the dynamic, yet stiff hollow tubes built from αβ-tubulin protein heterodimers, are thought to be present only in eukaryotic cells. Here, we report a 3.6-Å helical reconstruction electron cryomicroscopy structure of four-stranded mini microtubules formed by bacterial tubulin-like Prosthecobacter dejongeii BtubAB proteins. Despite their much smaller diameter, mini microtubules share many key structural features with eukaryotic microtubules, such as an M-loop, alternating subunits, and a seam that breaks overall helical symmetry. Using in vitro total internal reflection fluorescence microscopy, we show that bacterial mini microtubules treadmill and display dynamic instability, another hallmark of eukaryotic microtubules. The third protein in the btub gene cluster, BtubC, previously known as "bacterial kinesin light chain," binds along protofilaments every 8 nm, inhibits BtubAB mini microtubule catastrophe, and increases rescue. Our work reveals that some bacteria contain regulated and dynamic cytomotive microtubule systems that were once thought to be only useful in much larger and sophisticated eukaryotic cells.

Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management

NASA Astrophysics Data System (ADS)

Müller, Felix; Burkhard, Benjamin; Kroll, Franziska

In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the “adaptive cycle”. Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.

Clustered Dynamics of Inhibitory Synapses and Dendritic Spines in the Adult Neocortex

PubMed Central

Chen, Jerry L.; Villa, Katherine L; Cha, Jae Won; So, Peter T.C.; Kubota, Yoshiyuki; Nedivi, Elly

2012-01-01

A key feature of the mammalian brain is its capacity to adapt in response to experience, in part by remodeling of synaptic connections between neurons. Excitatory synapse rearrangements have been monitored in vivo by observation of dendritic spine dynamics, but lack of a vital marker for inhibitory synapses has precluded their observation. Here, we simultaneously monitor in vivo inhibitory synapse and dendritic spine dynamics across the entire dendritic arbor of pyramidal neurons in the adult mammalian cortex using large volume high-resolution dual color two-photon microscopy. We find that inhibitory synapses on dendritic shafts and spines differ in their distribution across the arbor and in their remodeling kinetics during normal and altered sensory experience. Further, we find inhibitory synapse and dendritic spine remodeling to be spatially clustered, and that clustering is influenced by sensory input. Our findings provide in vivo evidence for local coordination of inhibitory and excitatory synaptic rearrangements. PMID:22542188

Self-regulation in self-propelled nematic fluids.

PubMed

Baskaran, A; Marchetti, M C

2012-09-01

We consider the hydrodynamic theory of an active fluid of self-propelled particles with nematic aligning interactions. This class of materials has polar symmetry at the microscopic level, but forms macrostates of nematic symmetry. We highlight three key features of the dynamics. First, as in polar active fluids, the control parameter for the order-disorder transition, namely the density, is dynamically convected by the order parameter via active currents. The resulting dynamical self-regulation of the order parameter is a generic property of active fluids and destabilizes the uniform nematic state near the mean-field transition. Secondly, curvature-driven currents render the system unstable deep in the nematic state, as found previously. Finally, and unique to self-propelled nematics, nematic order induces local polar order that in turn leads to the growth of density fluctuations. We propose this as a possible mechanism for the smectic order of polar clusters seen in numerical simulations.

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

Yurk, Brian P; Cobbold, Christina A

2018-12-01

An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.

Natural neural projection dynamics underlying social behavior

PubMed Central

Gunaydin, Lisa A.; Grosenick, Logan; Finkelstein, Joel C.; Kauvar, Isaac V.; Fenno, Lief E.; Adhikari, Avishek; Lammel, Stephan; Mirzabekov, Julie J.; Airan, Raag D.; Zalocusky, Kelly A.; Tye, Kay M.; Anikeeva, Polina; Malenka, Robert C.; Deisseroth, Karl

2014-01-01

Social interaction is a complex behavior essential for many species, and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically- and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social but not novel-object interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type-1 dopamine receptor signaling downstream in the NAc. Direct observation of projection-specific activity in this way captures a fundamental and previously inaccessible dimension of circuit dynamics. PMID:24949967

Dynamical Evolution of Ring-Satellite Systems

NASA Technical Reports Server (NTRS)

Ohtsuki, Keiji

2005-01-01

The goal of this research was to understand dynamical processes related to the evolution of size distribution of particles in planetary rings and application of theoretical results to explain features in the present rings of giant planets. We studied velocity evolution and accretion rates of ring particles in the Roche zone. We developed a new numerical code for the evolution of ring particle size distribution, which takes into account the above results for particle velocity evolution and accretion rates. We also studied radial diffusion rate of ring particles due to inelastic collisions and gravitational encounters. Many of these results can be also applied to dynamical evolution of a planetesimal disk. Finally, we studied rotation rates of moonlets and particles in planetary rings, which would influence the accretional evolution of these bodies. We describe our key accomplishments during the past three years in more detail in the following.

Polynomial algebra of discrete models in systems biology.

PubMed

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

A covariant approach to entropic dynamics

NASA Astrophysics Data System (ADS)

Ipek, Selman; Abedi, Mohammad; Caticha, Ariel

2017-06-01

Entropic Dynamics (ED) is a framework for constructing dynamical theories of inference using the tools of inductive reasoning. A central feature of the ED framework is the special focus placed on time. In [2] a global entropic time was used to derive a quantum theory of relativistic scalar fields. This theory, however, suffered from a lack of explicit or manifest Lorentz symmetry. In this paper we explore an alternative formulation in which the relativistic aspects of the theory are manifest. The approach we pursue here is inspired by the methods of Dirac, Kuchař, and Teitelboim in their development of covariant Hamiltonian approaches. The key ingredient here is the adoption of a local notion of entropic time, which allows compatibility with an arbitrary notion of simultaneity. However, in order to ensure that the evolution does not depend on the particular sequence of hypersurfaces, we must impose a set of constraints that guarantee a consistent evolution.

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

PubMed Central

Beck, Cornelia; Neumann, Heiko

2011-01-01

Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543

Transverse beam splitting made operational: Key features of the multiturn extraction at the CERN Proton Synchrotron

NASA Astrophysics Data System (ADS)

Huschauer, A.; Blas, A.; Borburgh, J.; Damjanovic, S.; Gilardoni, S.; Giovannozzi, M.; Hourican, M.; Kahle, K.; Le Godec, G.; Michels, O.; Sterbini, G.; Hernalsteens, C.

2017-06-01

Following a successful commissioning period, the multiturn extraction (MTE) at the CERN Proton Synchrotron (PS) has been applied for the fixed-target physics programme at the Super Proton Synchrotron (SPS) since September 2015. This exceptional extraction technique was proposed to replace the long-serving continuous transfer (CT) extraction, which has the drawback of inducing high activation in the ring. MTE exploits the principles of nonlinear beam dynamics to perform loss-free beam splitting in the horizontal phase space. Over multiple turns, the resulting beamlets are then transferred to the downstream accelerator. The operational deployment of MTE was rendered possible by the full understanding and mitigation of different hardware limitations and by redesigning the extraction trajectories and nonlinear optics, which was required due to the installation of a dummy septum to reduce the activation of the magnetic extraction septum. This paper focuses on these key features including the use of the transverse damper and the septum shadowing, which allowed a transition from the MTE study to a mature operational extraction scheme.

Laser Absorption by Over-Critical Plasmas

NASA Astrophysics Data System (ADS)

May, J.; Tonge, J.; Fiuza, F.; Fonseca, R. A.; Silva, L. O.; Mori, W. B.

2015-11-01

Absorption of high intensity laser light by matter has important applications to emerging sciences and technology, such as Fast Ignition ICF and ion acceleration. As such, understanding the underlying mechanisms of this absorption is key to developing these technologies. Critical features which distinguish the interaction of high intensity light - defined here as a laser field having a normalized vector potential greater than unity - are that the reaction of the material to the fields results in sharp high-density interfaces; and that the movement of the electrons is in general relativistic, both in a fluid and a thermal sense. The results of these features are that the absorption mechanisms are qualitatively distinct from those at lower intensities. We will review previous work, by our group and others, on the absorption mechanisms, and highlight current research. We will show that the standing wave structure of the reflected laser light is key to particle dynamics for normally incident lasers. The authors acknowledge the support of the Department of Energy under contract DE-NA 0001833 and the National Science Foundation under contract ACI 1339893.

A Dynamical Approach Toward Understanding Mechanisms of Team Science: Change, Kinship, Tension, and Heritage in a Transdisciplinary Team

PubMed Central

2013-01-01

Abstract Since the concept of team science gained recognition among biomedical researchers, social scientists have been challenged with investigating evidence of team mechanisms and functional dynamics within transdisciplinary teams. Identification of these mechanisms has lacked substantial research using grounded theory models to adequately describe their dynamical qualities. Research trends continue to favor the measurement of teams by isolating occurrences of production over relational mechanistic team tendencies. This study uses a social constructionist‐grounded multilevel mixed methods approach to identify social dynamics and mechanisms within a transdisciplinary team. A National Institutes of Health—funded research team served as a sample. Data from observations, interviews, and focus groups were qualitatively coded to generate micro/meso level analyses. Social mechanisms operative within this biomedical scientific team were identified. Dynamics that support such mechanisms were documented and explored. Through theoretical and emergent coding, four social mechanisms dominated in the analysis—change, kinship, tension, and heritage. Each contains relational social dynamics. This micro/meso level study suggests such mechanisms and dynamics are key features of team science and as such can inform problems of integration, praxis, and engagement in teams. PMID:23919361

Finite temperature dynamics of a Holstein polaron: The thermo-field dynamics approach

NASA Astrophysics Data System (ADS)

Chen, Lipeng; Zhao, Yang

2017-12-01

Combining the multiple Davydov D2 Ansatz with the method of thermo-field dynamics, we study finite temperature dynamics of a Holstein polaron on a lattice. It has been demonstrated, using the hierarchy equations of motion method as a benchmark, that our approach provides an efficient, robust description of finite temperature dynamics of the Holstein polaron in the simultaneous presence of diagonal and off-diagonal exciton-phonon coupling. The method of thermo-field dynamics handles temperature effects in the Hilbert space with key numerical advantages over other treatments of finite-temperature dynamics based on quantum master equations in the Liouville space or wave function propagation with Monte Carlo importance sampling. While for weak to moderate diagonal coupling temperature increases inhibit polaron mobility, it is found that off-diagonal coupling induces phonon-assisted transport that dominates at high temperatures. Results on the mean square displacements show that band-like transport features dominate the diagonal coupling cases, and there exists a crossover from band-like to hopping transport with increasing temperature when including off-diagonal coupling. As a proof of concept, our theory provides a unified treatment of coherent and incoherent transport in molecular crystals and is applicable to any temperature.

A dynamical approach toward understanding mechanisms of team science: change, kinship, tension, and heritage in a transdisciplinary team.

PubMed

Lotrecchiano, Gaetano R

2013-08-01

Since the concept of team science gained recognition among biomedical researchers, social scientists have been challenged with investigating evidence of team mechanisms and functional dynamics within transdisciplinary teams. Identification of these mechanisms has lacked substantial research using grounded theory models to adequately describe their dynamical qualities. Research trends continue to favor the measurement of teams by isolating occurrences of production over relational mechanistic team tendencies. This study uses a social constructionist-grounded multilevel mixed methods approach to identify social dynamics and mechanisms within a transdisciplinary team. A National Institutes of Health-funded research team served as a sample. Data from observations, interviews, and focus groups were qualitatively coded to generate micro/meso level analyses. Social mechanisms operative within this biomedical scientific team were identified. Dynamics that support such mechanisms were documented and explored. Through theoretical and emergent coding, four social mechanisms dominated in the analysis-change, kinship, tension, and heritage. Each contains relational social dynamics. This micro/meso level study suggests such mechanisms and dynamics are key features of team science and as such can inform problems of integration, praxis, and engagement in teams. © 2013 Wiley Periodicals, Inc.

Geometric reduction of dynamical nonlocality in nanoscale quantum circuits.

PubMed

Strambini, E; Makarenko, K S; Abulizi, G; de Jong, M P; van der Wiel, W G

2016-01-06

Nonlocality is a key feature discriminating quantum and classical physics. Quantum-interference phenomena, such as Young's double slit experiment, are one of the clearest manifestations of nonlocality, recently addressed as dynamical to specify its origin in the quantum equations of motion. It is well known that loss of dynamical nonlocality can occur due to (partial) collapse of the wavefunction due to a measurement, such as which-path detection. However, alternative mechanisms affecting dynamical nonlocality have hardly been considered, although of crucial importance in many schemes for quantum information processing. Here, we present a fundamentally different pathway of losing dynamical nonlocality, demonstrating that the detailed geometry of the detection scheme is crucial to preserve nonlocality. By means of a solid-state quantum-interference experiment we quantify this effect in a diffusive system. We show that interference is not only affected by decoherence, but also by a loss of dynamical nonlocality based on a local reduction of the number of quantum conduction channels of the interferometer. With our measurements and theoretical model we demonstrate that this mechanism is an intrinsic property of quantum dynamics. Understanding the geometrical constraints protecting nonlocality is crucial when designing quantum networks for quantum information processing.

Encryption for Remote Control via Internet or Intranet

NASA Technical Reports Server (NTRS)

Lineberger, Lewis

2005-01-01

A data-communication protocol has been devised to enable secure, reliable remote control of processes and equipment via a collision-based network, while using minimal bandwidth and computation. The network could be the Internet or an intranet. Control is made secure by use of both a password and a dynamic key, which is sent transparently to a remote user by the controlled computer (that is, the computer, located at the site of the equipment or process to be controlled, that exerts direct control over the process). The protocol functions in the presence of network latency, overcomes errors caused by missed dynamic keys, and defeats attempts by unauthorized remote users to gain control. The protocol is not suitable for real-time control, but is well suited for applications in which control latencies up to about 0.5 second are acceptable. The encryption scheme involves the use of both a dynamic and a private key, without any additional overhead that would degrade performance. The dynamic key is embedded in the equipment- or process-monitor data packets sent out by the controlled computer: in other words, the dynamic key is a subset of the data in each such data packet. The controlled computer maintains a history of the last 3 to 5 data packets for use in decrypting incoming control commands. In addition, the controlled computer records a private key (password) that is given to the remote computer. The encrypted incoming command is permuted by both the dynamic and private key. A person who records the command data in a given packet for hostile purposes cannot use that packet after the public key expires (typically within 3 seconds). Even a person in possession of an unauthorized copy of the command/remote-display software cannot use that software in the absence of the password. The use of a dynamic key embedded in the outgoing data makes the central-processing unit overhead very small. The use of a National Instruments DataSocket(TradeMark) (or equivalent) protocol or the User Datagram Protocol makes it possible to obtain reasonably short response times: Typical response times in event-driven control, using packets sized .300 bytes, are <0.2 second for commands issued from locations anywhere on Earth. The protocol requires that control commands represent absolute values of controlled parameters (e.g., a specified temperature), as distinguished from changes in values of controlled parameters (e.g., a specified increment of temperature). Each command is issued three or more times to ensure delivery in crowded networks. The use of absolute-value commands prevents additional (redundant) commands from causing trouble. Because a remote controlling computer receives "talkback" in the form of data packets from the controlled computer, typically within a time interval < or =1 s, the controlling computer can re-issue a command if network failure has occurred. The controlled computer, the process or equipment that it controls, and any human operator(s) at the site of the controlled equipment or process should be equipped with safety measures to prevent damage to equipment or injury to humans. These features could be a combination of software, external hardware, and intervention by the human operator(s). The protocol is not fail-safe, but by adopting these safety measures as part of the protocol, one makes the protocol a robust means of controlling remote processes and equipment by use of typical office computers via intranets and/or the Internet.

Classification of holter registers by dynamic clustering using multi-dimensional particle swarm optimization.

PubMed

Kiranyaz, Serkan; Ince, Turker; Pulkkinen, Jenni; Gabbouj, Moncef

2010-01-01

In this paper, we address dynamic clustering in high dimensional data or feature spaces as an optimization problem where multi-dimensional particle swarm optimization (MD PSO) is used to find out the true number of clusters, while fractional global best formation (FGBF) is applied to avoid local optima. Based on these techniques we then present a novel and personalized long-term ECG classification system, which addresses the problem of labeling the beats within a long-term ECG signal, known as Holter register, recorded from an individual patient. Due to the massive amount of ECG beats in a Holter register, visual inspection is quite difficult and cumbersome, if not impossible. Therefore the proposed system helps professionals to quickly and accurately diagnose any latent heart disease by examining only the representative beats (the so called master key-beats) each of which is representing a cluster of homogeneous (similar) beats. We tested the system on a benchmark database where the beats of each Holter register have been manually labeled by cardiologists. The selection of the right master key-beats is the key factor for achieving a highly accurate classification and the proposed systematic approach produced results that were consistent with the manual labels with 99.5% average accuracy, which basically shows the efficiency of the system.

The relationship between 2D static features and 2D dynamic features used in gait recognition

NASA Astrophysics Data System (ADS)

Alawar, Hamad M.; Ugail, Hassan; Kamala, Mumtaz; Connah, David

2013-05-01

In most gait recognition techniques, both static and dynamic features are used to define a subject's gait signature. In this study, the existence of a relationship between static and dynamic features was investigated. The correlation coefficient was used to analyse the relationship between the features extracted from the "University of Bradford Multi-Modal Gait Database". This study includes two dimensional dynamic and static features from 19 subjects. The dynamic features were compromised of Phase-Weighted Magnitudes driven by a Fourier Transform of the temporal rotational data of a subject's joints (knee, thigh, shoulder, and elbow). The results concluded that there are eleven pairs of features that are considered significantly correlated with (p<0.05). This result indicates the existence of a statistical relationship between static and dynamics features, which challenges the results of several similar studies. These results bare great potential for further research into the area, and would potentially contribute to the creation of a gait signature using latent data.

Dimensionality reduction in epidemic spreading models

NASA Astrophysics Data System (ADS)

Frasca, M.; Rizzo, A.; Gallo, L.; Fortuna, L.; Porfiri, M.

2015-09-01

Complex dynamical systems often exhibit collective dynamics that are well described by a reduced set of key variables in a low-dimensional space. Such a low-dimensional description offers a privileged perspective to understand the system behavior across temporal and spatial scales. In this work, we propose a data-driven approach to establish low-dimensional representations of large epidemic datasets by using a dimensionality reduction algorithm based on isometric features mapping (ISOMAP). We demonstrate our approach on synthetic data for epidemic spreading in a population of mobile individuals. We find that ISOMAP is successful in embedding high-dimensional data into a low-dimensional manifold, whose topological features are associated with the epidemic outbreak. Across a range of simulation parameters and model instances, we observe that epidemic outbreaks are embedded into a family of closed curves in a three-dimensional space, in which neighboring points pertain to instants that are close in time. The orientation of each curve is unique to a specific outbreak, and the coordinates correlate with the number of infected individuals. A low-dimensional description of epidemic spreading is expected to improve our understanding of the role of individual response on the outbreak dynamics, inform the selection of meaningful global observables, and, possibly, aid in the design of control and quarantine procedures.

Ecohydrologic Dynamics in Areas of Complex Topography in Semiarid Ecosystems

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Bras, R. L.; Vivoni, E. R.

2008-12-01

Topography strongly affects the state and distribution of vegetation and this control is normally considered to operate through the regulation of the incoming solar radiation and lateral redistribution of water and elements. One of the areas of active research is how plants adjust to terrain effects relative to their location in a landscape and what the implications are for the spatial distribution of the water balance. This study emphasizes the coupled nature of interactions among vegetation-water-energy dynamics and their corresponding controls in complex topography of a semiarid ecosystem. These dynamics are investigated by constructing a coupled modeling system, tRIBS+VEGGIE, based on physical, biochemical, or mechanistic representation of individual processes. In a set of numerical experiments, linkages between terrain attributes, patterns of grass and shrub productivity, and water balance components are examined. For different imposed regimes of lateral water transfer, regions of relative vegetation "favorability" are identified. Their principal controlling mechanisms, as mediated by topographic features of the landscape, are investigated. It is argued that the long-term effects of site-specific and non-local terrain characteristics are superimposed and the key features of the superposition appear to be of the same form, irrespective of the soil hydraulic type or the actual water transport mechanism involved.

Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems.

PubMed

Adams, Alyssa; Zenil, Hector; Davies, Paul C W; Walker, Sara Imari

2017-04-20

Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.

Development of a tunable femtosecond stimulated raman apparatus and its application to beta-carotene.

PubMed

Shim, Sangdeok; Mathies, Richard A

2008-04-17

We have developed a tunable femtosecond stimulated Raman spectroscopy (FSRS) apparatus and used it to perform time-resolved resonance Raman experiments with <100 fs temporal and <35 cm(-1) spectral resolution. The key technical change that facilitates this advance is the use of a tunable narrow-bandwidth optical parametric amplifier (NB-OPA) presented recently by Shim et al. (Shim, S.; Mathies, R. A. Appl. Phys. Lett. 2006, 89, 121124). The practicality of tunable FSRS is demonstrated by examining the photophysical dynamics of beta-carotene. Using 560 nm Raman excitation, the resonant S1 state modes are enhanced by a factor of approximately 200 compared with 800 nm FSRS experiments. The improved signal-to-noise ratios facilitate the measurement of definitive time constants for beta-carotene dynamics including the 180 fs appearance of the S1 vibrational features due to direct internal conversion from S2 and their characteristic 9 ps decay to S0. By tuning the FSRS system to 590 nm Raman excitation, we are able to selectively enhance vibrational features of the hot ground state S hot 0 and monitor its approximately 5 ps cooling dynamics. This tunable FSRS system is valuable because it facilitates the direct observation of structural changes of selected resonantly enhanced states and intermediates during photochemical and photobiological reactions.

Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion

PubMed Central

Choi, Hannah; Pasupathy, Anitha; Shea-Brown, Eric

2018-01-01

The primate visual system has an exquisite ability to discriminate partially occluded shapes. Recent electrophysiological recordings suggest that response dynamics in intermediate visual cortical area V4, shaped by feedback from prefrontal cortex (PFC), may play a key role. To probe the algorithms that may underlie these findings, we build and test a model of V4 and PFC interactions based on a hierarchical predictive coding framework. We propose that probabilistic inference occurs in two steps. Initially, V4 responses are driven solely by bottom-up sensory input and are thus strongly influenced by the level of occlusion. After a delay, V4 responses combine both feedforward input and feedback signals from the PFC; the latter reflect predictions made by PFC about the visual stimulus underlying V4 activity. We find that this model captures key features of V4 and PFC dynamics observed in experiments. Specifically, PFC responses are strongest for occluded stimuli and delayed responses in V4 are less sensitive to occlusion, supporting our hypothesis that the feedback signals from PFC underlie robust discrimination of occluded shapes. Thus, our study proposes that area V4 and PFC participate in hierarchical inference, with feedback signals encoding top-down predictions about occluded shapes. PMID:29566355

Multiscale simulations give insight into the hydrogen in and out pathways of [NiFe]-hydrogenases from Aquifex aeolicus and Desulfovibrio fructosovorans.

PubMed

Oteri, Francesco; Baaden, Marc; Lojou, Elisabeth; Sacquin-Mora, Sophie

2014-12-04

[NiFe]-hydrogenases catalyze the cleavage of molecular hydrogen into protons and electrons and represent promising tools for H2-based technologies such as biofuel cells. However, many aspects of these enzymes remain to be understood, in particular how the catalytic center can be protected from irreversible inactivation by O2. In this work, we combined homology modeling, all-atom molecular dynamics, and coarse-grain Brownian dynamics simulations to investigate and compare the dynamic and mechanical properties of two [NiFe]-hydrogenases: the soluble O2-sensitive enzyme from Desulfovibrio fructosovorans, and the O2-tolerant membrane-bound hydrogenase from Aquifex aeolicus. We investigated the diffusion pathways of H2 from the enzyme surface to the central [NiFe] active site, and the possible proton pathways that are used to evacuate hydrogen after the oxidation reaction. Our results highlight common features of the two enzymes, such as a Val/Leu/Arg triad of key residues that controls ligand migration and substrate access in the vicinity of the active site, or the key role played by a Glu residue for proton transfer after hydrogen oxidation. We show specificities of each hydrogenase regarding the enzymes internal tunnel network or the proton transport pathways.

Electrostatic effects on clustering and ion dynamics in ionomer melts

NASA Astrophysics Data System (ADS)

Ma, Boran; Nguyen, Trung; Pryamitsyn, Victor; Olvera de La Cruz, Monica

An understanding of the relationships between ionomer chain morphology, dynamics and counter-ion mobility is a key factor in the design of ion conducting membranes for battery applications. In this study, we investigate the influence of electrostatic coupling between randomly charged copolymers (ionomers) and counter ions on the structural and dynamic features of a model system of ionomer melts. Using coarse-grained molecular dynamics (CGMD) simulations, we found that variations in electrostatic coupling strength (Γ) remarkably affect the formation of ion-counter ion clusters, ion mobility, and polymer dynamics for a range of charged monomer fractions. Specifically, an increase in Γ leads to larger ionic cluster sizes and reduced polymer and ion mobility. Analysis of the distribution of the radius of gyration of the clusters further reveals that the fractal dimension of the ion clusters is nearly independent from Γ for all the cases studied. Finally, at sufficiently high values of Γ, we observed arrested heterogeneous ions mobility, which is correlated with an increase in ion cluster size. These findings provide insight into the role of electrostatics in governing the nanostructures formed by ionomers.

A Validated Multiscale In-Silico Model for Mechano-sensitive Tumour Angiogenesis and Growth

PubMed Central

Loizidou, Marilena; Stylianopoulos, Triantafyllos; Hawkes, David J.

2017-01-01

Vascularisation is a key feature of cancer growth, invasion and metastasis. To better understand the governing biophysical processes and their relative importance, it is instructive to develop physiologically representative mathematical models with which to compare to experimental data. Previous studies have successfully applied this approach to test the effect of various biochemical factors on tumour growth and angiogenesis. However, these models do not account for the experimentally observed dependency of angiogenic network evolution on growth-induced solid stresses. This work introduces two novel features: the effects of hapto- and mechanotaxis on vessel sprouting, and mechano-sensitive dynamic vascular remodelling. The proposed three-dimensional, multiscale, in-silico model of dynamically coupled angiogenic tumour growth is specified to in-vivo and in-vitro data, chosen, where possible, to provide a physiologically consistent description. The model is then validated against in-vivo data from murine mammary carcinomas, with particular focus placed on identifying the influence of mechanical factors. Crucially, we find that it is necessary to include hapto- and mechanotaxis to recapitulate observed time-varying spatial distributions of angiogenic vasculature. PMID:28125582

Thumb-loops up for catalysis: a structure/function investigation of a functional loop movement in a GH11 xylanase

PubMed Central

Paës, Gabriel; Cortés, Juan; Siméon, Thierry; O'Donohue, Michael J.; Tran, Vinh

2012-01-01

Dynamics is a key feature of enzyme catalysis. Unfortunately, current experimental and computational techniques do not yet provide a comprehensive understanding and description of functional macromolecular motions. In this work, we have extended a novel computational technique, which combines molecular modeling methods and robotics algorithms, to investigate functional motions of protein loops. This new approach has been applied to study the functional importance of the so-called thumb-loop in the glycoside hydrolase family 11 xylanase from Thermobacillus xylanilyticus (Tx-xyl). The results obtained provide new insight into the role of the loop in the glycosylation/deglycosylation catalytic cycle, and underline the key importance of the nature of the residue located at the tip of the thumb-loop. The effect of mutations predicted in silico has been validated by in vitro site-directed mutagenesis experiments. Overall, we propose a comprehensive model of Tx-xyl catalysis in terms of substrate and product dynamics by identifying the action of the thumb-loop motion during catalysis. PMID:24688637

Shedding Synchrotron Light on a Puzzle of Glasses

ScienceCinema

Chumakov, Aleksandr [European Synchrotron Radiation Facility, Grenoble, France

2017-12-09

Vibrational dynamics of glasses remains a point of controversial discussions. In particular, the density of vibrational states (DOS) reveals an excess of states above the Debye model called "boson peak." Despite the fact that this universal feature for all glasses has been known for more than 35 years, the nature of the boson peak is still not understood. The application of nuclear inelastic scattering via synchrotron radiation perhaps provides a clearer, more consistent picture of the subject. The distinguishing features of nuclear inelastic scattering relative to, e.g., neutron inelastic scattering, are ideal momentum integration and exact scaling of the DOS in absolute units. This allows for reliable comparison to data from other techniques such as Brillouin light scattering. Another strong point is ideal isotope selectivity: the DOS is measured for a single isotope with a specific low-energy nuclear transition. This allows for special "design" of an experiment to study, for instance, the dynamics of only center-of-mass motions. Recently, we have investigated the transformation of the DOS as a function of several key parameters such as temperature, cooling rate, and density. In all cases the transformation of the DOS is sufficiently well described by a transformation of the continuous medium, in particular, by changes of the macroscopic density and the sound velocity. These results suggest a collective sound-like nature of vibrational dynamics in glasses and cast doubts on microscopic models of glass dynamics. Further insight can be obtained in combined studies of glass with nuclear inelastic and inelastic neutron scattering. Applying two techniques, we have measured the energy dependence of the characteristic correlation length of atomic motions. The data do not reveal localization of atomic vibrations at the energy of the boson peak. Once again, the results suggest that special features of glass dynamics are related to extended motions and not to local models.

Secure image retrieval with multiple keys

NASA Astrophysics Data System (ADS)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

A practical guide to assessing clinical decision-making skills using the key features approach.

PubMed

Farmer, Elizabeth A; Page, Gordon

2005-12-01

This paper in the series on professional assessment provides a practical guide to writing key features problems (KFPs). Key features problems test clinical decision-making skills in written or computer-based formats. They are based on the concept of critical steps or 'key features' in decision making and represent an advance on the older, less reliable patient management problem (PMP) formats. The practical steps in writing these problems are discussed and illustrated by examples. Steps include assembling problem-writing groups, selecting a suitable clinical scenario or problem and defining its key features, writing the questions, selecting question response formats, preparing scoring keys, reviewing item quality and item banking. The KFP format provides educators with a flexible approach to testing clinical decision-making skills with demonstrated validity and reliability when constructed according to the guidelines provided.

Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

History-dependent ion transport through conical nanopipettes and the implications in energy conversion dynamics at nanoscale interfaces† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c4sc02195a Click here for additional data file.

PubMed Central

Li, Yan; Wang, Dengchao; Kvetny, Maksim M.; Brown, Warren; Liu, Juan

2015-01-01

The dynamics of ion transport at nanostructured substrate–solution interfaces play vital roles in high-density energy conversion, stochastic chemical sensing and biosensing, membrane separation, nanofluidics and fundamental nanoelectrochemistry. Further advancements in these applications require a fundamental understanding of ion transport at nanoscale interfaces. The understanding of the dynamic or transient transport, and the key physical process involved, is limited, which contrasts sharply with widely studied steady-state ion transport features at atomic and nanometer scale interfaces. Here we report striking time-dependent ion transport characteristics at nanoscale interfaces in current–potential (I–V) measurements and theoretical analyses. First, a unique non-zero I–V cross-point and pinched I–V curves are established as signatures to characterize the dynamics of ion transport through individual conical nanopipettes. Second, ion transport against a concentration gradient is regulated by applied and surface electrical fields. The concept of ion pumping or separation is demonstrated via the selective ion transport against concentration gradients through individual nanopipettes. Third, this dynamic ion transport process under a predefined salinity gradient is discussed in the context of nanoscale energy conversion in supercapacitor type charging–discharging, as well as chemical and electrical energy conversion. The analysis of the emerging current–potential features establishes the urgently needed physical foundation for energy conversion employing ordered nanostructures. The elucidated mechanism and established methodology can be generalized into broadly-defined nanoporous materials and devices for improved energy, separation and sensing applications. PMID:28706626

A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity

PubMed Central

Hass, Joachim; Hertäg, Loreen; Durstewitz, Daniel

2016-01-01

The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition. PMID:27203563

Identifying Hydrogeological Controls of Catchment Low-Flow Dynamics Using Physically Based Modelling

NASA Astrophysics Data System (ADS)

Cochand, F.; Carlier, C.; Staudinger, M.; Seibert, J.; Hunkeler, D.; Brunner, P.

2017-12-01

Identifying key catchment characteristics and processes which control the hydrological response under low-flow conditions is important to assess the catchments' vulnerability to dry periods. In the context of a Swiss Federal Office for the Environment (FOEN) project, the low-flow behaviours of two mountainous catchments were investigated. These neighboring catchments are characterized by the same meteorological conditions, but feature completely different river flow dynamics. The Roethenbach is characterized by high peak flows and low mean flows. Conversely, the Langete is characterized by relatively low peak flows and high mean flow rates. To understand the fundamentally different behaviour of the two catchments, a physically-based surface-subsurface flow HydroGeoSphere (HGS) model for each catchment was developed. The main advantage of a physically-based model is its ability to realistically reproduce processes which play a key role during low-flow periods such as surface-subsurface interactions or evapotranspiration. Both models were calibrated to reproduce measured groundwater heads and the surface flow dynamics. Subsequently, the calibrated models were used to explore the fundamental physics that control hydrological processes during low-flow periods. To achieve this, a comparative sensitivity analysis of model parameters of both catchments was carried out. Results show that the hydraulic conductivity of the bedrock (and weathered bedrock) controls the catchment water dynamics in both models. Conversely, the properties of other geological formations such as alluvial aquifer or soil layer hydraulic conductivity or porosity play a less important role. These results change significantly our perception of the streamflow catchment dynamics and more specifically the way to assess catchment vulnerability to dry period. This study suggests that by analysing catchment scale bedrock properties, the catchment dynamics and the vulnerability to dry period may be assessed.

Dynamics of the CMZ - Giant Magnetic Loops Connection in the Galactic Center

NASA Astrophysics Data System (ADS)

Langer, William

2012-10-01

Understanding the mass transfer and dynamics among the Galactic Center, the disk, and the halo of the Milky Way is fundamental to the study of the evolution of galaxies and star formation. Several giant molecular loops (GML), detected in CO maps of the Galactic Center, are likely the result of the magnetic Parker instability. We have new evidence of a possible dynamical connection between these loops and the Central Molecular Zone (CMZ) from a sparse [CII] sampling from our Herschel Open Time Key Project GOT C+. The CMZ-GML region is dynamically active and is likely to have a significant ionized component. However, we have no information on the distribution and dynamics of the ionized gas. The fine-structure lines of [NII] are key probes of the warm ionized medium (WIM) and along with the [CII] can isolate the different ionization components. We have a Herschel OT2 Priority 1 program to map the GML and the CMZ-GML connection in [CII] in more detail. However, we did not propose needed [NII] observations due to an incomplete analysis of our limited GOT C+ data at the time. Here we propose to observe with the SOFIA/GREAT instrument, [NII] in the CMZ-GML interface region using the L1b band, and serendipitously CO (16-15) using band L2. With this data, combined with our Herschel HIFI [CII], Mopra 12CO (1-0) and 13CO (1-0), and HI, we will characterize these important ISM components and their motions in these Galactic Center features. These observations of the nearest such regions of galactic center activity, also have bearing on the dynamics of other galactic nuclei.

Implementing quantum Ricci curvature

NASA Astrophysics Data System (ADS)

Klitgaard, N.; Loll, R.

2018-05-01

Quantum Ricci curvature has been introduced recently as a new, geometric observable characterizing the curvature properties of metric spaces, without the need for a smooth structure. Besides coordinate invariance, its key features are scalability, computability, and robustness. We demonstrate that these properties continue to hold in the context of nonperturbative quantum gravity, by evaluating the quantum Ricci curvature numerically in two-dimensional Euclidean quantum gravity, defined in terms of dynamical triangulations. Despite the well-known, highly nonclassical properties of the underlying quantum geometry, its Ricci curvature can be matched well to that of a five-dimensional round sphere.

Adaptive Failure Compensation for Aircraft Tracking Control Using Engine Differential Based Model

NASA Technical Reports Server (NTRS)

Liu, Yu; Tang, Xidong; Tao, Gang; Joshi, Suresh M.

2006-01-01

An aircraft model that incorporates independently adjustable engine throttles and ailerons is employed to develop an adaptive control scheme in the presence of actuator failures. This model captures the key features of aircraft flight dynamics when in the engine differential mode. Based on this model an adaptive feedback control scheme for asymptotic state tracking is developed and applied to a transport aircraft model in the presence of two types of failures during operation, rudder failure and aileron failure. Simulation results are presented to demonstrate the adaptive failure compensation scheme.

Social-ecological resilience and law

USGS Publications Warehouse

Garmestani, Ahjond S.; Allen, Craig R.

2014-01-01

Environmental law envisions ecological systems as existing in an equilibrium state, reinforcing a rigid legal framework unable to absorb rapid environmental changes and innovations in sustainability. For the past four decades, “resilience theory,” which embraces uncertainty and nonlinear dynamics in complex adaptive systems, has provided a robust, invaluable foundation for sound environmental management. Reforming American law to incorporate this knowledge is the key to sustainability. This volume features top legal and resilience scholars speaking on resilience theory and its legal applications to climate change, biodiversity, national parks, and water law.

Self and world: large scale installations at science museums.

PubMed

Shimojo, Shinsuke

2008-01-01

This paper describes three examples of illusion installation in a science museum environment from the author's collaboration with the artist and architect. The installations amplify the illusory effects, such as vection (visually-induced sensation of self motion) and motion-induced blindness, to emphasize that perception is not just to obtain structure and features of objects, but rather to grasp the dynamic relationship between the self and the world. Scaling up the size and utilizing the live human body turned out to be keys for installations with higher emotional impact.

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

PubMed

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

The NASA/industry Design Analysis Methods for Vibrations (DAMVIBS) program: McDonnell-Douglas Helicopter Company achievements

NASA Technical Reports Server (NTRS)

Toossi, Mostafa; Weisenburger, Richard; Hashemi-Kia, Mostafa

1993-01-01

This paper presents a summary of some of the work performed by McDonnell Douglas Helicopter Company under NASA Langley-sponsored rotorcraft structural dynamics program known as DAMVIBS (Design Analysis Methods for VIBrationS). A set of guidelines which is applicable to dynamic modeling, analysis, testing, and correlation of both helicopter airframes and a large variety of structural finite element models is presented. Utilization of these guidelines and the key features of their applications to vibration modeling of helicopter airframes are discussed. Correlation studies with the test data, together with the development and applications of a set of efficient finite element model checkout procedures, are demonstrated on a large helicopter airframe finite element model. Finally, the lessons learned and the benefits resulting from this program are summarized.

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres.

PubMed

Ince, Robin A A; Jaworska, Katarzyna; Gross, Joachim; Panzeri, Stefano; van Rijsbergen, Nicola J; Rousselet, Guillaume A; Schyns, Philippe G

2016-08-22

A key to understanding visual cognition is to determine "where", "when", and "how" brain responses reflect the processing of the specific visual features that modulate categorization behavior-the "what". The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event. Reverse-correlation methods coupled with information-theoretic analyses revealed that visibility of the eyes influences face detection behavior. The N170 initially reflects coding of the behaviorally relevant eye contralateral to the sensor, followed by a causal communication of the other eye from the other hemisphere. These findings demonstrate that the deceptively simple N170 ERP hides a complex network information processing mechanism involving initial coding and subsequent cross-hemispheric transfer of visual features. © The Author 2016. Published by Oxford University Press.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

PubMed

Martins, João M; Ramos, Rui M; Pimenta, António C; Moreira, Irina S

2014-03-01

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set. Copyright © 2013 Wiley Periodicals, Inc.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

PubMed

Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

2016-01-01

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

Linking spatially distributed biogeochemical data with a two-host life-cycle pathogen:A model of whirling disease dynamics in salmonid fishes in the Intermountain West

NASA Astrophysics Data System (ADS)

Fytilis, N.; Lamb, R.; Stevens, L.; Morrissey, L. A.; Kerans, B.; Rizzo, D. M.

2010-12-01

Fish diseases are often caused by waterborne parasites, making them ideal systems for modeling the non-linear relationships between biogeochemical features and disease dynamics. Myxobolus cerebralis, the causative agent of whirling disease, has been a major contributor to the loss of wild rainbow trout populations in numerous streams within the Intermountain West (Colorado, Idaho, Montana, Utah, Wyoming). The parasite alternates between an invertebrate and vertebrate host, being transmitted between the sediment feeding worm T.Tubifex and salmonid fishes. A greater understanding of the linkage between biological stream integrity, geomorphic features, water quality parameters and whirling disease risk is needed to improve current management techniques. Biodiversity and abundance of the worm communities are influenced by biogeochemical features and linked to disease severity in fish. We collected and identified ~700 worms from eight sites using molecular genetic probes and a taxonomic key. Additionally, ~1700 worms were identified using only a taxonomic key. Our work examines the links between worm community structure and biogeochemical features. We use a modified Self-Organizing-Map (SOM), which is a non-parametric clustering method based on an artificial neural network (ANN). Clustering methods are particularly attractive for exploratory data analyses because they do not require either the target number of groupings or the data structure be specified at the outset. ANN clustering methods have been shown to be more robust and to account for more data variability than traditional methods when applied to clustering geo-hydrochemical and microbiological datasets. The SOM highlights spatial variation of worm community structure between sites; and is used in tandem with expert knowledge (Lamb and Kerans) of local worm communities and a Madison River, MT physiochemical dataset (GIS-derived layers, water quality parameters). We iteratively clustered the physiochemical data and then compared the resulting groups to site-specific worm community structures. The SOM mined patterns from this highly dimensional data and produced 2-D visualizations of the data clusters. This process, in concert with iterative feedback with stream ecologists, led to the adaptation of new nonlinear relations and suggests new subsets of input parameters that guide the next round of SOM simulations, expand the pool of concepts, hone existing hypotheses, generate new hypotheses, and so on. The methodologies developed here helped mine the relationship between dominant biogeochemical features and the distribution of an alternative host of a vertebrate disease. This collaboration between modelers, field ecologists and geneticists will prove useful in guiding future data gathering and modeling efforts. (i.e., identifying missing data gaps and sampling frequency), and will enable more effective, high-volume hypothesis generation that, in turn, will better guide complex experimental designs providing integrated understanding of disease dynamics.

Diagnostic methodology for incipient system disturbance based on a neural wavelet approach

NASA Astrophysics Data System (ADS)

Won, In-Ho

Since incipient system disturbances are easily mixed up with other events or noise sources, the signal from the system disturbance can be neglected or identified as noise. Thus, as available knowledge and information is obtained incompletely or inexactly from the measurements; an exploration into the use of artificial intelligence (AI) tools to overcome these uncertainties and limitations was done. A methodology integrating the feature extraction efficiency of the wavelet transform with the classification capabilities of neural networks is developed for signal classification in the context of detecting incipient system disturbances. The synergistic effects of wavelets and neural networks present more strength and less weakness than either technique taken alone. A wavelet feature extractor is developed to form concise feature vectors for neural network inputs. The feature vectors are calculated from wavelet coefficients to reduce redundancy and computational expense. During this procedure, the statistical features based on the fractal concept to the wavelet coefficients play a role as crucial key in the wavelet feature extractor. To verify the proposed methodology, two applications are investigated and successfully tested. The first involves pump cavitation detection using dynamic pressure sensor. The second pertains to incipient pump cavitation detection using signals obtained from a current sensor. Also, through comparisons between three proposed feature vectors and with statistical techniques, it is shown that the variance feature extractor provides a better approach in the performed applications.

A daily global mesoscale ocean eddy dataset from satellite altimetry.

PubMed

Faghmous, James H; Frenger, Ivy; Yao, Yuanshun; Warmka, Robert; Lindell, Aron; Kumar, Vipin

2015-01-01

Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993-2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System.

Music, Brain Plasticity and the Resilience: the Pillars of New Receptive Therapy.

PubMed

Dukić, Helena

2018-04-01

This paper describes a new type of receptive music therapy which aims to build the patients' psychological resilience by increasing the levels of dopamine, serotonin and oxytocin in order to increase standard psychopharmacological treatment efficiency. Previous research concerning the musically induced production of the two neurotransmitters and a hormone is discussed and reviewed. Based upon the existent studies concerning the influence of music on dopamine, serotonin and oxytocin induction, a new design of specific music features for this purpose is proposed and elaborated upon. The music features are numerically described using Music Information Retrieval software in order to objectivise the otherwise intuitively chosen music elements such as event density (number of notes started in one second of time), tempo, harmonic rhythm (number of harmonies changes in one second), dynamics, key changes and roughness coefficient (level of sensory dissonance). Finally, the new concept of resilience enhancing therapy is proposed and defined using the music features described above.

A daily global mesoscale ocean eddy dataset from satellite altimetry

PubMed Central

Faghmous, James H.; Frenger, Ivy; Yao, Yuanshun; Warmka, Robert; Lindell, Aron; Kumar, Vipin

2015-01-01

Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993–2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System. PMID:26097744

Towards Cloud-based Asynchronous Elasticity for Iterative HPC Applications

NASA Astrophysics Data System (ADS)

da Rosa Righi, Rodrigo; Facco Rodrigues, Vinicius; André da Costa, Cristiano; Kreutz, Diego; Heiss, Hans-Ulrich

2015-10-01

Elasticity is one of the key features of cloud computing. It allows applications to dynamically scale computing and storage resources, avoiding over- and under-provisioning. In high performance computing (HPC), initiatives are normally modeled to handle bag-of-tasks or key-value applications through a load balancer and a loosely-coupled set of virtual machine (VM) instances. In the joint-field of Message Passing Interface (MPI) and tightly-coupled HPC applications, we observe the need of rewriting source codes, previous knowledge of the application and/or stop-reconfigure-and-go approaches to address cloud elasticity. Besides, there are problems related to how profit this new feature in the HPC scope, since in MPI 2.0 applications the programmers need to handle communicators by themselves, and a sudden consolidation of a VM, together with a process, can compromise the entire execution. To address these issues, we propose a PaaS-based elasticity model, named AutoElastic. It acts as a middleware that allows iterative HPC applications to take advantage of dynamic resource provisioning of cloud infrastructures without any major modification. AutoElastic provides a new concept denoted here as asynchronous elasticity, i.e., it provides a framework to allow applications to either increase or decrease their computing resources without blocking the current execution. The feasibility of AutoElastic is demonstrated through a prototype that runs a CPU-bound numerical integration application on top of the OpenNebula middleware. The results showed the saving of about 3 min at each scaling out operations, emphasizing the contribution of the new concept on contexts where seconds are precious.

Examples of Mathematical Modeling

PubMed Central

Johnston, Matthew D.; Edwards, Carina M.; Bodmer, Walter F.; Maini, Philip K.; Chapman, S. Jonathan

2008-01-01

Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis. We use the cell population model by Johnston et al.5 to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt. We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters. PMID:17873520

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

PubMed

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

Key Program Features to Enhance the School-to-Career Transition for Youth with Disabilities

ERIC Educational Resources Information Center

Doren, Bonnie; Yan, Min-Chi; Tu, Wei-Mo

2013-01-01

The purpose of the article was to identify key features within research-based school-to-career programs that were linked to positive employment outcomes for youth disabilities. Three key program features were identified and discussed that could be incorporated into the practices and programs of schools and communities to support the employment…

Biased ART: a neural architecture that shifts attention toward previously disregarded features following an incorrect prediction.

PubMed

Carpenter, Gail A; Gaddam, Sai Chaitanya

2010-04-01

Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Two-dimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features

PubMed Central

Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T.

2016-01-01

Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer’s disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may be useful for monitoring disease progression over time or evaluating therapeutic interventions. PMID:27445790

Dynamics of a broad-band quantum cascade laser: from chaos to coherent dynamics and mode-locking

NASA Astrophysics Data System (ADS)

Columbo, L. L.; Barbieri, S.; Sirtori, C.; Brambilla, M.

2018-02-01

The dynamics of a multimode Quantum Cascade Laser, is studied in a model based on effective semiconductor Maxwell-Bloch equations, encompassing key features for the radiationmedium interaction such as an asymmetric, frequency dependent, gain and refractive index as well as the phase-amplitude coupling provided by the Henry factor. By considering the role of the free spectral range and Henry factor, we develop criteria suitable to identify the conditions which allow to destabilize, close to threshold, the traveling wave emitted by the laser and lead to chaotic or regular multimode dynamics. In the latter case our simulations show that the field oscillations are associated to self-confined structures which travel along the laser cavity, bridging mode-locking and solitary wave propagation. In addition, we show how a RF modulation of the bias current leads to active mode-locking yielding high-contrast, picosecond pulses. Our results compare well with recent experiments on broad-band THz-QCLs and may help understanding the conditions for the generation of ultrashort pulses and comb operation in Mid-IR and THz spectral regions

New Insights on Insect's Silent Flight. Part I: Vortex Dynamics and Wing Morphing

NASA Astrophysics Data System (ADS)

Ren, Yan; Liu, Geng; Dong, Haibo; Geng, Biao; Zheng, Xudong; Xue, Qian

2016-11-01

Insects are capable of conducting silent flights. This is attributed to its specially designed wing material properties for the control of vibration and surface morphing during the flapping flight. In current work, we focus on the roles of dynamic wing morphing on the unsteady vortex dynamics of a cicada in steady flight. A 3D image-based surface reconstruction method is used to obtain kinematical and morphological data of cicada wings from high-quality high-speed videos. The observed morphing wing kinematics is highly complex and a singular value decomposition method is used to decompose the wing motion to several dominant modes with distinct motion features. A high-fidelity immersed-boundary-based flow solver is then used to study the vortex dynamics in details. The results show that vortical structures closely relate to the morphing mode, which plays key role in the development and attachment of leading-edge vortex (LEV), thus helps the silent flapping of the cicada wings. This work is supported by AFOSR FA9550-12-1-0071 and NSF CBET-1313217.

Consensus Emerging from the Bottom-up: the Role of Cognitive Variables in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Giardini, Francesca; Vilone, Daniele; Conte, Rosaria

2015-09-01

The study of opinions - e.g., their formation and change, and their effects on our society - by means of theoretical and numerical models has been one of the main goals of sociophysics until now, but it is one of the defining topics addressed by social psychology and complexity science. Despite the flourishing of different models and theories, several key questions still remain unanswered. The aim of this paper is to provide a cognitively grounded computational model of opinions in which they are described as mental representations and defined in terms of distinctive mental features. We also define how these representations change dynamically through different processes, describing the interplay between mental and social dynamics of opinions. We present two versions of the model, one with discrete opinions (voter model-like), and one with continuous ones (Deffuant-like). By means of numerical simulations, we compare the behaviour of our cognitive model with the classical sociophysical models, and we identify interesting differences in the dynamics of consensus for each of the models considered.

Neural basis for dynamic updating of object representation in visual working memory.

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

Gait ataxia in humans: vestibular and cerebellar control of dynamic stability.

PubMed

Schniepp, Roman; Möhwald, Ken; Wuehr, Max

2017-10-01

During human locomotion, vestibular feedback control is fundamental for maintaining dynamic stability and adapting the gait pattern to external circumstances. Within the supraspinal locomotor network, the cerebellum represents the key site for the integration of vestibular feedback information. The cerebellum is further important for the fine-tuning and coordination of limb movements during walking. The aim of this review article is to highlight the shared structural and functional sensorimotor principles in vestibular and cerebellar locomotion control. Vestibular feedback for the maintenance of dynamic stability is integrated into the locomotor pattern via midline, caudal cerebellar structures (vermis, flocculonodular lobe). Hemispheric regions of the cerebellum facilitate feed-forward control of multi-joint coordination and higher locomotor functions. Characteristic features of the gait disorder in patients with vestibular deficits or cerebellar ataxia are increased levels of spatiotemporal gait variability in the fore-aft and the medio-lateral gait dimension. In the fore-aft dimension, pathologic increases of gait fluctuations critically depend on the locomotion speed and predominantly manifest during slow walking velocities. This feature is associated with an increased risk of falls in both patients with vestibular hypofunction as well as patients with cerebellar ataxia. Pharmacological approaches for the treatment of vestibular or cerebellar gait ataxia are currently not available. However, new promising options are currently tested in randomized, controlled trials (fampridine/FACEG; acetyl-DL-leucine/ALCAT).

A survey of hybrid Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

2018-04-01

This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

Specific features of goal setting in road traffic safety

NASA Astrophysics Data System (ADS)

Kolesov, V. I.; Danilov, O. F.; Petrov, A. I.

2017-10-01

Road traffic safety (RTS) management is inherently a branch of cybernetics and therefore requires clear formalization of the task. The paper aims at identification of the specific features of goal setting in RTS management under the system approach. The paper presents the results of cybernetic modeling of the cause-to-effect mechanism of a road traffic accident (RTA); in here, the mechanism itself is viewed as a complex system. A designed management goal function is focused on minimizing the difficulty in achieving the target goal. Optimization of the target goal has been performed using the Lagrange principle. The created working algorithms have passed the soft testing. The key role of the obtained solution in the tactical and strategic RTS management is considered. The dynamics of the management effectiveness indicator has been analyzed based on the ten-year statistics for Russia.

Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies.

PubMed

Patel, Shivani; Modi, Palmi; Chhabria, Mahesh

2018-05-01

Caspase-1 is a key endoprotease responsible for the post-translational processing of pro-inflammatory cytokines IL-1β, 18 & 33. Excessive secretion of IL-1β leads to numerous inflammatory and autoimmune diseases. Thus caspase-1 inhibition would be considered as an important therapeutic strategy for development of newer anti-inflammatory agents. Here we have employed an integrated virtual screening by combining pharmacophore mapping and docking to identify small molecules as caspase-1 inhibitors. The ligand based 3D pharmacophore model was generated having the essential structural features of (HBA, HY & RA) using a data set of 27 compounds. A validated pharmacophore hypothesis (Hypo 1) was used to screen ZINC and Minimaybridge chemical databases. The retrieved virtual hits were filtered by ADMET properties and molecular docking analysis. Subsequently, the cross-docking study was also carried out using crystal structure of caspase-1, 3, 7 and 8 to identify the key residual interaction for specific caspase-1 inhibition. Finally, the best mapped and top scored (ZINC00885612, ZINC72003647, BTB04175 and BTB04410) molecules were subjected to molecular dynamics simulation for accessing the dynamic structure of protein after ligand binding. This study identifies the most promising hits, which can be leads for the development of novel caspase-1 inhibitors as anti-inflammatory agents. Copyright © 2018 Elsevier Inc. All rights reserved.

ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.

PubMed

Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind; Chennubhotla, S Chakra

2018-05-08

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Electric-field assisted spin torque nano-oscillator and binary frequency shift keying modulation

NASA Astrophysics Data System (ADS)

Zhang, Xiangli; Chen, Hao-Hsuan; Zhang, Zongzhi; Liu, Yaowen

2018-04-01

Electric-controlled magnetization precession introduces technologically relevant possibility for developing spin torque nano-oscillators (STNO) with potential applications in microwave emission. Using the perpendicularly magnetized magnetic tunnel junction (MTJ), we show that the magnetization oscillation frequency can be tuned by the co-action of electric field and spin polarized current. The dynamical phase diagram of MTJ-based STNO is analytically predicted through coordinate transformation from the laboratory frame to the rotation frame, by which the nonstationary out-of-plane magnetization precession process is therefore transformed into the stationary process in the rotation frame. Furthermore, using this STNO as a microwave source, we numerically demonstrate that the bit signal can be transmitted by a binary frequency shift keying (BFSK) modulation technique. The BFSK scheme shows good modulation features with no transient state.

[How to produce a video to promote HIV testing in men who have sex with men?].

PubMed

Menacho, Luis A; Blas, Magaly M

2015-01-01

The aim of the study was to describe the process of designing and producing a video to promote HIV testing in Peruvian men who have sex with men (MSM). The process involved the following steps: identification of the theories of behavior change; identifying key messages and video features; developing a script that would captivate the target audience; working with an experienced production company; and piloting the video. A video with everyday situations of risk associated with HIV infection was the one preferred by participants. Key messages identified, and theoretical constructs models chosen were used to create the video scenes. Participants identified with the main, 9 minute video which they considered to be clear and dynamic. It is necessary to work with the target population to design a video according to their preferences.

Land and Law in Marijuana Country: Clean Capital, Dirty Money, and the Drug War's Rentier Nexus.

PubMed

Polson, Michael

2013-11-01

Despite its ongoing federal illegality, marijuana production has become a licit, or socially accepted, feature of northern California's real estate market. As such, marijuana is a key component of land values and the laundering of "illegal" wealth into legitimate circulation. By following land transaction practices, relations, and instruments, this article shows how formally equal property transactions become substantively unequal in light of the "il/legal" dynamics of marijuana land use. As marijuana becomes licit, prohibitionist policies have enabled the capture of ground rent by landed interests from the marijuana industry at a time when the price of marijuana is declining (in part due to its increasing licitness). The resulting "drug war rentier nexus," a state-land-finance complex, is becoming a key, if obscured, component within marijuana's contemporary political economy.

A Hierarchical and Dynamic Seascape Framework for Scaling and Comparing Ocean Biodiversity Observations

NASA Astrophysics Data System (ADS)

Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.

2016-02-01

The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.

Swimming motility plays a key role in the stochastic dynamics of cell clumping

NASA Astrophysics Data System (ADS)

Qi, Xianghong; Nellas, Ricky B.; Byrn, Matthew W.; Russell, Matthew H.; Bible, Amber N.; Alexandre, Gladys; Shen, Tongye

2013-04-01

Dynamic cell-to-cell interactions are a prerequisite to many biological processes, including development and biofilm formation. Flagellum induced motility has been shown to modulate the initial cell-cell or cell-surface interaction and to contribute to the emergence of macroscopic patterns. While the role of swimming motility in surface colonization has been analyzed in some detail, a quantitative physical analysis of transient interactions between motile cells is lacking. We examined the Brownian dynamics of swimming cells in a crowded environment using a model of motorized adhesive tandem particles. Focusing on the motility and geometry of an exemplary motile bacterium Azospirillum brasilense, which is capable of transient cell-cell association (clumping), we constructed a physical model with proper parameters for the computer simulation of the clumping dynamics. By modulating mechanical interaction (‘stickiness’) between cells and swimming speed, we investigated how equilibrium and active features affect the clumping dynamics. We found that the modulation of active motion is required for the initial aggregation of cells to occur at a realistic time scale. Slowing down the rotation of flagellar motors (and thus swimming speeds) is correlated to the degree of clumping, which is consistent with the experimental results obtained for A. brasilense.

Compact Conformations of Human Protein Disulfide Isomerase

PubMed Central

Cui, Lei; Ding, Xiang; Niu, Lili; Yang, Fuquan; Wang, Chao; Wang, Chih-chen; Lou, Jizhong

2014-01-01

Protein disulfide isomerase (PDI) composed of four thioredoxin-like domains a, b, b', and a', is a key enzyme catalyzing oxidative protein folding in the endoplasmic reticulum. Large scale molecular dynamics simulations starting from the crystal structures of human PDI (hPDI) in the oxidized and reduced states were performed. The results indicate that hPDI adopts more compact conformations in solution than in the crystal structures, which are stabilized primarily by inter-domain interactions, including the salt bridges between domains a and b' observed for the first time. A prominent feature of the compact conformations is that the two catalytic domains a and a' can locate close enough for intra-molecular electron transfer, which was confirmed by the characterization of an intermediate with a disulfide between the two domains. Mutations, which disrupt the inter-domain interactions, lead to decreased reductase activity of hPDI. Our molecular dynamics simulations and biochemical experiments reveal the intrinsic conformational dynamics of hPDI and its biological impact. PMID:25084354

Universal Hitting Time Statistics for Integrable Flows

NASA Astrophysics Data System (ADS)

Dettmann, Carl P.; Marklof, Jens; Strömbergsson, Andreas

2017-02-01

The perceived randomness in the time evolution of "chaotic" dynamical systems can be characterized by universal probabilistic limit laws, which do not depend on the fine features of the individual system. One important example is the Poisson law for the times at which a particle with random initial data hits a small set. This was proved in various settings for dynamical systems with strong mixing properties. The key result of the present study is that, despite the absence of mixing, the hitting times of integrable flows also satisfy universal limit laws which are, however, not Poisson. We describe the limit distributions for "generic" integrable flows and a natural class of target sets, and illustrate our findings with two examples: the dynamics in central force fields and ellipse billiards. The convergence of the hitting time process follows from a new equidistribution theorem in the space of lattices, which is of independent interest. Its proof exploits Ratner's measure classification theorem for unipotent flows, and extends earlier work of Elkies and McMullen.

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

DOE PAGES

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; ...

2017-08-14

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmentalmore » breathing studies. In conclusion, we implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.« less

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

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

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmentalmore » breathing studies. In conclusion, we implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.« less

Fluid Dynamics of Human Phonation and Speech

NASA Astrophysics Data System (ADS)

Mittal, Rajat; Erath, Byron D.; Plesniak, Michael W.

2013-01-01

This article presents a review of the fluid dynamics, flow-structure interactions, and acoustics associated with human phonation and speech. Our voice is produced through the process of phonation in the larynx, and an improved understanding of the underlying physics of this process is essential to advancing the treatment of voice disorders. Insights into the physics of phonation and speech can also contribute to improved vocal training and the development of new speech compression and synthesis schemes. This article introduces the key biomechanical features of the laryngeal physiology, reviews the basic principles of voice production, and summarizes the progress made over the past half-century in understanding the flow physics of phonation and speech. Laryngeal pathologies, which significantly enhance the complexity of phonatory dynamics, are discussed. After a thorough examination of the state of the art in computational modeling and experimental investigations of phonatory biomechanics, we present a synopsis of the pacing issues in this arena and an outlook for research in this fascinating subject.

Nature of Interactions between PEO-PPO-PEO Triblock Copolymers and Lipid Membranes: (I) The Effect of Polymer Hydrophobicity on Its Ability to Protect Liposomes from Peroxidation

PubMed Central

Wang, Jia-Yu; Marks, Jeremy; Lee, Ka Yee C.

2013-01-01

PEO-PPO-PEO triblock copolymers have opposing effects on lipid membrane integrity- they can behave either as membrane sealants or as membrane permeabilizers. To gain insights into their biomembrane activities, the fundamental interactions between a series of PEO-based polymers and phospholipid vesicles were investigated. Specifically, the effect of copolymer hydrophobicity on its ability to prevent liposomes from peroxidation was evaluated, and partitioning free energy and coefficient involved in the interactions were derived. Our results show that the high degree of hydrophilicity is a key feature of the copolymers that can effectively protect liposomes from peroxidation and the protective effect of the copolymers stems from their adsorption at the membrane surface without penetrating into the bilayer core. The origin of this protective effect induced by polymer absorption is attributed to the retardation of membrane hydration dynamics, which is further illustrated in the accompany study on dynamic nuclear polarization (DNP)-derived hydration dynamics1. PMID:22808900

A plasma source driven predator-prey like mechanism as a potential cause of spiraling intermittencies in linear plasma devices

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

Reiser, D.; Ohno, N.; Tanaka, H.

2014-03-15

Three-dimensional global drift fluid simulations are carried out to analyze coherent plasma structures appearing in the NAGDIS-II linear device (nagoya divertor plasma Simulator-II). The numerical simulations reproduce several features of the intermittent spiraling structures observed, for instance, statistical properties, rotation frequency, and the frequency of plasma expulsion. The detailed inspection of the three-dimensional plasma dynamics allows to identify the key mechanism behind the formation of these intermittent events. The resistive coupling between electron pressure and parallel electric field in the plasma source region gives rise to a quasilinear predator-prey like dynamics where the axisymmetric mode represents the prey and themore » spiraling structure with low azimuthal mode number represents the predator. This interpretation is confirmed by a reduced one-dimensional quasilinear model derived on the basis of the findings in the full three-dimensional simulations. The dominant dynamics reveals certain similarities to the classical Lotka-Volterra cycle.« less

From microporous regular frameworks to mesoporous materials with ultrahigh surface area: dynamic reorganization of porous polymer networks.

PubMed

Kuhn, Pierre; Forget, Aurélien; Su, Dangsheng; Thomas, Arne; Antonietti, Markus

2008-10-08

High surface area organic materials featuring both micro- and mesopores were synthesized under ionothermal conditions via the formation of polyaryltriazine networks. While the polytrimerization of nitriles in zinc chloride at 400 degrees C produces microporous polymers, higher reaction temperatures induce the formation of additional spherical mesopores with a narrow dispersity. The nitrogen-rich carbonaceous polymer materials thus obtained present surface areas and porosities up to 3300 m(2) g(-1) and 2.4 cm(3) g(-1), respectively. The key point of this synthesis relies on the occurrence of several high temperature polymerization reactions, where irreversible carbonization reactions coupled with the reversible trimerization of nitriles allow the reorganization of the dynamic triazine network. The ZnCl2 molten salt fulfills the requirement of a high temperature solvent, but is also required as catalyst. Thus, this dynamic polymerization system provides not only highly micro- and mesoporous materials, but also allows controlling the pore structure in amorphous organic materials.

Decrypting the structural, dynamic, and energetic basis of a monomeric kinesin interacting with a tubulin dimer in three ATPase states by all-atom molecular dynamics simulation.

PubMed

Chakraborty, Srirupa; Zheng, Wenjun

2015-01-27

We have employed molecular dynamics (MD) simulation to investigate, with atomic details, the structural dynamics and energetics of three major ATPase states (ADP, APO, and ATP state) of a human kinesin-1 monomer in complex with a tubulin dimer. Starting from a recently solved crystal structure of ATP-like kinesin-tubulin complex by the Knossow lab, we have used flexible fitting of cryo-electron-microscopy maps to construct new structural models of the kinesin-tubulin complex in APO and ATP state, and then conducted extensive MD simulations (total 400 ns for each state), followed by flexibility analysis, principal component analysis, hydrogen bond analysis, and binding free energy analysis. Our modeling and simulation have revealed key nucleotide-dependent changes in the structure and flexibility of the nucleotide-binding pocket (featuring a highly flexible and open switch I in APO state) and the tubulin-binding site, and allosterically coupled motions driving the APO to ATP transition. In addition, our binding free energy analysis has identified a set of key residues involved in kinesin-tubulin binding. On the basis of our simulation, we have attempted to address several outstanding issues in kinesin study, including the possible roles of β-sheet twist and neck linker docking in regulating nucleotide release and binding, the structural mechanism of ADP release, and possible extension and shortening of α4 helix during the ATPase cycle. This study has provided a comprehensive structural and dynamic picture of kinesin's major ATPase states, and offered promising targets for future mutational and functional studies to investigate the molecular mechanism of kinesin motors.

Computational study of the activity, dynamics, energetics and conformations of insulin analogues using molecular dynamics simulations: Application to hyperinsulinemia and the critical residue B26.

PubMed

Papaioannou, Anastasios; Kuyucak, Serdar; Kuncic, Zdenka

2017-09-01

Due to the increasing prevalence of diabetes, finding therapeutic analogues for insulin has become an urgent issue. While many experimental studies have been performed towards this end, they have limited scope to examine all aspects of the effect of a mutation. Computational studies can help to overcome these limitations, however, relatively few studies that focus on insulin analogues have been performed to date. Here, we present a comprehensive computational study of insulin analogues-three mutant insulins that have been identified with hyperinsulinemia and three mutations on the critical B26 residue that exhibit similar binding affinity to the insulin receptor-using molecular dynamics simulations with the aim of predicting how mutations of insulin affect its activity, dynamics, energetics and conformations. The time evolution of the conformers is studied in long simulations. The probability density function and potential of mean force calculations are performed on each insulin analogue to unravel the effect of mutations on the dynamics and energetics of insulin activation. Our conformational study can decrypt the key features and molecular mechanisms that are responsible for an enhanced or reduced activity of an insulin analogue. We find two key results: 1) hyperinsulinemia may be due to the drastically reduced activity (and binding affinity) of the mutant insulins. 2) Y26 B S and Y26 B E are promising therapeutic candidates for insulin as they are more active than WT-insulin. The analysis in this work can be readily applied to any set of mutations on insulin to guide development of more effective therapeutic analogues.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling.

PubMed

Zheng, Wenjun

2017-02-01

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

A combined coarse-grained and all-atom simulation of TRPV1 channel gating and heat activation

PubMed Central

Qin, Feng

2015-01-01

The transient receptor potential (TRP) channels act as key sensors of various chemical and physical stimuli in eukaryotic cells. Despite years of study, the molecular mechanisms of TRP channel activation remain unclear. To elucidate the structural, dynamic, and energetic basis of gating in TRPV1 (a founding member of the TRPV subfamily), we performed coarse-grained modeling and all-atom molecular dynamics (MD) simulation based on the recently solved high resolution structures of the open and closed form of TRPV1. Our coarse-grained normal mode analysis captures two key modes of collective motions involved in the TRPV1 gating transition, featuring a quaternary twist motion of the transmembrane domains (TMDs) relative to the intracellular domains (ICDs). Our transition pathway modeling predicts a sequence of structural movements that propagate from the ICDs to the TMDs via key interface domains (including the membrane proximal domain and the C-terminal domain), leading to sequential opening of the selectivity filter followed by the lower gate in the channel pore (confirmed by modeling conformational changes induced by the activation of ICDs). The above findings of coarse-grained modeling are robust to perturbation by lipids. Finally, our MD simulation of the ICD identifies key residues that contribute differently to the nonpolar energy of the open and closed state, and these residues are predicted to control the temperature sensitivity of TRPV1 gating. These computational predictions offer new insights to the mechanism for heat activation of TRPV1 gating, and will guide our future electrophysiology and mutagenesis studies. PMID:25918362

Key Management Scheme Based on Route Planning of Mobile Sink in Wireless Sensor Networks.

PubMed

Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming; Chen, Wei

2016-01-29

In many wireless sensor network application scenarios the key management scheme with a Mobile Sink (MS) should be fully investigated. This paper proposes a key management scheme based on dynamic clustering and optimal-routing choice of MS. The concept of Traveling Salesman Problem with Neighbor areas (TSPN) in dynamic clustering for data exchange is proposed, and the selection probability is used in MS route planning. The proposed scheme extends static key management to dynamic key management by considering the dynamic clustering and mobility of MSs, which can effectively balance the total energy consumption during the activities. Considering the different resources available to the member nodes and sink node, the session key between cluster head and MS is established by modified an ECC encryption with Diffie-Hellman key exchange (ECDH) algorithm and the session key between member node and cluster head is built with a binary symmetric polynomial. By analyzing the security of data storage, data transfer and the mechanism of dynamic key management, the proposed scheme has more advantages to help improve the resilience of the key management system of the network on the premise of satisfying higher connectivity and storage efficiency.

Three-dimensional magnetohydrodynamical simulation of expanding magnetic flux ropes

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

Arnold, L.; Dreher, J.; Grauer, R.

Three-dimensional, time-dependent numerical simulations of the dynamics of magnetic flux ropes are presented. The simulations are targeted towards an experiment previously conducted at California Institute of Technology [P. M. Bellan and J. F. Hansen, Phys. Plasmas 5, 1991 (1998)] which aimed at simulating solar prominence eruptions in the laboratory. The plasma dynamics is described by ideal magnetohydrodynamics using different models for the evolution of the mass density. The initial current distribution represents the situation at the plasma creation phase, while it is not increased during the simulation. Key features of the reported experimental observations like pinching of the current loop,more » its expansion and distortion into helical shape are reproduced in the numerical simulations. Details of the final structure depend on the choice of a specific model for the mass density.« less

Perceiving patterns of play in dynamic sport tasks: investigating the essential information underlying skilled performance.

PubMed

Willams, A Mark; Hodges, Nicola J; North, Jamie S; Barton, Gabor

2006-01-01

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.

Physiologically relevant organs on chips

PubMed Central

Yum, Kyungsuk; Hong, Soon Gweon; Lee, Luke P.

2015-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or organs on chips, that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue–tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. PMID:24357624

Interactions of social, terrestrial, and marine sub-systems in the Galapagos Islands, Ecuador.

PubMed

Walsh, Stephen J; Mena, Carlos F

2016-12-20

Galapagos is often cited as an example of the conflicts that are emerging between resource conservation and economic development in island ecosystems, as the pressures associated with tourism threaten nature, including the iconic and emblematic species, unique terrestrial landscapes, and special marine environments. In this paper, two projects are described that rely upon dynamic systems models and agent-based models to examine human-environment interactions. We use a theoretical context rooted in complexity theory to guide the development of our models that are linked to social-ecological dynamics. The goal of this paper is to describe key elements, relationships, and processes to inform and enhance our understanding of human-environment interactions in the Galapagos Islands of Ecuador. By formalizing our knowledge of how systems operate and the manner in which key elements are linked in coupled human-natural systems, we specify rules, relationships, and rates of exchange between social and ecological features derived through statistical functions and/or functions specified in theory or practice. The processes described in our models also have practical applications in that they emphasize how political policies generate different human responses and model outcomes, many detrimental to the social-ecological sustainability of the Galapagos Islands.

Revealing the distinct folding phases of an RNA three-helix junction.

PubMed

Plumridge, Alex; Katz, Andrea M; Calvey, George D; Elber, Ron; Kirmizialtin, Serdal; Pollack, Lois

2018-05-14

Remarkable new insight has emerged into the biological role of RNA in cells. RNA folding and dynamics enable many of these newly discovered functions, calling for an understanding of RNA self-assembly and conformational dynamics. Because RNAs pass through multiple structures as they fold, an ensemble perspective is required to visualize the flow through fleetingly populated sets of states. Here, we combine microfluidic mixing technology and small angle X-ray scattering (SAXS) to measure the Mg-induced folding of a small RNA domain, the tP5abc three helix junction. Our measurements are interpreted using ensemble optimization to select atomically detailed structures that recapitulate each experimental curve. Structural ensembles, derived at key stages in both time-resolved studies and equilibrium titrations, reproduce the features of known intermediates, and more importantly, offer a powerful new structural perspective on the time-progression of folding. Distinct collapse phases along the pathway appear to be orchestrated by specific interactions with Mg ions. These key interactions subsequently direct motions of the backbone that position the partners of tertiary contacts for later bonding, and demonstrate a remarkable synergy between Mg and RNA across numerous time-scales.

An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations

NASA Astrophysics Data System (ADS)

Xia, Xilin; Liang, Qiuhua; Ming, Xiaodong; Hou, Jingming

2017-05-01

Numerical models solving the full 2-D shallow water equations (SWEs) have been increasingly used to simulate overland flows and better understand the transient flow dynamics of flash floods in a catchment. However, there still exist key challenges that have not yet been resolved for the development of fully dynamic overland flow models, related to (1) the difficulty of maintaining numerical stability and accuracy in the limit of disappearing water depth and (2) inaccurate estimation of velocities and discharges on slopes as a result of strong nonlinearity of friction terms. This paper aims to tackle these key research challenges and present a new numerical scheme for accurately and efficiently modeling large-scale transient overland flows over complex terrains. The proposed scheme features a novel surface reconstruction method (SRM) to correctly compute slope source terms and maintain numerical stability at small water depth, and a new implicit discretization method to handle the highly nonlinear friction terms. The resulting shallow water overland flow model is first validated against analytical and experimental test cases and then applied to simulate a hypothetic rainfall event in the 42 km2 Haltwhistle Burn, UK.

Interactions of social, terrestrial, and marine sub-systems in the Galapagos Islands, Ecuador

PubMed Central

Walsh, Stephen J.; Mena, Carlos F.

2016-01-01

Galapagos is often cited as an example of the conflicts that are emerging between resource conservation and economic development in island ecosystems, as the pressures associated with tourism threaten nature, including the iconic and emblematic species, unique terrestrial landscapes, and special marine environments. In this paper, two projects are described that rely upon dynamic systems models and agent-based models to examine human–environment interactions. We use a theoretical context rooted in complexity theory to guide the development of our models that are linked to social–ecological dynamics. The goal of this paper is to describe key elements, relationships, and processes to inform and enhance our understanding of human–environment interactions in the Galapagos Islands of Ecuador. By formalizing our knowledge of how systems operate and the manner in which key elements are linked in coupled human–natural systems, we specify rules, relationships, and rates of exchange between social and ecological features derived through statistical functions and/or functions specified in theory or practice. The processes described in our models also have practical applications in that they emphasize how political policies generate different human responses and model outcomes, many detrimental to the social–ecological sustainability of the Galapagos Islands. PMID:27791072

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

Development and application of a new grey dynamic hierarchy analysis system (GDHAS) for evaluating urban ecological security.

PubMed

Shao, Chaofeng; Tian, Xiaogang; Guan, Yang; Ju, Meiting; Xie, Qiang

2013-05-21

Selecting indicators based on the characteristics and development trends of a given study area is essential for building a framework for assessing urban ecological security. However, few studies have focused on how to select the representative indicators systematically, and quantitative research is lacking. We developed an innovative quantitative modeling approach called the grey dynamic hierarchy analytic system (GDHAS) for both the procedures of indicator selection and quantitative assessment of urban ecological security. Next, a systematic methodology based on the GDHAS is developed to assess urban ecological security comprehensively and dynamically. This assessment includes indicator selection, driving force-pressure-state-impact-response (DPSIR) framework building, and quantitative evaluation. We applied this systematic methodology to assess the urban ecological security of Tianjin, which is a typical coastal super megalopolis and the industry base in China. This case study highlights the key features of our approach. First, 39 representative indicators are selected for the evaluation index system from 62 alternative ones available through the GDHAS. Second, the DPSIR framework is established based on the indicators selected, and the quantitative assessment of the eco-security of Tianjin is conducted. The results illustrate the following: urban ecological security of Tianjin in 2008 was in alert level but not very stable; the driving force and pressure subsystems were in good condition, but the eco-security levels of the remainder of the subsystems were relatively low; the pressure subsystem was the key to urban ecological security; and 10 indicators are defined as the key indicators for five subsystems. These results can be used as the basis for urban eco-environmental management.

Striking Plasticity of CRISPR-Cas9 and Key Role of Non-target DNA, as Revealed by Molecular Simulations.

PubMed

Palermo, Giulia; Miao, Yinglong; Walker, Ross C; Jinek, Martin; McCammon, J Andrew

2016-10-26

The CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system recently emerged as a transformative genome-editing technology that is innovating basic bioscience and applied medicine and biotechnology. The endonuclease Cas9 associates with a guide RNA to match and cleave complementary sequences in double stranded DNA, forming an RNA:DNA hybrid and a displaced non-target DNA strand. Although extensive structural studies are ongoing, the conformational dynamics of Cas9 and its interplay with the nucleic acids during association and DNA cleavage are largely unclear. Here, by employing multi-microsecond time scale molecular dynamics, we reveal the conformational plasticity of Cas9 and identify key determinants that allow its large-scale conformational changes during nucleic acid binding and processing. We show how the "closure" of the protein, which accompanies nucleic acid binding, fundamentally relies on highly coupled and specific motions of the protein domains, collectively initiating the prominent conformational changes needed for nucleic acid association. We further reveal a key role of the non-target DNA during the process of activation of the nuclease HNH domain, showing how the nontarget DNA positioning triggers local conformational changes that favor the formation of a catalytically competent Cas9. Finally, a remarkable conformational plasticity is identified as an intrinsic property of the HNH domain, constituting a necessary element that allows for the HNH repositioning. These novel findings constitute a reference for future experimental studies aimed at a full characterization of the dynamic features of the CRISPR-Cas9 system, and-more importantly-call for novel structure engineering efforts that are of fundamental importance for the rational design of new genome-engineering applications.

Development and Application of a New Grey Dynamic Hierarchy Analysis System (GDHAS) for Evaluating Urban Ecological Security

PubMed Central

Shao, Chaofeng; Tian, Xiaogang; Guan, Yang; Ju, Meiting; Xie, Qiang

2013-01-01

Selecting indicators based on the characteristics and development trends of a given study area is essential for building a framework for assessing urban ecological security. However, few studies have focused on how to select the representative indicators systematically, and quantitative research is lacking. We developed an innovative quantitative modeling approach called the grey dynamic hierarchy analytic system (GDHAS) for both the procedures of indicator selection and quantitative assessment of urban ecological security. Next, a systematic methodology based on the GDHAS is developed to assess urban ecological security comprehensively and dynamically. This assessment includes indicator selection, driving force-pressure-state-impact-response (DPSIR) framework building, and quantitative evaluation. We applied this systematic methodology to assess the urban ecological security of Tianjin, which is a typical coastal super megalopolis and the industry base in China. This case study highlights the key features of our approach. First, 39 representative indicators are selected for the evaluation index system from 62 alternative ones available through the GDHAS. Second, the DPSIR framework is established based on the indicators selected, and the quantitative assessment of the eco-security of Tianjin is conducted. The results illustrate the following: urban ecological security of Tianjin in 2008 was in alert level but not very stable; the driving force and pressure subsystems were in good condition, but the eco-security levels of the remainder of the subsystems were relatively low; the pressure subsystem was the key to urban ecological security; and 10 indicators are defined as the key indicators for five subsystems. These results can be used as the basis for urban eco-environmental management. PMID:23698700

Early stages of collapsing pentacene crystal by Au

NASA Astrophysics Data System (ADS)

Ihm, Kyuwook; Chung, Sukmin; Kang, Tai-Hee; Cheong, Sang-Wook

2008-10-01

The characteristic feature of metal contacts with gold on organics is deterioration of the organic crystals during the contact formation. The unveiled key challenge is to probe dynamic details of the microscopic evolution of the organic crystal when the atomic Au is introduced. Here, we report how the collapse of the pentacene crystal is initiated even by a few Au atoms. Our results indicate that the gentle decoupling of intra and intermolecular π-π interactions causes the localization of the lowest unoccupied molecular orbital as well as the removal of cohesive forces between molecules, leading to the subsequent crystal collapse.

Dynamic occupancy models for explicit colonization processes

USGS Publications Warehouse

Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

2016-01-01

The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

A series of active flow control experiments were recently conducted at high Reynolds numbers on a generic separated configuration. The model simulates the upper surface of a 20% thick Glauert-Goldschmied type airfoil at zero angle of attack. The flow is fully turbulent since the tunnel sidewall boundary layer flows over the model. The main motivation for the experiments is to generate a comprehensive data base for validation of unsteady numerical simulation as a first step in the development of a CFD design tool, without which it would not be possible to effectively utilize the great potential of unsteady flow control. This paper focuses on the dynamics of several key features of the baseline as well as the controlled flow. It was found that the thickness of the upstream boundary layer has a negligible effect on the flow dynamics. It is speculated that separation is caused mainly by the highly convex surface while viscous effects are less important. The two-dimensional separated flow contains unsteady waves centered on a reduced frequency of 0.9, while in the three dimensional separated flow, frequencies around a reduced frequency of 0.3 and 1 are active. Several scenarios of resonant wave interaction take place at the separated shear-layer and in the pressure recovery region. The unstable reduced frequency bands for periodic excitation are centered on 1.5 and 5, but these reduced frequencies are based on the length of the baseline bubble that shortens due to the excitation. The conventional works well for the coherent wave features. Reproduction of these dynamic effects by a numerical simulation would provide benchmark validation.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Towards a taxonomy for integrated care: a mixed-methods study

PubMed Central

Valentijn, Pim P.; Boesveld, Inge C.; van der Klauw, Denise M.; Ruwaard, Dirk; Struijs, Jeroen N.; Molema, Johanna J.W.; Bruijnzeels, Marc A.; Vrijhoef, Hubertus JM.

2015-01-01

Introduction Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. Methods First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. Results The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. Discussion This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective. PMID:25759607

Towards a taxonomy for integrated care: a mixed-methods study.

PubMed

Valentijn, Pim P; Boesveld, Inge C; van der Klauw, Denise M; Ruwaard, Dirk; Struijs, Jeroen N; Molema, Johanna J W; Bruijnzeels, Marc A; Vrijhoef, Hubertus Jm

2015-01-01

Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective.

Computer simulations of channel meandering and the formation of point bars: Linking channel dynamics to the preserved stratigraphy

NASA Astrophysics Data System (ADS)

Sun, T.; Covault, J. A.; Pyrcz, M.; Sullivan, M.

2012-12-01

Meandering rivers are probably one of the most recognizable geomorphic features on earth. As they meander across alluvial and delta plains, channels migrate laterally and develop point bars, splays, levees and other geomorphic and sedimentary features that compose substantial portions of the fill within many sedimentary basins. These basins can include hydrocarbon producing fields. Therefore, a good understanding of the processes of meandering channels and their associated deposits is critical for exploiting these reservoirs in the subsurface. In the past couple of decades, significant progress has been made in our understanding of the morphodynamics of channel meandering. Basic fluid dynamics and sediment transport (Ikeda and Parker, 1981; Howard, 1992) has shown that many characteristic features of meandering rivers, such as the meandering wavelength, growth rate and downstream migration rate, can be predicted quantitatively. As a result, a number of variations and improvement of the theory have emerged (e.g., Blondeaux and Seminara, 1985; Parker and Andrews, 1985, 1986; and Sun et al., 2001a, b).The main improvements include the recognition of so called "bar-bend" interactions, where the development of bars on the channel bed and their interactions with the channel bend is recognized as a primary cause for meandering channels to develop greater complexity than the classic goose-neck meander bend shapes, such as compound bend. Recently, Sun and others have shown that the spatial patterns of width variations in meandering channels can be explained by an extrinsic periodic flow variations coupled with the intrinsic bend instability dynamics. In contrast to the significant improvement of our understanding of channel meandering, little work has been done to link the geomorphic features of meandering channels to the geometry and heterogeneity of the deposits they form and ultimately preserves. A computer simulation model based on the work of Sun and others (1996, 2001a,b) is used to investigate the formation and preservation of point bars with meandering rivers. Rather than consisting of a single set of concentric scroll bar like feature as one would expect from the pattern of meandering channels, observations of point bar deposits in map view reveal the previously mentioned complexity in their internal organization. A preserved point bar deposit is often found to be composed of multiple sets of remnant scroll bar like features, each with different orientations. Each set is bounded by the unconformity resulting from one set of the scroll bar like feature truncated by the other set. This study links the channel dynamics to the preserved point bar architectures, and delineates the key controls that affect the point bar internal organization.

Edge states in the climate system: exploring global instabilities and critical transitions

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Bódai, Tamás

2017-07-01

Multistability is a ubiquitous feature in systems of geophysical relevance and provides key challenges for our ability to predict a system’s response to perturbations. Near critical transitions small causes can lead to large effects and—for all practical purposes—irreversible changes in the properties of the system. As is well known, the Earth climate is multistable: present astronomical and astrophysical conditions support two stable regimes, the warm climate we live in, and a snowball climate characterized by global glaciation. We first provide an overview of methods and ideas relevant for studying the climate response to forcings and focus on the properties of critical transitions in the context of both stochastic and deterministic dynamics, and assess strengths and weaknesses of simplified approaches to the problem. Following an idea developed by Eckhardt and collaborators for the investigation of multistable turbulent fluid dynamical systems, we study the global instability giving rise to the snowball/warm multistability in the climate system by identifying the climatic edge state, a saddle embedded in the boundary between the two basins of attraction of the stable climates. The edge state attracts initial conditions belonging to such a boundary and, while being defined by the deterministic dynamics, is the gate facilitating noise-induced transitions between competing attractors. We use a simplified yet Earth-like intermediate complexity climate model constructed by coupling a primitive equations model of the atmosphere with a simple diffusive ocean. We refer to the climatic edge states as Melancholia states and provide an extensive analysis of their features. We study their dynamics, their symmetry properties, and we follow a complex set of bifurcations. We find situations where the Melancholia state has chaotic dynamics. In these cases, we have that the basin boundary between the two basins of attraction is a strange geometric set with a nearly zero codimension, and relate this feature to the time scale separation between instabilities occurring on weather and climatic time scales. We also discover a new stable climatic state that is similar to a Melancholia state and is characterized by non-trivial symmetry properties.

Integration of nanoscale memristor synapses in neuromorphic computing architectures

NASA Astrophysics Data System (ADS)

Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis

2013-09-01

Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.

Core signalling motif displaying multistability through multi-state enzymes.

PubMed

Feng, Song; Sáez, Meritxell; Wiuf, Carsten; Feliu, Elisenda; Soyer, Orkun S

2016-10-01

Bistability, and more generally multistability, is a key system dynamics feature enabling decision-making and memory in cells. Deciphering the molecular determinants of multistability is thus crucial for a better understanding of cellular pathways and their (re)engineering in synthetic biology. Here, we show that a key motif found predominantly in eukaryotic signalling systems, namely a futile signalling cycle, can display bistability when featuring a two-state kinase. We provide necessary and sufficient mathematical conditions on the kinetic parameters of this motif that guarantee the existence of multiple steady states. These conditions foster the intuition that bistability arises as a consequence of competition between the two states of the kinase. Extending from this result, we find that increasing the number of kinase states linearly translates into an increase in the number of steady states in the system. These findings reveal, to our knowledge, a new mechanism for the generation of bistability and multistability in cellular signalling systems. Further the futile cycle featuring a two-state kinase is among the smallest bistable signalling motifs. We show that multi-state kinases and the described competition-based motif are part of several natural signalling systems and thereby could enable them to implement complex information processing through multistability. These results indicate that multi-state kinases in signalling systems are readily exploited by natural evolution and could equally be used by synthetic approaches for the generation of multistable information processing systems at the cellular level. © 2016 The Authors.

Optical Flow Estimation for Flame Detection in Videos

PubMed Central

Mueller, Martin; Karasev, Peter; Kolesov, Ivan; Tannenbaum, Allen

2014-01-01

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise. PMID:23613042

Highlights in asthma 2005.

PubMed

Heraghty, J L; Henderson, A J

2006-05-01

It is usual at the end of a year for top tens to feature large in our collective consciousness. These inevitably include the occasional controversial selection and without fail will overlook a number of gems, whether in the field of literature, art, or science. The approaches to such compilations include personal selections, convening expert committees through to letting the market decide. However, it is well recognised that experts can be wrong and markets distorted. A novel approach to identifying the key publications in the field of medicine, Faculty of 1000 Medicine (http://www.f1000medicine.com), uses faculty evaluations to assign ratings to published papers within topics and categories, bringing a flavour of the dynamism of post hoc peer review to biological sciences that exists in other fields of scholarship. Archives of Disease in Childhood has also developed a market led system of peer evaluation through its web based top ten most read articles feature.

Molecular Memory of Morphologies by Septins during Neuron Generation Allows Early Polarity Inheritance.

PubMed

Boubakar, Leila; Falk, Julien; Ducuing, Hugo; Thoinet, Karine; Reynaud, Florie; Derrington, Edmund; Castellani, Valérie

2017-08-16

Transmission of polarity established early during cell lineage history is emerging as a key process guiding cell differentiation. Highly polarized neurons provide a fascinating model to study inheritance of polarity over cell generations and across morphological transitions. Neural crest cells (NCCs) migrate to the dorsal root ganglia to generate neurons directly or after cell divisions in situ. Using live imaging of vertebrate embryo slices, we found that bipolar NCC progenitors lose their polarity, retracting their processes to round for division, but generate neurons with bipolar morphology by emitting processes from the same locations as the progenitor. Monitoring the dynamics of Septins, which play key roles in yeast polarity, indicates that Septin 7 tags process sites for re-initiation of process growth following mitosis. Interfering with Septins blocks this mechanism. Thus, Septins store polarity features during mitotic rounding so that daughters can reconstitute the initial progenitor polarity. Copyright © 2017 Elsevier Inc. All rights reserved.

Laplace-Runge-Lenz vector in quantum mechanics in noncommutative space

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

Gáliková, Veronika; Kováčik, Samuel; Prešnajder, Peter

2013-12-15

The main point of this paper is to examine a “hidden” dynamical symmetry connected with the conservation of Laplace-Runge-Lenz vector (LRL) in the hydrogen atom problem solved by means of non-commutative quantum mechanics (NCQM). The basic features of NCQM will be introduced to the reader, the key one being the fact that the notion of a point, or a zero distance in the considered configuration space, is abandoned and replaced with a “fuzzy” structure in such a way that the rotational invariance is preserved. The main facts about the conservation of LRL vector in both classical and quantum theory willmore » be reviewed. Finally, we will search for an analogy in the NCQM, provide our results and their comparison with the QM predictions. The key notions we are going to deal with are non-commutative space, Coulomb-Kepler problem, and symmetry.« less

Land and Law in Marijuana Country: Clean Capital, Dirty Money, and the Drug War’s Rentier Nexus

PubMed Central

Polson, Michael

2015-01-01

Despite its ongoing federal illegality, marijuana production has become a licit, or socially accepted, feature of northern California’s real estate market. As such, marijuana is a key component of land values and the laundering of “illegal” wealth into legitimate circulation. By following land transaction practices, relations, and instruments, this article shows how formally equal property transactions become substantively unequal in light of the “il/legal” dynamics of marijuana land use. As marijuana becomes licit, prohibitionist policies have enabled the capture of ground rent by landed interests from the marijuana industry at a time when the price of marijuana is declining (in part due to its increasing licitness). The resulting “drug war rentier nexus,” a state–land–finance complex, is becoming a key, if obscured, component within marijuana’s contemporary political economy. PMID:26594104

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

Sandhill crane roost selection, human disturbance, and forage resources

USGS Publications Warehouse

Pearse, Aaron T.; Krapu, Gary; Brandt, David

2017-01-01

Sites used for roosting represent a key habitat requirement for many species of birds because availability and quality of roost sites can influence individual fitness. Birds select roost sites based on numerous factors, requirements, and motivations, and selection of roosts can be dynamic in time and space because of various ecological and environmental influences. For sandhill cranes (Antigone canadensis) at their main spring-staging area along the Platte River in south-central Nebraska, USA, past investigations of roosting cranes focused on physical channel characteristics related to perceived security as motivating roost distribution. We used 6,310 roost sites selected by 313 sandhill cranes over 5 spring migration seasons (2003–2007) to quantify resource selection functions of roost sites on the central Platte River using a discrete choice analysis. Sandhill cranes generally showed stronger selection for wider channels with shorter bank vegetation situated farther from potential human disturbance features such as roads, bridges, and dwellings. Furthermore, selection for roost sites with preferable physical characteristics (wide channels with short bank vegetation) was more resilient to nearby disturbance features than more narrow channels with taller bank vegetation. The amount of cornfields surrounding sandhill crane roost sites positively influenced relative probability of use but only for more narrow channels < 100 m and those with shorter bank vegetation. We confirmed key resource features that sandhill cranes selected at river channels along the Platte River, and after incorporating spatial variation due to human disturbance, our understanding of roost site selection was more robust, providing insights on how disturbance may interact with physical habitat features. Managers can use information on roost-site selection when developing plans to increase probability of crane use at existing roost sites and to identify new areas for potential use if existing sites become limited.

A free-access online key to identify Amazonian ferns.

PubMed

Zuquim, Gabriela; Tuomisto, Hanna; Prado, Jefferson

2017-01-01

There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp.

A free-access online key to identify Amazonian ferns

PubMed Central

Zuquim, Gabriela; Tuomisto, Hanna; Prado, Jefferson

2017-01-01

Abstract There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp. PMID:28781548

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

Individualized grid-enabled mammographic training system

NASA Astrophysics Data System (ADS)

Yap, M. H.; Gale, A. G.

2009-02-01

The PERFORMS self-assessment scheme measures individuals skills in identifying key mammographic features on sets of known cases. One aspect of this is that it allows radiologists' skills to be trained, based on their data from this scheme. Consequently, a new strategy is introduced to provide revision training based on mammographic features that the radiologist has had difficulty with in these sets. To do this requires a lot of random cases to provide dynamic, unique, and up-to-date training modules for each individual. We propose GIMI (Generic Infrastructure in Medical Informatics) middleware as the solution to harvest cases from distributed grid servers. The GIMI middleware enables existing and legacy data to support healthcare delivery, research, and training. It is technology-agnostic, data-agnostic, and has a security policy. The trainee examines each case, indicating the location of regions of interest, and completes an evaluation form, to determine mammographic feature labelling, diagnosis, and decisions. For feedback, the trainee can choose to have immediate feedback after examining each case or batch feedback after examining a number of cases. All the trainees' result are recorded in a database which also contains their trainee profile. A full report can be prepared for the trainee after they have completed their training. This project demonstrates the practicality of a grid-based individualised training strategy and the efficacy in generating dynamic training modules within the coverage/outreach of the GIMI middleware. The advantages and limitations of the approach are discussed together with future plans.

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

Uncertainty Quantification in Alchemical Free Energy Methods.

PubMed

Bhati, Agastya P; Wan, Shunzhou; Hu, Yuan; Sherborne, Brad; Coveney, Peter V

2018-06-12

Alchemical free energy methods have gained much importance recently from several reports of improved ligand-protein binding affinity predictions based on their implementation using molecular dynamics simulations. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are available, each claimed to be better than the others in its own way. However, the key features of reproducibility and quantification of associated uncertainties in such methods have barely been discussed. Here, we apply a systematic protocol for uncertainty quantification to a number of popular alchemical free energy methods, covering both absolute and relative free energy predictions. We show that a reliable measure of error estimation is provided by ensemble simulation-an ensemble of independent MD simulations-which applies irrespective of the free energy method. The need to use ensemble methods is fundamental and holds regardless of the duration of time of the molecular dynamics simulations performed.

Antibiotic-induced changes in the microbiota disrupt redox dynamics in the gut

PubMed Central

Reese, Aspen T; Cho, Eugenia H; Klitzman, Bruce; Nichols, Scott P; Wisniewski, Natalie A; Villa, Max M; Durand, Heather K; Jiang, Sharon; Midani, Firas S; Nimmagadda, Sai N; O'Connell, Thomas M; Wright, Justin P; Deshusses, Marc A

2018-01-01

How host and microbial factors combine to structure gut microbial communities remains incompletely understood. Redox potential is an important environmental feature affected by both host and microbial actions. We assessed how antibiotics, which can impact host and microbial function, change redox state and how this contributes to post-antibiotic succession. We showed gut redox potential increased within hours of an antibiotic dose in mice. Host and microbial functioning changed under treatment, but shifts in redox potentials could be attributed specifically to bacterial suppression in a host-free ex vivo human gut microbiota model. Redox dynamics were linked to blooms of the bacterial family Enterobacteriaceae. Ecological succession to pre-treatment composition was associated with recovery of gut redox, but also required dispersal from unaffected gut communities. As bacterial competition for electron acceptors can be a key ecological factor structuring gut communities, these results support the potential for manipulating gut microbiota through managing bacterial respiration. PMID:29916366

Effects of the amino acid sequence on thermal conduction through β-sheet crystals of natural silk protein.

PubMed

Zhang, Lin; Bai, Zhitong; Ban, Heng; Liu, Ling

2015-11-21

Recent experiments have discovered very different thermal conductivities between the spider silk and the silkworm silk. Decoding the molecular mechanisms underpinning the distinct thermal properties may guide the rational design of synthetic silk materials and other biomaterials for multifunctionality and tunable properties. However, such an understanding is lacking, mainly due to the complex structure and phonon physics associated with the silk materials. Here, using non-equilibrium molecular dynamics, we demonstrate that the amino acid sequence plays a key role in the thermal conduction process through β-sheets, essential building blocks of natural silks and a variety of other biomaterials. Three representative β-sheet types, i.e. poly-A, poly-(GA), and poly-G, are shown to have distinct structural features and phonon dynamics leading to different thermal conductivities. A fundamental understanding of the sequence effects may stimulate the design and engineering of polymers and biopolymers for desired thermal properties.

Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

PubMed

Takahashi, Yuma; Kagawa, Kotaro; Svensson, Erik I; Kawata, Masakado

2014-07-18

The effect of evolutionary changes in traits and phenotypic/genetic diversity on ecological dynamics has received much theoretical attention; however, the mechanisms and ecological consequences are usually unknown. Female-limited colour polymorphism in damselflies is a counter-adaptation to male mating harassment, and thus, is expected to alter population dynamics through relaxing sexual conflict. Here we show the side effect of the evolution of female morph diversity on population performance (for example, population productivity and sustainability) in damselflies. Our theoretical model incorporating key features of the sexual interaction predicts that the evolution of increased phenotypic diversity will reduce overall fitness costs to females from sexual conflict, which in turn will increase productivity, density and stability of a population. Field data and mesocosm experiments support these model predictions. Our study suggests that increased phenotypic diversity can enhance population performance that can potentially reduce extinction rates and thereby influence macroevolutionary processes.

Exploiting bistable oscillator subharmonics for magnified broadband vibration energy harvesting

NASA Astrophysics Data System (ADS)

Huguet, Thomas; Badel, Adrien; Lallart, Mickaël

2017-10-01

Recent research on primary battery alternatives for supplying autonomous wireless devices has recently highlighted the advantages of nonlinear oscillators' dynamics and more particularly bistable oscillators' behavior for ambient vibration harvesting. The key property of bistable oscillators compared to linear ones is their enhanced operational frequency bandwidth under harmonic excitation, potentially leading to a better adaptation to the environment. However, the classical frequency response characterization of such devices does not reveal all the possible dynamic behaviors offered by bistable oscillators. Thus, subharmonic motions are experimentally investigated in this letter, and their energy harvesting potential as well as their ability to enhance the bistable generator bandwidth is evaluated. The results obtained with a generator integrating buckled beams for the bistability feature show that, in addition to the commonly considered harmonic behavior, subharmonics allow widening of the useful operating frequency band of the bistable microgenerator by 180% compared to the sole exploitation of the first harmonic motion.

Structural and dynamic features of HLA-B27 subtypes.

PubMed

Uchanska-Ziegler, Barbara; Ziegler, Andreas; Schmieder, Peter

2013-07-01

The differential association of HLA-B27 subtypes with ankylosing spondylitis provides the rationale for a comparative investigation of these proteins. Results from the last 2 years of research on minimally distinct HLA-B27 subtypes, primarily using biochemical and biophysical techniques, are presented and discussed. We summarize evidence that micropolymorphisms within the molecules' peptide-binding groove influence wide-ranging biochemical, biophysical and antigenic properties of HLA-B27 molecules, and suggest that distinct, subtype and peptide-dependent dynamics of peptide - heavy chain - β(2)-microglobulin heterotrimers could be instrumental for an understanding of the initiation of disease processes that are connected with certain HLA-B27 subtypes. The results indicate that mAbs that bind only to structurally distinguishable subsets of HLA-B27 molecules as well as techniques that assess the flexibility of these antigens may hold the key to comprehend molecular events contributing to the initial stages of disease pathogenesis in spondyloarthropathies.

The evolution of stable magnetic fields in stars: an analytical approach

NASA Astrophysics Data System (ADS)

Mestel, Leon; Moss, David

2010-07-01

The absence of a rigorous proof of the existence of dynamically stable, large-scale magnetic fields in radiative stars has been for many years a missing element in the fossil field theory for the magnetic Ap/Bp stars. Recent numerical simulations, by Braithwaite & Spruit and Braithwaite & Nordlund, have largely filled this gap, demonstrating convincingly that coherent global scale fields can survive for times of the order of the main-sequence lifetimes of A stars. These dynamically stable configurations take the form of magnetic tori, with linked poloidal and toroidal fields, that slowly rise towards the stellar surface. This paper studies a simple analytical model of such a torus, designed to elucidate the physical processes that govern its evolution. It is found that one-dimensional numerical calculations reproduce some key features of the numerical simulations, with radiative heat transfer, Archimedes' principle, Lorentz force and Ohmic decay all playing significant roles.

Population biological principles of drug-resistance evolution in infectious diseases.

PubMed

zur Wiesch, Pia Abel; Kouyos, Roger; Engelstädter, Jan; Regoes, Roland R; Bonhoeffer, Sebastian

2011-03-01

The emergence of resistant pathogens in response to selection pressure by drugs and their possible disappearance when drug use is discontinued are evolutionary processes common to many pathogens. Population biological models have been used to study the dynamics of resistance in viruses, bacteria, and eukaryotic microparasites both at the level of the individual treated host and of the treated host population. Despite the existence of generic features that underlie such evolutionary dynamics, different conclusions have been reached about the key factors affecting the rate of resistance evolution and how to best use drugs to minimise the risk of generating high levels of resistance. Improved understanding of generic versus specific population biological aspects will help to translate results between different studies, and allow development of a more rational basis for sustainable drug use than exists at present. Copyright © 2011 Elsevier Ltd. All rights reserved.

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources: Preprint

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higher-order dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higherorder dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Analyzing the dynamics of DNA replication in Mammalian cells using DNA combing.

PubMed

Bialic, Marta; Coulon, Vincent; Drac, Marjorie; Gostan, Thierry; Schwob, Etienne

2015-01-01

How cells duplicate their chromosomes is a key determinant of cell identity and genome stability. DNA replication can initiate from more than 100,000 sites distributed along mammalian chromosomes, yet a given cell uses only a subset of these origins due to inefficient origin activation and regulation by developmental or environmental cues. An impractical consequence of cell-to-cell variations in origin firing is that population-based techniques do not accurately describe how chromosomes are replicated in single cells. DNA combing is a biophysical DNA fiber stretching method which permits visualization of ongoing DNA synthesis along Mb-sized single-DNA molecules purified from cells that were previously pulse-labeled with thymidine analogues. This allows quantitative measurements of several salient features of chromosome replication dynamics, such as fork velocity, fork asymmetry, inter-origin distances, and global instant fork density. In this chapter we describe how to obtain this information from asynchronous cultures of mammalian cells.

FIR signature verification system characterizing dynamics of handwriting features

NASA Astrophysics Data System (ADS)

Thumwarin, Pitak; Pernwong, Jitawat; Matsuura, Takenobu

2013-12-01

This paper proposes an online signature verification method based on the finite impulse response (FIR) system characterizing time-frequency characteristics of dynamic handwriting features. First, the barycenter determined from both the center point of signature and two adjacent pen-point positions in the signing process, instead of one pen-point position, is used to reduce the fluctuation of handwriting motion. In this paper, among the available dynamic handwriting features, motion pressure and area pressure are employed to investigate handwriting behavior. Thus, the stable dynamic handwriting features can be described by the relation of the time-frequency characteristics of the dynamic handwriting features. In this study, the aforesaid relation can be represented by the FIR system with the wavelet coefficients of the dynamic handwriting features as both input and output of the system. The impulse response of the FIR system is used as the individual feature for a particular signature. In short, the signature can be verified by evaluating the difference between the impulse responses of the FIR systems for a reference signature and the signature to be verified. The signature verification experiments in this paper were conducted using the SUBCORPUS MCYT-100 signature database consisting of 5,000 signatures from 100 signers. The proposed method yielded equal error rate (EER) of 3.21% on skilled forgeries.

Key features of an EU health information system: a concept mapping study.

PubMed

Rosenkötter, Nicole; Achterberg, Peter W; van Bon-Martens, Marja J H; Michelsen, Kai; van Oers, Hans A M; Brand, Helmut

2016-02-01

Despite the acknowledged value of an EU health information system (EU-HISys) and the many achievements in this field, the landscape is still heavily fragmented and incomplete. Through a systematic analysis of the opinions and valuations of public health stakeholders, this study aims to conceptualize key features of an EU-HISys. Public health professionals and policymakers were invited to participate in a concept mapping procedure. First, participants (N = 34) formulated statements that reflected their vision of an EU-HISys. Second, participants (N = 28) rated the relative importance of each statement and grouped conceptually similar ones. Principal Component and cluster analyses were used to condense these results to EU-HISys key features in a concept map. The number of key features and the labelling of the concept map were determined by expert consensus. The concept map contains 10 key features that summarize 93 statements. The map consists of a horizontal axis that represents the relevance of an 'organizational strategy', which deals with the 'efforts' to design and develop an EU-HISys and the 'achievements' gained by a functioning EU-HISys. The vertical axis represents the 'professional orientation' of the EU-HISys, ranging from the 'scientific' through to the 'policy' perspective. The top ranking statement expressed the need to establish a system that is permanent and sustainable. The top ranking key feature focuses on data and information quality. This study provides insights into key features of an EU-HISys. The results can be used to guide future planning and to support the development of a health information system for Europe. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Defining competency-based evaluation objectives in family medicine

PubMed Central

Lawrence, Kathrine; Allen, Tim; Brailovsky, Carlos; Crichton, Tom; Bethune, Cheri; Donoff, Michel; Laughlin, Tom; Wetmore, Stephen; Carpentier, Marie-Pierre; Visser, Shaun

2011-01-01

Abstract Objective To develop key features for priority topics previously identified by the College of Family Physicians of Canada that, together with skill dimensions and phases of the clinical encounter, broadly describe competence in family medicine. Design Modified nominal group methodology, which was used to develop key features for each priority topic through an iterative process. Setting The College of Family Physicians of Canada. Participants An expert group of 7 family physicians and 1 educational consultant, all of whom had experience in assessing competence in family medicine. Group members represented the Canadian family medicine context with respect to region, sex, language, community type, and experience. Methods The group used a modified Delphi process to derive a detailed operational definition of competence, using multiple iterations until consensus was achieved for the items under discussion. The group met 3 to 4 times a year from 2000 to 2007. Main findings The group analyzed 99 topics and generated 773 key features. There were 2 to 20 (average 7.8) key features per topic; 63% of the key features focused on the diagnostic phase of the clinical encounter. Conclusion This project expands previous descriptions of the process of generating key features for assessment, and removes this process from the context of written examinations. A key-features analysis of topics focuses on higher-order cognitive processes of clinical competence. The project did not define all the skill dimensions of competence to the same degree, but it clearly identified those requiring further definition. This work generates part of a discipline-specific, competency-based definition of family medicine for assessment purposes. It limits the domain for assessment purposes, which is an advantage for the teaching and assessment of learners. A validation study on the content of this work would ensure that it truly reflects competence in family medicine. PMID:21998245

Collective Dynamics for Heterogeneous Networks of Theta Neurons

NASA Astrophysics Data System (ADS)

Luke, Tanushree

Collective behavior in neural networks has often been used as an indicator of communication between different brain areas. These collective synchronization and desynchronization patterns are also considered an important feature in understanding normal and abnormal brain function. To understand the emergence of these collective patterns, I create an analytic model that identifies all such macroscopic steady-states attainable by a network of Type-I neurons. This network, whose basic unit is the model "theta'' neuron, contains a mixture of excitable and spiking neurons coupled via a smooth pulse-like synapse. Applying the Ott-Antonsen reduction method in the thermodynamic limit, I obtain a low-dimensional evolution equation that describes the asymptotic dynamics of the macroscopic mean field of the network. This model can be used as the basis in understanding more complicated neuronal networks when additional dynamical features are included. From this reduced dynamical equation for the mean field, I show that the network exhibits three collective attracting steady-states. The first two are equilibrium states that both reflect partial synchronization in the network, whereas the third is a limit cycle in which the degree of network synchronization oscillates in time. In addition to a comprehensive identification of all possible attracting macro-states, this analytic model permits a complete bifurcation analysis of the collective behavior of the network with respect to three key network features: the degree of excitability of the neurons, the heterogeneity of the population, and the overall coupling strength. The network typically tends towards the two macroscopic equilibrium states when the neuron's intrinsic dynamics and the network interactions reinforce each other. In contrast, the limit cycle state, bifurcations, and multistability tend to occur when there is competition between these network features. I also outline here an extension of the above model where the neurons' excitability now varies in time sinuosoidally, thus simulating a parabolic bursting network. This time-varying excitability can lead to the emergence of macroscopic chaos and multistability in the collective behavior of the network. Finally, I expand the single population model described above to examine a two-population neuronal network where each population has its own unique mixture of excitable and spiking neurons, as well as its own coupling strength (either excitatory or inhibitory in nature). Specifically, I consider the situation where the first population is only allowed to influence the second population without any feedback, thus effectively creating a feed-forward "driver-response" system. In this special arrangement, the driver's asymptotic macroscopic dynamics are fully explored in the comprehensive analysis of the single population. Then, in the presence of an influence from the driver, the modified dynamics of the second population, which now acts as a response population, can also be fully analyzed. As in the time-varying model, these modifications give rise to richer dynamics to the response population than those found from the single population formalism, including multi-periodicity and chaos.

Stigmergic construction and topochemical information shape ant nest architecture

PubMed Central

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

2016-01-01

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

Stigmergic construction and topochemical information shape ant nest architecture.

PubMed

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

2016-02-02

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

Star formation and ISM morphology in tidally induced spiral structures

NASA Astrophysics Data System (ADS)

Pettitt, Alex R.; Tasker, Elizabeth J.; Wadsley, James W.; Keller, Ben W.; Benincasa, Samantha M.

2017-07-01

Tidal encounters are believed to be one of the key drivers of galactic spiral structure in the Universe. Such spirals are expected to produce different morphological and kinematic features compared to density wave and dynamic spiral arms. In this work, we present high-resolution simulations of a tidal encounter of a small mass companion with a disc galaxy. Included are the effects of gas cooling and heating, star formation and stellar feedback. The structure of the perturbed disc differs greatly from the isolated galaxy, showing clear spiral features that act as sites of new star formation, and displaying interarm spurs. The two arms of the galaxy, the bridge and tail, appear to behave differently; with different star formation histories and structure. Specific attention is focused on offsets between gas and stellar spiral features which can be directly compared to observations. We find that some offsets do exist between different media, with gaseous arms appearing mostly on the convex side of the stellar arms, though the exact locations appear highly time dependent. These results further highlight the differences between tidal spirals and other theories of arm structure.

Multi-rate DPSK optical transceivers for free-space applications

NASA Astrophysics Data System (ADS)

Caplan, D. O.; Carney, J. J.; Fitzgerald, J. J.; Gaschits, I.; Kaminsky, R.; Lund, G.; Hamilton, S. A.; Magliocco, R. J.; Murphy, R. J.; Rao, H. G.; Spellmeyer, N. W.; Wang, J. P.

2014-03-01

We describe a flexible high-sensitivity laser communication transceiver design that can significantly benefit performance and cost of NASA's satellite-based Laser Communications Relay Demonstration. Optical communications using differential phase shift keying, widely deployed for use in long-haul fiber-optic networks, is well known for its superior sensitivity and link performance over on-off keying, while maintaining a relatively straightforward design. However, unlike fiber-optic links, free-space applications often require operation over a wide dynamic range of power due to variations in link distance and channel conditions, which can include rapid kHz-class fading when operating through the turbulent atmosphere. Here we discuss the implementation of a robust, near-quantum-limited multi-rate DPSK transceiver, co-located transmitter and receiver subsystems that can operate efficiently over the highly-variable free-space channel. Key performance features will be presented on the master oscillator power amplifier (MOPA) based TX, including a wavelength-stabilized master laser, high-extinction-ratio burst-mode modulator, and 0.5 W single polarization power amplifier, as well as low-noise optically preamplified DSPK receiver and built-in test capabilities.

Activation amplitude and temporal synchrony among back extensor and abdominal muscles during a controlled transfer task: comparison of men and women.

PubMed

Hubley-Kozey, Cheryl L; Butler, Heather L; Kozey, John W

2012-08-01

Muscle synergies are important for spinal stability, but few studies examine temporal responses of spinal muscles to dynamic perturbations. This study examined activation amplitudes and temporal synergies among compartments of the back extensor and among abdominal wall muscles in response to dynamic bidirectional moments of force. We further examined whether responses were different between men and women. 19 women and 18 men performed a controlled transfer task. Surface electromyograms from bilateral sites over 6 back extensor compartments and 6 abdominal wall muscle sites were analyzed using principal component analysis. Key features were extracted from the measured electromyographic waveforms capturing amplitude and temporal variations among muscle sites. Three features explained 97% of the variance. Scores for each feature were computed for each measured waveform and analysis of variance found significant (p<.05) muscle main effects and a sex by muscle interaction. For the back extensors, post hoc analysis revealed that upper and more medial sites were recruited to higher amplitudes, medial sites responded to flexion moments, and the more lateral sites responded to lateral flexion moments. Women had more differences among muscle sites than men for the lateral flexion moment feature. For the abdominal wall muscles the oblique muscles responded with synergies related to fiber orientation, with women having higher amplitudes and more responsiveness to the lateral flexion moment than men. Synergies between the abdominal and back extensor sites as the moment demands change are discussed. These findings illustrate differential activation among erector spinae compartments and abdominal wall muscle sites supporting a highly organized pattern of response to bidirectional external moments with asynchronies more apparent in women. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatio-Temporal Dynamics of Field Cricket Calling Behaviour: Implications for Female Mate Search and Mate Choice.

PubMed

Nandi, Diptarup; Balakrishnan, Rohini

2016-01-01

Amount of calling activity (calling effort) is a strong determinant of male mating success in species such as orthopterans and anurans that use acoustic communication in the context of mating behaviour. While many studies in crickets have investigated the determinants of calling effort, patterns of variability in male calling effort in natural choruses remain largely unexplored. Within-individual variability in calling activity across multiple nights of calling can influence female mate search and mate choice strategies. Moreover, calling site fidelity across multiple nights of calling can also affect the female mate sampling strategy. We therefore investigated the spatio-temporal dynamics of acoustic signaling behaviour in a wild population of the field cricket species Plebeiogryllus guttiventris. We first studied the consistency of calling activity by quantifying variation in male calling effort across multiple nights of calling using repeatability analysis. Callers were inconsistent in their calling effort across nights and did not optimize nightly calling effort to increase their total number of nights spent calling. We also estimated calling site fidelity of males across multiple nights by quantifying movement of callers. Callers frequently changed their calling sites across calling nights with substantial displacement but without any significant directionality. Finally, we investigated trade-offs between within-night calling effort and energetically expensive calling song features such as call intensity and chirp rate. Calling effort was not correlated with any of the calling song features, suggesting that energetically expensive song features do not constrain male calling effort. The two key features of signaling behaviour, calling effort and call intensity, which determine the duration and spatial coverage of the sexual signal, are therefore uncorrelated and function independently.

Bloom Chasing With a Wave Glider: The MAGI (Mesoscale Features Aggregates Interaction) Project in the North Pacific

NASA Astrophysics Data System (ADS)

Wilson, C.; Villareal, T. A.; Anderson, E.

2015-12-01

Satellite ocean color data over the past decade has revealed the existence of large phytoplankton blooms in the North Pacific Ocean - specifically in the region NE of Hawai´I near 30°N. These blooms cover thousands of km2, persist for weeks or longer, and are often dominated by nitrogen-fixing diatom symbioses. These events have proven difficult to study outside of the time series station ALOHA at Hawai´i. The limited data indicates that the 30°N blooms are longer-lived, larger, and occur at a greater temperature range than the blooms that develop closer to Hawai´i. In the NE Pacific, at least some of these blooms occur at or near the subtropical front, a salinity-defined temperature compensated frontal zone that has a number of fronts imbedded in it. Here we will report on the results from the MAGI (Mesoscale features Aggregates Interaction) project. In this project, we deployed a Liquid Robotics SV2 Wave Glider® in June, 2015 for a multiple (up to 6) month mission to sample these features and assist in characterizing the bloom dynamics of this region. The Wave Gliders are the first unmanned autonomous marine robots to use only the ocean's wave energy for propulsion. The gliders are navigated remotely allowing a dynamic route through the keying of unique waypoints. Waypoints can be changed to sample features as they develop in the near-real time satellite imagery. The wave glider named Honey Badger is equipped with a CTD, two C3 fluorometers (one with an anti-biofouling coating applied), a Turner Designs PhytoFlash, meteorology and wave sensors, a downward facing camera, a Vengmar passive acoustic monitor, and a towed LISST-Holo.

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure.

PubMed

Simmering, Vanessa R; Wood, Chelsey M

2017-08-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Dynamics of a broad-band quantum cascade laser: from chaos to coherent dynamics and mode-locking.

PubMed

Columbo, L L; Barbieri, S; Sirtori, C; Brambilla, M

2018-02-05

The dynamics of a multimode quantum cascade laser, are studied in a model based on effective semiconductor Maxwell-Bloch equations, encompassing key features for the radiation-medium interaction such as an asymmetric frequency dependent gain and refractive index as well as the phase-amplitude coupling provided by the linewidth enhancement factor. By considering its role and that of the free spectral range, we find the conditions in which the traveling wave emitted by the laser at the threshold can be destabilized by adjacent modes, thus leading the laser emission towards chaotic or regular multimode dynamics. In the latter case our simulations show that the field oscillations are associated to self-confined structures which travel along the laser cavity, bridging mode-locking and solitary wave propagation. In addition, we show how a RF modulation of the bias current leads to active mode-locking yielding high-contrast, picosecond pulses. Our results compare well with recent experiments on broad-band THz-QCLs and may help in the understanding of the conditions for the generation of ultrashort pulses and comb operation in mid-IR and THz spectral regions.

Habituation based synaptic plasticity and organismic learning in a quantum perovskite.

PubMed

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; Li, Jiarui; Kang, Mingu; Mazzoli, Claudio; Zhou, Hua; Barbour, Andi; Wilkins, Stuart; Narayanan, Badri; Cherukara, Mathew; Zhang, Zhen; Sankaranarayanan, Subramanian K R S; Comin, Riccardo; Rabe, Karin M; Roy, Kaushik; Ramanathan, Shriram

2017-08-14

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.Habituation is a learning mechanism that enables control over forgetting and learning. Zuo, Panda et al., demonstrate adaptive synaptic plasticity in SmNiO 3 perovskites to address catastrophic forgetting in a dynamic learning environment via hydrogen-induced electron localization.

Hyper-resting brain entropy within chronic smokers and its moderation by Sex.

PubMed

Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze

2016-07-05

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers' brains, however less is known about the temporal dynamics within smokers' brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.

WINCS Harmoni: Closed-loop dynamic neurochemical control of therapeutic interventions

NASA Astrophysics Data System (ADS)

Lee, Kendall H.; Lujan, J. Luis; Trevathan, James K.; Ross, Erika K.; Bartoletta, John J.; Park, Hyung Ook; Paek, Seungleal Brian; Nicolai, Evan N.; Lee, Jannifer H.; Min, Hoon-Ki; Kimble, Christopher J.; Blaha, Charles D.; Bennet, Kevin E.

2017-04-01

There has been significant progress in understanding the role of neurotransmitters in normal and pathologic brain function. However, preclinical trials aimed at improving therapeutic interventions do not take advantage of real-time in vivo neurochemical changes in dynamic brain processes such as disease progression and response to pharmacologic, cognitive, behavioral, and neuromodulation therapies. This is due in part to a lack of flexible research tools that allow in vivo measurement of the dynamic changes in brain chemistry. Here, we present a research platform, WINCS Harmoni, which can measure in vivo neurochemical activity simultaneously across multiple anatomical targets to study normal and pathologic brain function. In addition, WINCS Harmoni can provide real-time neurochemical feedback for closed-loop control of neurochemical levels via its synchronized stimulation and neurochemical sensing capabilities. We demonstrate these and other key features of this platform in non-human primate, swine, and rodent models of deep brain stimulation (DBS). Ultimately, systems like the one described here will improve our understanding of the dynamics of brain physiology in the context of neurologic disease and therapeutic interventions, which may lead to the development of precision medicine and personalized therapies for optimal therapeutic efficacy.

A dynamical model of plasma turbulence in the solar wind

PubMed Central

Howes, G. G.

2015-01-01

A dynamical approach, rather than the usual statistical approach, is taken to explore the physical mechanisms underlying the nonlinear transfer of energy, the damping of the turbulent fluctuations, and the development of coherent structures in kinetic plasma turbulence. It is argued that the linear and nonlinear dynamics of Alfvén waves are responsible, at a very fundamental level, for some of the key qualitative features of plasma turbulence that distinguish it from hydrodynamic turbulence, including the anisotropic cascade of energy and the development of current sheets at small scales. The first dynamical model of kinetic turbulence in the weakly collisional solar wind plasma that combines self-consistently the physics of Alfvén waves with the development of small-scale current sheets is presented and its physical implications are discussed. This model leads to a simplified perspective on the nature of turbulence in a weakly collisional plasma: the nonlinear interactions responsible for the turbulent cascade of energy and the formation of current sheets are essentially fluid in nature, while the collisionless damping of the turbulent fluctuations and the energy injection by kinetic instabilities are essentially kinetic in nature. PMID:25848075

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Molecular dynamics simulations reveal the conformational dynamics of Arabidopsis thaliana BRI1 and BAK1 receptor-like kinases.

PubMed

Moffett, Alexander S; Bender, Kyle W; Huber, Steven C; Shukla, Diwakar

2017-07-28

The structural motifs responsible for activation and regulation of eukaryotic protein kinases in animals have been studied extensively in recent years, and a coherent picture of their activation mechanisms has begun to emerge. In contrast, non-animal eukaryotic protein kinases are not as well understood from a structural perspective, representing a large knowledge gap. To this end, we investigated the conformational dynamics of two key Arabidopsis thaliana receptor-like kinases, brassinosteroid-insensitive 1 (BRI1) and BRI1-associated kinase 1 (BAK1), through extensive molecular dynamics simulations of their fully phosphorylated kinase domains. Molecular dynamics simulations calculate the motion of each atom in a protein based on classical approximations of interatomic forces, giving researchers insight into protein function at unparalleled spatial and temporal resolutions. We found that in an otherwise "active" BAK1 the αC helix is highly disordered, a hallmark of deactivation, whereas the BRI1 αC helix is moderately disordered and displays swinging behavior similar to numerous animal kinases. An analysis of all known sequences in the A. thaliana kinome found that αC helix disorder may be a common feature of plant kinases. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Tangled nature model of evolutionary dynamics reconsidered: Structural and dynamical effects of trait inheritance

NASA Astrophysics Data System (ADS)

Andersen, Christian Walther; Sibani, Paolo

2016-05-01

Based on the stochastic dynamics of interacting agents which reproduce, mutate, and die, the tangled nature model (TNM) describes key emergent features of biological and cultural ecosystems' evolution. While trait inheritance is not included in many applications, i.e., the interactions of an agent and those of its mutated offspring are taken to be uncorrelated, in the family of TNMs introduced in this work correlations of varying strength are parametrized by a positive integer K . We first show that the interactions generated by our rule are nearly independent of K . Consequently, the structural and dynamical effects of trait inheritance can be studied independently of effects related to the form of the interactions. We then show that changing K strengthens the core structure of the ecology, leads to population abundance distributions better approximated by log-normal probability densities, and increases the probability that a species extant at time tw also survives at t >tw . Finally, survival probabilities of species are shown to decay as powers of the ratio t /tw , a so-called pure aging behavior usually seen in glassy systems of physical origin. We find a quantitative dynamical effect of trait inheritance, namely, that increasing the value of K numerically decreases the decay exponent of the species survival probability.

Tangled nature model of evolutionary dynamics reconsidered: Structural and dynamical effects of trait inheritance.

PubMed

Andersen, Christian Walther; Sibani, Paolo

2016-05-01

Based on the stochastic dynamics of interacting agents which reproduce, mutate, and die, the tangled nature model (TNM) describes key emergent features of biological and cultural ecosystems' evolution. While trait inheritance is not included in many applications, i.e., the interactions of an agent and those of its mutated offspring are taken to be uncorrelated, in the family of TNMs introduced in this work correlations of varying strength are parametrized by a positive integer K. We first show that the interactions generated by our rule are nearly independent of K. Consequently, the structural and dynamical effects of trait inheritance can be studied independently of effects related to the form of the interactions. We then show that changing K strengthens the core structure of the ecology, leads to population abundance distributions better approximated by log-normal probability densities, and increases the probability that a species extant at time t_{w} also survives at t>t_{w}. Finally, survival probabilities of species are shown to decay as powers of the ratio t/t_{w}, a so-called pure aging behavior usually seen in glassy systems of physical origin. We find a quantitative dynamical effect of trait inheritance, namely, that increasing the value of K numerically decreases the decay exponent of the species survival probability.

Data-adaptive harmonic analysis and prediction of sea level change in North Atlantic region

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2017-12-01

This study aims to characterize North Atlantic sea level variability across the temporal and spatial scales. We apply recently developed data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) stochastic modeling techniques [Chekroun and Kondrashov, 2017] to monthly 1993-2017 dataset of Combined TOPEX/Poseidon, Jason-1 and Jason-2/OSTM altimetry fields over North Atlantic region. The key numerical feature of the DAH relies on the eigendecomposition of a matrix constructed from time-lagged spatial cross-correlations. In particular, eigenmodes form an orthogonal set of oscillating data-adaptive harmonic modes (DAHMs) that come in pairs and in exact phase quadrature for a given temporal frequency. Furthermore, the pairs of data-adaptive harmonic coefficients (DAHCs), obtained by projecting the dataset onto associated DAHMs, can be very efficiently modeled by a universal parametric family of simple nonlinear stochastic models - coupled Stuart-Landau oscillators stacked per frequency, and synchronized across different frequencies by the stochastic forcing. Despite the short record of altimetry dataset, developed DAH-MSLM model provides for skillful prediction of key dynamical and statistical features of sea level variability. References M. D. Chekroun and D. Kondrashov, Data-adaptive harmonic spectra and multilayer Stuart-Landau models. HAL preprint, 2017, https://hal.archives-ouvertes.fr/hal-01537797

Molecular modeling and SPRi investigations of interleukin 6 (IL6) protein and DNA aptamers.

PubMed

Rhinehardt, Kristen L; Vance, Stephen A; Mohan, Ram V; Sandros, Marinella; Srinivas, Goundla

2018-06-01

Interleukin 6 (IL6), an inflammatory response protein has major implications in immune-related inflammatory diseases. Identification of aptamers for the IL6 protein aids in diagnostic, therapeutic, and theranostic applications. Three different DNA aptamers and their interactions with IL6 protein were extensively investigated in a phosphate buffed saline (PBS) solution. Molecular-level modeling through molecular dynamics provided insights of structural, conformational changes and specific binding domains of these protein-aptamer complexes. Multiple simulations reveal consistent binding region for all protein-aptamer complexes. Conformational changes coupled with quantitative analysis of center of mass (COM) distance, radius of gyration (R g ), and number of intermolecular hydrogen bonds in each IL6 protein-aptamer complex was used to determine their binding performance strength and obtain molecular configurations with strong binding. A similarity comparison of the molecular configurations with strong binding from molecular-level modeling concurred with Surface Plasmon Resonance imaging (SPRi) for these three aptamer complexes, thus corroborating molecular modeling analysis findings. Insights from the natural progression of IL6 protein-aptamer binding modeled in this work has identified key features such as the orientation and location of the aptamer in the binding event. These key features are not readily feasible from wet lab experiments and impact the efficacy of the aptamers in diagnostic and theranostic applications.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

Firing Costs and Flexibility: Evidence from Firms’ Employment Responses to Shocks in India*

PubMed Central

Adhvaryu, Achyuta; Chari, A. V.; Sharma, Siddharth

2013-01-01

A key prediction of dynamic labor demand models is that firing restrictions attenuate firms’ employment responses to economic fluctuations. We provide the first direct test of this prediction using data from India. We exploit the fact that rainfall fluctuations, through their effects on agricultural productivity, generate variation in local demand within districts over time. Consistent with the theory, we find that industrial employment is more sensitive to shocks where labor regulation is less restrictive. Our results are robust to controlling for endogenous firm placement and vary across factory size in a pattern consistent with institutional features of Indian labor law. PMID:24357882

Space Shuttle propulsion performance reconstruction from flight data

NASA Technical Reports Server (NTRS)

Rogers, Robert M.

1989-01-01

The aplication of extended Kalman filtering to estimating Space Shuttle Solid Rocket Booster (SRB) performance, specific impulse, from flight data in a post-flight processing computer program. The flight data used includes inertial platform acceleration, SRB head pressure, and ground based radar tracking data. The key feature in this application is the model used for the SRBs, which represents a reference quasi-static internal ballistics model normalized to the propellant burn depth. Dynamic states of mass overboard and propellant burn depth are included in the filter model to account for real-time deviations from the reference model used. Aerodynamic, plume, wind and main engine uncertainties are included.

Tempest: Tools for Addressing the Needs of Next-Generation Climate Models

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.; Pinheiro, M. C.; Fong, J.

2015-12-01

Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for identifying weather extremes in large climate datasets. In this presentation, the latest advances with the implementation of this framework will be discussed, and a number of projects now utilizing these tools will be featured.

Imaging of Myocardial Fatty Acid Oxidation

PubMed Central

Mather, Kieren J; DeGrado, Tim

2016-01-01

Myocardial fuel selection is a key feature of the health and function of the heart, with clear links between myocardial function and fuel selection and important impacts of fuel selection on ischemia tolerance. Radiopharmaceuticals provide uniquely valuable tools for in vivo, non-invasive assessment of these aspects of cardiac function and metabolism. Here we review the landscape of imaging probes developed to provide noninvasive assessment of myocardial fatty acid oxidation (MFAO). Also, we review the state of current knowledge that myocardial fatty acid imaging has helped establish of static and dynamic fuel selection that characterizes cardiac and cardiometabolic disease and the interplay between fuel selection and various aspects of cardiac function. PMID:26923433

Residual perception of biological motion in cortical blindness.

PubMed

Ruffieux, Nicolas; Ramon, Meike; Lao, Junpeng; Colombo, Françoise; Stacchi, Lisa; Borruat, François-Xavier; Accolla, Ettore; Annoni, Jean-Marie; Caldara, Roberto

2016-12-01

From birth, the human visual system shows a remarkable sensitivity for perceiving biological motion. This visual ability relies on a distributed network of brain regions and can be preserved even after damage of high-level ventral visual areas. However, it remains unknown whether this critical biological skill can withstand the loss of vision following bilateral striate damage. To address this question, we tested the categorization of human and animal biological motion in BC, a rare case of cortical blindness after anoxia-induced bilateral striate damage. The severity of his impairment, encompassing various aspects of vision (i.e., color, shape, face, and object recognition) and causing blind-like behavior, contrasts with a residual ability to process motion. We presented BC with static or dynamic point-light displays (PLDs) of human or animal walkers. These stimuli were presented either individually, or in pairs in two alternative forced choice (2AFC) tasks. When confronted with individual PLDs, the patient was unable to categorize the stimuli, irrespective of whether they were static or dynamic. In the 2AFC task, BC exhibited appropriate eye movements towards diagnostic information, but performed at chance level with static PLDs, in stark contrast to his ability to efficiently categorize dynamic biological agents. This striking ability to categorize biological motion provided top-down information is important for at least two reasons. Firstly, it emphasizes the importance of assessing patients' (visual) abilities across a range of task constraints, which can reveal potential residual abilities that may in turn represent a key feature for patient rehabilitation. Finally, our findings reinforce the view that the neural network processing biological motion can efficiently operate despite severely impaired low-level vision, positing our natural predisposition for processing dynamicity in biological agents as a robust feature of human vision. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

A series of active flow control experiments were recently conducted at high Reynolds numbers on a generic separated configuration. The model simulates the upper surface of a 20% thick Glauert-Goldschmied type airfoil at zero angle of attack. The flow is fully turbulent since the tunnel sidewall boundary layer flows over the model. The main motivation for the experiments is to generate a comprehensive data base for validation of unsteady numerical simulation as a first step in the development of a CFD design tool, without which it would not be possible to effectively utilize the great potential of unsteady flow control. This paper focuses on the dynamics of several key features of the baseline as well as the controlled flow. It was found that the thickness of the upstream boundary layer has a negligible effect on the flow dynamics. It is speculated that separation is caused mainly by the highly convex surface while viscous effects are less important. The two-dimensional separated flow contains unsteady waves centered on a reduced frequency of 0.8, while in the three dimensional separated flow, frequencies around a reduced frequency of 0.3 and 1 are active. Several scenarios of resonant wave interaction take place at the separated shear-layer and in the pressure recovery region. The unstable reduced frequency bands for periodic excitation are centered on 1.5 and 5, but these reduced frequencies are based on the length of the baseline bubble that shortens due to the excitation. The conventional swept wing-scaling works well for the coherent wave features. Reproduction of these dynamic effects by a numerical simulation would provide benchmark validation.

Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration

PubMed Central

Lobo, Daniel; Levin, Michael

2015-01-01

Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form. PMID:26042810

Conceptualizing intragroup and intergroup dynamics within a controlled crowd evacuation.

PubMed

Elzie, Terra; Frydenlund, Erika; Collins, Andrew J; Robinson, R Michael

2015-01-01

Social dynamics play a critical role in successful pedestrian evacuations. Crowd modeling research has made progress in capturing the way individual and group dynamics affect evacuations; however, few studies have simultaneously examined how individuals and groups interact with one another during egress. To address this gap, the researchers present a conceptual agent-based model (ABM) designed to study the ways in which autonomous, heterogeneous, decision-making individuals negotiate intragroup and intergroup behavior while exiting a large venue. A key feature of this proposed model is the examination of the dynamics among and between various groupings, where heterogeneity at the individual level dynamically affects group behavior and subsequently group/group interactions. ABM provides a means of representing the important social factors that affect decision making among diverse social groups. Expanding on the 2013 work of Vizzari et al., the researchers focus specifically on social factors and decision making at the individual/group and group/group levels to more realistically portray dynamic crowd systems during a pedestrian evacuation. By developing a model with individual, intragroup, and intergroup interactions, the ABM provides a more representative approximation of real-world crowd egress. The simulation will enable more informed planning by disaster managers, emergency planners, and other decision makers. This pedestrian behavioral concept is one piece of a larger simulation model. Future research will build toward an integrated model capturing decision-making interactions between pedestrians and vehicles that affect evacuation outcomes.

Sequential memory: Binding dynamics

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

Combining Mechanistic Approaches for Studying Eco-Hydro-Geomorphic Coupling

NASA Astrophysics Data System (ADS)

Francipane, A.; Ivanov, V.; Akutina, Y.; Noto, V.; Istanbullouglu, E.

2008-12-01

Vegetation interacts with hydrology and geomorphic form and processes of a river basin in profound ways. Despite recent advances in hydrological modeling, the dynamic coupling between these processes is yet to be adequately captured at the basin scale to elucidate key features of process interaction and their role in the organization of vegetation and landscape morphology. In this study, we present a blueprint for integrating a geomorphic component into the physically-based, spatially distributed ecohydrological model, tRIBS- VEGGIE, which reproduces essential water and energy processes over the complex topography of a river basin and links them to the basic plant life regulatory processes. We present a preliminary design of the integrated modeling framework in which hillslope and channel erosion processes at the catchment scale, will be coupled with vegetation-hydrology dynamics. We evaluate the developed framework by applying the integrated model to Lucky Hills basin, a sub-catchment of the Walnut Gulch Experimental Watershed (Arizona). The evaluation is carried out by comparing sediment yields at the basin outlet, that follows a detailed verification of simulated land-surface energy partition, biomass dynamics, and soil moisture states.

Feshbach resonances in the exit channel of the F + CH3OH → HF + CH3O reaction observed using transition-state spectroscopy

NASA Astrophysics Data System (ADS)

Weichman, Marissa L.; Devine, Jessalyn A.; Babin, Mark C.; Li, Jun; Guo, Lifen; Ma, Jianyi; Guo, Hua; Neumark, Daniel M.

2017-10-01

The transition state governs how chemical bonds form and cleave during a chemical reaction and its direct characterization is a long-standing challenge in physical chemistry. Transition state spectroscopy experiments based on negative-ion photodetachment provide a direct probe of the vibrational structure and metastable resonances that are characteristic of the reactive surface. Dynamical resonances are extremely sensitive to the topography of the reactive surface and provide an exceptional point of comparison with theory. Here we study the seven-atom F + CH3OH → HF + CH3O reaction using slow photoelectron velocity-map imaging spectroscopy of cryocooled CH3OHF- anions. These measurements reveal spectral features associated with a manifold of vibrational Feshbach resonances and bound states supported by the post-transition state potential well. Quantum dynamical calculations yield excellent agreement with the experimental results, allow the assignment of spectral structure and demonstrate that the key dynamics of complex bimolecular reactions can be captured with a relatively simple theoretical framework.

Fractal patterns in Stock Intertrading Times

NASA Astrophysics Data System (ADS)

White, Ainslie; Lee, Youngki; Ivanov, Plamen Ch.

2003-03-01

We study intertrades times (ITT) of stock trades of a range of companies included in the New York Stock Exchange's Trades and Quotes (TAQ) database. The time between transactions is an indicator of the dynamics of the market, and in the field of econometrics, intertrade durations play a key role in the understanding of the market activity and microstructure. Previous work has mainly focused on the properties of price changes of individual company stocks as well as global financial indices (e.g. SP500, DJ etc.). We hypothesize that there is a relation between the dynamics of price change and the trading activity. To investigate this relation we first study the statistical features of ITT data. The TAQ database covers all transactions on the NSE, AMEX, NASDAQ and the US regional exchanges. We have performed a preliminary analysis of 100 company stocks from a range of industries of the US economy selecting predominantly those companies which have large market capitalisations (MC). We focus on companies with large MC, since the dynamics of the price change and trading activity of stocks of such companies has a considerable impact on the market behaviour.

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

The Sagittarius Stream: Probing the Outer Halo Potential

NASA Astrophysics Data System (ADS)

Fardal, Mark; HSTPROMO

2018-01-01

The Sagittarius Stream should be the premier probe of the outer Milky Way halo potential. Instead it has generated a series of puzzles that have frustrated modelers and prevented us from measuring the halo forces. The latest such puzzle is the factor of two difference between leading and trailing apocenter distances, seen most clearly in a recent sample of RR Lyraes from PS1. Using a set of dynamical models, we explain how to match this feature. The key element are that the debris at apocenter should dynamically young, originating from the last two pericentric passages only. We also explain the important roles played by the mass profile of the halo, dynamical friction, and departures from sphericity. The models show that the separate components already visible in the PS1 data should separate clearly once velocities are obtained, and the youngest component should probe the potential even beyond the observed distances of >~ 100 kpc. We explain what observations would be useful to eliminate remaining degeneracies in the models and fulfill the promise of the stream for understanding the Milky Way.

Feshbach resonances in the exit channel of the F + CH3OH → HF + CH3O reaction observed using transition-state spectroscopy.

PubMed

Weichman, Marissa L; DeVine, Jessalyn A; Babin, Mark C; Li, Jun; Guo, Lifen; Ma, Jianyi; Guo, Hua; Neumark, Daniel M

2017-10-01

The transition state governs how chemical bonds form and cleave during a chemical reaction and its direct characterization is a long-standing challenge in physical chemistry. Transition state spectroscopy experiments based on negative-ion photodetachment provide a direct probe of the vibrational structure and metastable resonances that are characteristic of the reactive surface. Dynamical resonances are extremely sensitive to the topography of the reactive surface and provide an exceptional point of comparison with theory. Here we study the seven-atom F + CH 3 OH → HF + CH 3 O reaction using slow photoelectron velocity-map imaging spectroscopy of cryocooled CH 3 OHF - anions. These measurements reveal spectral features associated with a manifold of vibrational Feshbach resonances and bound states supported by the post-transition state potential well. Quantum dynamical calculations yield excellent agreement with the experimental results, allow the assignment of spectral structure and demonstrate that the key dynamics of complex bimolecular reactions can be captured with a relatively simple theoretical framework.

Single-camera displacement field correlation method for centrosymmetric 3D dynamic deformation measurement

NASA Astrophysics Data System (ADS)

Zhao, Jiaye; Wen, Huihui; Liu, Zhanwei; Rong, Jili; Xie, Huimin

2018-05-01

Three-dimensional (3D) deformation measurements are a key issue in experimental mechanics. In this paper, a displacement field correlation (DFC) method to measure centrosymmetric 3D dynamic deformation using a single camera is proposed for the first time. When 3D deformation information is collected by a camera at a tilted angle, the measured displacement fields are coupling fields of both the in-plane and out-of-plane displacements. The features of the coupling field are analysed in detail, and a decoupling algorithm based on DFC is proposed. The 3D deformation to be measured can be inverted and reconstructed using only one coupling field. The accuracy of this method was validated by a high-speed impact experiment that simulated an underwater explosion. The experimental results show that the approach proposed in this paper can be used in 3D deformation measurements with higher sensitivity and accuracy, and is especially suitable for high-speed centrosymmetric deformation. In addition, this method avoids the non-synchronisation problem associated with using a pair of high-speed cameras, as is common in 3D dynamic measurements.

Spatially Localized Chemical Patterns around an A + B → Oscillator Front.

PubMed

Budroni, M A; Lemaigre, L; Escala, D M; Muñuzuri, A P; De Wit, A

2016-02-18

When two gels, each loaded with a different set of reactants A and B of an oscillatory reaction, are brought into contact, reaction-diffusion patterns such as waves or Turing patterns can develop in the reactive contact zone. The initial condition which separates the reactants at the beginning leads to a localization in space of the different dynamical regimes accessible to the chemical oscillator. We study here both numerically and experimentally the composite traveling structures resulting from the interaction between chemical fronts and localized waves in the case in which the reactants of such an A + B → oscillator system are those of the canonical Belousov-Zhabotinsky (BZ) oscillating reaction. A transition between different dynamics is obtained by varying the initial concentration of the organic substrate of the BZ reactants, which is one of the parameters controlling the local excitability. We show that the dynamical regime (excitable or oscillatory) characterizing the BZ oscillator in the initial contact area is the key feature which determines the spatiotemporal evolution of the system. The experimental results are in qualitative agreement with the theoretical predictions.

Recommendations for oversight of nanobiotechnology: dynamic oversight for complex and convergent technology

NASA Astrophysics Data System (ADS)

Ramachandran, Gurumurthy; Wolf, Susan M.; Paradise, Jordan; Kuzma, Jennifer; Hall, Ralph; Kokkoli, Efrosini; Fatehi, Leili

2011-04-01

Federal oversight of nanobiotechnology in the U.S. has been fragmented and incremental. The prevailing approach has been to use existing laws and other administrative mechanisms for oversight. However, this "stay-the-course" approach will be inadequate for such a complex and convergent technology and may indeed undermine its promise. The technology demands a new, more dynamic approach to oversight. The authors are proposing a new oversight framework with three essential features: (a) the oversight trajectory needs to be able to move dynamically between "soft" and "hard" approaches as information and nano-products evolve; (b) it needs to integrate inputs from all stakeholders, with strong public engagement in decision-making to assure adequate analysis and transparency; and (c) it should include an overarching coordinating entity to assure strong inter-agency coordination and communication that can meet the challenge posed by the convergent nature of nanobiotechnology. The proposed framework arises from a detailed case analysis of several key oversight regimes relevant to nanobiotechnology and is informed by inputs from experts in academia, industry, NGOs, and government.

Sequential memory: Binding dynamics.

PubMed

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

A nonlinear dynamical system approach for the yielding behaviour of a viscoplastic material.

PubMed

Burghelea, Teodor; Moyers-Gonzalez, Miguel; Sainudiin, Raazesh

2017-03-08

A nonlinear dynamical system model that approximates a microscopic Gibbs field model for the yielding of a viscoplastic material subjected to varying external stresses recently reported in R. Sainudiin, M. Moyers-Gonzalez and T. Burghelea, Soft Matter, 2015, 11(27), 5531-5545 is presented. The predictions of the model are in fair agreement with microscopic simulations and are in very good agreement with the micro-structural semi-empirical model reported in A. M. V. Putz and T. I. Burghelea, Rheol. Acta, 2009, 48, 673-689. With only two internal parameters, the nonlinear dynamical system model captures several key features of the solid-fluid transition observed in experiments: the effect of the interactions between microscopic constituents on the yield point, the abruptness of solid-fluid transition and the emergence of a hysteresis of the micro-structural states upon increasing/decreasing external forces. The scaling behaviour of the magnitude of the hysteresis with the degree of the steadiness of the flow is consistent with previous experimental observations. Finally, the practical usefulness of the approach is demonstrated by fitting a rheological data set measured with an elasto-viscoplastic material.

Measuring dynamics of household vulnerability in selected coastal megacities to inform transformative adaptation

NASA Astrophysics Data System (ADS)

Birkmann, J.; Solecki, W. D.

2016-12-01

Understanding conditions and dynamics of household vulnerability and risk is key for building community resilience. Two different methodological approaches of vulnerability, risk and resilience assessment for selected global megacities are presented to address this research issue. First, an indicator-based approach was executed to compare susceptibility, coping and adaptive capacities for Lagos, Kolkata, Lagos, London, New York, and Tokyo on a neighborhood by neighborhood scale. Second, a household survey that has been conducted in Kolkata, Lagos, and New York to explore specific features of susceptibility, risk management capacities and transformations within at risk neighborhoods. The results of both methods underscore the dynamics of vulnerability. Lessons learned for disaster risk management and urban planning are derived, particularly in terms of defining priorities for a more inclusive and resilient urban development, and transformative adaptation. The findings also provide opportunity to critically review the potential outcomes of the New Urban Agenda (outcome of UN-Habitat III). The research has been undertaken within a larger international research team in the Belmont funded project Transformation of Urban Coasts.

Examination of tracer transport in the NCAR CCM2 by comparison of CFCl3 simulations with ALE/GAGE observations

NASA Technical Reports Server (NTRS)

Hartley, Dana E.; Williamson, David L.; Rasch, Philip J.; Prinn, Ronald G.

1994-01-01

The latest version of the National Center for Atmospheric Research (NCAR) community climate model (CCM2) contains a semi-Lagrangian tracer transport scheme for the purpose of advecting water vapor and for including chemistry in the climate model. One way to diagnose the CCM2 transport is to simulate CFCl3 in the CCM2 since it has a well-known industry-based source distribution and a photochemical sink and to compare the model results to Atmospheric Lifetime Experiment/Global Atmospheric Gases Experiment ALE/GAGE observations around the globe. In this paper we focus on this comparison and discuss the synoptic scale issues of tracer transport where appropriate. We compare the model and observations on both 12-hour and monthly timescales. The higher-frequency events allow us to diagnose the synoptic scale transport in the CCM2 associated with the observational sites and to determine uncertainties in our high-resolution source distribution. We find that the CCM2 does simulate many of the key features such as pollution events and some seasonal transports, but there are still some dynamical features of tracer transport such as the storm track dynamics and cross-equatorial flow that merit further study in both the model and the real atmosphere.

A Comparative Study of Human Saposins.

PubMed

Garrido-Arandia, María; Cuevas-Zuviría, Bruno; Díaz-Perales, Araceli; Pacios, Luis F

2018-02-14

Saposins are small proteins implicated in trafficking and loading of lipids onto Cluster of Differentiation 1 (CD1) receptor proteins that in turn present lipid antigens to T cells and a variety of T-cell receptors, thus playing a crucial role in innate and adaptive immune responses in humans. Despite their low sequence identity, the four types of human saposins share a similar folding pattern consisting of four helices linked by three conserved disulfide bridges. However, their lipid-binding abilities as well as their activities in extracting, transporting and loading onto CD1 molecules a variety of sphingo- and phospholipids in biological membranes display two striking characteristics: a strong pH-dependence and a structural change between a compact, closed conformation and an open conformation. In this work, we present a comparative computational study of structural, electrostatic, and dynamic features of human saposins based upon their available experimental structures. By means of structural alignments, surface analyses, calculation of pH-dependent protonation states, Poisson-Boltzmann electrostatic potentials, and molecular dynamics simulations at three pH values representative of biological media where saposins fulfill their function, our results shed light into their intrinsic features. The similarities and differences in this class of proteins depend on tiny variations of local structural details that allow saposins to be key players in triggering responses in the human immune system.

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

PubMed Central

Balaguer-Ballester, Emili; Clark, Nicholas R.; Coath, Martin; Krumbholz, Katrin; Denham, Susan L.

2009-01-01

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing. PMID:19266015

KOSMOS: a universal morph server for nucleic acids, proteins and their complexes.

PubMed

Seo, Sangjae; Kim, Moon Ki

2012-07-01

KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos.

Effective user management with high strength crypto -key in dynamic group environment in cloud

NASA Astrophysics Data System (ADS)

Kumar, P. J.; Suganya, P.; Karthik, G.

2017-11-01

Cloud Clusters consists of various collections of files which are being accessed by multiple users of Cloud. The users are managed as a group and the association of the user to a particular group is dynamic in nature. Every group has a manager who handles the membership of a user to a particular group by issuing keys for encryption and decryption. Due to the dynamic nature of a user he/she may leave the group very frequently. But an attempt can be made by the user who has recently left the group to access a file maintained by that group. Key distribution becomes a critical issue while the behavior of the user is dynamic. Existing techniques to manage the users of group in terms of security and key distribution has been investigated so that to arrive at an objective to identify the scopes to increase security and key management scheme in cloud. The usage of various key combinations to measure the strength of security and efficiency of user management in dynamic cloud environment has been investigated.

Physiologically relevant organs on chips.

PubMed

Yum, Kyungsuk; Hong, Soon Gweon; Healy, Kevin E; Lee, Luke P

2014-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or also known as "ogans-on-chips", that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue-tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamics of tissue topology during cancer invasion and metastasis

NASA Astrophysics Data System (ADS)

Munn, Lance L.

2013-12-01

During tumor progression, cancer cells mix with other cell populations including epithelial and endothelial cells. Although potentially important clinically as well as for our understanding of basic tumor biology, the process of mixing is largely a mystery. Furthermore, there is no rigorous, analytical measure available for quantifying the mixing of compartments within a tumor. I present here a mathematical model of tissue repair and tumor growth based on collective cell migration that simulates a wide range of observed tumor behaviors with correct tissue compartmentalization and connectivity. The resulting dynamics are analyzed in light of the Euler characteristic number (χ), which describes key topological features such as fragmentation, looping and cavities. The analysis predicts a number of regimes in which the cancer cells can encapsulate normal tissue, form a co-interdigitating mass, or become fragmented and encapsulated by endothelial or epithelial structures. Key processes that affect the topological changes are the production of provisional matrix in the tumor, and the migration of endothelial or epithelial cells on this matrix. Furthermore, the simulations predict that topological changes during tumor invasion into blood vessels may contribute to metastasis. The topological analysis outlined here could be useful for tumor diagnosis or monitoring response to therapy and would only require high resolution, 3D image data to resolve and track the various cell compartments.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI.

PubMed

Iliff, Jeffrey J; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-03-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer's disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer's disease susceptibility and progression in the live human brain.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI

PubMed Central

Iliff, Jeffrey J.; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-01-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer’s disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer’s disease susceptibility and progression in the live human brain. PMID:23434588

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning optimal filters automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal filters optimized using the proposed learning approach. PMID:18364986

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability

Dynamical Constraints On The Galaxy-Halo Connection

NASA Astrophysics Data System (ADS)

Desmond, Harry

2017-07-01

Dark matter halos comprise the bulk of the universe's mass, yet must be probed by the luminous galaxies that form within them. A key goal of modern astrophysics, therefore, is to robustly relate the visible and dark mass, which to first order means relating the properties of galaxies and halos. This may be expected not only to improve our knowledge of galaxy formation, but also to enable high-precision cosmological tests using galaxies and hence maximise the utility of future galaxy surveys. As halos are inaccessible to observations - as galaxies are to N-body simulations - this relation requires an additional modelling step.The aim of this thesis is to develop and evaluate models of the galaxy-halo connection using observations of galaxy dynamics. In particular, I build empirical models based on the technique of halo abundance matching for five key dynamical scaling relations of galaxies - the Tully-Fisher, Faber-Jackson, mass-size and mass discrepancy-acceleration relations, and Fundamental Plane - which relate their baryon distributions and rotation or velocity dispersion profiles. I then develop a statistical scheme based on approximate Bayesian computation to compare the predicted and measured values of a number of summary statistics describing the relations' important features. This not only provides quantitative constraints on the free parameters of the models, but also allows absolute goodness-of-fit measures to be formulated. I find some features to be naturally accounted for by an abundance matching approach and others to impose new constraints on the galaxy-halo connection; the remainder are challenging to account for and may imply galaxy-halo correlations beyond the scope of basic abundance matching.Besides providing concrete statistical tests of specific galaxy formation theories, these results will be of use for guiding the inputs of empirical and semi-analytic galaxy formation models, which require galaxy-halo correlations to be imposed by hand. As galaxy datasets become larger and more precise in the future, we may expect these methods to continue providing insight into the relation between the visible and dark matter content of the universe and the physical processes that underlie it.

Decorrelation dynamics and spectra in drift-Alfven turbulence

NASA Astrophysics Data System (ADS)

Fernandez Garcia, Eduardo

Motivated by the inability of one-fluid magnetohydrodynamics (MHD) to explain key turbulence characteristics in systems ranging from the solar wind and interstellar medium to fusion devices like the reversed field pinch, this thesis studies magnetic turbulence using a drift-Alfven model that extends MHD by including electron density dynamics. Electron effects play a significant role in the dynamics by changing the structure of turbulent decorrelation in the Alfvenic regime (where fast Alfvenic propagation provides the fastest decorrelation of the system): besides the familiar counter-propagating Alfvenic branches of MHD, an additional branch tied to the diamagnetic and eddy-turn- over rates enters in the turbulent response. This kinematic branch gives hydrodynamic features to turbulence that is otherwise strongly magnetic. Magnetic features are observed in the RMS frequency, energy partitions, cross-field energy transfer and in the turbulent response, whereas hydrodynamic features appear in the average frequency, self-field transfer, turbulent response and finally the wavenumber spectrum. These features are studied via renormalized closure theory and numerical simulation. The closure calculation naturally incorporates the eigenmode structure of the turbulent response in specifying spectral energy balance equations for the magnetic, kinetic and internal (density) energies. Alfvenic terms proportional to cross correlations and involved in cross field transfer compete with eddy-turn-over, self transfer, auto-correlation terms. In the steady state, the kinematic terms dominate the energy balances and yield a 5/3 Kolmogorov spectrum (as observed in the interstellar medium) for the three field energies in the strong turbulence, long wavelength limit. Alfvenic terms establish equipartition of kinetic and magnetic energies. In the limit where wavelengths are short compared to the gyroradius, the Alfvenic terms equipartition the internal and magnetic energies resulting in a steep (-2) spectrum fall-off for those energies while the largely uncoupled kinetic modes still obey a 5/3 law. From the numerical simulations, the response function of drift-Alfven turbulence is measured. Here, a statistical ensemble is constructed from small perturbations of the turbulent amplitudes at fixed wavenumber. The decorrelation structure born out of the eigenmode calculation is verified in the numerical measurement.

Insight into the structural requirements of aminopyrimidine derivatives for good potency against both purified enzyme and whole cells of M. tuberculosis: combination of HQSAR, CoMSIA, and MD simulation studies.

PubMed

Punkvang, Auradee; Hannongbua, Supa; Saparpakorn, Patchreenart; Pungpo, Pornpan

2016-05-01

The Mycobacterium tuberculosis protein kinase B (PknB) is critical for growth and survival of M. tuberculosis within the host. The series of aminopyrimidine derivatives show impressive activity against PknB (IC50 < .5 μM). However, most of them show weak or no cellular activity against M. tuberculosis (MIC > 63 μM). Consequently, the key structural features related to activity against of both PknB and M. tuberculosis need to be investigated. Here, two- and three-dimensional quantitative structure-activity relationship (2D and 3D QSAR) analyses combined with molecular dynamics (MD) simulations were employed with the aim to evaluate these key structural features of aminopyrimidine derivatives. Hologram quantitative structure-activity relationship (HQSAR) and CoMSIA models constructed from IC50 and MIC values of aminopyrimidine compounds could establish the structural requirements for better activity against of both PknB and M. tuberculosis. The NH linker and the R1 substituent of the template compound are not only crucial for the biological activity against PknB but also for the biological activity against M. tuberculosis. Moreover, the results obtained from MD simulations show that these moieties are the key fragments for binding of aminopyrimidine compounds in PknB. The combination of QSAR analysis and MD simulations helps us to provide a structural concept that could guide future design of PknB inhibitors with improved potency against both the purified enzyme and whole M. tuberculosis cells.

Real-Space Imaging of Carrier Dynamics of Materials Surfaces by Second-Generation Four-Dimensional Scanning Ultrafast Electron Microscopy.

PubMed

Sun, Jingya; Melnikov, Vasily A; Khan, Jafar I; Mohammed, Omar F

2015-10-01

In the fields of photocatalysis and photovoltaics, ultrafast dynamical processes, including carrier trapping and recombination on material surfaces, are among the key factors that determine the overall energy conversion efficiency. A precise knowledge of these dynamical events on the nanometer (nm) and femtosecond (fs) scales was not accessible until recently. The only way to access such fundamental processes fully is to map the surface dynamics selectively in real space and time. In this study, we establish a second generation of four-dimensional scanning ultrafast electron microscopy (4D S-UEM) and demonstrate the ability to record time-resolved images (snapshots) of material surfaces with 650 fs and ∼5 nm temporal and spatial resolutions, respectively. In this method, the surface of a specimen is excited by a clocking optical pulse and imaged using a pulsed primary electron beam as a probe pulse, generating secondary electrons (SEs), which are emitted from the surface of the specimen in a manner that is sensitive to the local electron/hole density. This method provides direct and controllable information regarding surface dynamics. We clearly demonstrate how the surface morphology, grains, defects, and nanostructured features can significantly impact the overall dynamical processes on the surface of photoactive-materials. In addition, the ability to access two regimes of dynamical probing in a single experiment and the energy loss of SEs in semiconductor-nanoscale materials will also be discussed.

Early Visual Cortex Dynamics during Top-Down Modulated Shifts of Feature-Selective Attention.

PubMed

Müller, Matthias M; Trautmann, Mireille; Keitel, Christian

2016-04-01

Shifting attention from one color to another color or from color to another feature dimension such as shape or orientation is imperative when searching for a certain object in a cluttered scene. Most attention models that emphasize feature-based selection implicitly assume that all shifts in feature-selective attention underlie identical temporal dynamics. Here, we recorded time courses of behavioral data and steady-state visual evoked potentials (SSVEPs), an objective electrophysiological measure of neural dynamics in early visual cortex to investigate temporal dynamics when participants shifted attention from color or orientation toward color or orientation, respectively. SSVEPs were elicited by four random dot kinematograms that flickered at different frequencies. Each random dot kinematogram was composed of dashes that uniquely combined two features from the dimensions color (red or blue) and orientation (slash or backslash). Participants were cued to attend to one feature (such as color or orientation) and respond to coherent motion targets of the to-be-attended feature. We found that shifts toward color occurred earlier after the shifting cue compared with shifts toward orientation, regardless of the original feature (i.e., color or orientation). This was paralleled in SSVEP amplitude modulations as well as in the time course of behavioral data. Overall, our results suggest different neural dynamics during shifts of attention from color and orientation and the respective shifting destinations, namely, either toward color or toward orientation.

Impacts of Changing Climatic Drivers and Land use features on Future Stormwater Runoff in the Northwest Florida Basin: A Large-Scale Hydrologic Modeling Assessment

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2017-12-01

Potential changes in climatic drivers and land cover features can significantly influence the stormwater budget in the Northwest Florida Basin. We investigated the hydro-climatic and land use sensitivities of stormwater runoff by developing a large-scale process-based rainfall-runoff model for the large basin by using the EPA Storm Water Management Model (SWMM 5.1). Climatic and hydrologic variables, as well as land use/cover features were incorporated into the model to account for the key processes of coastal hydrology and its dynamic interactions with groundwater and sea levels. We calibrated and validated the model by historical daily streamflow observations during 2009-2012 at four major rivers in the basin. Downscaled climatic drivers (precipitation, temperature, solar radiation) projected by twenty GCMs-RCMs under CMIP5, along with the projected future land use/cover features were also incorporated into the model. The basin storm runoff was then simulated for the historical (2000s = 1976-2005) and two future periods (2050s = 2030-2059, and 2080s = 2070-2099). Comparative evaluation of the historical and future scenarios leads to important guidelines for stormwater management in Northwest Florida and similar regions under a changing climate and environment.

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption.

PubMed

Chandrasekaran, Jeyamala; Thiruvengadam, S J

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security.

From Shell Midden to Midden-Mound: The Geoarchaeology of Mound Key, an Anthropogenic Island in Southwest Florida, USA

PubMed Central

Cherkinsky, Alexander; Roberts Thompson, Amanda D.; Walker, Karen J.; Newsom, Lee A.; Savarese, Michael

2016-01-01

Mound Key was once the capital of the Calusa Kingdom, a large Pre-Hispanic polity that controlled much of southern Florida. Mound Key, like other archaeological sites along the southwest Gulf Coast, is a large expanse of shell and other anthropogenic sediments. The challenges that these sites pose are largely due to the size and areal extent of the deposits, some of which begin up to a meter below and exceed nine meters above modern sea levels. Additionally, the complex depositional sequences at these sites present difficulties in determining their chronology. Here, we examine the development of Mound Key as an anthropogenic island through systematic coring of the deposits, excavations, and intensive radiocarbon dating. The resulting data, which include the reversals of radiocarbon dates from cores and dates from mound-top features, lend insight into the temporality of site formation. We use these insights to discuss the nature and scale of human activities that worked to form this large island in the context of its dynamic, environmental setting. We present the case that deposits within Mound Key’s central area accumulated through complex processes that represent a diversity of human action including midden accumulation and the redeposition of older sediments as mound fill. PMID:27123928

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption

PubMed Central

Chandrasekaran, Jeyamala; Thiruvengadam, S. J.

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security. PMID:26550603

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.

Biophysical Aspects of T Lymphocyte Activation at the Immune Synapse

PubMed Central

Hivroz, Claire; Saitakis, Michael

2016-01-01

T lymphocyte activation is a pivotal step of the adaptive immune response. It requires the recognition by T-cell receptors (TCR) of peptides presented in the context of major histocompatibility complex molecules (pMHC) present at the surface of antigen-presenting cells (APCs). T lymphocyte activation also involves engagement of costimulatory receptors and adhesion molecules recognizing ligands on the APC. Integration of these different signals requires the formation of a specialized dynamic structure: the immune synapse. While the biochemical and molecular aspects of this cell–cell communication have been extensively studied, its mechanical features have only recently been addressed. Yet, the immune synapse is also the place of exchange of mechanical signals. Receptors engaged on the T lymphocyte surface are submitted to many tensile and traction forces. These forces are generated by various phenomena: membrane undulation/protrusion/retraction, cell mobility or spreading, and dynamic remodeling of the actomyosin cytoskeleton inside the T lymphocyte. Moreover, the TCR can both induce force development, following triggering, and sense and convert forces into biochemical signals, as a bona fide mechanotransducer. Other costimulatory molecules, such as LFA-1, engaged during immune synapse formation, also display these features. Moreover, T lymphocytes themselves are mechanosensitive, since substrate stiffness can modulate their response. In this review, we will summarize recent studies from a biophysical perspective to explain how mechanical cues can affect T lymphocyte activation. We will particularly discuss how forces are generated during immune synapse formation; how these forces affect various aspects of T lymphocyte biology; and what are the key features of T lymphocyte response to stiffness. PMID:26913033

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

Wang, Shaobu; Lu, Shuai; Zhou, Ning

In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highestmore » similarity, forming a suboptimal ‘basis’ of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.« less

The Temporal Dynamics of Visual Search: Evidence for Parallel Processing in Feature and Conjunction Searches

PubMed Central

McElree, Brian; Carrasco, Marisa

2012-01-01

Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310

Dynamical scattering in coherent hard x-ray nanobeam Bragg diffraction

NASA Astrophysics Data System (ADS)

Pateras, A.; Park, J.; Ahn, Y.; Tilka, J. A.; Holt, M. V.; Kim, H.; Mawst, L. J.; Evans, P. G.

2018-06-01

Unique intensity features arising from dynamical diffraction arise in coherent x-ray nanobeam diffraction patterns of crystals having thicknesses larger than the x-ray extinction depth or exhibiting combinations of nanoscale and mesoscale features. We demonstrate that dynamical scattering effects can be accurately predicted using an optical model combined with the Darwin theory of dynamical x-ray diffraction. The model includes the highly divergent coherent x-ray nanobeams produced by Fresnel zone plate focusing optics and accounts for primary extinction, multiple scattering, and absorption. The simulation accurately reproduces the dynamical scattering features of experimental diffraction patterns acquired from a GaAs/AlGaAs epitaxial heterostructure on a GaAs (001) substrate.

Toward On-Demand Deep Brain Stimulation Using Online Parkinson's Disease Prediction Driven by Dynamic Detection.

PubMed

Mohammed, Ameer; Zamani, Majid; Bayford, Richard; Demosthenous, Andreas

2017-12-01

In Parkinson's disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation, and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction, and classification algorithms that have been used in brain-machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction, and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves a classification accuracy of 99.29%, an F1-score of 97.90%, and a choice probability of 99.86%.

Biology of Three ICE Families: SXT/R391, ICEBs1, and ICESt1/ICESt3.

PubMed

Carraro, Nicolas; Burrus, Vincent

2014-12-01

Integrative and Conjugative Elements (ICEs) are bacterial mobile genetic elements that play a key role in bacterial genomes dynamics and evolution. ICEs are widely distributed among virtually all bacterial genera. Recent extensive studies have unraveled their high diversity and complexity. The present review depicts the general conserved features of ICEs and describes more precisely three major families of ICEs that have been extensively studied in the past decade for their biology, their evolution and their impact on genomes dynamics. First, the large SXT/R391 family of ICEs disseminates antibiotic resistance genes and drives the exchange of mobilizable genomic islands (MGIs) between many enteric pathogens such as Vibrio cholerae. Second, ICEBs1 of Bacillus subtilis is the most well understood ICE of Gram-positive bacteria, notably regarding the regulation of its dissemination and its initially unforeseen extrachromosomal replication, which could be a common feature of ICEs of both Gram-positive and Gram-negative bacteria. Finally, ICESt1 and ICESt3 of Streptococcus thermophilus are the prototypes of a large family of ICEs widely distributed among various streptococci. These ICEs carry an original regulation module that associates regulators related to those of both SXT/R391 and ICEBs1. Study of ICESt1 and ICESt3 uncovered the cis-mobilization of related genomic islands (CIMEs) by a mechanism called accretion-mobilization, which likely represents a paradigm for the evolution of many ICEs and genomic islands. These three major families of ICEs give a glimpse about ICEs dynamics and their high impact on bacterial adaptation.

Computational study of β-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility.

PubMed

Kulik, Natallia; Slámová, Kristýna; Ettrich, Rüdiger; Křen, Vladimír

2015-01-28

β-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum β-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest. Computational methods including homology modeling and molecular dynamics simulations were applied to shad light on the structure-activity relationship in the enzyme. Primary sequence analysis revealed some variable regions able to influence difference in substrate affinity of hexosaminidases. Moreover, docking in combination with consequent molecular dynamics simulations of C-6 modified glycosides enabled us to identify the structural features required for accommodation and processing of these bulky substrates in the active site of hexosaminidase from T. flavus. To access the reliability of predictions on basis of the reported model, all results were confronted with available experimental data that demonstrated the principal correctness of the predictions as well as the model. The main variable regions in β-N-acetylhexosaminidases determining difference in modified substrate affinity are located close to the active site entrance and engage two loops. Differences in primary sequence and the spatial arrangement of these loops and their interplay with active site amino acids, reflected by interaction energies and dynamics, account for the different catalytic activity and substrate specificity of the various fungal and bacterial β-N-acetylhexosaminidases.

Retrocausation in quantum mechanics and the effects of minds on the creation of physical reality

NASA Astrophysics Data System (ADS)

Stapp, Henry P.

2017-05-01

The classical physical theories that prevailed in science from the time of Isaac Newton until the dawn of the twentieth century were empirically based on human experience and made predictions about our mental experiences, yet excluded from the dynamics all mental properties. But how can one rationally get mental things out if no mental elements are put in? The key step in the creation of quantum mechanics during 1925 by Heisenberg and his colleagues was to recognize and emphasize the essential dynamical role of mental properties in the creation of our mental empirical findings. This basic feature of quantum mechanics was cast into rigorous mathematical form by John von Neumann, and was made a central feature of contemporary relativistic quantum field theory by the work of Tomonaga and Schwinger. That theory is causally strictly forward in time. But it is explained here how it can nevertheless accommodate the seeming backward-in-time causal effects reported by D.J. Bem, and many others, by means of a slight biasing of the famous Born Rule. The purpose of this communication is to explain how those reported retrocausal findings can be explained by a strictly forward-in-time and nearly orthodox causal dynamics that, however, permits the Born Rule to be slightly biased under certain conditions. A feasible experiment is proposed that, if it gives the outcomes predicted by the proposed theory, will provide evidence in favor of this causally forward-in-time and nearly orthodox explanation of the reported retrocausal effects.

An artificial nociceptor based on a diffusive memristor.

PubMed

Yoon, Jung Ho; Wang, Zhongrui; Kim, Kyung Min; Wu, Huaqiang; Ravichandran, Vignesh; Xia, Qiangfei; Hwang, Cheol Seong; Yang, J Joshua

2018-01-29

A nociceptor is a critical and special receptor of a sensory neuron that is able to detect noxious stimulus and provide a rapid warning to the central nervous system to start the motor response in the human body and humanoid robotics. It differs from other common sensory receptors with its key features and functions, including the "no adaptation" and "sensitization" phenomena. In this study, we propose and experimentally demonstrate an artificial nociceptor based on a diffusive memristor with critical dynamics for the first time. Using this artificial nociceptor, we further built an artificial sensory alarm system to experimentally demonstrate the feasibility and simplicity of integrating such novel artificial nociceptor devices in artificial intelligence systems, such as humanoid robots.

Finite driving rate and anisotropy effects in landslide modeling

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

Piegari, E.; Cataudella, V.; Di Maio, R.

2006-02-15

In order to characterize landslide frequency-size distributions and individuate hazard scenarios and their possible precursors, we investigate a cellular automaton where the effects of a finite driving rate and the anisotropy are taken into account. The model is able to reproduce observed features of landslide events, such as power-law distributions, as experimentally reported. We analyze the key role of the driving rate and show that, as it is increased, a crossover from power-law to non-power-law behaviors occurs. Finally, a systematic investigation of the model on varying its anisotropy factors is performed and the full diagram of its dynamical behaviors ismore » presented.« less

Efficiency reduction and pseudo-convergence in replica exchange sampling of peptide folding unfolding equilibria

NASA Astrophysics Data System (ADS)

Denschlag, Robert; Lingenheil, Martin; Tavan, Paul

2008-06-01

Replica exchange (RE) molecular dynamics (MD) simulations are frequently applied to sample the folding-unfolding equilibria of β-hairpin peptides in solution, because efficiency gains are expected from this technique. Using a three-state Markov model featuring key aspects of β-hairpin folding we show that RE simulations can be less efficient than conventional techniques. Furthermore we demonstrate that one is easily seduced to erroneously assign convergence to the RE sampling, because RE ensembles can rapidly reach long-lived stationary states. We conclude that typical REMD simulations covering a few tens of nanoseconds are by far too short for sufficient sampling of β-hairpin folding-unfolding equilibria.

Lévy walks

NASA Astrophysics Data System (ADS)

Zaburdaev, V.; Denisov, S.; Klafter, J.

2015-04-01

Random walk is a fundamental concept with applications ranging from quantum physics to econometrics. Remarkably, one specific model of random walks appears to be ubiquitous across many fields as a tool to analyze transport phenomena in which the dispersal process is faster than dictated by Brownian diffusion. The Lévy-walk model combines two key features, the ability to generate anomalously fast diffusion and a finite velocity of a random walker. Recent results in optics, Hamiltonian chaos, cold atom dynamics, biophysics, and behavioral science demonstrate that this particular type of random walk provides significant insight into complex transport phenomena. This review gives a self-consistent introduction to Lévy walks, surveys their existing applications, including latest advances, and outlines further perspectives.

Digital cytology: current state of the art and prospects for the future.

PubMed

Wilbur, David C

2011-01-01

The growth of digital methods in pathology is accelerating. Digital images can be used for a variety of applications in cytology, including rapid interpretations, primary diagnosis and second opinions, continuing education and proficiency testing. All of these functions can be performed using small static digital images, real-time dynamic digital microscopy, or whole-slide images. This review will discuss the general principles of digital pathology, its methods and applications to cytologic specimens. As cytologic specimens have unique features compared to histopathology specimens, the key differences will be discussed. Technical and administrative issues in digital pathology applications and the outlook for the future of the field will be presented. Copyright © 2011 S. Karger AG, Basel.

Review of phase measuring deflectometry

DOE PAGES

Huang, Lei; Idir, Mourad; Zuo, Chao; ...

2018-04-07

As a low cost, full-field three-dimensional shape measurement technique with high dynamic range, Phase Measuring Deflectometry (PMD) has been studied and improved to be a simple and effective manner to inspect specular reflecting surfaces. In this review, the fundamental principle and the basic concepts of PMD technique are introduced and followed by a brief overview of its key developments since it was first proposed. In addition, the similarities and differences compared with other related techniques are discussed to highlight the distinguishing features of the PMD technique. In conclusion, we will address the major challenges, the existing solutions and the remainingmore » limitations in this technique to provide some suggestions for potential future investigations.« less

Flotation separation of waste plastics for recycling-A review.

PubMed

Wang, Chong-qing; Wang, Hui; Fu, Jian-gang; Liu, You-nian

2015-07-01

The sharp increase of plastic wastes results in great social and environmental pressures, and recycling, as an effective way currently available to reduce the negative impacts of plastic wastes, represents one of the most dynamic areas in the plastics industry today. Froth flotation is a promising method to solve the key problem of recycling process, namely separation of plastic mixtures. This review surveys recent literature on plastics flotation, focusing on specific features compared to ores flotation, strategies, methods and principles, flotation equipments, and current challenges. In terms of separation methods, plastics flotation is divided into gamma flotation, adsorption of reagents, surface modification and physical regulation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

PubMed

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D; Jeong, Jaeseung

2014-08-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

Presidential Address: Turbulent magnetic fields in the Sun

NASA Astrophysics Data System (ADS)

Weiss, Nigel

2001-06-01

Nigel Weiss recounts his Presidential Address 2001, given to the RAS A&G Ordinary Meeting on 9 February 2001. Recent high-resolution observations, from the ground and from space, have revealed the fine structure of magnetic features at the surface of the Sun. At the same time, advances in computing power have at last made it possible to develop models of turbulent magnetoconvection that can be related to these observations. The key features of flux emergence and annihilation, as observed by the MDI experiment on SOHO, are reproduced in kinematic calculations, while three-dimensional numerical experiments reveal the dynamical processes that are involved. The pattern of convection depends on the strength of the magnetic field: as the mean field decreases, slender rising plumes give way to a regime where magnetic flux is separated from the motion and then to one where locally intense magnetic fields nestle between broad and vigorously convecting plumes. Moreover, turbulent convection is itself able to act as a small-scale dynamo, generating disordered fields near the solar surface.

Quantum Tunneling Affects Engine Performance.

PubMed

Som, Sibendu; Liu, Wei; Zhou, Dingyu D Y; Magnotti, Gina M; Sivaramakrishnan, Raghu; Longman, Douglas E; Skodje, Rex T; Davis, Michael J

2013-06-20

We study the role of individual reaction rates on engine performance, with an emphasis on the contribution of quantum tunneling. It is demonstrated that the effect of quantum tunneling corrections for the reaction HO2 + HO2 = H2O2 + O2 can have a noticeable impact on the performance of a high-fidelity model of a compression-ignition (e.g., diesel) engine, and that an accurate prediction of ignition delay time for the engine model requires an accurate estimation of the tunneling correction for this reaction. The three-dimensional model includes detailed descriptions of the chemistry of a surrogate for a biodiesel fuel, as well as all the features of the engine, such as the liquid fuel spray and turbulence. This study is part of a larger investigation of how the features of the dynamics and potential energy surfaces of key reactions, as well as their reaction rate uncertainties, affect engine performance, and results in these directions are also presented here.

Genome-wide chromatin state transitions associated with developmental and environmental cues.

PubMed

Zhu, Jiang; Adli, Mazhar; Zou, James Y; Verstappen, Griet; Coyne, Michael; Zhang, Xiaolan; Durham, Timothy; Miri, Mohammad; Deshpande, Vikram; De Jager, Philip L; Bennett, David A; Houmard, Joseph A; Muoio, Deborah M; Onder, Tamer T; Camahort, Ray; Cowan, Chad A; Meissner, Alexander; Epstein, Charles B; Shoresh, Noam; Bernstein, Bradley E

2013-01-31

Differences in chromatin organization are key to the multiplicity of cell states that arise from a single genetic background, yet the landscapes of in vivo tissues remain largely uncharted. Here, we mapped chromatin genome-wide in a large and diverse collection of human tissues and stem cells. The maps yield unprecedented annotations of functional genomic elements and their regulation across developmental stages, lineages, and cellular environments. They also reveal global features of the epigenome, related to nuclear architecture, that also vary across cellular phenotypes. Specifically, developmental specification is accompanied by progressive chromatin restriction as the default state transitions from dynamic remodeling to generalized compaction. Exposure to serum in vitro triggers a distinct transition that involves de novo establishment of domains with features of constitutive heterochromatin. We describe how these global chromatin state transitions relate to chromosome and nuclear architecture, and discuss their implications for lineage fidelity, cellular senescence, and reprogramming. Copyright © 2013 Elsevier Inc. All rights reserved.

Enhancing the Sensitivity of Pharmacophore-Based Virtual Screening by Incorporating Customized ZBG Features: A Case Study Using Histone Deacetylase 8.

PubMed

Hou, Xuben; Du, Jintong; Liu, Renshuai; Zhou, Yi; Li, Minyong; Xu, Wenfang; Fang, Hao

2015-04-27

As key regulators of epigenetic regulation, human histone deacetylases (HDACs) have been identified as drug targets for the treatment of several cancers. The proper recognition of zinc-binding groups (ZBGs) will help improve the accuracy of virtual screening for novel HDAC inhibitors. Here, we developed a high-specificity ZBG-based pharmacophore model for HDAC8 inhibitors by incorporating customized ZBG features. Subsequently, pharmacophore-based virtual screening led to the discovery of three novel HDAC8 inhibitors with low micromole IC50 values (1.8-1.9 μM). Further studies demonstrated that compound H8-A5 was selective for HDAC8 over HDAC 1/4 and showed antiproliferation activity in MDA-MB-231 cancer cells. Molecular docking and molecular dynamic studies suggested a possible binding mode for H8-A5, which provides a good starting point for the development of HDAC8 inhibitors in cancer treatment.

A simple and low-cost Internet-based teleconsultation system that could effectively solve the health care access problems in underserved areas of developing countries.

PubMed

Kuntalp, Mehmet; Akar, Orkun

2004-08-01

In many developing countries including Turkey, telemedicine systems are not in wide use due to the high cost and complexity of the required technology. Lack of these systems however has serious implications on patients who live in rural areas. The objective of this paper is to present a simple and economically affordable alternative to the current systems that would allow experts to easily access the medical data of their remote patients over the Internet. The system is developed in client-server architecture with a user-friendly graphical interface and various services are implemented as dynamic web pages based on PHP. The other key features of the system are its powerful security features and platform independency. An academic prototype is implemented and presented to the evaluation of a group of physicians. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries.

Crystal Structure of an LSD-Bound Human Serotonin Receptor

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

Wacker, Daniel; Wang, Sheng; McCorvy, John D.

The prototypical hallucinogen LSD acts via serotonin receptors, and here we describe the crystal structure of LSD in complex with the human serotonin receptor 5-HT2B. The complex reveals conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD’s key diethylamide moiety. LSD dissociates exceptionally slow from both 5-HT2BR and 5-HT2AR—a major target for its psychoactivity. Molecular dynamics (MD) simulations suggest that LSD’s slow binding kinetics may be due to a “lid” formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatlymore » accelerates LSD’s binding kinetics and selectively dampens LSD-mediated β-arrestin2 recruitment. This study thus reveals an unexpected binding mode of LSD; illuminates key features of its kinetics, stereochemistry, and signaling; and provides a molecular explanation for LSD’s actions at human serotonin receptors.« less

Crystal Structure of an LSD-Bound Human Serotonin Receptor.

PubMed

Wacker, Daniel; Wang, Sheng; McCorvy, John D; Betz, Robin M; Venkatakrishnan, A J; Levit, Anat; Lansu, Katherine; Schools, Zachary L; Che, Tao; Nichols, David E; Shoichet, Brian K; Dror, Ron O; Roth, Bryan L

2017-01-26

The prototypical hallucinogen LSD acts via serotonin receptors, and here we describe the crystal structure of LSD in complex with the human serotonin receptor 5-HT 2B . The complex reveals conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD's key diethylamide moiety. LSD dissociates exceptionally slow from both 5-HT 2B R and 5-HT 2A R-a major target for its psychoactivity. Molecular dynamics (MD) simulations suggest that LSD's slow binding kinetics may be due to a "lid" formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatly accelerates LSD's binding kinetics and selectively dampens LSD-mediated β-arrestin2 recruitment. This study thus reveals an unexpected binding mode of LSD; illuminates key features of its kinetics, stereochemistry, and signaling; and provides a molecular explanation for LSD's actions at human serotonin receptors. PAPERCLIP. Copyright © 2017 Elsevier Inc. All rights reserved.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

Land use change around protected areas: management to balance human needs and ecological function.

PubMed

DeFries, Ruth; Hansen, Andrew; Turner, B L; Reid, Robin; Liu, Jianguo

2007-06-01

Protected areas throughout the world are key for conserving biodiversity, and land use is key for providing food, fiber, and other ecosystem services essential for human sustenance. As land use change isolates protected areas from their surrounding landscapes, the challenge is to identify management opportunities that maintain ecological function while minimizing restrictions on human land use. Building on the case studies in this Invited Feature and on ecological principles, we identify opportunities for regional land management that maintain both ecological function in protected areas and human land use options, including preserving crucial habitats and migration corridors, and reducing dependence of local human populations on protected area resources. Identification of appropriate and effective management opportunities depends on clear definitions of: (1) the biodiversity attributes of concern; (2) landscape connections to delineate particular locations with strong ecological interactions between the protected area and its surrounding landscape; and (3) socioeconomic dynamics that determine current and future use of land resources in and around the protected area.

Ares-I-X Stability and Control Flight Test: Analysis and Plans

NASA Technical Reports Server (NTRS)

Brandon, Jay M.; Derry, Stephen D.; Heim, Eugene H.; Hueschen, Richard M.; Bacon, Barton J.

2008-01-01

The flight test of the Ares I-X vehicle provides a unique opportunity to reduce risk of the design of the Ares I vehicle and test out design, math modeling, and analysis methods. One of the key features of the Ares I design is the significant static aerodynamic instability coupled with the relatively flexible vehicle - potentially resulting in a challenging controls problem to provide adequate flight path performance while also providing adequate structural mode damping and preventing adverse control coupling to the flexible structural modes. Another challenge is to obtain enough data from the single flight to be able to conduct analysis showing the effectiveness of the controls solutions and have data to inform design decisions for Ares I. This paper will outline the modeling approaches and control system design to conduct this flight test, and also the system identification techniques developed to extract key information such as control system performance (gain/phase margins, for example), structural dynamics responses, and aerodynamic model estimations.

In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force

NASA Astrophysics Data System (ADS)

Menichetti, Roberto; Kanekal, Kiran H.; Kremer, Kurt; Bereau, Tristan

2017-09-01

The partitioning of small molecules in cell membranes—a key parameter for pharmaceutical applications—typically relies on experimentally available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics-based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400 000 compounds. The potential of mean force hereby becomes an easily accessible quantity—already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.

Controlling Rayleigh-Taylor Instabilities in Magnetically Driven Solid Metal Shells by Means of a Dynamic Screw Pinch

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

Schmit, P. F.; Velikovich, A. L.; McBride, R. D.

Magnetically driven implosions of solid metal shells are an effective vehicle to compress materials to extreme pressures and densities. Rayleigh-Taylor instabilities (RTI) are ubiquitous, yet typically undesired features in all such experiments where solid materials are rapidly accelerated to high velocities. In cylindrical shells (“liners”), the magnetic field driving the implosion can exacerbate the RTI. Here, we suggest an approach to implode solid metal liners enabling a remarkable reduction in the growth of magnetized RTI (MRTI) by employing a magnetic drive with a tilted, dynamic polarization, forming a dynamic screw pinch. Our calculations, based on a self-consistent analytic framework, demonstratemore » that the cumulative growth of the most deleterious MRTI modes may be reduced by as much as 1 to 2 orders of magnitude. One key application of this technique is to generate increasingly stable, higher-performance implosions of solid metal liners to achieve fusion [M. R. Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)]. Finally, we weigh the potentially dramatic benefits of the solid liner dynamic screw pinch against the experimental tradeoffs required to achieve the desired drive field history and identify promising designs for future experimental and computational studies.« less

Hyper-resting brain entropy within chronic smokers and its moderation by Sex

PubMed Central

Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze

2016-01-01

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking. PMID:27377552

Controlling Rayleigh-Taylor Instabilities in Magnetically Driven Solid Metal Shells by Means of a Dynamic Screw Pinch

DOE PAGES

Schmit, P. F.; Velikovich, A. L.; McBride, R. D.; ...

2016-11-11

Magnetically driven implosions of solid metal shells are an effective vehicle to compress materials to extreme pressures and densities. Rayleigh-Taylor instabilities (RTI) are ubiquitous, yet typically undesired features in all such experiments where solid materials are rapidly accelerated to high velocities. In cylindrical shells (“liners”), the magnetic field driving the implosion can exacerbate the RTI. Here, we suggest an approach to implode solid metal liners enabling a remarkable reduction in the growth of magnetized RTI (MRTI) by employing a magnetic drive with a tilted, dynamic polarization, forming a dynamic screw pinch. Our calculations, based on a self-consistent analytic framework, demonstratemore » that the cumulative growth of the most deleterious MRTI modes may be reduced by as much as 1 to 2 orders of magnitude. One key application of this technique is to generate increasingly stable, higher-performance implosions of solid metal liners to achieve fusion [M. R. Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)]. Finally, we weigh the potentially dramatic benefits of the solid liner dynamic screw pinch against the experimental tradeoffs required to achieve the desired drive field history and identify promising designs for future experimental and computational studies.« less

Key Features of High-Quality Policies and Guidelines to Support Social and Emotional Learning: Recommendations and Examples for the Collaborating States Initiative (CSI)

ERIC Educational Resources Information Center

Dusenbury, Linda; Yoder, Nick

2017-01-01

The current document serves two purposes. First, it provides an overview of six key features of a high-quality, comprehensive package of policies and guidance to support student social and emotional learning (SEL). These features are based on Collaborative for Academic Social, and Emotional Learning's (CASEL's) review of the research literature on…

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

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

Rubel, Oliver; Geddes, Cameron G.R.; Cormier-Michel, Estelle

2009-10-19

Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, an increasingly acute challenge is the practical need for computational techniques that aid in scientific knowledge discovery. To that end, we present a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. These techniques work cooperatively by first identifying features of interest in individual timesteps,more » then integrating features across timesteps, and based on the information derived perform analysis of temporally dynamic features. This combination of techniques supports accurate detection of particle beams enabling a deeper level of scientific understanding of physical phenomena than hasbeen possible before. By combining efficient data analysis algorithms and state-of-the-art data management we enable high-performance analysis of extremely large particle datasets in 3D. We demonstrate the usefulness of our methods for a variety of 2D and 3D datasets and discuss the performance of our analysis pipeline.« less

Observation of Reconnection Features in the Chromosphere through a Chromospheric Jet Observed by SOT/Hinode

NASA Astrophysics Data System (ADS)

Singh, K. A. P.; Isobe, H.; Shibata, K.

2012-08-01

High-resolution observations from Solar Optical Telescope (SOT) onboard Hinode has shown number of jet-like structures in the solar chromosphere. One of the key features in the observations is the clear presence of tiny, inverted Y-shaped jets called Chromospheric Anemone Jets. These jets are supposed to be formed as a result of the magnetic reconnection, however, whether and how fast magnetic reconnection is realized in partially ionized, fully collisional chromosphere is poorly understood. In this paper, we report the observation of a well resolved jet phenomenon observed from SOT. The jets were found to recur at the same location. We observed multiple blobs ejected along the jet. The jets occur after the ejection of blobs. It is noticed that the brightness enhancements at the footpoint of the jet are related with the height of the jet. These features indicate an important role of plasmoid dynamics and intermittent nature of the chromospheric reconnection. The lifetime of the plasmoid is 30 s - 50 s. We noticed the undulations in chromospheric anemone jets. The evolution of a single jet is consistent with the Sweeping-Magnetic-Twist mechanism proposed by Shibata and Uchida (1986).

Web Based Semi-automatic Scientific Validation of Models of the Corona and Inner Heliosphere

NASA Astrophysics Data System (ADS)

MacNeice, P. J.; Chulaki, A.; Taktakishvili, A.; Kuznetsova, M. M.

2013-12-01

Validation is a critical step in preparing models of the corona and inner heliosphere for future roles supporting either or both the scientific research community and the operational space weather forecasting community. Validation of forecasting quality tends to focus on a short list of key features in the model solutions, with an unchanging order of priority. Scientific validation exposes a much larger range of physical processes and features, and as the models evolve to better represent features of interest, the research community tends to shift its focus to other areas which are less well understood and modeled. Given the more comprehensive and dynamic nature of scientific validation, and the limited resources available to the community to pursue this, it is imperative that the community establish a semi-automated process which engages the model developers directly into an ongoing and evolving validation process. In this presentation we describe the ongoing design and develpment of a web based facility to enable this type of validation of models of the corona and inner heliosphere, on the growing list of model results being generated, and on strategies we have been developing to account for model results that incorporate adaptively refined numerical grids.

Fuzzy Nonlinear Proximal Support Vector Machine for Land Extraction Based on Remote Sensing Image

PubMed Central

Zhong, Xiaomei; Li, Jianping; Dou, Huacheng; Deng, Shijun; Wang, Guofei; Jiang, Yu; Wang, Yongjie; Zhou, Zebing; Wang, Li; Yan, Fei

2013-01-01

Currently, remote sensing technologies were widely employed in the dynamic monitoring of the land. This paper presented an algorithm named fuzzy nonlinear proximal support vector machine (FNPSVM) by basing on ETM+ remote sensing image. This algorithm is applied to extract various types of lands of the city Da’an in northern China. Two multi-category strategies, namely “one-against-one” and “one-against-rest” for this algorithm were described in detail and then compared. A fuzzy membership function was presented to reduce the effects of noises or outliers on the data samples. The approaches of feature extraction, feature selection, and several key parameter settings were also given. Numerous experiments were carried out to evaluate its performances including various accuracies (overall accuracies and kappa coefficient), stability, training speed, and classification speed. The FNPSVM classifier was compared to the other three classifiers including the maximum likelihood classifier (MLC), back propagation neural network (BPN), and the proximal support vector machine (PSVM) under different training conditions. The impacts of the selection of training samples, testing samples and features on the four classifiers were also evaluated in these experiments. PMID:23936016

Estrogen Receptor Folding Modulates cSrc Kinase SH2 Interaction via a Helical Binding Mode.

PubMed

Nieto, Lidia; Tharun, Inga M; Balk, Mark; Wienk, Hans; Boelens, Rolf; Ottmann, Christian; Milroy, Lech-Gustav; Brunsveld, Luc

2015-11-20

The estrogen receptors (ERs) feature, next to their transcriptional role, important nongenomic signaling actions, with emerging clinical relevance. The Src Homology 2 (SH2) domain mediated interaction between cSrc kinase and ER plays a key role in this; however the molecular determinants of this interaction have not been elucidated. Here, we used phosphorylated ER peptide and semisynthetic protein constructs in a combined biochemical and structural study to, for the first time, provide a quantitative and structural characterization of the cSrc SH2-ER interaction. Fluorescence polarization experiments delineated the SH2 binding motif in the ER sequence. Chemical shift perturbation analysis by nuclear magnetic resonance (NMR) together with molecular dynamics (MD) simulations allowed us to put forward a 3D model of the ER-SH2 interaction. The structural basis of this protein-protein interaction has been compared with that of the high affinity SH2 binding sequence GpYEEI. The ER features a different binding mode from that of the "two-pronged plug two-hole socket" model in the so-called specificity determining region. This alternative binding mode is modulated via the folding of ER helix 12, a structural element directly C-terminal of the key phosphorylated tyrosine. The present findings provide novel molecular entries for understanding nongenomic ER signaling and targeting the corresponding disease states.

Community engagement as conflict prevention: Understanding the social license to operate

NASA Astrophysics Data System (ADS)

Knih, Dejana

This thesis examines community engagement as a form of conflict prevention in order to obtain the social license to operate (SLO) in Alberta's oil and gas industry. It does this by answering the question: what are the key elements of the Social License to Operate and how can these elements be applied to community engagement/consultation in a way that prevents conflicts in Alberta's oil and gas industry? The underlying assumption of this thesis is that building good relationships and working collaboratively functions as a form of conflict prevention and that this in turn leads to the SLO. This thesis outlines the key features of both successful community engagement and of the SLO, to provide a guideline for what is needed to obtain the SLO. Data was collected from semi-structured interviews and through a literature review. The data analysis concluded that there are direct parallels between the key elements of effective community engagement and the key elements of the SLO as identified in the interviews. These parallels are: knowing the community, addressing community needs, corporate social responsibility, relationship building, follow through and evidence for what has been done, executive buy-in, excellent communication, and open dialogue, all within a process which is principled (there is trust, understanding, transparency and respect), inclusive, dynamic, flexible, ongoing, and long-term. Moreover, the key elements of effective community engagement and of the SLO identified in the interviews also overlapped with those found in the literature review, with only one exception. The literature review explicitly named early involvement as a key element of both effective community engagement and the SLO, whereas the interview participants only explicitly indicated it as a key factor of community engagement and implied it to be a key element of the SLO.

Dynamical organization towards consensus in the Axelrod model on complex networks

NASA Astrophysics Data System (ADS)

Guerra, Beniamino; Poncela, Julia; Gómez-Gardeñes, Jesús; Latora, Vito; Moreno, Yamir

2010-05-01

We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.

Location-Aware Dynamic Session-Key Management for Grid-Based Wireless Sensor Networks

PubMed Central

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths. PMID:22163606

Location-aware dynamic session-key management for grid-based Wireless Sensor Networks.

PubMed

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths.

Anomalous Transient Amplification of Waves in Non-normal Photonic Media

NASA Astrophysics Data System (ADS)

Makris, K. G.; Ge, L.; Türeci, H. E.

2014-10-01

Dissipation is a ubiquitous phenomenon in dynamical systems encountered in nature because no finite system is fully isolated from its environment. In optical systems, a key challenge facing any technological application has traditionally been the mitigation of optical losses. Recent work has shown that a new class of optical materials that consist of a precisely balanced distribution of loss and gain can be exploited to engineer novel functionalities for propagating and filtering electromagnetic radiation. Here we show a generic property of optical systems that feature an unbalanced distribution of loss and gain, described by non-normal operators, namely, that an overall lossy optical system can transiently amplify certain input signals by several orders of magnitude. We present a mathematical framework to analyze the dynamics of wave propagation in media with an arbitrary distribution of loss and gain, and we construct the initial conditions to engineer such non-normal power amplifiers. Our results point to a new design space for engineered optical systems employed in photonics and quantum optics.

Quantized transport and steady states of Floquet topological insulators

NASA Astrophysics Data System (ADS)

Esin, Iliya; Rudner, Mark S.; Refael, Gil; Lindner, Netanel H.

2018-06-01

Robust electronic edge or surface modes play key roles in the fascinating quantized responses exhibited by topological materials. Even in trivial materials, topological bands and edge states can be induced dynamically by a time-periodic drive. Such Floquet topological insulators (FTIs) inherently exist out of equilibrium; the extent to which they can host quantized transport, which depends on the steady-state population of their dynamically induced edge states, remains a crucial question. In this work, we obtain the steady states of two-dimensional FTIs in the presence of the natural dissipation mechanisms present in solid state systems. We give conditions under which the steady-state distribution resembles that of a topological insulator in the Floquet basis. In this state, the distribution in the Floquet edge modes exhibits a sharp feature akin to a Fermi level, while the bulk hosts a small density of excitations. We determine the regimes where topological edge-state transport persists and can be observed in FTIs.

Thermally-Driven Mantle Plumes Reconcile Hot-spot Observations

NASA Astrophysics Data System (ADS)

Davies, D.; Davies, J.

2008-12-01

Hot-spots are anomalous regions of magmatism that cannot be directly associated with plate tectonic processes (e.g. Morgan, 1972). They are widely regarded as the surface expression of upwelling mantle plumes. Hot-spots exhibit variable life-spans, magmatic productivity and fixity (e.g. Ito and van Keken, 2007). This suggests that a wide-range of upwelling structures coexist within Earth's mantle, a view supported by geochemical and seismic evidence, but, thus far, not reproduced by numerical models. Here, results from a new, global, 3-D spherical, mantle convection model are presented, which better reconcile hot-spot observations, the key modification from previous models being increased convective vigor. Model upwellings show broad-ranging dynamics; some drift slowly, while others are more mobile, displaying variable life-spans, intensities and migration velocities. Such behavior is consistent with hot-spot observations, indicating that the mantle must be simulated at the correct vigor and in the appropriate geometry to reproduce Earth-like dynamics. Thermally-driven mantle plumes can explain the principal features of hot-spot volcanism on Earth.

Atomic species identification at the (101) anatase surface by simultaneous scanning tunnelling and atomic force microscopy

PubMed Central

Stetsovych, Oleksandr; Todorović, Milica; Shimizu, Tomoko K.; Moreno, César; Ryan, James William; León, Carmen Pérez; Sagisaka, Keisuke; Palomares, Emilio; Matolín, Vladimír; Fujita, Daisuke; Perez, Ruben; Custance, Oscar

2015-01-01

Anatase is a pivotal material in devices for energy-harvesting applications and catalysis. Methods for the accurate characterization of this reducible oxide at the atomic scale are critical in the exploration of outstanding properties for technological developments. Here we combine atomic force microscopy (AFM) and scanning tunnelling microscopy (STM), supported by first-principles calculations, for the simultaneous imaging and unambiguous identification of atomic species at the (101) anatase surface. We demonstrate that dynamic AFM-STM operation allows atomic resolution imaging within the material's band gap. Based on key distinguishing features extracted from calculations and experiments, we identify candidates for the most common surface defects. Our results pave the way for the understanding of surface processes, like adsorption of metal dopants and photoactive molecules, that are fundamental for the catalytic and photovoltaic applications of anatase, and demonstrate the potential of dynamic AFM-STM for the characterization of wide band gap materials. PMID:26118408

Maximal aggregation of polynomial dynamical systems

PubMed Central

Cardelli, Luca; Tschaikowski, Max

2017-01-01

Ordinary differential equations (ODEs) with polynomial derivatives are a fundamental tool for understanding the dynamics of systems across many branches of science, but our ability to gain mechanistic insight and effectively conduct numerical evaluations is critically hindered when dealing with large models. Here we propose an aggregation technique that rests on two notions of equivalence relating ODE variables whenever they have the same solution (backward criterion) or if a self-consistent system can be written for describing the evolution of sums of variables in the same equivalence class (forward criterion). A key feature of our proposal is to encode a polynomial ODE system into a finitary structure akin to a formal chemical reaction network. This enables the development of a discrete algorithm to efficiently compute the largest equivalence, building on approaches rooted in computer science to minimize basic models of computation through iterative partition refinements. The physical interpretability of the aggregation is shown on polynomial ODE systems for biochemical reaction networks, gene regulatory networks, and evolutionary game theory. PMID:28878023

Visualizing the non-equilibrium dynamics of photoinduced intramolecular electron transfer with femtosecond X-ray pulses

PubMed Central

Canton, Sophie E.; Kjær, Kasper S.; Vankó, György; van Driel, Tim B.; Adachi, Shin-ichi; Bordage, Amélie; Bressler, Christian; Chabera, Pavel; Christensen, Morten; Dohn, Asmus O.; Galler, Andreas; Gawelda, Wojciech; Gosztola, David; Haldrup, Kristoffer; Harlang, Tobias; Liu, Yizhu; Møller, Klaus B.; Németh, Zoltán; Nozawa, Shunsuke; Pápai, Mátyás; Sato, Tokushi; Sato, Takahiro; Suarez-Alcantara, Karina; Togashi, Tadashi; Tono, Kensuke; Uhlig, Jens; Vithanage, Dimali A.; Wärnmark, Kenneth; Yabashi, Makina; Zhang, Jianxin; Sundström, Villy; Nielsen, Martin M.

2015-01-01

Ultrafast photoinduced electron transfer preceding energy equilibration still poses many experimental and conceptual challenges to the optimization of photoconversion since an atomic-scale description has so far been beyond reach. Here we combine femtosecond transient optical absorption spectroscopy with ultrafast X-ray emission spectroscopy and diffuse X-ray scattering at the SACLA facility to track the non-equilibrated electronic and structural dynamics within a bimetallic donor–acceptor complex that contains an optically dark centre. Exploiting the 100-fold increase in temporal resolution as compared with storage ring facilities, these measurements constitute the first X-ray-based visualization of a non-equilibrated intramolecular electron transfer process over large interatomic distances. Experimental and theoretical results establish that mediation through electronically excited molecular states is a key mechanistic feature. The present study demonstrates the extensive potential of femtosecond X-ray techniques as diagnostics of non-adiabatic electron transfer processes in synthetic and biological systems, and some directions for future studies, are outlined. PMID:25727920

Nucleosome-free DNA regions differentially affect distant communication in chromatin

PubMed Central

Nizovtseva, Ekaterina V.; Clauvelin, Nicolas; Todolli, Stefjord; Kulaeva, Olga I.; Wengrzynek, Scott

2017-01-01

Abstract Communication between distantly spaced genomic regions is one of the key features of gene regulation in eukaryotes. Chromatin per se can stimulate efficient enhancer-promoter communication (EPC); however, the role of chromatin structure and dynamics in this process remains poorly understood. Here we show that nucleosome spacing and the presence of nucleosome-free DNA regions can modulate chromatin structure/dynamics and, in turn, affect the rate of EPC in vitro and in silico. Increasing the length of internucleosomal linker DNA from 25 to 60 bp results in more efficient EPC. The presence of longer nucleosome-free DNA regions can positively or negatively affect the rate of EPC, depending upon the length and location of the DNA region within the chromatin fiber. Thus the presence of histone-free DNA regions can differentially affect the efficiency of EPC, suggesting that gene regulation over a distance could be modulated by changes in the length of internucleosomal DNA spacers. PMID:27940560

Visualizing the non-equilibrium dynamics of photoinduced intramolecular electron transfer with femtosecond X-ray pulses

DOE PAGES

Canton, Sophie E.; Kjær, Kasper S.; Vankó, György; ...

2015-03-02

Ultrafast photoinduced electron transfer preceding energy equilibration still poses many experimental and conceptual challenges to the optimization of photoconversion since an atomic-scale description has so far been beyond reach. Here we combine femtosecond transient optical absorption spectroscopy with ultrafast X-ray emission spectroscopy and diffuse X-ray scattering at the SACLA facility to track the non-equilibrated electronic and structural dynamics within a bimetallic donor–acceptor complex that contains an optically dark centre. Exploiting the 100-fold increase in temporal resolution as compared with storage ring facilities, these measurements constitute the first X-ray-based visualization of a non-equilibrated intramolecular electron transfer process over large interatomic distances.more » Thus experimental and theoretical results establish that mediation through electronically excited molecular states is a key mechanistic feature. The present study demonstrates the extensive potential of femtosecond X-ray techniques as diagnostics of non-adiabatic electron transfer processes in synthetic and biological systems, and some directions for future studies, are outlined.« less

Percolation Model of Sensory Transmission and Loss of Consciousness Under General Anesthesia

NASA Astrophysics Data System (ADS)

Zhou, David W.; Mowrey, David D.; Tang, Pei; Xu, Yan

2015-09-01

Neurons communicate with each other dynamically; how such communications lead to consciousness remains unclear. Here, we present a theoretical model to understand the dynamic nature of sensory activity and information integration in a hierarchical network, in which edges are stochastically defined by a single parameter p representing the percolation probability of information transmission. We validate the model by comparing the transmitted and original signal distributions, and we show that a basic version of this model can reproduce key spectral features clinically observed in electroencephalographic recordings of transitions from conscious to unconscious brain activities during general anesthesia. As p decreases, a steep divergence of the transmitted signal from the original was observed, along with a loss of signal synchrony and a sharp increase in information entropy in a critical manner; this resembles the precipitous loss of consciousness during anesthesia. The model offers mechanistic insights into the emergence of information integration from a stochastic process, laying the foundation for understanding the origin of cognition.

Role of word-of-mouth for programs of voluntary vaccination: A game-theoretic approach.

PubMed

Bhattacharyya, Samit; Bauch, Chris T; Breban, Romulus

2015-11-01

We propose a model describing the synergetic feedback between word-of-mouth (WoM) and epidemic dynamics controlled by voluntary vaccination. The key feature consists in combining a game-theoretic model for the spread of WoM and a compartmental model describing VSIR disease dynamics in the presence of a program of voluntary vaccination. We evaluate and compare two scenarios for determinants of behavior, depending on what WoM disseminates: (1) vaccine advertising, which may occur whether or not an epidemic is ongoing and (2) epidemic status, notably disease prevalence. Understanding the synergy between the two strategies could be particularly important for designing voluntary vaccination campaigns. We find that, in the initial phase of an epidemic, vaccination uptake is determined more by vaccine advertising than the epidemic status. As the epidemic progresses, epidemic status becomes increasingly important for vaccination uptake, considerably accelerating vaccination uptake toward a stable vaccination coverage. Copyright © 2015 Elsevier Inc. All rights reserved.

The Latest on the Venus Thermospheric General Circulation Model: Capabilities and Simulations

NASA Technical Reports Server (NTRS)

Brecht, A. S.; Bougher, S. W.; Parkinson, C. D.

2017-01-01

Venus has a complex and dynamic upper atmosphere. This has been observed many times by ground-based, orbiters, probes, and fly-by missions going to other planets. Two over-arching questions are generally asked when examining the Venus upper atmosphere: (1) what creates the complex structure in the atmosphere, and (2) what drives the varying dynamics. A great way to interpret and connect observations to address these questions utilizes numerical modeling; and in the case of the middle and upper atmosphere (above the cloud tops), a 3D hydrodynamic numerical model called the Venus Thermospheric General Circulation Model (VTGCM) can be used. The VTGCM can produce climatological averages of key features in comparison to observations (i.e. nightside temperature, O2 IR nightglow emission). More recently, the VTGCM has been expanded to include new chemical constituents and airglow emissions, as well as new parameterizations to address waves and their impact on the varying global circulation and corresponding airglow distributions.

Effect of point defects on the thermal conductivity of UO2: molecular dynamics simulations

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

Liu, Xiang-Yang; Stanek, Christopher Richard; Andersson, Anders David Ragnar

2015-07-21

The thermal conductivity of uranium dioxide (UO 2) fuel is an important materials property that affects fuel performance since it is a key parameter determining the temperature distribution in the fuel, thus governing, e.g., dimensional changes due to thermal expansion, fission gas release rates, etc. [1] The thermal conductivity of UO 2 nuclear fuel is also affected by fission gas, fission products, defects, and microstructural features such as grain boundaries. Here, molecular dynamics (MD) simulations are carried out to determine quantitatively, the effect of irradiation induced point defects on the thermal conductivity of UO 2, as a function of defectmore » concentrations, for a range of temperatures, 300 – 1500 K. The results will be used to develop enhanced continuum thermal conductivity models for MARMOT and BISON by INL. These models express the thermal conductivity as a function of microstructure state-variables, thus enabling thermal conductivity models with closer connection to the physical state of the fuel [2].« less

Trace explosives sensor testbed (TESTbed)

NASA Astrophysics Data System (ADS)

Collins, Greg E.; Malito, Michael P.; Tamanaha, Cy R.; Hammond, Mark H.; Giordano, Braden C.; Lubrano, Adam L.; Field, Christopher R.; Rogers, Duane A.; Jeffries, Russell A.; Colton, Richard J.; Rose-Pehrsson, Susan L.

2017-03-01

A novel vapor delivery testbed, referred to as the Trace Explosives Sensor Testbed, or TESTbed, is demonstrated that is amenable to both high- and low-volatility explosives vapors including nitromethane, nitroglycerine, ethylene glycol dinitrate, triacetone triperoxide, 2,4,6-trinitrotoluene, pentaerythritol tetranitrate, and hexahydro-1,3,5-trinitro-1,3,5-triazine. The TESTbed incorporates a six-port dual-line manifold system allowing for rapid actuation between a dedicated clean air source and a trace explosives vapor source. Explosives and explosives-related vapors can be sourced through a number of means including gas cylinders, permeation tube ovens, dynamic headspace chambers, and a Pneumatically Modulated Liquid Delivery System coupled to a perfluoroalkoxy total-consumption microflow nebulizer. Key features of the TESTbed include continuous and pulseless control of trace vapor concentrations with wide dynamic range of concentration generation, six sampling ports with reproducible vapor profile outputs, limited low-volatility explosives adsorption to the manifold surface, temperature and humidity control of the vapor stream, and a graphical user interface for system operation and testing protocol implementation.

Probing RNA Native Conformational Ensembles with Structural Constraints.

PubMed

Fonseca, Rasmus; van den Bedem, Henry; Bernauer, Julie

2016-05-01

Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

mizer: an R package for multispecies, trait-based and community size spectrum ecological modelling.

PubMed

Scott, Finlay; Blanchard, Julia L; Andersen, Ken H

2014-10-01

Size spectrum ecological models are representations of a community of individuals which grow and change trophic level. A key emergent feature of these models is the size spectrum; the total abundance of all individuals that scales negatively with size. The models we focus on are designed to capture fish community dynamics useful for assessing the community impacts of fishing.We present mizer , an R package for implementing dynamic size spectrum ecological models of an entire aquatic community subject to fishing. Multiple fishing gears can be defined and fishing mortality can change through time making it possible to simulate a range of exploitation strategies and management options. mizer implements three versions of the size spectrum modelling framework: the community model, where individuals are only characterized by their size; the trait-based model, where individuals are further characterized by their asymptotic size; and the multispecies model where additional trait differences are resolved.A range of plot, community indicator and summary methods are available to inspect the results of the simulations.

Dynamical tuning between nearly perfect reflection, absorption, and transmission of light via graphene/dielectric structures

PubMed Central

Linder, Jacob; Halterman, Klaus

2016-01-01

Exerting well-defined control over the reflection (R), absorption (A), and transmission (T) of electromagnetic waves is a key objective in quantum optics. To this end, one often utilizes hybrid structures comprised of elements with different optical properties in order to achieve features such as high R or high A for incident light. A desirable goal would be the possibility to tune between all three regimes of nearly perfect reflection, absorption, and transmission within the same device, thus swapping between the cases R → 1, A → 1, and T → 1 dynamically. We here show that a dielectric interfaced with a graphene layer on each side allows for precisely this: by tuning only the Fermi level of graphene, all three regimes can be reached in the THz regime and below. Moreover, we show that the inclusion of cylindrical defects in the system offers a different type of control of the scattering of electromagnetic waves by means of the graphene layers. PMID:27917886

Magnetic structure and excitation spectrum of the hyperhoneycomb Kitaev magnet β -Li2IrO3

NASA Astrophysics Data System (ADS)

Ducatman, Samuel; Rousochatzakis, Ioannis; Perkins, Natalia B.

2018-03-01

We present a theoretical study of the static and dynamical properties of the three-dimensional, hyperhoneycomb Kitaev magnet β -Li2IrO3 . We argue that the observed incommensurate order can be understood in terms of a long-wavelength twisting of a nearby commensurate period-3 state, with the same key qualitatively features. The period-3 state shows very different structure when either the Kitaev interaction K or the off-diagonal exchange anisotropy Γ is dominant. A comparison of the associated static spin structure factors with reported scattering experiments in zero and finite fields gives strong evidence that β -Li2IrO3 lies in the regime of dominant Kitaev coupling, and that the Heisenberg exchange J is much weaker than both K and Γ . Our predictions for the magnon excitation spectra, the dynamical spin structure factors, and their polarization dependence provide additional distinctive fingerprints that can be checked experimentally.

Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique.

PubMed

Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong

2016-09-01

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.

Dynamic modeling and validation of a lignocellulosic enzymatic hydrolysis process--a demonstration scale study.

PubMed

Prunescu, Remus Mihail; Sin, Gürkan

2013-12-01

The enzymatic hydrolysis process is one of the key steps in second generation biofuel production. After being thermally pretreated, the lignocellulosic material is liquefied by enzymes prior to fermentation. The scope of this paper is to evaluate a dynamic model of the hydrolysis process on a demonstration scale reactor. The following novel features are included: the application of the Convection-Diffusion-Reaction equation to a hydrolysis reactor to assess transport and mixing effects; the extension of a competitive kinetic model with enzymatic pH dependency and hemicellulose hydrolysis; a comprehensive pH model; and viscosity estimations during the course of reaction. The model is evaluated against real data extracted from a demonstration scale biorefinery throughout several days of operation. All measurements are within predictions uncertainty and, therefore, the model constitutes a valuable tool to support process optimization, performance monitoring, diagnosis and process control at full-scale studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Shape dynamics and Mach's principles: Gravity from conformal geometrodynamics

NASA Astrophysics Data System (ADS)

Gryb, Sean

2012-04-01

In this PhD thesis, we develop a new approach to classical gravity starting from Mach's principles and the idea that the local shape of spatial configurations is fundamental. This new theory, "shape dynamics", is equivalent to general relativity but differs in an important respect: shape dynamics is a theory of dynamic conformal 3-geometry, not a theory of spacetime. Equivalence is achieved by trading foliation invariance for local conformal invariance (up to a global scale). After the trading, what is left is a gauge theory invariant under 3d diffeomorphisms and conformal transformations that preserve the volume of space. The local canonical constraints are linear and the constraint algebra closes with structure constants. Shape dynamics, thus, provides a novel new starting point for quantum gravity. The procedure for the trading of symmetries was inspired by a technique called "best matching". We explain best matching and its relation to Mach's principles. The key features of best matching are illustrated through finite dimensional toy models. A general picture is then established where relational theories are treated as gauge theories on configuration space. Shape dynamics is then constructed by applying best matching to conformal geometry. We then study shape dynamics in more detail by computing its Hamiltonian and Hamilton-Jacobi functional perturbatively. This thesis is intended as a pedagogical but complete introduction to shape dynamics and the Machian ideas that led to its discovery. The reader is encouraged to start with the introduction, which gives a conceptual outline and links to the relevant sections in the text for a more rigorous exposition. When full rigor is lacking, references to the literature are given. It is hoped that this thesis may provide a starting point for anyone interested in learning about shape dynamics.

Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model.

PubMed

Brunker, K; Hampson, K; Horton, D L; Biek, R

2012-12-01

Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

How causal analysis can reveal autonomy in models of biological systems

NASA Astrophysics Data System (ADS)

Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

2017-11-01

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

The Emergent Executive: A Dynamic Field Theory of the Development of Executive Function

PubMed Central

Buss, Aaron T.; Spencer, John P.

2015-01-01

A dynamic neural field (DNF) model is presented which provides a process-based account of behavior and developmental change in a key task used to probe the early development of executive function—the Dimensional Change Card Sort (DCCS) task. In the DCCS, children must flexibly switch from sorting cards either by shape or color to sorting by the other dimension. Typically, 3-year-olds, but not 4-year-olds, lack the flexibility to do so and perseverate on the first set of rules when instructed to switch. In the DNF model, rule-use and behavioral flexibility come about through a form of dimensional attention which modulates activity within different cortical fields tuned to specific feature dimensions. In particular, we capture developmental change by increasing the strength of excitatory and inhibitory neural interactions in the dimensional attention system as well as refining the connectivity between this system and the feature-specific cortical fields. Note that although this enables the model to effectively switch tasks, the dimensional attention system does not ‘know’ the details of task-specific performance. Rather, correct performance emerges as a property of system-wide neural interactions. We show how this captures children's behavior in quantitative detail across 12 versions of the DCCS task. Moreover, we successfully test a set of novel predictions with 3-year-old children from a version of the task not explained by other theories. PMID:24818836

Invasion and Persistence of Infectious Agents in Fragmented Host Populations

PubMed Central

Jesse, Marieke; Mazzucco, Rupert; Dieckmann, Ulf; Heesterbeek, Hans; Metz, Johan A. J.

2011-01-01

One of the important questions in understanding infectious diseases and their prevention and control is how infectious agents can invade and become endemic in a host population. A ubiquitous feature of natural populations is that they are spatially fragmented, resulting in relatively homogeneous local populations inhabiting patches connected by the migration of hosts. Such fragmented population structures are studied extensively with metapopulation models. Being able to define and calculate an indicator for the success of invasion and persistence of an infectious agent is essential for obtaining general qualitative insights into infection dynamics, for the comparison of prevention and control scenarios, and for quantitative insights into specific systems. For homogeneous populations, the basic reproduction ratio plays this role. For metapopulations, defining such an ‘invasion indicator’ is not straightforward. Some indicators have been defined for specific situations, e.g., the household reproduction number . However, these existing indicators often fail to account for host demography and especially host migration. Here we show how to calculate a more broadly applicable indicator for the invasion and persistence of infectious agents in a host metapopulation of equally connected patches, for a wide range of possible epidemiological models. A strong feature of our method is that it explicitly accounts for host demography and host migration. Using a simple compartmental system as an example, we illustrate how can be calculated and expressed in terms of the key determinants of epidemiological dynamics. PMID:21980339

KOSMOS: a universal morph server for nucleic acids, proteins and their complexes

PubMed Central

Seo, Sangjae; Kim, Moon Ki

2012-01-01

KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos. PMID:22669912

Missouri Program Highlights How Standards Make a Difference

ERIC Educational Resources Information Center

Killion, Joellen

2017-01-01

Professional development designed to integrate key features of research-based professional learning has positive and significant effects on teacher practice and student achievement in mathematics when implemented in schools that meet specified technology-readiness criteria. Key features of research-based professional learning include intensive…

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Emotional Responses to Music: Shifts in Frontal Brain Asymmetry Mark Periods of Musical Change.

PubMed

Arjmand, Hussain-Abdulah; Hohagen, Jesper; Paton, Bryan; Rickard, Nikki S

2017-01-01

Recent studies have demonstrated increased activity in brain regions associated with emotion and reward when listening to pleasurable music. Unexpected change in musical features intensity and tempo - and thereby enhanced tension and anticipation - is proposed to be one of the primary mechanisms by which music induces a strong emotional response in listeners. Whether such musical features coincide with central measures of emotional response has not, however, been extensively examined. In this study, subjective and physiological measures of experienced emotion were obtained continuously from 18 participants (12 females, 6 males; 18-38 years) who listened to four stimuli-pleasant music, unpleasant music (dissonant manipulations of their own music), neutral music, and no music, in a counter-balanced order. Each stimulus was presented twice: electroencephalograph (EEG) data were collected during the first, while participants continuously subjectively rated the stimuli during the second presentation. Frontal asymmetry (FA) indices from frontal and temporal sites were calculated, and peak periods of bias toward the left (indicating a shift toward positive affect) were identified across the sample. The music pieces were also examined to define the temporal onset of key musical features. Subjective reports of emotional experience averaged across the condition confirmed participants rated their music selection as very positive, the scrambled music as negative, and the neutral music and silence as neither positive nor negative. Significant effects in FA were observed in the frontal electrode pair FC3-FC4, and the greatest increase in left bias from baseline was observed in response to pleasurable music. These results are consistent with findings from previous research. Peak FA responses at this site were also found to co-occur with key musical events relating to change, for instance, the introduction of a new motif, or an instrument change, or a change in low level acoustic factors such as pitch, dynamics or texture. These findings provide empirical support for the proposal that change in basic musical features is a fundamental trigger of emotional responses in listeners.

Ice Streams as the Critical Link Between the Interior Ice Reservoir of the Antarctic Ice Sheet and the Global Climate System - a WISSARD Perspective (Invited)

NASA Astrophysics Data System (ADS)

Tulaczyk, S. M.; Beem, L.; Walter, J. I.; Hossainzadeh, S.; Mankoff, K. D.

2010-12-01

Fast flowing ice streams represent crucial features of the Antarctic ice sheet because they provide discharge ‘valves’ for the interior ice reservoir and because their grounding lines are exposed to ocean thermal forcing. Even with no/little topographic control ice flow near the perimeter of a polar ice sheet self-organizes into discrete, fast-flowing ice streams. Within these features basal melting (i.e. lubrication for ice sliding) is sustained through elevated basal shear heating in a region of thin ice that would otherwise be characterized by basal freezing and slow ice motion. Because faster basal ice motion is typically associated with faster subglacial erosion, ice streams tend to localize themselves over time by carving troughs into underlying rocks and sediments. Debris generated by this erosional activity is carried to the continental shelf and/or continental slope where it may be deposited at very high rates, rivaling these associated with deposition by some of the largest rivers on Earth. In terms of their hydrologic and geological functions, Antarctic ice streams play pretty much the same role as rivers do on non-glaciated continents. However, understanding of their dynamics is still quite rudimentary, largely because of the relative inaccessibility of the key basal and marine boundaries of ice streams where pertinent measurements need to be made. The present elevated interest in predicting future contribution of Antarctica to global sea level changes is driving ambitious research programs aimed at scientific exploration of these poorly investigated environments that will play a key role in defining the response of the ice sheet to near future climate changes. We will review one of these programs, the Whillans Ice Stream Subglacial Access Research Drilling (WISSARD) with particular focus on its planned contributions to understanding of ice stream dynamics.

Tumor heterogeneity and progression: conceptual foundations for modeling.

PubMed

Greller, L D; Tobin, F L; Poste, G

1996-01-01

A conceptual foundation for modeling tumor progression, growth, and heterogeneity is presented. The purpose of such models is to aid understanding, test ideas, formulate experiments, and to model cancer 'in machina' to address the dynamic features of tumor cell heterogeneity, progression, and growth. The descriptive capabilities of such an approach provides a consistent language for qualitatively reasoning about tumor behavior. This approach provides a schema for building conceptual models that combine three key phenomenological driving elements: growth, progression, and genetic instability. The growth element encompasses processes contributing to changes in tumor bulk and is distinct from progression per se. The progression element subsumes a broad collection of processes underlying phenotypic progression. The genetics elements represents heritable changes which potentially affect tumor character and behavior. Models, conceptual and mathematical, can be built for different tumor situations by drawing upon the interaction of these three distinct driving elements. These models can be used as tools to explore a diversity of hypotheses concerning dynamic changes in cellular populations during tumor progression, including the generation of intratumor heterogeneity. Such models can also serve to guide experimentation and to gain insight into dynamic aspects of complex tumor behavior.

Circadian rhythms and fractal fluctuations in forearm motion

NASA Astrophysics Data System (ADS)

Hu, Kun; Hilton, Michael F.

2005-03-01

Recent studies have shown that the circadian pacemaker --- an internal body clock located in the brain which is normally synchronized with the sleep/wake behavioral cycles --- influences key physiologic functions such as the body temperature, hormone secretion and heart rate. Surprisingly, no previous studies have investigated whether the circadian pacemaker impacts human motor activity --- a fundamental physiologic function. We investigate high-frequency actigraph recordings of forearm motion from a group of young and healthy subjects during a forced desynchrony protocol which allows to decouple the sleep/wake cycles from the endogenous circadian cycle while controlling scheduled behaviors. We investigate both static properties (mean value, standard deviation), dynamical characteristics (long-range correlations), and nonlinear features (magnitude and Fourier-phase correlations) in the fluctuations of forearm acceleration across different circadian phases. We demonstrate that while the static properties exhibit significant circadian rhythms with a broad peak in the afternoon, the dynamical and nonlinear characteristics remain invariant with circadian phase. This finding suggests an intrinsic multi-scale dynamic regulation of forearm motion the mechanism of which is not influenced by the circadian pacemaker, thus suggesting that increased cardiac risk in the early morning hours is not related to circadian-mediated influences on motor activity.

Role of direct electron-phonon coupling across metal-semiconductor interfaces in thermal transport via molecular dynamics.

PubMed

Lin, Keng-Hua; Strachan, Alejandro

2015-07-21

Motivated by significant interest in metal-semiconductor and metal-insulator interfaces and superlattices for energy conversion applications, we developed a molecular dynamics-based model that captures the thermal transport role of conduction electrons in metals and heat transport across these types of interface. Key features of our model, denoted eleDID (electronic version of dynamics with implicit degrees of freedom), are the natural description of interfaces and free surfaces and the ability to control the spatial extent of electron-phonon (e-ph) coupling. Non-local e-ph coupling enables the energy of conduction electrons to be transferred directly to the semiconductor/insulator phonons (as opposed to having to first couple to the phonons in the metal). We characterize the effect of the spatial e-ph coupling range on interface resistance by simulating heat transport through a metal-semiconductor interface to mimic the conditions of ultrafast laser heating experiments. Direct energy transfer from the conduction electrons to the semiconductor phonons not only decreases interfacial resistance but also increases the ballistic transport behavior in the semiconductor layer. These results provide new insight for experiments designed to characterize e-ph coupling and thermal transport at the metal-semiconductor/insulator interfaces.

Monge-Ampére simulation of fourth order PDEs in two dimensions with application to elastic-electrostatic contact problems

NASA Astrophysics Data System (ADS)

DiPietro, Kelsey L.; Lindsay, Alan E.

2017-11-01

We present an efficient moving mesh method for the simulation of fourth order nonlinear partial differential equations (PDEs) in two dimensions using the Parabolic Monge-Ampére (PMA) equation. PMA methods have been successfully applied to the simulation of second order problems, but not on systems with higher order equations which arise in many topical applications. Our main application is the resolution of fine scale behavior in PDEs describing elastic-electrostatic interactions. The PDE system considered has multiple parameter dependent singular solution modalities, including finite time singularities and sharp interface dynamics. We describe how to construct a dynamic mesh algorithm for such problems which incorporates known self similar or boundary layer scalings of the underlying equation to locate and dynamically resolve fine scale solution features in these singular regimes. We find a key step in using the PMA equation for mesh generation in fourth order problems is the adoption of a high order representation of the transformation from the computational to physical mesh. We demonstrate the efficacy of the new method on a variety of examples and establish several new results and conjectures on the nature of self-similar singularity formation in higher order PDEs.

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space

PubMed Central

Karnik, Rahul; Beer, Michael A.

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs. PMID:26465884

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.

PubMed

Karnik, Rahul; Beer, Michael A

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs.

Insights into proton translocation in cbb3 oxidase from MD simulations.

PubMed

Carvalheda, Catarina A; Pisliakov, Andrei V

2017-05-01

Heme-copper oxidases are membrane protein complexes that catalyse the final step of the aerobic respiration, namely the reduction of oxygen to water. The energy released during catalysis is coupled to the active translocation of protons across the membrane, which contributes to the establishment of an electrochemical gradient that is used for ATP synthesis. The distinctive C-type (or cbb 3 ) cytochrome c oxidases, which are mostly present in proteobacteria, exhibit a number of unique structural and functional features, including high catalytic activity at low oxygen concentrations. At the moment, the functioning mechanism of C-type oxidases, in particular the proton transfer/pumping mechanism presumably via a single proton channel, is still poorly understood. In this work we used all-atom molecular dynamics simulations and continuum electrostatics calculations to obtain atomic-level insights into the hydration and dynamics of a cbb 3 oxidase. We provide the details of the water dynamics and proton transfer pathways for both the "chemical" and "pumped" protons, and show that formation of protonic connections is strongly affected by the protonation state of key residues, namely H243, E323 and H337. Copyright © 2017 Elsevier B.V. All rights reserved.

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms 1D wavelet.

Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

PubMed

Venkataraman, Vinay; Turaga, Pavan

2016-12-01

This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

Multiphase flow modelling of explosive volcanic eruptions using adaptive unstructured meshes

NASA Astrophysics Data System (ADS)

Jacobs, Christian T.; Collins, Gareth S.; Piggott, Matthew D.; Kramer, Stephan C.

2014-05-01

Explosive volcanic eruptions generate highly energetic plumes of hot gas and ash particles that produce diagnostic deposits and pose an extreme environmental hazard. The formation, dispersion and collapse of these volcanic plumes are complex multiscale processes that are extremely challenging to simulate numerically. Accurate description of particle and droplet aggregation, movement and settling requires a model capable of capturing the dynamics on a range of scales (from cm to km) and a model that can correctly describe the important multiphase interactions that take place. However, even the most advanced models of eruption dynamics to date are restricted by the fixed mesh-based approaches that they employ. The research presented herein describes the development of a compressible multiphase flow model within Fluidity, a combined finite element / control volume computational fluid dynamics (CFD) code, for the study of explosive volcanic eruptions. Fluidity adopts a state-of-the-art adaptive unstructured mesh-based approach to discretise the domain and focus numerical resolution only in areas important to the dynamics, while decreasing resolution where it is not needed as a simulation progresses. This allows the accurate but economical representation of the flow dynamics throughout time, and potentially allows large multi-scale problems to become tractable in complex 3D domains. The multiphase flow model is verified with the method of manufactured solutions, and validated by simulating published gas-solid shock tube experiments and comparing the numerical results against pressure gauge data. The application of the model considers an idealised 7 km by 7 km domain in which the violent eruption of hot gas and volcanic ash high into the atmosphere is simulated. Although the simulations do not correspond to a particular eruption case study, the key flow features observed in a typical explosive eruption event are successfully captured. These include a shock wave resulting from the sudden high-velocity inflow of gas and ash; the formation of a particle-laden plume rising several hundred metres into the atmosphere; the eventual collapse of the plume which generates a volcanic ash fountain and a fast ground-hugging pyroclastic density current; and the growth of a dilute convective region that rises above the ash fountain as a result of buoyancy effects. The results from Fluidity are also compared with results from MFIX, a fixed structured mesh-based multiphase flow code, that uses the same set-up. The key flow features are also captured in MFIX, providing at least some confidence in the plausibility of the numerical results in the absence of quantitative field data. Finally, it is shown by a convergence analysis that Fluidity offers the same solution accuracy for reduced computational cost using an adaptive mesh, compared to the same simulation performed with a uniform fixed mesh.

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

On the Fluctuations that Order and Frustrate Liquid Water

NASA Astrophysics Data System (ADS)

Limmer, David Tyler

At ambient conditions, water sits close to phase coexistence with its crystal. More so than in many other materials, this fact is manifested in the fluctuations that maintain a large degree of local order in the liquid. These fluctuations and how they result in long-ranged order, or its absence, are emergent features of many interacting molecules. Their study therefore requires using the tools of statistical mechanics for their their systematic understanding. In this dissertation we develop such an understanding. In particular, we focus on collective behavior that emerges in liquid and solid water. At room temperatures, the thermophysical properties of water are quantified and rationalized with simple molecular models. A key feature of these models is the correct characterization of the competition between entropic forces of packing and the energetic preference for tetrahedral order. At cold temperatures, the properties of ice surfaces are studied with statistical field theory. The theory we develop for the long wavelength features of ice interfaces allows us to explain the existence of a premelting layer on the surface of ice and the stability of ice in confinement. In between these extremes, the dynamics of supercooled water are considered. A detailed theory for the early stages of coarsening is developed and used to explain the peculiar observation of a transient second liquid state of water. When coarsening dynamics are arrested, the result is the formation of a glassy states of water. We show that out-of-equilibrium the phase diagram for supercooled water exhibits a rich amount of structure, including a triple point between two glass phases of water and the liquid. At the end, we explore possible technological implications for the interplay between ordering and frustration in studies of water at metal interfaces.

Polycystic ovary syndrome: perceptions and attitudes of women and primary health care physicians on features of PCOS and renaming the syndrome.

PubMed

Teede, Helena; Gibson-Helm, Melanie; Norman, Robert J; Boyle, Jacqueline

2014-01-01

Polycystic ovary syndrome (PCOS) is an under-recognized, common, and complex endocrinopathy. The name PCOS is a misnomer, and there have been calls for a change to reflect the broader clinical syndrome. The aim of the study was to determine perceptions held by women and primary health care physicians around key clinical features of PCOS and attitudes toward current and alternative names for the syndrome. We conducted a cross-sectional study utilizing a devised questionnaire. Participants were recruited throughout Australia via professional associations, women's health organizations, and a PCOS support group. Fifty-seven women with PCOS and 105 primary care physicians participated in the study. Perceptions of key clinical PCOS features and attitudes toward current and alternative syndrome names were investigated. Irregular periods were identified as a key clinical feature of PCOS by 86% of the women with PCOS and 90% of the primary care physicians. In both groups, 60% also identified hormone imbalance as a key feature. Among women with PCOS, 47% incorrectly identified ovarian cysts as key, 48% felt the current name is confusing, and 51% supported a change. Most primary care physicians agreed that the name is confusing (74%) and needs changing (81%); however, opinions on specific alternative names were divided. The name "polycystic ovary syndrome" is perceived as confusing, and there is general support for a change to reflect the broader clinical syndrome. Engagement of primary health care physicians and consumers is strongly recommended to ensure that an alternative name enhances understanding and recognition of the syndrome and its complex features.

Predicting Key Events in the Popularity Evolution of Online Information.

PubMed

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Predicting Key Events in the Popularity Evolution of Online Information

PubMed Central

Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the “burst”, “peak”, and “fade” key events together as a representative summary of popularity evolution. We propose a novel prediction task—predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify “burst”, “peak”, and “fade” in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution. PMID:28046121

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

Differential flap dynamics in l,d-transpeptidase2 from mycobacterium tuberculosis revealed by molecular dynamics.

PubMed

Fakhar, Zeynab; Govender, Thavendran; Maguire, Glenn E M; Lamichhane, Gyanu; Walker, Ross C; Kruger, Hendrik G; Honarparvar, Bahareh

2017-06-01

Despite the advances in tuberculosis treatment, TB is still one the most deadly infectious diseases and remains a major global health quandary. Mycobacterium tuberculosis (Mtb) is the only known mycobacterium with a high content of 3→3 crosslinks in the biosynthesis of peptidoglycan, which is negligible in most bacterial species. An Mtb lacking Ldt Mt2 leads to alteration of the colony morphology and loss of virulence which makes this enzyme an attractive target. Regardless of the vital role of Ldt Mt2 for cell wall survival, the impact of ligand binding on the dynamics of the β-hairpin flap is still unknown. Understanding the structural and dynamical behaviour of the flap regions provides clear insight into the design of the effective inhibitors against Ldt Mt2 . Carbapenems, an specific class of β-lactam family, have been shown to inactivate this enzyme. Herein a comprehensive investigation of the flap dynamics of Ldt Mt2 complex with substrate and three carbapenems namely, ertapenem, imipenem and meropenem is discussed and analyzed for the first account using 140 ns molecular dynamics simulations. The structural features (RMSD, RMSF and R g ) derived by MD trajectories were analyzed. Distance analysis, particularly tip-tip SER135-ASN167 index, identified conformational changes in terms of flap opening and closure within binding process. Principal component analysis (PCA) was employed to qualitatively understand the divergent effects of different inhibitors on the dominant motion of each residue. To probe different internal dynamics induced by ligand binding, dynamic cross-correlation marix (DCCM) analysis was used. The binding free energies of the selected complexes were assessed using MM-GBSA method and per residue free energy decomposition analysis were performed to characterize the contribution of the key residues to the total binding free energies.

Observational and Dynamical Wave Climatologies. VOS vs Satellite Data

NASA Astrophysics Data System (ADS)

Grigorieva, Victoria; Badulin, Sergei; Chernyshova, Anna

2013-04-01

The understanding physics of wind-driven waves is crucially important for fundamental science and practical applications. This is why experimental efforts are targeted at both getting reliable information on sea state and elaborating effective tools of the sea wave forecasting. The global Visual Wave Observations and satellite data from the GLOBWAVE project of the European Space Agency are analyzed in the context of these two viewpoints. Within the first "observational" aspect we re-analyze conventional climatologies of all basic wave parameters for the last decades [5]. An alternative "dynamical" climatology is introduced as a tool of prediction of dynamical features of sea waves on global scales. The features of wave dynamics are studied in terms of one-parametric dependencies of wave heights on wave periods following the theoretical concept of self-similar wind-driven seas [3, 1, 4] and recently proposed approach to analysis of Voluntary Observing Ship (VOS) data [2]. Traditional "observational" climatologies based on VOS and satellite data collections demonstrate extremely consistent pictures for significant wave heights and dominant periods. On the other hand, collocated satellite and VOS data show significant differences in wave heights, wind speeds and, especially, in wave periods. Uncertainties of visual wave observations can explain these differences only partially. We see the key reason of this inconsistency in the methods of satellite data processing which are based on formal application of data interpolation methods rather than on up-to-date physics of wind-driven waves. The problem is considered within the alternative climatology approach where dynamical criteria of wave height-to-period linkage are used for retrieving wave periods and constructing physically consistent dynamical climatology. The key dynamical parameter - exponent R of one-parametric dependence Hs ~ TR shows dramatically less pronounced latitudinal dependence as compared to observed Hs and T of conventional climatology in both satellite and VOS data collections. It can be treated as an effect of interaction of wind-driven seas and swell on global scales as it was stated in [2]. Further study combining the alternative and conventional climatologies can help to detail this important dynamical effect of global wave dynamics. The progress in satellite data processing and their physical interpretation is of great value for such study. The work was supported by Russian Foundation for Basic Research grant 11-05-01114-a and the Russian government contracts No.11.G34.31.0035, No.11.G34.31.0078. References [1] S. I. Badulin, A. V. Babanin, D. Resio, and V. Zakharov. Weakly turbulent laws of wind-wave growth. J. Fluid Mech., 591:339-378, 2007. [2] S. I. Badulin and Grigorieva V. G. On discriminating swell and wind-driven seas in voluntary observing ship data. J. Geophys. Res., 117(C00J29), 2012. [3] S. I. Badulin, A. N. Pushkarev, D. Resio, and V. E. Zakharov. Self-similarity of wind-driven seas. Nonl. Proc. Geophys., 12:891-946, 2005. [4] E. Gagnaire-Renou, M. Benoit, and S. I. Badulin. On weakly turbulent scaling of wind sea in simulations of fetch-limited growth. J. Fluid Mech., 669:178-213, 2011. [5] S. K. Gulev, V. Grigorieva, A. Sterl, and D. Woolf. Assessment for the reliability of wave observations from voluntary observing ships: insights from the validation of a global wind wave climatology based on voluntary observing ship data. J. Geophys. Res. - Oceans, 108(C7):3236, doi:10,1029/2002JC001437, 2003.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Dynamical features of an anisotropic cosmological model

NASA Astrophysics Data System (ADS)

Mishra, B.; Tarai, Sankarsan; Tripathy, S. K.

2018-04-01

The dynamical features of Bianchi type VI_h (BVI_h) universe are investigated in f(R, T) theory of gravity. The field equations and the physical properties of the model are derived considering a power law expansion of the universe. The effect of anisotropy on the dynamics of the universe as well as on the energy conditions are studied. The assumed anisotropy of the model is found to have substantial effects on the energy conditions and dynamical parameters.

Don't break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrain.

PubMed

Birn-Jeffery, Aleksandra V; Hubicki, Christian M; Blum, Yvonne; Renjewski, Daniel; Hurst, Jonathan W; Daley, Monica A

2014-11-01

Cursorial ground birds are paragons of bipedal running that span a 500-fold mass range from quail to ostrich. Here we investigate the task-level control priorities of cursorial birds by analysing how they negotiate single-step obstacles that create a conflict between body stability (attenuating deviations in body motion) and consistent leg force-length dynamics (for economy and leg safety). We also test the hypothesis that control priorities shift between body stability and leg safety with increasing body size, reflecting use of active control to overcome size-related challenges. Weight-support demands lead to a shift towards straighter legs and stiffer steady gait with increasing body size, but it remains unknown whether non-steady locomotor priorities diverge with size. We found that all measured species used a consistent obstacle negotiation strategy, involving unsteady body dynamics to minimise fluctuations in leg posture and loading across multiple steps, not directly prioritising body stability. Peak leg forces remained remarkably consistent across obstacle terrain, within 0.35 body weights of level running for obstacle heights from 0.1 to 0.5 times leg length. All species used similar stance leg actuation patterns, involving asymmetric force-length trajectories and posture-dependent actuation to add or remove energy depending on landing conditions. We present a simple stance leg model that explains key features of avian bipedal locomotion, and suggests economy as a key priority on both level and uneven terrain. We suggest that running ground birds target the closely coupled priorities of economy and leg safety as the direct imperatives of control, with adequate stability achieved through appropriately tuned intrinsic dynamics. © 2014. Published by The Company of Biologists Ltd.

Integration and visualization of systems biology data in context of the genome

PubMed Central

2010-01-01

Background High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment. PMID:20642854

Don't break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrain

PubMed Central

Birn-Jeffery, Aleksandra V.; Hubicki, Christian M.; Blum, Yvonne; Renjewski, Daniel; Hurst, Jonathan W.; Daley, Monica A.

2014-01-01

Cursorial ground birds are paragons of bipedal running that span a 500-fold mass range from quail to ostrich. Here we investigate the task-level control priorities of cursorial birds by analysing how they negotiate single-step obstacles that create a conflict between body stability (attenuating deviations in body motion) and consistent leg force–length dynamics (for economy and leg safety). We also test the hypothesis that control priorities shift between body stability and leg safety with increasing body size, reflecting use of active control to overcome size-related challenges. Weight-support demands lead to a shift towards straighter legs and stiffer steady gait with increasing body size, but it remains unknown whether non-steady locomotor priorities diverge with size. We found that all measured species used a consistent obstacle negotiation strategy, involving unsteady body dynamics to minimise fluctuations in leg posture and loading across multiple steps, not directly prioritising body stability. Peak leg forces remained remarkably consistent across obstacle terrain, within 0.35 body weights of level running for obstacle heights from 0.1 to 0.5 times leg length. All species used similar stance leg actuation patterns, involving asymmetric force–length trajectories and posture-dependent actuation to add or remove energy depending on landing conditions. We present a simple stance leg model that explains key features of avian bipedal locomotion, and suggests economy as a key priority on both level and uneven terrain. We suggest that running ground birds target the closely coupled priorities of economy and leg safety as the direct imperatives of control, with adequate stability achieved through appropriately tuned intrinsic dynamics. PMID:25355848

Ab initio multiple spawning dynamics study of dimethylnitramine and dimethylnitramine-Fe complex to model their ultrafast nonadiabatic chemistry

NASA Astrophysics Data System (ADS)

Bera, Anupam; Ghosh, Jayanta; Bhattacharya, Atanu

2017-07-01

Conical intersections are now firmly established to be the key features in the excited electronic state processes of polyatomic energetic molecules. In the present work, we have explored conical intersection-mediated nonadiabatic chemical dynamics of a simple analogue nitramine molecule, dimethylnitramine (DMNA, containing one N-NO2 energetic group), and its complex with an iron atom (DMNA-Fe). For this task, we have used the ab initio multiple spawning (AIMS) dynamics simulation at the state averaged-complete active space self-consistent field(8,5)/6-31G(d) level of theory. We have found that DMNA relaxes back to the ground (S0) state following electronic excitation to the S1 excited state [which is an (n,π*) excited state] with a time constant of approximately 40 fs. This AIMS result is in very good agreement with the previous surface hopping-result and femtosecond laser spectroscopy result. DMNA does not dissociate during this fast internal conversion from the S1 to the S0 state. DMNA-Fe also undergoes extremely fast relaxation from the upper S1 state to the S0 state; however, this relaxation pathway is dissociative in nature. DMNA-Fe undergoes initial Fe-O, N-O, and N-N bond dissociations during relaxation from the upper S1 state to the ground S0 state through the respective conical intersection. The AIMS simulation reveals the branching ratio of these three channels as N-N:Fe-O:N-O = 6:3:1 (based on 100 independent simulations). Furthermore, the AIMS simulation reveals that the Fe-O bond dissociation channel exhibits the fastest (time constant 24 fs) relaxation, while the N-N bond dissociation pathway features the slowest (time constant 128 fs) relaxation. An intermediate time constant (30 fs) is found for the N-O bond dissociation channel. This is the first nonadiabatic chemical dynamics study of metal-contained energetic molecules through conical intersections.

Special Aspects of Flight Dynamics of a Reusable Cryogenic Booster Stage

NASA Astrophysics Data System (ADS)

Klevanski, J.; Sippel, M.

2005-02-01

The semi-reusable Space Transportation System (STS) investigated in the German ASTRA research program consists of two reusable winged liquid fly-back booster stages called LFBB attached to the expendable Ariane 5 core at an upgraded technology level. The focus of the presented study is the in-depth research of the special aspects of flight dynamics of a LFBB in all flight phases and especially the investigation of the trimmablity, stability and controllability. The LFBB-layout is developed under consideration of tight structural and geometrical constraints of using European cryogenic rocket engine technology [1]. These design conditions result in the special LFBB layout features, such as its large diameter fuselage and a forward position of the air-breathing engines. The great variation in the location of the center of pressure for different Mach numbers caused by large diameter fuselage and a wide range of center of gravity position demand canards for trim and control purposes. The aerodynamic investigation loop performed by the DLR Institute of Aerodynamics and Flow Technology in Braunschweig [2],[3] and in the DLR Wind Tunnel in Cologne [6] allowed optimizing the key features of the aerodynamical layout, such as the canards shape and the wing profile. The main task of this study is the investigation of the longitudinal flight dynamics of the LFBB using the obtained aerodynamic data within a closed loop simulation taking into account rigid body equations of motion, control law and actuators by realistic assumption. This paper discusses the controllability of the whole STS during the ascent phase until separation including wind gust influence, guaranteeing of the structural constraints during re-entry phase and the trimmablity and controllability of the LFBB during the cruise return flight. The flight dynamics behavior of the LFBB is investigated for different center of gravity positions with reasonable margins.

UA-ICON - A non-hydrostatic global model for studying gravity waves from the troposphere to the thermosphere

NASA Astrophysics Data System (ADS)

Borchert, Sebastian; Zängl, Günther; Baldauf, Michael; Zhou, Guidi; Schmidt, Hauke; Manzini, Elisa

2017-04-01

In numerical weather prediction as well as climate simulations, there are ongoing efforts to raise the upper model lid, acknowledging the possible influence of middle and upper atmosphere dynamics on tropospheric weather and climate. As the momentum deposition of gravity waves (GWs) is responsible for key features of the large scale flow in the middle and upper atmosphere, the upward model extension has put GWs in the focus of atmospheric research needs. The Max Planck Institute for Meteorology (MPI-M) and the German Weather Service (DWD) have been developing jointly the non-hydrostatic global model ICON (Zängl et al, 2015) which features a new dynamical core based on an icosahedral grid. The extension of ICON beyond the mesosphere, where most GWs deposit their momentum, requires, e.g., relaxing the shallow-atmosphere and other traditional approximations as well as implementing additional physical processes that are important to the upper atmosphere. We would like to present aspects of the model development and its evaluation, and first results from a simulation of a period of the DEEPWAVE campaign in New Zealand in 2014 (Fritts et al, 2016) using grid nesting up to a horizontal mesh size of about 1.25 km. This work is part of the research unit: Multi-Scale Dynamics of Gravity Waves (MS-GWaves: sub-project GWING, https://ms-gwaves.iau.uni-frankfurt.de/index.php), funded by the German Research Foundation. Fritts, D.C. and Coauthors, 2016: "The Deep Propagating Gravity Wave Experiment (DEEPWAVE): An airborne and ground-based exploration of gravity wave propagation and effects from their sources throughout the lower and middle atmosphere". Bull. Amer. Meteor. Soc., 97, 425 - 453, doi:10.1175/BAMS-D-14-00269.1 Zängl, G., Reinert, D., Ripodas, P., Baldauf, M., 2015: "The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core". Quart. J. Roy. Met. Soc., 141, 563 - 579, doi:10.1002/qj.2378

Feature integration across space, time, and orientation

PubMed Central

Otto, Thomas U.; Öğmen, Haluk; Herzog, Michael H.

2012-01-01

The perception of a visual target can be strongly influenced by flanking stimuli. In static displays, performance on the target improves when the distance to the flanking elements increases- proposedly because feature pooling and integration vanishes with distance. Here, we studied feature integration with dynamic stimuli. We show that features of single elements presented within a continuous motion stream are integrated largely independent of spatial distance (and orientation). Hence, space based models of feature integration cannot be extended to dynamic stimuli. We suggest that feature integration is guided by perceptual grouping operations that maintain the identity of perceptual objects over space and time. PMID:19968428

Foundations to the unified psycho-cognitive engine.

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

Bernard, Michael Lewis; Bier, Asmeret Brooke; Backus, George A.

This document outlines the key features of the SNL psychological engine. The engine is designed to be a generic presentation of cognitive entities interacting among themselves and with the external world. The engine combines the most accepted theories of behavioral psychology with those of behavioral economics to produce a unified simulation of human response from stimuli through executed behavior. The engine explicitly recognizes emotive and reasoned contributions to behavior and simulates the dynamics associated with cue processing, learning, and choice selection. Most importantly, the model parameterization can come from available media or survey information, as well subject-matter-expert information. The frameworkmore » design allows the use of uncertainty quantification and sensitivity analysis to manage confidence in using the analysis results for intervention decisions.« less

Design techniques for low-voltage analog integrated circuits

NASA Astrophysics Data System (ADS)

Rakús, Matej; Stopjaková, Viera; Arbet, Daniel

2017-08-01

In this paper, a review and analysis of different design techniques for (ultra) low-voltage integrated circuits (IC) are performed. This analysis shows that the most suitable design methods for low-voltage analog IC design in a standard CMOS process include techniques using bulk-driven MOS transistors, dynamic threshold MOS transistors and MOS transistors operating in weak or moderate inversion regions. The main advantage of such techniques is that there is no need for any modification of standard CMOS structure or process. Basic circuit building blocks like differential amplifiers or current mirrors designed using these approaches are able to operate with the power supply voltage of 600 mV (or even lower), which is the key feature towards integrated systems for modern portable applications.

Broadband diffuse optical characterization of elastin for biomedical applications.

PubMed

Konugolu Venkata Sekar, Sanathana; Beh, Joo Sin; Farina, Andrea; Dalla Mora, Alberto; Pifferi, Antonio; Taroni, Paola

2017-10-01

Elastin is a key structural protein of dynamic connective tissues widely found in the extracellular matrix of skin, arteries, lungs and ligaments. It is responsible for a range of diseases related to aging of biological tissues. The optical characterization of elastin can open new opportunities for its investigation in biomedical studies. In this work, we present the absorption spectra of elastin using a broadband (550-1350nm) diffuse optical spectrometer. Distortions caused by fluorescence and finite bandwidth of the laser source on estimated absorption were effectively accounted for in measurements and data analysis and compensated. A comprehensive summary and comparison between collagen and elastin is presented, highlighting distinct features for its accurate quantification in biological applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Shock Structure Analysis and Aerodynamics in a Weakly Ionized Gas Flow

NASA Technical Reports Server (NTRS)

Saeks, R.; Popovic, S.; Chow, A. S.

2006-01-01

The structure of a shock wave propagating through a weakly ionized gas is analyzed using an electrofluid dynamics model composed of classical conservation laws and Gauss Law. A viscosity model is included to correctly model the spatial scale of the shock structure, and quasi-neutrality is not assumed. A detailed analysis of the structure of a shock wave propagating in a weakly ionized gas is presented, together with a discussion of the physics underlying the key features of the shock structure. A model for the flow behind a shock wave propagating through a weakly ionized gas is developed and used to analyze the effect of the ionization on the aerodynamics and performance of a two-dimensional hypersonic lifting body.

Dose accuracy and injection force dynamics of a novel disposable insulin pen.

PubMed

Clarke, Alastair; Spollett, Geralyn

2007-03-01

SoloStar (sanofi-aventis) is a new, disposable insulin pen for the administration of insulin glargine (Lantus, sanofi-aventis) or insulin glulisine (Apidra, sanofi-aventis). SoloStar was developed to address a wide range of patient needs and demonstrates advancement over previous devices, owing to its appropriate combination of ergonomically-tested and mechanically improved features. The authors report the results of key investigations carried out by sanofi-aventis as part of the SoloStar development plan, including dose accuracy and injection force testing. Comparisons between SoloStar and two commonly used pens, FlexPen (Novo Nordisk) and the Humulin/Humalog pen (Eli Lilly) establish SoloStar as a state of the art pen that is suitable for most patients with diabetes.

Experiments on Thermal Convection in Rotating Spherical Shells With Radial Gravity: The Geophysical Fluid Flow Cell

NASA Technical Reports Server (NTRS)

Hart, John E.

1996-01-01

Experiments designed to study the fluid dynamics of buoyancy driven circulations in rotating spherical shells were conducted on the United States Microgravity Laboratory 2 spacelab mission. These experiments address several aspects of prototypical global convection relevant to large scale motions on the Sun, Earth, and on the giant planets. The key feature is the consistent modeling of radially directed gravity in spherical geometry by using dielectric polarization forces. Imagery of the planforms of thermally driven flows for rapidly-rotating regimes shows an initial separation and eventual merger of equatorial and polar convection as the heating (i.e. the Rayleigh number) is increased. At low rotation rates, multiple-states of motion for the same external parameters were observed.

Evaluation of Image Segmentation and Object Recognition Algorithms for Image Parsing

DTIC Science & Technology

2013-09-01

generation of the features from the key points. OpenCV uses Euclidean distance to match the key points and has the option to use Manhattan distance...feature vector includes polarity and intensity information. Final step is matching the key points. In OpenCV , Euclidean distance or Manhattan...the code below is one way and OpenCV offers the function radiusMatch (a pair must have a distance less than a given maximum distance). OpenCV’s

Identification and functional analysis of a core gene module associated with hepatitis C virus-induced human hepatocellular carcinoma progression.

PubMed

Bai, Gaobo; Zheng, Wenling; Ma, Wenli

2018-05-01

Hepatitis C virus (HCV)-induced human hepatocellular carcinoma (HCC) progression may be due to a complex multi-step processes. The developmental mechanism of these processes is worth investigating for the prevention, diagnosis and therapy of HCC. The aim of the present study was to investigate the molecular mechanism underlying the progression of HCV-induced hepatocarcinogenesis. First, the dynamic gene module, consisting of key genes associated with progression between the normal stage and HCC, was identified using the Weighted Gene Co-expression Network Analysis tool from R language. By defining those genes in the module as seeds, the change of co-expression in differentially expressed gene sets in two consecutive stages of pathological progression was examined. Finally, interaction pairs of HCV viral proteins and their directly targeted proteins in the identified module were extracted from the literature and a comprehensive interaction dataset from yeast two-hybrid experiments. By combining the interactions between HCV and their targets, and protein-protein interactions in the Search Tool for the Retrieval of Interacting Genes database (STRING), the HCV-key genes interaction network was constructed and visualized using Cytoscape software 3.2. As a result, a module containing 44 key genes was identified to be associated with HCC progression, due to the dynamic features and functions of those genes in the module. Several important differentially co-expressed gene pairs were identified between non-HCC and HCC stages. In the key genes, cyclin dependent kinase 1 (CDK1), NDC80, cyclin A2 (CCNA2) and rac GTPase activating protein 1 (RACGAP1) were shown to be targeted by the HCV nonstructural proteins NS5A, NS3 and NS5B, respectively. The four genes perform an intermediary role between the HCV viral proteins and the dysfunctional module in the HCV key genes interaction network. These findings provided valuable information for understanding the mechanism of HCV-induced HCC progression and for seeking drug targets for the therapy and prevention of HCC.

A Self-Adaptive Dynamic Recognition Model for Fatigue Driving Based on Multi-Source Information and Two Levels of Fusion

PubMed Central

Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai

2015-01-01

To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615

Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions

PubMed Central

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D.; Jeong, Jaeseung

2014-01-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices. PMID:25122498

Dynamical Consequences of Bandpass Feedback Loops in a Bacterial Phosphorelay

PubMed Central

Sen, Shaunak; Garcia-Ojalvo, Jordi; Elowitz, Michael B.

2011-01-01

Under conditions of nutrient limitation, Bacillus subtilis cells terminally differentiate into a dormant spore state. Progression to sporulation is controlled by a genetic circuit consisting of a phosphorelay embedded in multiple transcriptional feedback loops, which is used to activate the master regulator Spo0A by phosphorylation. These transcriptional regulatory interactions are “bandpass”-like, in the sense that activation occurs within a limited band of Spo0A∼P concentrations. Additionally, recent results show that the phosphorelay activation occurs in pulses, in a cell-cycle dependent fashion. However, the impact of these pulsed bandpass interactions on the circuit dynamics preceding sporulation remains unclear. In order to address this question, we measured key features of the bandpass interactions at the single-cell level and analyzed them in the context of a simple mathematical model. The model predicted the emergence of a delayed phase shift between the pulsing activity of the different sporulation genes, as well as the existence of a stable state, with elevated Spo0A activity but no sporulation, embedded within the dynamical structure of the system. To test the model, we used time-lapse fluorescence microscopy to measure dynamics of single cells initiating sporulation. We observed the delayed phase shift emerging during the progression to sporulation, while a re-engineering of the sporulation circuit revealed behavior resembling the predicted additional state. These results show that periodically-driven bandpass feedback loops can give rise to complex dynamics in the progression towards sporulation. PMID:21980382

Linguistic labels, dynamic visual features, and attention in infant category learning.

PubMed

Deng, Wei Sophia; Sloutsky, Vladimir M

2015-06-01

How do words affect categorization? According to some accounts, even early in development words are category markers and are different from other features. According to other accounts, early in development words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12-month-old infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye-tracking results indicated that infants exhibited better category learning in the motion-defined condition than in the label-defined condition, and their attention was more distributed among different features when there was a dynamic visual feature compared with the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Linguistic Labels, Dynamic Visual Features, and Attention in Infant Category Learning

PubMed Central

Deng, Wei (Sophia); Sloutsky, Vladimir M.

2015-01-01

How do words affect categorization? According to some accounts, even early in development, words are category markers and are different from other features. According to other accounts, early in development, words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12- month infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye tracking results indicated that infants exhibited better category learning in the motion-defined than in the label-defined condition and their attention was more distributed among different features when there was a dynamic visual feature compared to the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. PMID:25819100

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Improving resolution of dynamic communities in human brain networks through targeted node removal

PubMed Central

Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2017-01-01

Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

Replica-exchange molecular dynamics simulations of cellulose solvated in water and in the ionic liquid 1-butyl-3-methylimidazolium chloride

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

Mostofian, Barmak; Cheng, Xiaolin; Smith, Jeremy C.

2014-09-02

Ionic liquids have become a popular solvent for cellulose pretreatment in biorefineries due to their efficiency in dissolution and their reusability. Understanding the interactions between cations, anions, and cellulose is key to the development of better solvents and the improvement of pretreatment conditions. While previous studies described the interactions between ionic liquids and cellulose fibers, shedding light on the initial stages of the cellulose dissolution process, we study the end state of that process by exploring the structure and dynamics of a single cellulose decamer solvated in 1-butyl-3-methyl-imidazolium chloride (BmimCl) and in water using replica-exchange molecular dynamics. In both solvents,more » global structural features of the cellulose chain are similar. However, analyses of local structural properties show that cellulose explores greater conformational variability in the ionic liquid than in water. For instance, in BmimCl the cellulose intramolecular hydrogen bond O3H'••• O5 is disrupted more often resulting in greater flexibility of the solute. Our results indicate that the cellulose chain is more dynamic in BmimCl than in water, which may play a role in the favorable dissolution of cellulose in the ionic liquid. Here, the calculation of the configurational entropy of the cellulose decamer confirms its higher conformational flexibility in BmimCl than in water at elevated temperatures.« less

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

PubMed Central

Kim, Minsu; Or, Dani

2016-01-01

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

Wetland restoration, flood pulsing, and disturbance dynamics

USGS Publications Warehouse

Middleton, Beth A.

1999-01-01

While it is generally accepted that flood pulsing and disturbance dynamics are critical to wetland viability, there is as yet no consensus among those responsible for wetland restoration about how best to plan for those phenomena or even whether it is really necessary to do so at all. In this groundbreaking book, Dr. Beth Middleton draws upon the latest research from around the world to build a strong case for making flood pulsing and disturbance dynamics integral to the wetland restoration planning process.While the initial chapters of the book are devoted to laying the conceptual foundations, most of the coverage is concerned with demonstrating the practical implications for wetland restoration and management of the latest ecological theory and research. It includes a fascinating case history section in which Dr. Middleton explores the restoration models used in five major North American, European, Australian, African, and Asian wetland projects, and analyzes their relative success from the perspective of flood pulsing and disturbance dynamics planning.Wetland Restoration also features a wealth of practical information useful to all those involved in wetland restoration and management, including: * A compendium of water level tolerances, seed germination, seedling recruitment, adult survival rates, and other key traits of wetland plant species * A bibliography of 1,200 articles and monographs covering all aspects of wetland restoration * A comprehensive directory of wetland restoration ftp sites worldwide * An extensive glossary of essential terms

Qualitative dynamics semantics for SBGN process description.

PubMed

Rougny, Adrien; Froidevaux, Christine; Calzone, Laurence; Paulevé, Loïc

2016-06-16

Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far. We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F. The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

Optimal channel efficiency in a sensory network

NASA Astrophysics Data System (ADS)

Mosqueiro, Thiago S.; Maia, Leonardo P.

2013-07-01

Spontaneous neural activity has been increasingly recognized as a subject of key relevance in neuroscience. It exhibits nontrivial spatiotemporal structure reflecting the organization of the underlying neural network and has proved to be closely intertwined with stimulus-induced activity patterns. As an additional contribution in this regard, we report computational studies that strongly suggest that a stimulus-free feature rules the behavior of an important psychophysical measure of the sensibility of a sensory system to a stimulus, the so-called dynamic range. Indeed in this paper we show that the entropy of the distribution of avalanche lifetimes (information efficiency, since it can be interpreted as the efficiency of the network seen as a communication channel) always accompanies the dynamic range in the benchmark model for sensory systems. Specifically, by simulating the Kinouchi-Copelli (KC) model on two broad families of model networks, we generically observed that both quantities always increase or decrease together as functions of the average branching ratio (the control parameter of the KC model) and that the information efficiency typically exhibits critical optimization jointly with the dynamic range (i.e., both quantities are optimized at the same value of that control parameter, that turns out to be the critical point of a nonequilibrium phase transition). In contrast with the practice of taking power laws to identify critical points in most studies describing measured neuronal avalanches, we rely on data collapses as more robust signatures of criticality to claim that critical optimization may happen even when the distribution of avalanche lifetimes is not a power law, as suggested by a recent experiment. Finally, we note that the entropy of the size distribution of avalanches (information capacity) does not always follow the dynamic range and the information efficiency when they are critically optimized, despite being more widely used than the latter to describe the computational capabilities of a neural network. This strongly suggests that dynamical rules allowing a proper temporal matching of the states of the interacting neurons is the key for achieving good performance in information processing, rather than increasing the number of available units.

How seismic waves can be used to understand and constrain landslide dynamics

NASA Astrophysics Data System (ADS)

Mangeney, A.; Favreau, P.; Moretti, L.; Lucas, A.; Le Friant, A.; Bouchut, F.

2010-12-01

Gravitational instabilities such as debris flows, landslide or avalanches play a key role in erosion processes on the Earth’s surface and represent one of the major natural hazard threatening life and property in mountainous, volcanic, seismic and coastal areas. Despite the great amount of experimental, numerical and field studies, the understanding of landslide dynamics is still an open question. In particular, there is no consensus to explain the high mobility of natural avalanches. Field measurements relevant to the dynamics of natural landslides are scarce. This is due to their unpredictability and destructive power and prevents detailed investigation of the mechanical properties of the flowing material. Recent studies have shown that the seismic signal generated by landslides provides a unique way to detect gravitational instabilities and to get information on their dynamics and geometrical characteristics. In particular, Favreau et al. [2009] show that simulation of landslides and generated seismic waves reproduce the main features of the recorded low frequency seismic signal, making it possible to discriminate between possible alternative scenarios for flow dynamics and to provide first estimates of the rheological parameters. We propose here to go further in this direction by investigating the following key questions: What is the effect of the topography and of the landslide volume on the generated seismic signal? What is the sensitivity of the generated seismic signal to the mechanical behavior of the landslide? At what distance and frequency is the point source approximation correct? To address these issues, numerical simulation of two well constrained landslides has been performed: the 2.5 Mm3 Thurwieser landslide that occurred in Italy in 2004 and the 60 Mm3 Boxing Day debris avalanche that occurred in Montserrat in 1997 during the volcanic eruption. For both landslides, simulation shows the major role of topography curvature on the generated seismic signal even for the signal recorded as far as 450 km from the source. Furthermore, comparison between observed and simulated seismic signal in Montserrat provides insights into the time sequence of the gravitational events associated to the eruption.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Modular and scalable RESTful API to sustain STAR collaboration's record keeping

NASA Astrophysics Data System (ADS)

Arkhipkin, D.; Lauret, J.; Shanmuganathan, P. V.

2015-12-01

STAR collaboration's record system is a collection of heterogeneous and sparse information associated to each members and institutions. In its original incarnation, only flat information was stored revealing many restrictions such as the lack of historical change information, the inability to keep track of members leaving and re-joining STAR, or the ability to easily extend the saved information as new requirements appeared. In mid-2013, a new project was launched covering an extensive set of revisited requirements. The requirements led us to a design based on a RESTful API, back-end storage engine relying on key/value pair data representation model coupled with a tiered architecture design. This design was motivated by the fact that unifying many STAR tools, relying on the same business logic and storage engine, was a key and central feature for the maintainability and presentation of records. This central service API would leave no ambiguities and provide easy service integration between STAR tools. The new design stores the changes in records dynamically and allows tracking the changes chronologically. The storage engine is extensible as new field of information emerges (member specific or general) without affecting the presentation or the business logic layers. The new record system features a convenient administrative interface, fuzzy algorithms for data entry and search, and provides basic statistics and graphs. Finally, this modular approach is supplemented with access control, allowing private information and administrative operations to be hidden away from public eyes.

Dynamics and design principles of a basic regulatory architecture controlling metabolic pathways.

PubMed

Chin, Chen-Shan; Chubukov, Victor; Jolly, Emmitt R; DeRisi, Joe; Li, Hao

2008-06-17

The dynamic features of a genetic network's response to environmental fluctuations represent essential functional specifications and thus may constrain the possible choices of network architecture and kinetic parameters. To explore the connection between dynamics and network design, we have analyzed a general regulatory architecture that is commonly found in many metabolic pathways. Such architecture is characterized by a dual control mechanism, with end product feedback inhibition and transcriptional regulation mediated by an intermediate metabolite. As a case study, we measured with high temporal resolution the induction profiles of the enzymes in the leucine biosynthetic pathway in response to leucine depletion, using an automated system for monitoring protein expression levels in single cells. All the genes in the pathway are known to be coregulated by the same transcription factors, but we observed drastically different dynamic responses for enzymes upstream and immediately downstream of the key control point-the intermediate metabolite alpha-isopropylmalate (alphaIPM), which couples metabolic activity to transcriptional regulation. Analysis based on genetic perturbations suggests that the observed dynamics are due to differential regulation by the leucine branch-specific transcription factor Leu3, and that the downstream enzymes are strictly controlled and highly expressed only when alphaIPM is available. These observations allow us to build a simplified mathematical model that accounts for the observed dynamics and can correctly predict the pathway's response to new perturbations. Our model also suggests that transient dynamics and steady state can be separately tuned and that the high induction levels of the downstream enzymes are necessary for fast leucine recovery. It is likely that principles emerging from this work can reveal how gene regulation has evolved to optimize performance in other metabolic pathways with similar architecture.

Multi-temporal high resolution monitoring of debris-covered glaciers using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip; Immerzeel, Walter; de Jong, Steven; Shea, Joseph; Pellicciotti, Francesca; Meijer, Sander; Shresta, Arun

2016-04-01

Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed multiple times over two debris covered glaciers in the Langtang catchment, located in the Nepalese Himalayas. Using differential GPS measurements and the Structure for Motion algorithm the UAV imagery was processed into accurate high-resolution digital elevation models and orthomosaics for both pre- and post-monsoon periods. These data were successfully used to estimate seasonal surface flow and mass wasting by using cross-correlation feature tracking and DEM differencing techniques. The results reveal large heterogeneity in mass loss and surface flow over the glacier surfaces, which are primarily caused by the presence of surface features such as ice cliffs and supra-glacial lakes. Accordingly, we systematically analyze those features using an object-based approach and relate their characteristics to the observed dynamics. We show that ice cliffs and supra-glacial lakes are contributing to a significant portion of the melt water of debris covered glaciers and we conclude that UAVs have great potential in understanding the key surface processes that remain largely undetected by using satellite remote sensing.

Indirect and Direct Signatures of Young Planets in Protoplanetary Disks

NASA Astrophysics Data System (ADS)

Zhu, Zhaohuan; Stone, James M.; Dong, Ruobing; Rafikov, Roman; Bai, Xue-Ning

2015-12-01

Directly finding young planets around protostars is challenging since protostars are highly variable and obscured by dust. However, young planets will interact with protoplanetary disks, inducing disk features such as gaps, spiral arms, and asymmetric features, which are much easier to be detected. Transitional disks, which are protoplanetary disks with gaps and holes, are excellent candidates for finding young planets. Although these disks have been studied extensively in observations (e.g. using Subaru, VLT, ALMA, EVLA), theoretical models still need to be developed to explain observations. We have constructed numerical simulations, including dust particle dynamics and MHD effects, to study planet-disk interaction, with an emphasis on explaining observations. Our simulations have successfully reproduced spiral arms, gaps and asymmetric features observed in transitional disks. Furthermore, by comparing with observations, we have constrained protoplanetary disk properties and pinpoint potential planets in these disks. We will present progress in constructing global simulations to study transitional disks, including using our recently developed Athena++ code with static-mesh-refinement for MHD. Finally we suggest that accreting circumplanetary disks can release an observable amount of energy and could be the key to detect young planets directly. We will discuss how JWST and next generation telescopes can help to find these young planets with circumplanetary disks.

Radiotherapy volume delineation using dynamic [18F]-FDG PET/CT imaging in patients with oropharyngeal cancer: a pilot study.

PubMed

Silvoniemi, Antti; Din, Mueez U; Suilamo, Sami; Shepherd, Tony; Minn, Heikki

2016-11-01

Delineation of gross tumour volume in 3D is a critical step in the radiotherapy (RT) treatment planning for oropharyngeal cancer (OPC). Static [ 18 F]-FDG PET/CT imaging has been suggested as a method to improve the reproducibility of tumour delineation, but it suffers from low specificity. We undertook this pilot study in which dynamic features in time-activity curves (TACs) of [ 18 F]-FDG PET/CT images were applied to help the discrimination of tumour from inflammation and adjacent normal tissue. Five patients with OPC underwent dynamic [ 18 F]-FDG PET/CT imaging in treatment position. Voxel-by-voxel analysis was performed to evaluate seven dynamic features developed with the knowledge of differences in glucose metabolism in different tissue types and visual inspection of TACs. The Gaussian mixture model and K-means algorithms were used to evaluate the performance of the dynamic features in discriminating tumour voxels compared to the performance of standardized uptake values obtained from static imaging. Some dynamic features showed a trend towards discrimination of different metabolic areas but lack of consistency means that clinical application is not recommended based on these results alone. Impact of inflammatory tissue remains a problem for volume delineation in RT of OPC, but a simple dynamic imaging protocol proved practicable and enabled simple data analysis techniques that show promise for complementing the information in static uptake values.

Improving Teaching through Continuous Learning: The Inquiry Process John Wooden Used to Become Coach of the Century

ERIC Educational Resources Information Center

Ermeling, Bradley Alan

2012-01-01

Past and contemporary scholars have emphasized the importance of job-embedded, systematic instructional inquiry for educators. A recent review of the literature highlights four key features shared by several well documented inquiry approaches for classroom teachers. Interestingly, another line of research suggests that these key features also…

Improving the Design and Implementation of In-Service Professional Development in Early Childhood Intervention

ERIC Educational Resources Information Center

Dunst, Carl J.

2015-01-01

A model for designing and implementing evidence-­based in­-service professional development in early childhood intervention as well as the key features of the model are described. The key features include professional development specialist (PDS) description and demonstration of an intervention practice, active and authentic job-­embedded…

Salient Key Features of Actual English Instructional Practices in Saudi Arabia

ERIC Educational Resources Information Center

Al-Seghayer, Khalid

2015-01-01

This is a comprehensive review of the salient key features of the actual English instructional practices in Saudi Arabia. The goal of this work is to gain insights into the practices and pedagogic approaches to English as a foreign language (EFL) teaching currently employed in this country. In particular, we identify the following central features…

Improving Latino Children's Early Language and Literacy Development: Key Features of Early Childhood Education within Family Literacy Programmes

ERIC Educational Resources Information Center

Jung, Youngok; Zuniga, Stephen; Howes, Carollee; Jeon, Hyun-Joo; Parrish, Deborah; Quick, Heather; Manship, Karen; Hauser, Alison

2016-01-01

Noting the lack of research on how early childhood education (ECE) programmes within family literacy programmes influence Latino children's early language and literacy development, this study examined key features of ECE programmes, specifically teacher-child interactions and child engagement in language and literacy activities and how these…

Topological edge states and impurities: Manifestation in the local static and dynamical characteristics of dimerized quantum chains

NASA Astrophysics Data System (ADS)

Zvyagin, A. A.

2018-04-01

Based on the results of exact analytic calculations, we show that topological edge states and impurities in quantum dimerized chains manifest themselves in various local static and dynamical characteristics, which can be measured in experiments. In particular, topological edge states can be observed in the magnetic field behavior of the local magnetization or magnetic susceptibility of dimerized spin chains as jumps (for the magnetization) and features (for the static susceptibility) at zero field. In contrast, impurities reveal themselves in similar jumps and features, however, at nonzero values of the critical field. We also show that dynamical characteristics of dimerized quantum chains also manifest the features, related to the topological edge states and impurities. Those features, as a rule, can be seen more sharply than the manifestation of bulk extended states in, e.g., the dynamical local susceptibility. Such peculiarities can be observed in one-dimensional dimerized spin chains, e.g., in NMR experiments, or in various realizations of quantum dimerized chains in optical experiments.

Drag reduction and the dynamics of turbulence in simple and complex fluidsa)

NASA Astrophysics Data System (ADS)

Graham, Michael D.

2014-10-01

Addition of a small amount of very large polymer molecules or micelle-forming surfactants to a liquid can dramatically reduce the energy dissipation it exhibits in the turbulent flow regime. This rheological drag reduction phenomenon is widely used, for example, in the Alaska pipeline, but it is not well-understood, and no comparable technology exists to reduce turbulent energy consumption in flows of gases, in which polymers or surfactants cannot be dissolved. The most striking feature of this phenomenon is the existence of a so-called maximum drag reduction (MDR) asymptote: for a given geometry and driving force, there is a maximum level of drag reduction that can be achieved through addition of polymers. Changing the concentration, molecular weight or even the chemical structure of the additives has little to no effect on this asymptotic value. This universality is the major puzzle of drag reduction. We describe direct numerical simulations of turbulent minimal channel flow of Newtonian fluids and viscoelastic polymer solutions. Even in the absence of polymers, we show that there are intervals of "hibernating" turbulence that display very low drag as well as many other features of the MDR asymptote observed in polymer solutions. As Weissenberg number increases to moderate values the frequency of these intervals also increases, and a simple theory captures key features of the intermittent dynamics observed in the simulations. At higher Weissenberg number, these intervals are altered - for example, their duration becomes substantially longer and the instantaneous Reynolds shear stress during them becomes very small. Additionally, simulations of "edge states," dynamical trajectories that lie on the boundary between turbulent and laminar flow, display characteristics that are similar to those of hibernating turbulence and thus to the MDR asymptote, again even in the absence of polymer additives. Based on these observations, we propose a tentative unified description of rheological drag reduction. The existence of MDR-like intervals even in the absence of additives sheds light on the observed universality of MDR and may ultimately lead to new flow control approaches for improving energy efficiency in a wide range of processes.

Dynamics of spontaneous otoacoustic emissions

NASA Astrophysics Data System (ADS)

Bergevin, Christopher; Salerno, Anthony

2015-12-01

Spontaneous otoacoustic emissions (SOAEs) have become a hallmark feature in modern theories of an `active' inner ear, given their numerous correlations to auditory function (e.g., threshold microstructure, neurophysiological tuning curves), near universality across tetrapod classes, and physiological correlates at the single hair cell level. However, while several different classes of nonlinear models exist that describe the mechanisms underlying SOAE generation (e.g., coupled limit-cycle oscillators, global standing waves), there is still disagreement as to precisely which biophysical concepts are at work. Such is further compounded by the idiosyncratic nature of SOAEs: Not all ears emit, and when present, SOAE activity can occur at seemingly arbitrary frequencies (though always within the most sensitive range of the audiogram) and in several forms (e.g., peaks, broad `baseline' plateaus). The goal of the present study was to develop new signal processing and stimulation techniques that would allow for novel features of SOAE activity to be revealed. To this end, we analyzed data from a variety of different species: human, lizard, and owl. First, we explored several strategies for examining SOAE waveforms in the absence of external stimuli to further ascertain what constitutes `self-sustained sinusoids' versus `filtered noise'. We found that seemingly similar peaks in the spectral domain could exhibit key differences in the time domain, which we interpret as providing critical information about the underlying oscillators and their coupling. Second, we introduced dynamic stimuli (swept-tones, tone bursts) at a range of levels, whose interaction with SOAEs could be visualized in the time-frequency domain. Aside from offering a readily accessible way to visualize many previously reported effects (e.g., entrainment, facilitation), we observed several new features such as subharmonic distortion generation and competing pulling/pushing effects when multiple tones were present. Furthermore, the tone burst data provide quantitative bounds on the dynamics of the relaxation oscillations. These data should provide new insights into how precisely how SOAE generators are related to (the more commonly measured) OAEs evoked via external stimuli and presumably speak to the robustness of the hair cell as the underlying basis for SOAE activity.

Dynamic Digital Maps as Vehicles for Distributing Digital Geologic Maps and Embedded Analytical Data and Multimedia

NASA Astrophysics Data System (ADS)

Condit, C. D.; Mninch, M.

2012-12-01

The Dynamic Digital Map (DDM) is an ideal vehicle for the professional geologist to use to describe the geologic setting of key sites to the public in a format that integrates and presents maps and associated analytical data and multimedia without the need for an ArcGIS interface. Maps with field trip guide stops that include photographs, movies and figures and animations, showing, for example, how the features seen in the field formed, or how data might be best visualized in "time-frame" sequences are ideally included in DDMs. DDMs distribute geologic maps, images, movies, analytical data, and text such as field guides, in an integrated cross-platform, web enabled format that are intuitive to use, easily and quickly searchable, and require no additional proprietary software to operate. Maps, photos, movies and animations are stored outside the program, which acts as an organizational framework and index to present these data. Once created, the DDM can be downloaded from the web site hosting it in the flavor matching the user's operating system (e.g. Linux, Windows and Macintosh) as zip, dmg or tar files (and soon as iOS and Android tablet apps). When decompressed, the DDM can then access its associated data directly from that site with no browser needed. Alternatively, the entire package can be distributed and used from CD, DVD, or flash-memory storage. The intent of this presentation is to introduce the variety of geology that can be accessed from the over 25 DDMs created to date, concentrating on the DDM of the Springerville Volcanic Field. We will highlight selected features of some of them, introduce a simplified interface to the original DDM (that we renamed DDMC for Classic) and give a brief look at a the recently (2010-2011) completed geologic maps of the Springerville Volcanic field to see examples of each of the features discussed above, and a display of the integrated analytical data set. We will also highlight the differences between the classic or DDMCs and the new Dynamic Digital Map Extended (DDME) designed from the ground up to take advantage of the expanded connectedness this redesigned program will accommodate.

AVIRIS spectra correlated with the chlorophyll concentration of a forest canopy

NASA Technical Reports Server (NTRS)

Kupiec, John; Smith, Geoffrey M.; Curran, Paul J.

1993-01-01

Imaging spectrometers have many potential applications in the environmental sciences. One of the more promising applications is that of estimating the biochemical concentrations of key foliar biochemicals in forest canopies. These estimates are based on spectroscopic theory developed in agriculture and could be used to provide the spatial inputs necessary for the modeling of forest ecosystem dynamics and productivity. Several foliar biochemicals are currently under investigation ranging from those with primary absorption features in visible to middle infrared wavelengths (e.g., water, chlorophyll) to those with secondary to tertiary absorption features in this part of the spectrum (e.g., nitrogen, lignin). The foliar chemical of interest in this paper is chlorophyll; this is a photoreceptor and catalyst for the conversion of sunlight into chemical energy and as such plays a vital role in the photochemical synthesis of carbohydrates in plants. The aim of the research reported here was to determine if the chlorophyll concentration of a forest canopy could be correlated with the reflectance spectra recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Moist convection: a key to tropical wave-moisture interaction in Indian monsoon intraseasonal oscillation

NASA Astrophysics Data System (ADS)

Wu, Longtao; Wong, Sun; Wang, Tao; Huffman, George J.

2018-01-01

Simulation of moist convective processes is critical for accurately representing the interaction among tropical wave activities, atmospheric water vapor transport, and clouds associated with the Indian monsoon Intraseasonal Oscillation (ISO). In this study, we apply the Weather Research and Forecasting (WRF) model to simulate Indian monsoon ISO with three different treatments of moist convective processes: (1) the Betts-Miller-Janjić (BMJ) adjustment cumulus scheme without explicit simulation of moist convective processes; (2) the New Simplified Arakawa-Schubert (NSAS) mass-flux scheme with simplified moist convective processes; and (3) explicit simulation of moist convective processes at convection permitting scale (Nest). Results show that the BMJ experiment is unable to properly reproduce the equatorial Rossby wave activities and the corresponding phase relationship between moisture advection and dynamical convergence during the ISO. These features associated with the ISO are approximately captured in the NSAS experiment. The simulation with resolved moist convective processes significantly improves the representation of the ISO evolution, and has good agreements with the observations. This study features the first attempt to investigate the Indian monsoon at convection permitting scale.

LGBT Family Lawyers and Same-Sex Marriage Recognition: How Legal Change Shapes Professional Identity and Practice.

PubMed

Baumle, Amanda K

2018-01-10

Lawyers who practice family law for LGBT clients are key players in the tenuous and evolving legal environment surrounding same-sex marriage recognition. Building on prior research on factors shaping the professional identities of lawyers generally, and activist lawyers specifically, I examine how practice within a rapidly changing, patchwork legal environment shapes professional identity for this group of lawyers. I draw on interviews with 21 LGBT family lawyers to analyze how the unique features of LGBT family law shape their professional identities and practice, as well as their predictions about the development of the practice in a post-Obergefell world. Findings reveal that the professional identities and practice of LGBT family lawyers are shaped by uncertainty, characteristics of activist lawyering, community membership, and community service. Individual motivations and institutional forces work to generate a professional identity that is resilient and dynamic, characterized by skepticism and distrust coupled with flexibility and creativity. These features are likely to play a role in the evolution of the LGBT family lawyer professional identity post-marriage equality.

The essence of yeast quiescence.

PubMed

De Virgilio, Claudio

2012-03-01

Like all microorganisms, yeast cells spend most of their natural lifetime in a reversible, quiescent state that is primarily induced by limitation for essential nutrients. Substantial progress has been made in defining the features of quiescent cells and the nutrient-signaling pathways that shape these features. A view that emerges from the wealth of new data is that yeast cells dynamically configure the quiescent state in response to nutritional challenges by using a set of key nutrient-signaling pathways, which (1) regulate pathway-specific effectors, (2) converge on a few regulatory nodes that bundle multiple inputs to communicate unified, graded responses, and (3) mutually modulate their competences to transmit signals. Here, I present an overview of our current understanding of the architecture of these pathways, focusing on how the corresponding core signaling protein kinases (i.e. PKA, TORC1, Snf1, and Pho85) are wired to ensure an adequate response to nutrient starvation, which enables cells to tide over decades, if not centuries, of famine. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

pypet: A Python Toolkit for Data Management of Parameter Explorations

PubMed Central

Meyer, Robert; Obermayer, Klaus

2016-01-01

pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data for further analyses. pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2) quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines. PMID:27610080

Cyberbullying in Children and Youth: Implications for Health and Clinical Practice

PubMed Central

Faris, Robert; Mishna, Faye

2016-01-01

We review the recent literature on cyberbullying and its effects on victimised youth, identifying key points. We conclude that cyberbullying, while following many of the underlying dynamics of more traditional forms of bullying, features some unique qualities that can both magnify the damage caused and make it more difficult to detect. These features include the pervasive, never-ending nature of cyberbullying and the ability to quickly reach large audiences. The potential for anonymity and the related distance afforded by screens and devices compared to in-person interaction allow the cruelty of cyberbullying to go unchecked. Despite the perceived anonymity of cyberbullying, cyberbullying can be perpetrated by friends, who often have intimate knowledge about the victimised youth that can be devastating when made public. Given the difficulty schools face in preventing or even detecting cyberbullying, health care providers are an important ally, due to their knowledge of the youth, the sense of trust they bring to youth, and their independence from the school setting. We conclude by calling for routine screening of bullying by health care providers who deal with paediatric populations. PMID:28562091

Cyberbullying in Children and Youth: Implications for Health and Clinical Practice.

PubMed

Vaillancourt, Tracy; Faris, Robert; Mishna, Faye

2017-06-01

We review the recent literature on cyberbullying and its effects on victimised youth, identifying key points. We conclude that cyberbullying, while following many of the underlying dynamics of more traditional forms of bullying, features some unique qualities that can both magnify the damage caused and make it more difficult to detect. These features include the pervasive, never-ending nature of cyberbullying and the ability to quickly reach large audiences. The potential for anonymity and the related distance afforded by screens and devices compared to in-person interaction allow the cruelty of cyberbullying to go unchecked. Despite the perceived anonymity of cyberbullying, cyberbullying can be perpetrated by friends, who often have intimate knowledge about the victimised youth that can be devastating when made public. Given the difficulty schools face in preventing or even detecting cyberbullying, health care providers are an important ally, due to their knowledge of the youth, the sense of trust they bring to youth, and their independence from the school setting. We conclude by calling for routine screening of bullying by health care providers who deal with paediatric populations.

Mitochondrial defects and oxidative stress in Alzheimer disease and Parkinson disease.

PubMed

Yan, Michael H; Wang, Xinglong; Zhu, Xiongwei

2013-09-01

Alzheimer disease (AD) and Parkinson disease (PD) are the two most common age-related neurodegenerative diseases characterized by prominent neurodegeneration in selective neural systems. Although a small fraction of AD and PD cases exhibit evidence of heritability, among which many genes have been identified, the majority are sporadic without known causes. Molecular mechanisms underlying neurodegeneration and pathogenesis of these diseases remain elusive. Convincing evidence demonstrates oxidative stress as a prominent feature in AD and PD and links oxidative stress to the development of neuronal death and neural dysfunction, which suggests a key pathogenic role for oxidative stress in both AD and PD. Notably, mitochondrial dysfunction is also a prominent feature in these diseases, which is likely to be of critical importance in the genesis and amplification of reactive oxygen species and the pathophysiology of these diseases. In this review, we focus on changes in mitochondrial DNA and mitochondrial dynamics, two aspects critical to the maintenance of mitochondrial homeostasis and function, in relationship with oxidative stress in the pathogenesis of AD and PD. Copyright © 2012 Elsevier Inc. All rights reserved.

pypet: A Python Toolkit for Data Management of Parameter Explorations.

PubMed

Meyer, Robert; Obermayer, Klaus

2016-01-01

pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data for further analyses. pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2) quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines.

Nanoparticle Vaccines Adopting Virus-like Features for Enhanced Immune Potentiation

PubMed Central

Chattopadhyay, Saborni; Chen, Jui-Yi; Chen, Hui-Wen; Hu, Che-Ming Jack

2017-01-01

Synthetic nanoparticles play an increasingly significant role in vaccine design and development as many nanoparticle vaccines show improved safety and efficacy over conventional formulations. These nanoformulations are structurally similar to viruses, which are nanoscale pathogenic organisms that have served as a key selective pressure driving the evolution of our immune system. As a result, mechanisms behind the benefits of nanoparticle vaccines can often find analogue to the interaction dynamics between the immune system and viruses. This review covers the advances in vaccine nanotechnology with a perspective on the advantages of virus mimicry towards immune potentiation. It provides an overview to the different types of nanomaterials utilized for nanoparticle vaccine development, including functionalization strategies that bestow nanoparticles with virus-like features. As understanding of human immunity and vaccine mechanisms continue to evolve, recognizing the fundamental semblance between synthetic nanoparticles and viruses may offer an explanation for the superiority of nanoparticle vaccines over conventional vaccines and may spur new design rationales for future vaccine research. These nanoformulations are poised to provide solutions towards pressing and emerging human diseases. PMID:29071191

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Mitochondrial defects and oxidative stress in Alzheimer disease and Parkinson disease

PubMed Central

Yan, Michael H.; Wang, Xinglong; Zhu, Xiongwei

2013-01-01

Alzheimer disease (AD) and Parkinson disease (PD) are the two most common age-related neurodegenerative diseases characterized by prominent neurodegeneration in selective neural systems. Although a small fraction of AD and PD cases exhibit evidence of heritability, among which many genes have been identified, the majority are sporadic without known causes. Molecular mechanisms underlying neurodegeneration and pathogenesis of these diseases remain elusive. Convincing evidence demonstrates oxidative stress as a prominent feature in AD and PD and links oxidative stress to the development of neuronal death and neural dysfunction, which suggests a key pathogenic role for oxidative stress in both AD and PD. Notably, mitochondrial dysfunction is also a prominent feature in these diseases, which is likely to be of critical importance in the genesis and amplification of reactive oxygen species and the pathophysiology of these diseases. In this review, we focus on changes in mitochondrial DNA and mitochondrial dynamics, two aspects critical to the maintenance of mitochondrial homeostasis and function, in relationship with oxidative stress in the pathogenesis of AD and PD. PMID:23200807

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

PubMed

Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.

PubMed

Benedek, C; Descombes, X; Zerubia, J

2012-01-01

In this paper, we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: 1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low-level change information between the time layers and object-level building description to recognize and separate changed and unaltered buildings. 2) To answer the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature-based modules. 3) To simultaneously ensure the convergence, optimality, and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel nonuniform stochastic object birth process which generates relevant objects with higher probability based on low-level image features.

CD38-NAD+Axis Regulates Immunotherapeutic Anti-Tumor T Cell Response.

PubMed

Chatterjee, Shilpak; Daenthanasanmak, Anusara; Chakraborty, Paramita; Wyatt, Megan W; Dhar, Payal; Selvam, Shanmugam Panneer; Fu, Jianing; Zhang, Jinyu; Nguyen, Hung; Kang, Inhong; Toth, Kyle; Al-Homrani, Mazen; Husain, Mahvash; Beeson, Gyda; Ball, Lauren; Helke, Kristi; Husain, Shahid; Garrett-Mayer, Elizabeth; Hardiman, Gary; Mehrotra, Meenal; Nishimura, Michael I; Beeson, Craig C; Bupp, Melanie Gubbels; Wu, Jennifer; Ogretmen, Besim; Paulos, Chrystal M; Rathmell, Jeffery; Yu, Xue-Zhong; Mehrotra, Shikhar

2018-01-09

Heightened effector function and prolonged persistence, the key attributes of Th1 and Th17 cells, respectively, are key features of potent anti-tumor T cells. Here, we established ex vivo culture conditions to generate hybrid Th1/17 cells, which persisted long-term in vivo while maintaining their effector function. Using transcriptomics and metabolic profiling approaches, we showed that the enhanced anti-tumor property of Th1/17 cells was dependent on the increased NAD + -dependent activity of the histone deacetylase Sirt1. Pharmacological or genetic inhibition of Sirt1 activity impaired the anti-tumor potential of Th1/17 cells. Importantly, T cells with reduced surface expression of the NADase CD38 exhibited intrinsically higher NAD + , enhanced oxidative phosphorylation, higher glutaminolysis, and altered mitochondrial dynamics that vastly improved tumor control. Lastly, blocking CD38 expression improved tumor control even when using Th0 anti-tumor T cells. Thus, strategies targeting the CD38-NAD + axis could increase the efficacy of anti-tumor adoptive T cell therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

Transitions in Physiologic Coupling: Sleep Stage and Age Dependence of Cardio-respiratory Phase Synchronization

NASA Astrophysics Data System (ADS)

Bartsch, Ronny P.; Ivanov, Plamen Ch.

2012-02-01

Recent studies have focused on various features of cardiac and respiratory dynamics with the aim to better understand key aspects of the underlying neural control of these systems. We investigate how sleep influences cardio-respiratory coupling, and how the degree of this coupling changes with transitions across sleep stages in healthy young and elderly subjects. We analyze full night polysomnographic recordings of 189 healthy subjects (age range: 20 to 90 years). To probe cardio-respiratory coupling, we apply a novel phase synchronization analysis method to quantify the adjustment of rhythms between heartbeat and breathing signals. We investigate how cardio-respiratory synchronization changes with sleep-stage transitions and under healthy aging. We find a statistically significant difference in the degree of cardio-respiratory synchronization during different sleep stages for both young and elderly subjects and a significant decline of synchronization with age. This is a first evidence of how sleep regulation and aging influence a key nonlinear mechanism of physiologic coupling as quantified by the degree of phase synchronization between the cardiac and respiratory systems, which is of importance to develop adequate modeling approaches.

Effects of inverting contour and features on processing for static and dynamic face perception: an MEG study.

PubMed

Miki, Kensaku; Takeshima, Yasuyuki; Watanabe, Shoko; Honda, Yukiko; Kakigi, Ryusuke

2011-04-06

We investigated the effects of inverting facial contour (hair and chin) and features (eyes, nose and mouth) on processing for static and dynamic face perception using magnetoencephalography (MEG). We used apparent motion, in which the first stimulus (S1) was replaced by a second stimulus (S2) with no interstimulus interval and subjects perceived visual motion, and presented three conditions as follows: (1) U&U: Upright contour and Upright features, (2) U&I: Upright contour and Inverted features, and (3) I&I: Inverted contour and Inverted features. In static face perception (S1 onset), the peak latency of the fusiform area's activity, which was related to static face perception, was significantly longer for U&I and I&I than for U&U in the right hemisphere and for U&I than for U&U and I&I in the left. In dynamic face perception (S2 onset), the strength (moment) of the occipitotemporal area's activity, which was related to dynamic face perception, was significantly larger for I&I than for U&U and U&I in the right hemisphere, but not the left. These results can be summarized as follows: (1) in static face perception, the activity of the right fusiform area was more affected by the inversion of features while that of the left fusiform area was more affected by the disruption of the spatial relation between the contour and features, and (2) in dynamic face perception, the activity of the right occipitotemporal area was affected by the inversion of the facial contour. Copyright © 2011 Elsevier B.V. All rights reserved.

Multi-spectral fiber spectroscopy in 0,4-16μm range for biomedical applications(Conference Presentation)

NASA Astrophysics Data System (ADS)

Artyushenko, Viacheslav

2017-02-01

Various biomedical applications of fiber optics in a broad spectral range 0,4-16μm span from endoscopic imaging and Photo Dynamic Diagnostics (PDD) to laser power delivery for minimal invasive laser surgery, tissue coagulation and welding, Photo Dynamic Therapy (PDT), etc. Present review will highlight the latest results in advanced fiber solutions for a precise tissue diagnostics and control of some therapy methods - for so called "theranostic". Spectral fiber sensing for label free analysis of tissue composition helps to differentiate malignant and normal tissue to secure minimal invasive, but complete tumor removal or treatment. All key methods of Raman, fluorescence, diffuse reflection & MIR-absorption spectroscopy will be compared when used for the same spot of tissue - to select the most specific, sensitive and accurate method or to combine them for the synergy enhanced effect. The most informative spectral features for distinct organs/ tumor can be used to design special fiber sensors to be developed for portable and low cost applications with modern IT-features. Examples of multi-spectral tissue diagnostics promising for the future clinical applications will be presented to enable reduced mortality from cancer in the future. Translation of described methods into clinical practice will be discussed in comparison with the other method of optical diagnostics which should enhance modern medicine by less invasive, more precise and more effective methods of therapy to be fused with in-vivo diagnostics sensors & systems.

Approaches in Health Human Resource Forecasting: A Roadmap for Improvement.

PubMed

Rafiei, Sima; Mohebbifar, Rafat; Hashemi, Fariba; Ezzatabadi, Mohammad Ranjbar; Farzianpour, Fereshteh

2016-09-01

Forecasting the demand and supply of health manpower in an accurate manner makes appropriate planning possible. The aim of this paper was to review approaches and methods for health manpower forecasting and consequently propose the features that improve the effectiveness of this important process of health manpower planning. A literature review was conducted for studies published in English from 1990-2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Review articles, qualitative studies, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. The authors designed an extraction data sheet based on study questions to collect data on studies' references, designs, and types of forecasting approaches, whether discussed or applied, with their strengths and weaknesses. Forty studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified. Each approach had several strengths and weaknesses. As a whole, most of them were faced with some challenges, such as being static and unable to capture dynamic variables in manpower forecasting and causal relationships. They also lacked the capacity to benefit from scenario making to assist policy makers in effective decision making. An effective forecasting approach is supposed to resolve all the deficits that exist in current approaches and meet the key features found in the literature in order to develop an open system and a dynamic and comprehensive method necessary for today complex health care systems.

A simple, efficient polarizable coarse-grained water model for molecular dynamics simulations.

PubMed

Riniker, Sereina; van Gunsteren, Wilfred F

2011-02-28

The development of coarse-grained (CG) models that correctly represent the important features of compounds is essential to overcome the limitations in time scale and system size currently encountered in atomistic molecular dynamics simulations. Most approaches reported in the literature model one or several molecules into a single uncharged CG bead. For water, this implicit treatment of the electrostatic interactions, however, fails to mimic important properties, e.g., the dielectric screening. Therefore, a coarse-grained model for water is proposed which treats the electrostatic interactions between clusters of water molecules explicitly. Five water molecules are embedded in a spherical CG bead consisting of two oppositely charged particles which represent a dipole. The bond connecting the two particles in a bead is unconstrained, which makes the model polarizable. Experimental and all-atom simulated data of liquid water at room temperature are used for parametrization of the model. The experimental density and the relative static dielectric permittivity were chosen as primary target properties. The model properties are compared with those obtained from experiment, from clusters of simple-point-charge water molecules of appropriate size in the liquid phase, and for other CG water models if available. The comparison shows that not all atomistic properties can be reproduced by a CG model, so properties of key importance have to be selected when coarse graining is applied. Yet, the CG model reproduces the key characteristics of liquid water while being computationally 1-2 orders of magnitude more efficient than standard fine-grained atomistic water models.

A perturbation method to the tent map based on Lyapunov exponent and its application

NASA Astrophysics Data System (ADS)

Cao, Lv-Chen; Luo, Yu-Ling; Qiu, Sen-Hui; Liu, Jun-Xiu

2015-10-01

Perturbation imposed on a chaos system is an effective way to maintain its chaotic features. A novel parameter perturbation method for the tent map based on the Lyapunov exponent is proposed in this paper. The pseudo-random sequence generated by the tent map is sent to another chaos function — the Chebyshev map for the post processing. If the output value of the Chebyshev map falls into a certain range, it will be sent back to replace the parameter of the tent map. As a result, the parameter of the tent map keeps changing dynamically. The statistical analysis and experimental results prove that the disturbed tent map has a highly random distribution and achieves good cryptographic properties of a pseudo-random sequence. As a result, it weakens the phenomenon of strong correlation caused by the finite precision and effectively compensates for the digital chaos system dynamics degradation. Project supported by the Guangxi Provincial Natural Science Foundation, China (Grant No. 2014GXNSFBA118271), the Research Project of Guangxi University, China (Grant No. ZD2014022), the Fund from Guangxi Provincial Key Laboratory of Multi-source Information Mining & Security, China (Grant No. MIMS14-04), the Fund from the Guangxi Provincial Key Laboratory of Wireless Wideband Communication & Signal Processing, China (Grant No. GXKL0614205), the Education Development Foundation and the Doctoral Research Foundation of Guangxi Normal University, the State Scholarship Fund of China Scholarship Council (Grant No. [2014]3012), and the Innovation Project of Guangxi Graduate Education, China (Grant No. YCSZ2015102).

Quantitative cell polarity imaging defines leader-to-follower transitions during collective migration and the key role of microtubule-dependent adherens junction formation.

PubMed

Revenu, Céline; Streichan, Sebastian; Donà, Erika; Lecaudey, Virginie; Hufnagel, Lars; Gilmour, Darren

2014-03-01

The directed migration of cell collectives drives the formation of complex organ systems. A characteristic feature of many migrating collectives is a 'tissue-scale' polarity, whereby 'leader' cells at the edge of the tissue guide trailing 'followers' that become assembled into polarised epithelial tissues en route. Here, we combine quantitative imaging and perturbation approaches to investigate epithelial cell state transitions during collective migration and organogenesis, using the zebrafish lateral line primordium as an in vivo model. A readout of three-dimensional cell polarity, based on centrosomal-nucleus axes, allows the transition from migrating leaders to assembled followers to be quantitatively resolved for the first time in vivo. Using live reporters and a novel fluorescent protein timer approach, we investigate changes in cell-cell adhesion underlying this transition by monitoring cadherin receptor localisation and stability. This reveals that while cadherin 2 is expressed across the entire tissue, functional apical junctions are first assembled in the transition zone and become progressively more stable across the leader-follower axis of the tissue. Perturbation experiments demonstrate that the formation of these apical adherens junctions requires dynamic microtubules. However, once stabilised, adherens junction maintenance is microtubule independent. Combined, these data identify a mechanism for regulating leader-to-follower transitions within migrating collectives, based on the relocation and stabilisation of cadherins, and reveal a key role for dynamic microtubules in this process.

Ambient response of a unique performance-based design building with dynamic response modification features

USGS Publications Warehouse

Çelebi, Mehmet; Huang, Moh; Shakal, Antony; Hooper, John; Klemencic, Ron

2012-01-01

A 64-story, performance-based design building with reinforced concrete core shear-walls and unique dynamic response modification features (tuned liquid sloshing dampers and buckling-restrained braces) has been instrumented with a monitoring array of 72 channels of accelerometers. Ambient vibration data recorded are analyzed to identify modes and associated frequencies and damping. The low-amplitude dynamic characteristics are considerably different than those computed from design analyses, but serve as a baseline against which to compare with future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the added features to the building and help improve designs in the future.

Using dynamic geometry software for teaching conditional probability with area-proportional Venn diagrams

NASA Astrophysics Data System (ADS)

Radakovic, Nenad; McDougall, Douglas

2012-10-01

This classroom note illustrates how dynamic visualization can be used to teach conditional probability and Bayes' theorem. There are two features of the visualization that make it an ideal pedagogical tool in probability instruction. The first feature is the use of area-proportional Venn diagrams that, along with showing qualitative relationships, describe the quantitative relationship between two sets. The second feature is the slider and animation component of dynamic geometry software enabling students to observe how the change in the base rate of an event influences conditional probability. A hypothetical instructional sequence using a well-known breast cancer example is described.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Islands of spatially discordant APD alternans underlie arrhythmogenesis by promoting electrotonic dyssynchrony in models of fibrotic rat ventricular myocardium

NASA Astrophysics Data System (ADS)

Majumder, Rupamanjari; Engels, Marc C.; de Vries, Antoine A. F.; Panfilov, Alexander V.; Pijnappels, Daniël A.

2016-04-01

Fibrosis and altered gap junctional coupling are key features of ventricular remodelling and are associated with abnormal electrical impulse generation and propagation. Such abnormalities predispose to reentrant electrical activity in the heart. In the absence of tissue heterogeneity, high-frequency impulse generation can also induce dynamic electrical instabilities leading to reentrant arrhythmias. However, because of the complexity and stochastic nature of such arrhythmias, the combined effects of tissue heterogeneity and dynamical instabilities in these arrhythmias have not been explored in detail. Here, arrhythmogenesis was studied using in vitro and in silico monolayer models of neonatal rat ventricular tissue with 30% randomly distributed cardiac myofibroblasts and systematically lowered intercellular coupling achieved in vitro through graded knockdown of connexin43 expression. Arrhythmia incidence and complexity increased with decreasing intercellular coupling efficiency. This coincided with the onset of a specialized type of spatially discordant action potential duration alternans characterized by island-like areas of opposite alternans phase, which positively correlated with the degree of connexinx43 knockdown and arrhythmia complexity. At higher myofibroblast densities, more of these islands were formed and reentrant arrhythmias were more easily induced. This is the first study exploring the combinatorial effects of myocardial fibrosis and dynamic electrical instabilities on reentrant arrhythmia initiation and complexity.

Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting

NASA Astrophysics Data System (ADS)

Fabbri, Emiliana; Nachtegaal, Maarten; Binninger, Tobias; Cheng, Xi; Kim, Bae-Jung; Durst, Julien; Bozza, Francesco; Graule, Thomas; Schäublin, Robin; Wiles, Luke; Pertoso, Morgan; Danilovic, Nemanja; Ayers, Katherine E.; Schmidt, Thomas J.

2017-09-01

The growing need to store increasing amounts of renewable energy has recently triggered substantial R&D efforts towards efficient and stable water electrolysis technologies. The oxygen evolution reaction (OER) occurring at the electrolyser anode is central to the development of a clean, reliable and emission-free hydrogen economy. The development of robust and highly active anode materials for OER is therefore a great challenge and has been the main focus of research. Among potential candidates, perovskites have emerged as promising OER electrocatalysts. In this study, by combining a scalable cutting-edge synthesis method with time-resolved X-ray absorption spectroscopy measurements, we were able to capture the dynamic local electronic and geometric structure during realistic operando conditions for highly active OER perovskite nanocatalysts. Ba0.5Sr0.5Co0.8Fe0.2O3-δ as nano-powder displays unique features that allow a dynamic self-reconstruction of the material’s surface during OER, that is, the growth of a self-assembled metal oxy(hydroxide) active layer. Therefore, besides showing outstanding performance at both the laboratory and industrial scale, we provide a fundamental understanding of the operando OER mechanism for highly active perovskite catalysts. This understanding significantly differs from design principles based on ex situ characterization techniques.

Structure and Relaxation in Solutions of Monoclonal Antibodies.

PubMed

Wang, Gang; Varga, Zsigmond; Hofmann, Jennifer; Zarraga, Isidro E; Swan, James W

2018-03-22

Reversible self-association of therapeutic antibodies is a key factor in high protein solution viscosities. In the present work, a coarse-grained computational model accounting for electrostatic, dispersion, and long-ranged hydrodynamic interactions of two model monoclonal antibodies is applied to understand the nature of self-association, predicting the solution microstructure and resulting transport properties of the solution. For the proteins investigated, the structure factor across a range of solution conditions shows quantitative agreement with neutron-scattering experiments. We observe a homogeneous, dynamical association of the antibodies with no evidence of phase separation. Calculations of self-diffusivity and viscosity from coarse-grained dynamic simulations show the appropriate trends with concentration but, respectively, over- and under-predict the experimentally measured values. By adding constraints to the self-associated clusters that rigidify them under flow, prediction of the transport properties is significantly improved with respect to experimental measurements. We hypothesize that these rigidity constraints are associated with missing degrees of freedom in the coarse-grained model resulting from patchy and heterogeneous interactions among coarse-grained domains. These results demonstrate how structural anisotropy and anisotropy of interactions generated by features at the 2-5 nm length scale in antibodies are sufficient to recover the dynamics and rheological properties of these important macromolecular solutions.

Dynamics of spacing adjustment and recovery mechanisms of ABAC-type growth pattern in ternary eutectic systems

NASA Astrophysics Data System (ADS)

Mohagheghi, Samira; Şerefoğlu, Melis

2017-07-01

In directionally solidified 2D samples at ternary eutectic compositions, the stable three-phase pattern is established to be lamellar structure with ABAC stacking, where A, B, and C are crystalline phases. Beyond the stability limits of the ABAC pattern, the system uses various spacing adjustment mechanisms to revert to the stable regime. In this study, the dynamics of spacing adjustment and recovery mechanisms of isotropic ABAC patterns were investigated using three-phase In-Bi-Sn alloy. Unidirectional solidification experiments were performed on 23.0 and 62.7 μm-thick samples, where solidification front was monitored in real-time from both sides of the sample using a particular microscopy system. At these thicknesses, the pattern was found to be 2D during steady-state growth, i.e. both top and bottom microstructures were the same. However, during spacing adjustment and recovery mechanisms, 3D features were observed. Dynamics of two major instabilities, lamellae branching and elimination, were quantified. After these instabilities, two key ABAC pattern recovery mechanisms, namely, phase invasion and phase exchange processes, were identified and analyzed. After elimination, ABAC pattern is recovered by either continuous eliminations of all phases or by phase exchange. After branching, the recovery mechanisms are established to be phase invasion and phase exchange.

Fortune favours the brave: Movement responses shape demographic dynamics in strongly competing populations.

PubMed

Potts, Jonathan R; Petrovskii, Sergei V

2017-05-07

Animal movement is a key mechanism for shaping population dynamics. The effect of interactions between competing animals on a population's survival has been studied for many decades. However, interactions also affect an animal's subsequent movement decisions. Despite this, the indirect effect of these decisions on animal survival is much less well-understood. Here, we incorporate movement responses to foreign animals into a model of two competing populations, where inter-specific competition is greater than intra-specific competition. When movement is diffusive, the travelling wave moves from the stronger population to the weaker. However, by incorporating behaviourally induced directed movement towards the stronger population, the weaker one can slow the travelling wave down, even reversing its direction. Hence movement responses can switch the predictions of traditional mechanistic models. Furthermore, when environmental heterogeneity is combined with aggressive movement strategies, it is possible for spatially segregated co-existence to emerge. In this situation, the spatial patterns of the competing populations have the unusual feature that they are slightly out-of-phase with the environmental patterns. Finally, incorporating dynamic movement responses can also enable stable co-existence in a homogeneous environment, giving a new mechanism for spatially segregated co-existence. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computationally Guided Design of Polymer Electrolytes for Battery Applications

NASA Astrophysics Data System (ADS)

Wang, Zhen-Gang; Webb, Michael; Savoie, Brett; Miller, Thomas

We develop an efficient computational framework for guiding the design of polymer electrolytes for Li battery applications. Short-times molecular dynamics (MD) simulations are employed to identify key structural and dynamic features in the solvation and motion of Li ions, such as the structure of the solvation shells, the spatial distribution of solvation sites, and the polymer segmental mobility. Comparative studies on six polyester-based polymers and polyethylene oxide (PEO) yield good agreement with experimental data on the ion conductivities, and reveal significant differences in the ion diffusion mechanism between PEO and the polyesters. The molecular insights from the MD simulations are used to build a chemically specific coarse-grained model in the spirit of the dynamic bond percolation model of Druger, Ratner and Nitzan. We apply this coarse-grained model to characterize Li ion diffusion in several existing and yet-to-be synthesized polyethers that differ by oxygen content and backbone stiffness. Good agreement is obtained between the predictions of the coarse-grained model and long-timescale atomistic MD simulations, thus providing validation of the model. Our study predicts higher Li ion diffusivity in poly(trimethylene oxide-alt-ethylene oxide) than in PEO. These results demonstrate the potential of this computational framework for rapid screening of new polymer electrolytes based on ion diffusivity.

Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems

DOE PAGES

Adalsteinsson, Helgi; Debusschere, Bert J.; Long, Kevin R.; ...

2008-01-01

Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-levelmore » dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.« less

Nonlinear microrheology and molecular imaging to map microscale deformations of entangled DNA networks

NASA Astrophysics Data System (ADS)

Wu, Tsai-Chin; Anderson, Rae

We use active microrheology coupled to single-molecule fluorescence imaging to elucidate the microscale dynamics of entangled DNA. DNA naturally exists in a wide range of lengths and topologies, and is often confined in cell nucleui, forming highly concentrated and entangled biopolymer networks. Thus, DNA is the model polymer for understanding entangled polymer dynamics as well as the crowded environment of cells. These networks display complex viscoelastic properties that are not well understood, especially at the molecular-level and in response to nonlinear perturbations. Specifically, how microscopic stresses and strains propagate through entangled networks, and what molecular deformations lead to the network stress responses are unknown. To answer these important questions, we optically drive a microsphere through entangled DNA, perturbing the system far from equilibrium, while measuring the resistive force the DNA exerts on the bead during and after bead motion. We simultaneously image single fluorescent-labeled DNA molecules throughout the network to directly link the microscale stress response to molecular deformations. We characterize the deformation of the network from the molecular-level to the mesoscale, and map the stress propagation throughout the network. We further study the impact of DNA length (11 - 115 kbp) and topology (linear vs ring DNA) on deformation and propagation dynamics, exploring key nonlinear features such as tube dilation and power-law relaxation.

Universal dynamics and deterministic switching of dissipative Kerr solitons in optical microresonators

NASA Astrophysics Data System (ADS)

Guo, H.; Karpov, M.; Lucas, E.; Kordts, A.; Pfeiffer, M. H. P.; Brasch, V.; Lihachev, G.; Lobanov, V. E.; Gorodetsky, M. L.; Kippenberg, T. J.

2017-01-01

Temporal dissipative Kerr solitons in optical microresonators enable the generation of ultrashort pulses and low-noise frequency combs at microwave repetition rates. They have been demonstrated in a growing number of microresonator platforms, enabling chip-scale frequency combs, optical synthesis of low-noise microwaves and multichannel coherent communications. In all these applications, accessing and maintaining a single-soliton state is a key requirement--one that remains an outstanding challenge. Here, we study the dynamics of multiple-soliton states and report the discovery of a simple mechanism that deterministically switches the soliton state by reducing the number of solitons one by one. We demonstrate this control in Si3N4 and MgF2 resonators and, moreover, we observe a secondary peak to emerge in the response of the system to a pump modulation, an effect uniquely associated with the soliton regime. Exploiting this feature, we map the multi-stability diagram of a microresonator experimentally. Our measurements show the physical mechanism of the soliton switching and provide insight into soliton dynamics in microresonators. The technique provides a method to sequentially reduce, monitor and stabilize an arbitrary state with solitons, in particular allowing for feedback stabilization of single-soliton states, which is necessary for practical applications.

A new task scheduling algorithm based on value and time for cloud platform

NASA Astrophysics Data System (ADS)

Kuang, Ling; Zhang, Lichen

2017-08-01

Tasks scheduling, a key part of increasing resource utilization and enhancing system performance, is a never outdated problem especially in cloud platforms. Based on the value density algorithm of the real-time task scheduling system and the character of the distributed system, the paper present a new task scheduling algorithm by further studying the cloud technology and the real-time system: Least Level Value Density First (LLVDF). The algorithm not only introduces some attributes of time and value for tasks, it also can describe weighting relationships between these properties mathematically. As this feature of the algorithm, it can gain some advantages to distinguish between different tasks more dynamically and more reasonably. When the scheme was used in the priority calculation of the dynamic task scheduling on cloud platform, relying on its advantage, it can schedule and distinguish tasks with large amounts and many kinds more efficiently. The paper designs some experiments, some distributed server simulation models based on M/M/C model of queuing theory and negative arrivals, to compare the algorithm against traditional algorithm to observe and show its characters and advantages.

Visualizing cellulase activity.

PubMed

Bubner, Patricia; Plank, Harald; Nidetzky, Bernd

2013-06-01

Commercial exploitation of lignocellulose for biotechnological production of fuels and commodity chemicals requires efficient-usually enzymatic-saccharification of the highly recalcitrant insoluble substrate. A key characteristic of cellulose conversion is that the actual hydrolysis of the polysaccharide chains is intrinsically entangled with physical disruption of substrate morphology and structure. This "substrate deconstruction" by cellulase activity is a slow, yet markedly dynamic process that occurs at different length scales from and above the nanometer range. Little is currently known about the role of progressive substrate deconstruction on hydrolysis efficiency. Application of advanced visualization techniques to the characterization of enzymatic degradation of different celluloses has provided important new insights, at the requisite nano-scale resolution and down to the level of single enzyme molecules, into cellulase activity on the cellulose surface. Using true in situ imaging, dynamic features of enzyme action and substrate deconstruction were portrayed at different morphological levels of the cellulose, thus providing new suggestions and interpretations of rate-determining factors. Here, we review the milestones achieved through visualization, the methods which significantly promoted the field, compare suitable (model) substrates, and identify limiting factors, challenges and future tasks. Copyright © 2013 Wiley Periodicals, Inc.

Phytoplankton productivity and microzooplankton grazing within planktonic thin layers in the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Boyette, A.; Redalje, D.; Krause, J. W.; Graham, W. M.

2016-02-01

Plankton thin layers (PTLs) serve as trophic hot spots and have significant impacts on regional aquatic food webs. While much of the physical and biological dynamics associated with PTL formation, persistence, and dissipation have been examined, less is known about the variability in phytoplankton-productivity and microzooplankton-grazing rates. Thus, our overarching research objectives were to describe the trophic interactions between single-celled autrotrophic and heterotrophic eukaryotes (protists) within PTLs in the Mississippi Bight (MB). Specific objectives were to describe phytoplankton photosynthetic potential using photosynthesis-irradiance (P-E) parameters, quantify protist-grazing rates, and identify microplankton (20-200 µm) species and their particle characteristics (e.g. biovolume) using imaging flow cytometry (FlowCAM®). Although PTLs are ephemeral features, they may account for a considerable fraction of total water column primary production and contain a significant fraction of water-column integrated autotrophic biomass. The research presented here will fill information gaps in PTL dynamics, and will serve to calibrate regional ecological models that are key to our visualization of energy flows within this ecosystem.