quantify dynamic similarity: Topics by Science.gov

Sample records for quantify dynamic similarity

Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways

PubMed Central

Seyler, Sean L.; Kumar, Avishek; Thorpe, M. F.; Beckstein, Oliver

2015-01-01

Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example, showed that
A novel method for quantifying arm motion similarity.

PubMed

Zhi Li; Hauser, Kris; Roldan, Jay Ryan; Milutinovic, Dejan; Rosen, Jacob

2015-08-01

This paper proposes a novel task-independent method for quantifying arm motion similarity that can be applied to any kinematic/dynamic variable of interest. Given two arm motions for the same task, not necessarily with the same completion time, it plots the time-normalized curves against one another and generates four real-valued features. To validate these features we apply them to quantify the relationship between healthy and paretic arm motions of chronic stroke patients. Studying both unimanual and bimanual arm motions of eight chronic stroke patients, we find that inter-arm coupling that tends to synchronize the motions of both arms in bimanual motions, has a stronger effect at task-relevant joints than at task-irrelevant joints. It also revealed that the paretic arm suppresses the shoulder flexion of the non-paretic arm, while the latter encourages the shoulder rotation of the former.
Quantifying similarity of pore-geometry in nanoporous materials

DOE PAGES

Lee, Yongjin; Barthel, Senja D.; Dłotko, Paweł; ...

2017-05-23

In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials. But, the mathematical language and tools to identify materials with similar pore structures, but different composition, has been lacking. We develop a pore recognition approach to quantify similarity of pore structures and classify themmore » using topological data analysis. This then allows us to identify materials with similar pore geometries, and to screen for materials that are similar to given top-performing structures. Using methane storage as a case study, we also show that materials can be divided into topologically distinct classes requiring different optimization strategies.« less
Quantifying stochasticity in the dynamics of delay-coupled semiconductor lasers via forbidden patterns.

PubMed

Tiana-Alsina, Jordi; Buldú, Javier M; Torrent, M C; García-Ojalvo, Jordi

2010-01-28

We quantify the level of stochasticity in the dynamics of two mutually coupled semiconductor lasers. Specifically, we concentrate on a regime in which the lasers synchronize their dynamics with a non-zero lag time, and the leader and laggard roles alternate irregularly between the lasers. We analyse this switching dynamics in terms of the number of forbidden patterns of the alternate time series. The results reveal that the system operates in a stochastic regime, with the level of stochasticity decreasing as the lasers are pumped further away from their lasing threshold. This behaviour is similar to that exhibited by a single semiconductor laser subject to external optical feedback, as its dynamics shifts from the regime of low-frequency fluctuations to coherence collapse. This journal is © 2010 The Royal Society
Using multidimensional scaling to quantify similarity in visual search and beyond

PubMed Central

Godwin, Hayward J.; Fitzsimmons, Gemma; Robbins, Arryn; Menneer, Tamaryn; Goldinger, Stephen D.

2017-01-01

Visual search is one of the most widely studied topics in vision science, both as an independent topic of interest, and as a tool for studying attention and visual cognition. A wide literature exists that seeks to understand how people find things under varying conditions of difficulty and complexity, and in situations ranging from the mundane (e.g., looking for one’s keys) to those with significant societal importance (e.g., baggage or medical screening). A primary determinant of the ease and probability of success during search are the similarity relationships that exist in the search environment, such as the similarity between the background and the target, or the likeness of the non-targets to one another. A sense of similarity is often intuitive, but it is seldom quantified directly. This presents a problem in that similarity relationships are imprecisely specified, limiting the capacity of the researcher to examine adequately their influence. In this article, we present a novel approach to overcoming this problem that combines multidimensional scaling (MDS) analyses with behavioral and eye-tracking measurements. We propose a method whereby MDS can be repurposed to successfully quantify the similarity of experimental stimuli, thereby opening up theoretical questions in visual search and attention that cannot currently be addressed. These quantifications, in conjunction with behavioral and oculomotor measures, allow for critical observations about how similarity affects performance, information selection, and information processing. We provide a demonstration and tutorial of the approach, identify documented examples of its use, discuss how complementary computer vision methods could also be adopted, and close with a discussion of potential avenues for future application of this technique. PMID:26494381
Quantifying similarity in reliability surfaces using the probability of agreement

DOE PAGES

Stevens, Nathaniel T.; Anderson-Cook, Christine Michaela

2017-03-30

When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two-factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. As a result, new graphical summaries provide strategies formore » visualizing the results.« less
Quantifying similarity in reliability surfaces using the probability of agreement

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

Stevens, Nathaniel T.; Anderson-Cook, Christine Michaela

When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two-factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. As a result, new graphical summaries provide strategies formore » visualizing the results.« less
Similarity Metrics for Closed Loop Dynamic Systems

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Yang, Lee C.; Bedrossian, Naz; Hall, Robert A.

2008-01-01

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and
Dynamic similarity in erosional processes

USGS Publications Warehouse

Scheidegger, A.E.

1963-01-01

A study is made of the dynamic similarity conditions obtaining in a variety of erosional processes. The pertinent equations for each type of process are written in dimensionless form; the similarity conditions can then easily be deduced. The processes treated are: raindrop action, slope evolution and river erosion. ?? 1963 Istituto Geofisico Italiano.
Proteins with similar architecture exhibit similar large-scale dynamic behavior.

PubMed Central

Keskin, O; Jernigan, R L; Bahar, I

2000-01-01

We have investigated the similarities and differences in the computed dynamic fluctuations exhibited by six members of a protein fold family with a coarse-grained Gaussian network model. Specifically, we consider the cofactor binding fragment of CysB; the lysine/arginine/ornithine-binding protein (LAO); the enzyme porphobilinogen deaminase (PBGD); the ribose-binding protein (RBP); the N-terminal lobe of ovotransferrin in apo-form (apo-OVOT); and the leucine/isoleucine/valine-binding protein (LIVBP). All have domains that resemble a Rossmann fold, but there are also some significant differences. Results indicate that similar global dynamic behavior is preserved for the members of a fold family, and that differences usually occur in regions only where specific function is localized. The present work is a computational demonstration that the scaffold of a protein fold may be utilized for diverse purposes. LAO requires a bound ligand before it conforms to the large-scale fluctuation behavior of the three other members of the family, CysB, PBGD, and RBP, all of which contain a substrate (cofactor) at the active site cleft. The dynamics of the ligand-free enzymes LIVBP and apo-OVOT, on the other hand, concur with that of unliganded LAO. The present results suggest that it is possible to construct structure alignments based on dynamic fluctuation behavior. PMID:10733987
Quantifying chaotic dynamics from integrate-and-fire processes

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

Pavlov, A. N.; Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov; Pavlova, O. N.

2015-01-15

Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periodsmore » of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.« less
Predicting the evolution of complex networks via similarity dynamics

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-01-01

Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.
Quantifying cadherin mechanotransduction machinery assembly/disassembly dynamics using fluorescence covariance analysis.

PubMed

Vedula, Pavan; Cruz, Lissette A; Gutierrez, Natasha; Davis, Justin; Ayee, Brian; Abramczyk, Rachel; Rodriguez, Alexis J

2016-06-30

Quantifying multi-molecular complex assembly in specific cytoplasmic compartments is crucial to understand how cells use assembly/disassembly of these complexes to control function. Currently, biophysical methods like Fluorescence Resonance Energy Transfer and Fluorescence Correlation Spectroscopy provide quantitative measurements of direct protein-protein interactions, while traditional biochemical approaches such as sub-cellular fractionation and immunoprecipitation remain the main approaches used to study multi-protein complex assembly/disassembly dynamics. In this article, we validate and quantify multi-protein adherens junction complex assembly in situ using light microscopy and Fluorescence Covariance Analysis. Utilizing specific fluorescently-labeled protein pairs, we quantified various stages of adherens junction complex assembly, the multiprotein complex regulating epithelial tissue structure and function following de novo cell-cell contact. We demonstrate: minimal cadherin-catenin complex assembly in the perinuclear cytoplasm and subsequent localization to the cell-cell contact zone, assembly of adherens junction complexes, acto-myosin tension-mediated anchoring, and adherens junction maturation following de novo cell-cell contact. Finally applying Fluorescence Covariance Analysis in live cells expressing fluorescently tagged adherens junction complex proteins, we also quantified adherens junction complex assembly dynamics during epithelial monolayer formation.
Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

DTIC Science & Technology

2017-02-01

note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based...this technical note are widely used and may have an important role when computing the distance and similarity of large datasets and when considering high...throughput processes. In this technical note, a number of different measures implemented in both MAT- LAB and Python as functions are used to
Quantifying dynamic characteristics of human walking for comprehensive gait cycle.

PubMed

Mummolo, Carlotta; Mangialardi, Luigi; Kim, Joo H

2013-09-01

Normal human walking typically consists of phases during which the body is statically unbalanced while maintaining dynamic stability. Quantifying the dynamic characteristics of human walking can provide better understanding of gait principles. We introduce a novel quantitative index, the dynamic gait measure (DGM), for comprehensive gait cycle. The DGM quantifies the effects of inertia and the static balance instability in terms of zero-moment point and ground projection of center of mass and incorporates the time-varying foot support region (FSR) and the threshold between static and dynamic walking. Also, a framework of determining the DGM from experimental data is introduced, in which the gait cycle segmentation is further refined. A multisegmental foot model is integrated into a biped system to reconstruct the walking motion from experiments, which demonstrates the time-varying FSR for different subphases. The proof-of-concept results of the DGM from a gait experiment are demonstrated. The DGM results are analyzed along with other established features and indices of normal human walking. The DGM provides a measure of static balance instability of biped walking during each (sub)phase as well as the entire gait cycle. The DGM of normal human walking has the potential to provide some scientific insights in understanding biped walking principles, which can also be useful for their engineering and clinical applications.
Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials.

PubMed

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound
Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

PubMed Central

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound
Musical structure analysis using similarity matrix and dynamic programming

NASA Astrophysics Data System (ADS)

Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay

2005-10-01

Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
Quantifying the similarity of seismic polarizations

NASA Astrophysics Data System (ADS)

Jones, Joshua P.; Eaton, David W.; Caffagni, Enrico

2016-02-01

Assessing the similarities of seismic attributes can help identify tremor, low signal-to-noise (S/N) signals and converted or reflected phases, in addition to diagnosing site noise and sensor misalignment in arrays. Polarization analysis is a widely accepted method for studying the orientation and directional characteristics of seismic phases via computed attributes, but similarity is ordinarily discussed using qualitative comparisons with reference values or known seismic sources. Here we introduce a technique for quantitative polarization similarity that uses weighted histograms computed in short, overlapping time windows, drawing on methods adapted from the image processing and computer vision literature. Our method accounts for ambiguity in azimuth and incidence angle and variations in S/N ratio. Measuring polarization similarity allows easy identification of site noise and sensor misalignment and can help identify coherent noise and emergent or low S/N phase arrivals. Dissimilar azimuths during phase arrivals indicate misaligned horizontal components, dissimilar incidence angles during phase arrivals indicate misaligned vertical components and dissimilar linear polarization may indicate a secondary noise source. Using records of the Mw = 8.3 Sea of Okhotsk earthquake, from Canadian National Seismic Network broad-band sensors in British Columbia and Yukon Territory, Canada, and a vertical borehole array at Hoadley gas field, central Alberta, Canada, we demonstrate that our method is robust to station spacing. Discrete wavelet analysis extends polarization similarity to the time-frequency domain in a straightforward way. Time-frequency polarization similarities of borehole data suggest that a coherent noise source may have persisted above 8 Hz several months after peak resource extraction from a `flowback' type hydraulic fracture.
Quantifying the Diversity and Similarity of Surgical Procedures Among Hospitals and Anesthesia Providers.

PubMed

Dexter, Franklin; Ledolter, Johannes; Hindman, Bradley J

2016-01-01

In this Statistical Grand Rounds, we review methods for the analysis of the diversity of procedures among hospitals, the activities among anesthesia providers, etc. We apply multiple methods and consider their relative reliability and usefulness for perioperative applications, including calculations of SEs. We also review methods for comparing the similarity of procedures among hospitals, activities among anesthesia providers, etc. We again apply multiple methods and consider their relative reliability and usefulness for perioperative applications. The applications include strategic analyses (e.g., hospital marketing) and human resource analytics (e.g., comparisons among providers). Measures of diversity of procedures and activities (e.g., Herfindahl and Gini-Simpson index) are used for quantification of each facility (hospital) or anesthesia provider, one at a time. Diversity can be thought of as a summary measure. Thus, if the diversity of procedures for 48 hospitals is studied, the diversity (and its SE) is being calculated for each hospital. Likewise, the effective numbers of common procedures at each hospital can be calculated (e.g., by using the exponential of the Shannon index). Measures of similarity are pairwise assessments. Thus, if quantifying the similarity of procedures among cases with a break or handoff versus cases without a break or handoff, a similarity index represents a correlation coefficient. There are several different measures of similarity, and we compare their features and applicability for perioperative data. We rely extensively on sensitivity analyses to interpret observed values of the similarity index.

Self similarities in desalination dynamics and performance using capacitive deionization.

PubMed

Ramachandran, Ashwin; Hemmatifar, Ali; Hawks, Steven A; Stadermann, Michael; Santiago, Juan G

2018-09-01

Charge transfer and mass transport are two underlying mechanisms which are coupled in desalination dynamics using capacitive deionization (CDI). We developed simple reduced-order models based on a mixed reactor volume principle which capture the coupled dynamics of CDI operation using closed-form semi-analytical and analytical solutions. We use the models to identify and explore self-similarities in the dynamics among flow rate, current, and voltage for CDI cell operation including both charging and discharging cycles. The similarity approach identifies the specific combination of cell (e.g. capacitance, resistance) and operational parameters (e.g. flow rate, current) which determine a unique effluent dynamic response. We here demonstrate self-similarity using a conventional flow between CDI (fbCDI) architecture, and we hypothesize that our similarity approach has potential application to a wide range of designs. We performed an experimental study of these dynamics and used well-controlled experiments of CDI cell operation to validate and explore limits of the model. For experiments, we used a CDI cell with five electrode pairs and a standard flow between (electrodes) architecture. Guided by the model, we performed a series of experiments that demonstrate natural response of the CDI system. We also identify cell parameters and operation conditions which lead to self-similar dynamics under a constant current forcing function and perform a series of experiments by varying flowrate, currents, and voltage thresholds to demonstrate self-similarity. Based on this study, we hypothesize that the average differential electric double layer (EDL) efficiency (a measure of ion adsorption rate to EDL charging rate) is mainly dependent on user-defined voltage thresholds, whereas flow efficiency (measure of how well desalinated water is recovered from inside the cell) depends on cell volumes flowed during charging, which is determined by flowrate, current and voltage thresholds
Quantifying humpback whale song sequences to understand the dynamics of song exchange at the ocean basin scale.

PubMed

Garland, Ellen C; Noad, Michael J; Goldizen, Anne W; Lilley, Matthew S; Rekdahl, Melinda L; Garrigue, Claire; Constantine, Rochelle; Daeschler Hauser, Nan; Poole, M Michael; Robbins, Jooke

2013-01-01

Humpback whales have a continually evolving vocal sexual display, or "song," that appears to undergo both evolutionary and "revolutionary" change. All males within a population adhere to the current content and arrangement of the song. Populations within an ocean basin share similarities in their songs; this sharing is complex as multiple variations of the song (song types) may be present within a region at any one time. To quantitatively investigate the similarity of song types, songs were compared at both the individual singer and population level using the Levenshtein distance technique and cluster analysis. The highly stereotyped sequences of themes from the songs of 211 individuals from populations within the western and central South Pacific region from 1998 through 2008 were grouped together based on the percentage of song similarity, and compared to qualitatively assigned song types. The analysis produced clusters of highly similar songs that agreed with previous qualitative assignments. Each cluster contained songs from multiple populations and years, confirming the eastward spread of song types and their progressive evolution through the study region. Quantifying song similarity and exchange will assist in understanding broader song dynamics and contribute to the use of vocal displays as population identifiers.
Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Ogunsua, Babalola

2018-04-01

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

PubMed Central

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

2011-01-01

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

PubMed

Reeves, M T; Billam, T P; Anderson, B P; Bradley, A S

2015-04-17

The Reynolds number provides a characterization of the transition to turbulent flow, with wide application in classical fluid dynamics. Identifying such a parameter in superfluid systems is challenging due to their fundamentally inviscid nature. Performing a systematic study of superfluid cylinder wakes in two dimensions, we observe dynamical similarity of the frequency of vortex shedding by a cylindrical obstacle. The universality of the turbulent wake dynamics is revealed by expressing shedding frequencies in terms of an appropriately defined superfluid Reynolds number, Re(s), that accounts for the breakdown of superfluid flow through quantum vortex shedding. For large obstacles, the dimensionless shedding frequency exhibits a universal form that is well-fitted by a classical empirical relation. In this regime the transition to turbulence occurs at Re(s)≈0.7, irrespective of obstacle width.
A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

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

2018-02-23

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

PubMed Central

Girard, Pascal; Ioannou, Konstantinos; Klinkhardt, Ute; Munafo, Alain

2018-01-01

Mathematical models of tumor dynamics generally omit information on individual target lesions (iTLs), and consider the most important variable to be the sum of tumor sizes (TS). However, differences in lesion dynamics might be predictive of tumor progression. To exploit this information, we have developed a novel and flexible approach for the non‐parametric analysis of iTLs, which integrates knowledge from signal processing and machine learning. We called this new methodology ClassIfication Clustering of Individual Lesions (CICIL). We used CICIL to assess similarities among the TS dynamics of 3,223 iTLs measured in 1,056 patients with metastatic colorectal cancer treated with cetuximab combined with irinotecan, in two phase II studies. We mainly observed similar dynamics among lesions within the same tumor site classification. In contrast, lesions in anatomic locations with different features showed different dynamics in about 35% of patients. The CICIL methodology has also been implemented in a user‐friendly and efficient Java‐based framework. PMID:29388396
Quantifying the effect of hydrogen on dislocation dynamics: A three-dimensional discrete dislocation dynamics framework

NASA Astrophysics Data System (ADS)

Gu, Yejun; El-Awady, Jaafar A.

2018-03-01

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

PubMed Central

Cheddadi, Rachid; de Beaulieu, Jacques-Louis; Jouzel, Jean; Andrieu-Ponel, Valérie; Laurent, Jeanne-Marine; Reille, Maurice; Raynaud, Dominique; Bar-Hen, Avner

2005-01-01

The Velay sequence (France) provides a unique, continuous, palynological record spanning the last four climatic cycles. A pollen-based reconstruction of temperature and precipitation displays marked climatic cycles. An analysis of the climate and vegetation changes during the interglacial periods reveals comparable features and identical major vegetation successions. Although Marine Isotope Stage (MIS) 11.3 and the Holocene had similar earth precessional variations, their correspondence in terms of vegetation dynamics is low. MIS 9.5, 7.5, and especially 5.5 display closer correlation to the Holocene than MIS 11.3. Ecological factors, such as the distribution and composition of glacial refugia or postglacial migration patterns, may explain these discrepancies. Comparison of ecosystem dynamics during the past five interglacials suggests that vegetation development in the current interglacial has no analogue from the past 500,000 years. PMID:16162676
Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks

PubMed Central

Shelton, Christian; Mednick, Sara C.

2018-01-01

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

PubMed

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

2018-01-01

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

NASA Astrophysics Data System (ADS)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.
The similarity law for hypersonic flow and requirements for dynamic similarity of related bodies in free flight

NASA Technical Reports Server (NTRS)

Hamaker, Frank M; Neice, Stanford E; Wong, Thomas J

1953-01-01

The similarity law for nonsteady, inviscid, hypersonic flow about slender three-dimensional shapes is derived. Conclusions drawn are shown to be valid for rotational flow. Requirements for dynamic similarity of related shapes in free flight are obtained. The law is examined for steady flow about related three-dimensional shapes. Results of an experimental investigation of the pressures acting on two inclined cones are found to check the law as it applies to bodies of revolution.
Similarity Measures for Protein Ensembles

PubMed Central

Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper

2009-01-01

Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations. However, instead of examining individual conformations it is in many cases more relevant to analyse ensembles of conformations that have been obtained either through experiments or from methods such as molecular dynamics simulations. We here present three approaches that can be used to compare conformational ensembles in the same way as the root mean square deviation is used to compare individual pairs of structures. The methods are based on the estimation of the probability distributions underlying the ensembles and subsequent comparison of these distributions. We first validate the methods using a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single-molecule refinement. PMID:19145244
A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

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

PubMed Central

Singh, Aarti; Poczos, Barnabas; Erickson, Kirk I.; Tseng, Wen-Yih I.; Verstynen, Timothy D.

2016-01-01

Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N = 213), we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns for repeat scans acquired within 3 months. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings, relative to differences between unrelated subjects. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome. PMID:27846212
Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

DOE PAGES

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

2016-10-20

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

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

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

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

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

PubMed Central

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

2016-01-01

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

NASA Astrophysics Data System (ADS)

Godinho, jose; Gerke, kirill

2016-04-01

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

PubMed

Basu, Sohini; Sen, Srikanta

2013-02-25

Structure and dynamics both are known to be important for the activity of a protein. A fundamental question is whether a thermophilic protein and its mesophilic homologue exhibit similar dynamics at their respective optimal growth temperatures. We have addressed this question by performing molecular dynamics (MD) simulations of a natural mesophilic-thermophilic homologue pair at their respective optimal growth temperatures to compare their structural, dynamical, and solvent properties. The MD simulations were done in explicit aqueous solvent under periodic boundary and constant pressure and temperature (CPT) conditions and continued for 10.0 ns using the same protocol for the two proteins, excepting the temperatures. The trajectories were analyzed to compare the properties of the two proteins. Results indicated that the dynamical behaviors of the two proteins at the respective optimal growth temperatures were remarkably similar. For the common residues in the thermophilic protein, the rms fluctuations have a general trend to be slightly higher compared to that in the mesophilic counterpart. Lindemann parameter values indicated that only a few residues exhibited solid-like dynamics while the protein as a whole appeared as a molten globule in each case. Interestingly, the water-water interaction was found to be strikingly similar in spite of the difference in temperatures while, the protein-water interaction was significantly different in the two simulations.
PCB Food Web Dynamics Quantify Nutrient and Energy Flow in Aquatic Ecosystems.

PubMed

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

2015-11-03

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

PubMed

Pezard, Laurent; Doba, Karyn; Lesne, Annick; Nandrino, Jean-Louis

2017-07-01

Emotional interactions have been considered dynamical processes involved in the affective life of humans and their disturbances may induce mental disorders. Most studies of emotional interactions have focused on dyadic behaviors or self-reports of emotional states but neglected the dynamical processes involved in family therapy. The main objective of this study is to quantify the dynamics of emotional expressions and their changes using the family therapy of patients with anorexia nervosa as an example. Nonlinear methods characterize the variability of the dynamics at the level of the whole therapeutic system and reciprocal influence between the participants during family therapy. Results show that the variability of the dynamics is higher at the end of the therapy than at the beginning. The reciprocal influences between therapist and each member of the family and between mother and patient decrease with the course of family therapy. Our results support the development of new interpersonal strategies of emotion regulation during family therapy. The quantification of emotional dynamics can help understanding the emotional processes underlying psychopathology and evaluating quantitatively the changes achieved by the therapeutic intervention. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
Simulating Food Web Dynamics along a Gradient: Quantifying Human Influence

PubMed Central

Jordán, Ferenc; Gjata, Nerta; Mei, Shu; Yule, Catherine M.

2012-01-01

Realistically parameterized and dynamically simulated food-webs are useful tool to explore the importance of the functional diversity of ecosystems, and in particular relations between the dynamics of species and the whole community. We present a stochastic dynamical food web simulation for the Kelian River (Borneo). The food web was constructed for six different locations, arrayed along a gradient of increasing human perturbation (mostly resulting from gold mining activities) along the river. Along the river, the relative importance of grazers, filterers and shredders decreases with increasing disturbance downstream, while predators become more dominant in governing eco-dynamics. Human activity led to increased turbidity and sedimentation which adversely impacts primary productivity. Since the main difference between the study sites was not the composition of the food webs (structure is quite similar) but the strengths of interactions and the abundance of the trophic groups, a dynamical simulation approach seemed to be useful to better explain human influence. In the pristine river (study site 1), when comparing a structural version of our model with the dynamical model we found that structurally central groups such as omnivores and carnivores were not the most important ones dynamically. Instead, primary consumers such as invertebrate grazers and shredders generated a greater dynamical response. Based on the dynamically most important groups, bottom-up control is replaced by the predominant top-down control regime as distance downstream and human disturbance increased. An important finding, potentially explaining the poor structure to dynamics relationship, is that indirect effects are at least as important as direct ones during the simulations. We suggest that our approach and this simulation framework could serve systems-based conservation efforts. Quantitative indicators on the relative importance of trophic groups and the mechanistic modeling of eco-dynamics
Analyzing complex networks evolution through Information Theory quantifiers

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

PubMed

Suryakumar, Rajaraman; Meyers, Jason P; Irving, Elizabeth L; Bobier, William R

2007-02-01

Retinal blur and disparity are two different sensory signals known to cause a change in accommodative response. These inputs have differing neurological correlates that feed into a final common pathway. The purpose of this study was to investigate the dynamic properties of monocular blur driven accommodation and binocular disparity driven vergence-accommodation (VA) in human subjects. The results show that when response amplitudes are matched, blur accommodation and VA share similar dynamic properties.
Market dynamics immediately before and after financial shocks: Quantifying the Omori, productivity, and Bath laws

NASA Astrophysics Data System (ADS)

Petersen, Alexander M.; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene

2010-09-01

We study the cascading dynamics immediately before and immediately after 219 market shocks. We define the time of a market shock Tc to be the time for which the market volatility V(Tc) has a peak that exceeds a predetermined threshold. The cascade of high volatility “aftershocks” triggered by the “main shock” is quantitatively similar to earthquakes and solar flares, which have been described by three empirical laws—the Omori law, the productivity law, and the Bath law. We analyze the most traded 531 stocks in U.S. markets during the 2 yr period of 2001-2002 at the 1 min time resolution. We find quantitative relations between the main shock magnitude M≡log10V(Tc) and the parameters quantifying the decay of volatility aftershocks as well as the volatility preshocks. We also find that stocks with larger trading activity react more strongly and more quickly to market shocks than stocks with smaller trading activity. Our findings characterize the typical volatility response conditional on M , both at the market and the individual stock scale. We argue that there is potential utility in these three statistical quantitative relations with applications in option pricing and volatility trading.
A machine learning approach to quantifying geologic similarities between sites of gas hydrate accumulation

NASA Astrophysics Data System (ADS)

Runyan, T. E.; Wood, W. T.; Palmsten, M. L.; Zhang, R.

2016-12-01

Gas hydrates, specifically methane hydrates, are sparsely sampled on a global scale, and their accumulation is difficult to predict geospatially. Several attempts have been made at estimating global inventories, and to some extent geospatial distribution, using geospatial extrapoltions guided with geophysical and geochemical methods. Our objective is to quantitatively predict the geospatial likelihood of encountering methane hydrates, with uncertainty. Predictions could be incorporated into analyses of drilling hazards as well as climate change. We use global data sets (including water depth, temperature, pressure, TOC, sediment thickness, and heat flow) as parameters to train a k-nearest neighbor (KNN) machine learning technique. The KNN is unsupervised and non-parametric, we do not provide any interpretive influence on prior probability distribution, so our results are strictly data driven. We have selected as test sites several locations where gas hydrates have been well studied, each with significantly different geologic settings.These include: The Blake Ridge (U.S. East Coast), Hydrate Ridge (U.S. West Coast), and the Gulf of Mexico. We then use KNN to quantify similarities between these sites, and determine, via the distance in parameter space, what is the likelihood and uncertainty of encountering gas hydrate anywhere in the world. Here we are operating under the assumption that the distance in parameter space is proportional to the probability of the occurrence of gas hydrate. We then compare these global similarity maps made from our several test sites to identify the geologic (geophyisical, bio-geochemical) parameters best suited for predicting gas hydrate occurrence.
A new look at the Dynamic Similarity Hypothesis: the importance of swing phase.

PubMed

Raichlen, David A; Pontzer, Herman; Shapiro, Liza J

2013-01-01

The Dynamic Similarity Hypothesis (DSH) suggests that when animals of different size walk at similar Froude numbers (equal ratios of inertial and gravitational forces) they will use similar size-corrected gaits. This application of similarity theory to animal biomechanics has contributed to fundamental insights in the mechanics and evolution of a diverse set of locomotor systems. However, despite its popularity, many mammals fail to walk with dynamically similar stride lengths, a key element of gait that determines spontaneous speed and energy costs. Here, we show that the applicability of the DSH is dependent on the inertial forces examined. In general, the inertial forces are thought to be the centripetal force of the inverted pendulum model of stance phase, determined by the length of the limb. If instead we model inertial forces as the centripetal force of the limb acting as a suspended pendulum during swing phase (determined by limb center of mass position), the DSH for stride length variation is fully supported. Thus, the DSH shows that inter-specific differences in spatial kinematics are tied to the evolution of limb mass distribution patterns. Selection may act on morphology to produce a given stride length, or alternatively, stride length may be a "spandrel" of selection acting on limb mass distribution.
The self-similarly expanding Eshelby ellipsoidal inclusion: II. The Dynamic Eshelby Tensor for the expanding sphere

NASA Astrophysics Data System (ADS)

Ni, Luqun; Markenscoff, Xanthippi

2016-11-01

The field solution of a self-similarly (subsonically) expanding Eshelby ellipsoidal inclusion obtained in Part I is evaluated for the case of the expanding spherical inclusion under general uniform eigenstrain ɛij* in self-similar motion R = υt, starting from zero dimension. The particle velocity in the interior domain vanishes and the displacement gradient is constant exhibiting the Eshelby property in the self-similar dynamic case. All components of the interior and exterior Dynamic Eshelby Tensor are obtained for the sphere, with the interior ones depending on the wave speeds and the expansion speed of the inclusion, while the exterior ones depend, in addition, on the variable of self-similarity r / t and the direction of the field point. By a limiting procedure the static Eshelby tensor both interior and exterior is retrieved, thus making the static inclusion a special limit of the dynamic self-similarly expanding one. The jump of the particle velocity across the moving inclusion boundary is obtained, and it depends only on the wave and expansion speeds and the direction of the normal.
Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate.

PubMed

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

2018-10-15

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

PubMed

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

2015-08-15

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

PubMed Central

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

2015-01-01

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

PubMed

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

2017-09-01

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

PubMed

Minati, Ludovico; Winkel, Julia; Bifone, Angelo; Oświęcimka, Paweł; Jovicich, Jorge

2017-04-01

Self-similarity across length scales is pervasively observed in natural systems. Here, we investigate topological self-similarity in complex networks representing diverse forms of connectivity in the brain and some related dynamical systems, by considering the correlation between edges directly connecting any two nodes in a network and indirect connection between the same via all triangles spanning the rest of the network. We note that this aspect of self-similarity, which is distinct from hierarchically nested connectivity (coarse-grain similarity), is closely related to idempotence of the matrix representing the graph. We introduce two measures, ι(1) and ι(∞), which represent the element-wise correlation coefficients between the initial matrix and the ones obtained after squaring it once or infinitely many times, and term the matrices which yield large values of these parameters "quasi-idempotent". These measures delineate qualitatively different forms of "shallow" and "deep" quasi-idempotence, which are influenced by nodal strength heterogeneity. A high degree of quasi-idempotence was observed for partially synchronized mean-field Kuramoto oscillators with noise, electronic chaotic oscillators, and cultures of dissociated neurons, wherein the expression of quasi-idempotence correlated strongly with network maturity. Quasi-idempotence was also detected for macro-scale brain networks representing axonal connectivity, synchronization of slow activity fluctuations during idleness, and co-activation across experimental tasks, and preliminary data indicated that quasi-idempotence of structural connectivity may decrease with ageing. This initial study highlights that the form of network self-similarity indexed by quasi-idempotence is detectable in diverse dynamical systems, and draws attention to it as a possible basis for measures representing network "collectivity" and pattern formation.
Self-similarity and quasi-idempotence in neural networks and related dynamical systems

NASA Astrophysics Data System (ADS)

Minati, Ludovico; Winkel, Julia; Bifone, Angelo; Oświecimka, Paweł; Jovicich, Jorge

2017-04-01

Self-similarity across length scales is pervasively observed in natural systems. Here, we investigate topological self-similarity in complex networks representing diverse forms of connectivity in the brain and some related dynamical systems, by considering the correlation between edges directly connecting any two nodes in a network and indirect connection between the same via all triangles spanning the rest of the network. We note that this aspect of self-similarity, which is distinct from hierarchically nested connectivity (coarse-grain similarity), is closely related to idempotence of the matrix representing the graph. We introduce two measures, ι ( 1 ) and ι ( ∞ ) , which represent the element-wise correlation coefficients between the initial matrix and the ones obtained after squaring it once or infinitely many times, and term the matrices which yield large values of these parameters "quasi-idempotent". These measures delineate qualitatively different forms of "shallow" and "deep" quasi-idempotence, which are influenced by nodal strength heterogeneity. A high degree of quasi-idempotence was observed for partially synchronized mean-field Kuramoto oscillators with noise, electronic chaotic oscillators, and cultures of dissociated neurons, wherein the expression of quasi-idempotence correlated strongly with network maturity. Quasi-idempotence was also detected for macro-scale brain networks representing axonal connectivity, synchronization of slow activity fluctuations during idleness, and co-activation across experimental tasks, and preliminary data indicated that quasi-idempotence of structural connectivity may decrease with ageing. This initial study highlights that the form of network self-similarity indexed by quasi-idempotence is detectable in diverse dynamical systems, and draws attention to it as a possible basis for measures representing network "collectivity" and pattern formation.
A family of interaction-adjusted indices of community similarity.

PubMed

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

2017-03-01

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

A family of interaction-adjusted indices of community similarity

PubMed Central

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

2017-01-01

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

PubMed

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

2018-05-30

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

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

NASA Astrophysics Data System (ADS)

Ochiai, T.; Nacher, J. C.; Akutsu, T.

2007-08-01

Many theoretical models have recently been proposed to understand the structure of cellular systems composed of various types of elements (e.g., proteins, metabolites and genes) and their interactions. However, the cell is a highly dynamic system with thousands of functional elements fluctuating across temporal states. Therefore, structural analysis alone is not sufficient to reproduce the cell's observed behavior. In this article, we analyze the gene expression dynamics (i.e., how the amount of mRNA molecules in cell fluctuate in time) by using a new constructive approach, which reveals a symmetry embedded in gene expression fluctuations and characterizes the dynamical equation of gene expression (i.e., a specific stochastic differential equation). First, by using experimental data of human and yeast gene expression time series, we found a symmetry in short-time transition probability from time t to time t+1. We call it self-similarity symmetry (i.e., the gene expression short-time fluctuations contain a repeating pattern of smaller and smaller parts that are like the whole, but different in size). Secondly, we reconstruct the global behavior of the observed distribution of gene expression (i.e., scaling-law) and the local behavior of the power-law tail of this distribution. This approach may represent a step forward toward an integrated image of the basic elements of the whole cell.
Self-similar dynamic converging shocks - I. An isothermal gas sphere with self-gravity

NASA Astrophysics Data System (ADS)

Lou, Yu-Qing; Shi, Chun-Hui

2014-07-01

We explore novel self-similar dynamic evolution of converging spherical shocks in a self-gravitating isothermal gas under conceivable astrophysical situations. The construction of such converging shocks involves a time-reversal operation on feasible flow profiles in self-similar expansion with a proper care for the increasing direction of the specific entropy. Pioneered by Guderley since 1942 but without self-gravity so far, self-similar converging shocks are important for implosion processes in aerodynamics, combustion, and inertial fusion. Self-gravity necessarily plays a key role for grossly spherical structures in very broad contexts of astrophysics and cosmology, such as planets, stars, molecular clouds (cores), compact objects, planetary nebulae, supernovae, gamma-ray bursts, supernova remnants, globular clusters, galactic bulges, elliptical galaxies, clusters of galaxies as well as relatively hollow cavity or bubble structures on diverse spatial and temporal scales. Large-scale dynamic flows associated with such quasi-spherical systems (including collapses, accretions, fall-backs, winds and outflows, explosions, etc.) in their initiation, formation, and evolution are likely encounter converging spherical shocks at times. Our formalism lays an important theoretical basis for pertinent astrophysical and cosmological applications of various converging shock solutions and for developing and calibrating numerical codes. As examples, we describe converging shock triggered star formation, supernova explosions, and void collapses.
Self-similarity in the inertial region of wall turbulence.

PubMed

Klewicki, J; Philip, J; Marusic, I; Chauhan, K; Morrill-Winter, C

2014-12-01

The inverse of the von Kármán constant κ is the leading coefficient in the equation describing the logarithmic mean velocity profile in wall bounded turbulent flows. Klewicki [J. Fluid Mech. 718, 596 (2013)] connects the asymptotic value of κ with an emerging condition of dynamic self-similarity on an interior inertial domain that contains a geometrically self-similar hierarchy of scaling layers. A number of properties associated with the asymptotic value of κ are revealed. This is accomplished using a framework that retains connection to invariance properties admitted by the mean statement of dynamics. The development leads toward, but terminates short of, analytically determining a value for κ. It is shown that if adjacent layers on the hierarchy (or their adjacent positions) adhere to the same self-similarity that is analytically shown to exist between any given layer and its position, then κ≡Φ(-2)=0.381966..., where Φ=(1+√5)/2 is the golden ratio. A number of measures, derived specifically from an analysis of the mean momentum equation, are subsequently used to empirically explore the veracity and implications of κ=Φ(-2). Consistent with the differential transformations underlying an invariant form admitted by the governing mean equation, it is demonstrated that the value of κ arises from two geometric features associated with the inertial turbulent motions responsible for momentum transport. One nominally pertains to the shape of the relevant motions as quantified by their area coverage in any given wall-parallel plane, and the other pertains to the changing size of these motions in the wall-normal direction. In accord with self-similar mean dynamics, these two features remain invariant across the inertial domain. Data from direct numerical simulations and higher Reynolds number experiments are presented and discussed relative to the self-similar geometric structure indicated by the analysis, and in particular the special form of self-similarity
Groundwater similarity across a watershed derived from time-warped and flow-corrected time series

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, H. J.

2017-05-01

Information about catchment-scale groundwater dynamics is necessary to understand how catchments store and release water and why water quantity and quality varies in streams. However, groundwater level monitoring is often restricted to a limited number of sites. Knowledge of the factors that determine similarity between monitoring sites can be used to predict catchment-scale groundwater storage and connectivity of different runoff source areas. We used distance-based and correlation-based similarity measures to quantify the spatial and temporal differences in shallow groundwater similarity for 51 monitoring sites in a Swiss prealpine catchment. The 41 months long time series were preprocessed using Dynamic Time-Warping and a Flow-corrected Time Transformation to account for small timing differences and bias toward low-flow periods. The mean distance-based groundwater similarity was correlated to topographic indices, such as upslope contributing area, topographic wetness index, and local slope. Correlation-based similarity was less related to landscape position but instead revealed differences between seasons. Analysis of variance and partial Mantel tests showed that landscape position, represented by the topographic wetness index, explained 52% of the variability in mean distance-based groundwater similarity, while spatial distance, represented by the Euclidean distance, explained only 5%. The variability in distance-based similarity and correlation-based similarity between groundwater and streamflow time series was significantly larger for midslope locations than for other landscape positions. This suggests that groundwater dynamics at these midslope sites, which are important to understand runoff source areas and hydrological connectivity at the catchment scale, are most difficult to predict.
An immunological approach to quantifying the saprotrophic growth dynamics of Trichoderma species during antagonistic interactions with Rhizoctonia solani in a soil-less mix.

PubMed

Thornton, Christopher R

2004-04-01

Studies of the saprotrophic growth dynamics of Trichoderma species and their fungal hosts during antagonistic interactions are severely hampered by the absence of methods that allow the unambiguous identification and quantification of individual genera in complex environments such as soil or compost containing mixed populations of fungi. Furthermore, methods are required that allow discrimination between active hyphal growth and other components of fungal biomass such as quiescent spores that are produced in large numbers by Trichoderma species. This study details the use of monoclonal antibodies to quantify the saprotrophic growth dynamics of the soil-borne plant pathogen Rhizoctonia solani and biological control strains of Trichoderma asperellum and Trichoderma harzianum during antagonistic interactions in peat-based microcosms. Quantification was based on the immunological detection of constitutive, extracellular antigens that are secreted from the growing tip of Rhizoctonia and Trichoderma mycelium and, in the case of Trichoderma harzianum, from quiescent phialoconidia also. The Trichoderma-specific monoclonal antibody (MF2) binds to a protein epitope of the enzyme glucoamylase, which was shown by immunofluorescence and immunogold electron gold microscopy studies of Trichoderma virens in vitro to be produced at the origin of germ tube emergence in phialoconidia and from the growing tip of germ tubes. In addition, a non-destructive immunoblotting technique showed that the enzyme was secreted during active growth of Trichoderma asperellum mycelium in peat. The Rhizoctonia solani-specific monoclonal antibody (EH2) similarly binds to a protein epitope of a glycoprotein that is secreted during active mycelial growth. Extracts derived from lyophilized mycelium were used as a quantifiable and repeatable source of antigens for construction of calibration curves. These curves were used to convert the absorbance values obtained in ELISA tests of peat extracts to biomass
Vertical-axis wind turbine experiments at full dynamic similarity

NASA Astrophysics Data System (ADS)

Duvvuri, Subrahmanyam; Miller, Mark; Brownstein, Ian; Dabiri, John; Hultmark, Marcus

2017-11-01

This study presents results from pressurized (upto 200 atm) wind tunnel tests of a self-spinning 5-blade model Vertical-Axis Wind Turbine (VAWT). The model is geometrically similar (scale ratio 1:22) to a commercially available VAWT, which has a rotor diameter of 2.17 meters and blade span of 3.66 meters, and is used at the Stanford university field lab. The use of pressurized air as working fluid allows for the unique ability to obtain full dynamic similarity with field conditions in terms of matched Reynolds numbers (Re), tip-speed ratios (λ), and Mach number (M). Tests were performed across a wide range of Re and λ, with the highest Re exceeding the maximum operational field Reynolds number (Remax) by a factor of 3. With an extended range of accessible Re conditions, the peak turbine power efficiency was seen to occur roughly at Re = 2 Remax and λ = 1 . Beyond Re > 2 Remax the turbine performance is invariant in Re for all λ. A clear demonstration of Reynolds number invariance for an actual full-scale wind turbine lends novelty to this study, and overall the results show the viability of the present experimental technique in testing turbines at field conditions.
Tumorigenesis and Greenhouse-Effect System Dynamics: Phenomenally Diverse, but Noumenally Similar?

NASA Astrophysics Data System (ADS)

Prakash, Sai

We present a physicochemical model of tumorigenesis leading to cancer invasion and metastasis. The continuum-theoretic model, congruent with recent experiments, analyzes the plausibility of oncogenic neoplasia-induced cavitation or tensile yielding (plasticity) of the tumoral basement membrane (BM) to activate stromal invasion. The model abstracts a spheroid of normal and cancer cells that grows radially via water and nutrient influx while constrained by a stiffer BM and cell adhesion molecules. It is based on coupled fluid-solid mechanics and ATP-fueled mechano-damped cell kinetics, and uses empirical data alone as parameters. The model predicts the dynamic force and exergy (ATP) fields, and tumor size among other variables, and generates the sigmoidal dynamics of far-from-equilibrium biota. Simulations show that the tumor-membrane system, on neoplastic perturbation, evolves from one homeostatic steady state to another over time. Integrated with system dynamics theory, the model renders a key, emergent tissue-level feedback control perspective of malignancy: neoplastic tumors coupled with pathologically-softened BMs appear to participate in altered autoregulatory behavior, and likely undergo BM cavitation and stress-localized ruptures to their adhesome, with or without invadopoiesis, thereby, initiating invasion. Serendipitously, the results also reveal a noumenal similarity of the tumor-membrane to the earth-atmosphere open reactive system as concerns self-regulation.
Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

PubMed

Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

2015-03-01

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.
Which similarity measure is better for analyzing protein structures in a molecular dynamics trajectory?

PubMed

Cossio, Pilar; Laio, Alessandro; Pietrucci, Fabio

2011-06-14

An important step in the computer simulation of the dynamics of biomolecules is the comparison of structures in a trajectory by exploiting a measure of distance. This allows distinguishing structures which are geometrically similar from those which are different. By analyzing microseconds-long all-atom molecular dynamics simulations of a polypeptide, we find that a distance based on backbone dihedral angles performs very well in distinguishing structures that are kinetically correlated from those that are not, while the widely used C(α) root mean square distance performs more poorly. The root mean square difference between contact matrices turns out instead to be the metric providing the highest clustering coefficient, namely, according to this similarity measure, the neighbors of a structure are also, on average, neighbors among themselves. We also propose a combined distance measure which, for the system considered here, performs well both for distinguishing structures which are distant in time and for giving a consistent cluster analysis. This journal is © the Owner Societies 2011
Numerosity underestimation with item similarity in dynamic visual display.

PubMed

Au, Ricky K C; Watanabe, Katsumi

2013-01-01

The estimation of numerosity of a large number of objects in a static visual display is possible even at short durations. Such coarse approximations of numerosity are distinct from subitizing, in which the number of objects can be reported with high precision when a small number of objects are presented simultaneously. The present study examined numerosity estimation of visual objects in dynamic displays and the effect of object similarity on numerosity estimation. In the basic paradigm (Experiment 1), two streams of dots were presented and observers were asked to indicate which of the two streams contained more dots. Streams consisting of dots that were identical in color were judged as containing fewer dots than streams where the dots were different colors. This underestimation effect for identical visual items disappeared when the presentation rate was slower (Experiment 1) or the visual display was static (Experiment 2). In Experiments 3 and 4, in addition to the numerosity judgment task, observers performed an attention-demanding task at fixation. Task difficulty influenced observers' precision in the numerosity judgment task, but the underestimation effect remained evident irrespective of task difficulty. These results suggest that identical or similar visual objects presented in succession might induce substitution among themselves, leading to an illusion that there are few items overall and that exploiting attentional resources does not eliminate the underestimation effect.
Using text analysis to quantify the similarity and evolution of scientific disciplines

PubMed Central

Dias, Laércio; Scharloth, Joachim

2018-01-01

We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g. computer science) are becoming increasingly central, but that on average the similarity between pairs of disciplines has not changed in the last decades. This suggests that tendencies of convergence (e.g. multi-disciplinarity) and divergence (e.g. specialization) of disciplines are in balance. PMID:29410857
Using text analysis to quantify the similarity and evolution of scientific disciplines.

PubMed

Dias, Laércio; Gerlach, Martin; Scharloth, Joachim; Altmann, Eduardo G

2018-01-01

We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g. computer science) are becoming increasingly central, but that on average the similarity between pairs of disciplines has not changed in the last decades. This suggests that tendencies of convergence (e.g. multi-disciplinarity) and divergence (e.g. specialization) of disciplines are in balance.
The effects of gravity on human walking: a new test of the dynamic similarity hypothesis using a predictive model.

PubMed

Raichlen, David A

2008-09-01

The dynamic similarity hypothesis (DSH) suggests that differences in animal locomotor biomechanics are due mostly to differences in size. According to the DSH, when the ratios of inertial to gravitational forces are equal between two animals that differ in size [e.g. at equal Froude numbers, where Froude = velocity2/(gravity x hip height)], their movements can be made similar by multiplying all time durations by one constant, all forces by a second constant and all linear distances by a third constant. The DSH has been generally supported by numerous comparative studies showing that as inertial forces differ (i.e. differences in the centripetal force acting on the animal due to variation in hip heights), animals walk with dynamic similarity. However, humans walking in simulated reduced gravity do not walk with dynamically similar kinematics. The simulated gravity experiments did not completely account for the effects of gravity on all body segments, and the importance of gravity in the DSH requires further examination. This study uses a kinematic model to predict the effects of gravity on human locomotion, taking into account both the effects of gravitational forces on the upper body and on the limbs. Results show that dynamic similarity is maintained in altered gravitational environments. Thus, the DSH does account for differences in the inertial forces governing locomotion (e.g. differences in hip height) as well as differences in the gravitational forces governing locomotion.
Cholera and shigellosis in Bangladesh: similarities and differences in population dynamics under climate forcing

NASA Astrophysics Data System (ADS)

Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.

2012-12-01

The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.

Marking Student Programs Using Graph Similarity

ERIC Educational Resources Information Center

Naude, Kevin A.; Greyling, Jean H.; Vogts, Dieter

2010-01-01

We present a novel approach to the automated marking of student programming assignments. Our technique quantifies the structural similarity between unmarked student submissions and marked solutions, and is the basis by which we assign marks. This is accomplished through an efficient novel graph similarity measure ("AssignSim"). Our experiments…
POSTFUNDOPLICATION DYSPHAGIA CAUSES SIMILAR WATER INGESTION DYNAMICS AS ACHALASIA.

PubMed

Dantas, Roberto Oliveira; Santos, Carla Manfredi; Cassiani, Rachel Aguiar; Alves, Leda Maria Tavares; Nascimento, Weslania Viviane

2016-01-01

- After surgical treatment of gastroesophageal reflux disease dysphagia is a symptom in the majority of patients, with decrease in intensity over time. However, some patients may have persistent dysphagia. - The objective of this investigation was to evaluate the dynamics of water ingestion in patients with postfundoplication dysphagia compared with patients with dysphagia caused by achalasia, idiopathic or consequent to Chagas' disease, and controls. - Thirty-three patients with postfundoplication dysphagia, assessed more than one year after surgery, together with 50 patients with Chagas' disease, 27 patients with idiopathic achalasia and 88 controls were all evaluated by the water swallow test. They drunk, in triplicate, 50 mL of water without breaks while being precisely timed and the number of swallows counted. Also measured was: (a) inter-swallows interval - the time to complete the task, divided by the number of swallows during the task; (b) swallowing flow - volume drunk divided by the time taken; (c) volume of each swallow - volume drunk divided by the number of swallows. - Patients with postfundoplication dysphagia, Chagas' disease and idiopathic achalasia took longer to ingest all the volume, had an increased number of swallows, an increase in interval between swallows, a decrease in swallowing flow and a decrease in water volume of each swallow compared with the controls. There was no difference between the three groups of patients. There was no correlation between postfundoplication time and the results. - It was concluded that patients with postfundoplication dysphagia have similar water ingestion dynamics as patients with achalasia.
Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

PubMed

Marasco, Daniel E; Hunter, Betsy N; Culligan, Patricia J; Gaffin, Stuart R; McGillis, Wade R

2014-09-02

Quantifying green roof evapotranspiration (ET) in urban climates is important for assessing environmental benefits, including stormwater runoff attenuation and urban heat island mitigation. In this study, a dynamic chamber method was developed to quantify ET on two extensive green roofs located in New York City, NY. Hourly chamber measurements taken from July 2009 to December 2009 and April 2012 to October 2013 illustrate both diurnal and seasonal variations in ET. Observed monthly total ET depth ranged from 0.22 cm in winter to 15.36 cm in summer. Chamber results were compared to two predictive methods for estimating ET; namely the Penman-based ASCE Standardized Reference Evapotranspiration (ASCE RET) equation, and an energy balance model, both parametrized using on-site environmental conditions. Dynamic chamber ET results were similar to ASCE RET estimates; however, the ASCE RET equation overestimated bottommost ET values during the winter months, and underestimated peak ET values during the summer months. The energy balance method was shown to underestimate ET compared the ASCE RET equation. The work highlights the utility of the chamber method for quantifying green roof evapotranspiration and indicates green roof ET might be better estimated by Penman-based evapotranspiration equations than energy balance methods.
Fluctuation of similarity to detect transitions between distinct dynamical regimes in short time series

NASA Astrophysics Data System (ADS)

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2014-06-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [N. Malik et al., Europhys. Lett. 97, 40009 (2012), 10.1209/0295-5075/97/40009], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In this work, we describe the details of the analytical relationships between this newly introduced measure and the well-known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method's robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the US crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980s and early 1990s, leading to increase in the dynamical complexity of these rates.
Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

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

PubMed Central

Sullivan, Nora L.; Tzeranis, Dimitrios S.; Wang, Yun; So, Peter T.C.; Newman, Dianne

2011-01-01

Phenazines, a group of fluorescent small molecules produced by the bacterium Pseudomonas aeruginosa, play a role in maintaining cellular redox homeostasis. Phenazines have been challenging to study in vivo due to their redox activity, presence both intra- and extracellularly, and their diverse chemical properties. Here, we describe a non-invasive in vivo optical technique to monitor phenazine concentrations within bacterial cells using time-lapsed spectral multi-photon fluorescence microscopy. This technique enables simultaneous monitoring of multiple weakly-fluorescent molecules (phenazines, siderophores, NAD(P)H) expressed by bacteria in culture. This work provides the first in vivo measurements of reduced phenazine concentration as well as the first description of the temporal dynamics of the phenazine-NAD(P)H redox system in Pseudomonas aeruginosa, illuminating an unanticipated role for 1-hydroxyphenazine. Similar approaches could be used to study the abundance and redox dynamics of a wide range of small molecules within bacteria, both as single cells and in communities. PMID:21671613
Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations

USGS Publications Warehouse

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

2018-01-01

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

Hyporheic exchange is an important mechanism taking place in riverbanks and riverbed sediments, where the river water and shallow groundwater mix and interact with each other. The direction and magnitude of hyporheic flux that penetrates the river bed and residence time of river water in the hyporheic zone are critical for biogeochemical processes such as carbon and nitrogen cycling, and biodegradation of organic contaminants. Hyporheic flux can be quantified using many direct and indirect measurements as well as analytical and numerical modeling tools. However, in a relatively large river, these methods can be limited by the accessibility, spatial constraints, complexity of geomorphologic features and subsurface properties, and computational power. In rivers regulated by hydroelectric dams, quantifying hyporheic fluxes becomes more challenging due to frequent hydropeaking events created by dam operations. In this study, we developed and validated methods that combined field measurements and numerical modeling for estimating hyporheic fluxes across the river bed in a 7-km long reach of the highly regulated Columbia River. The reach has a minimum width of about 800 meters and variations in river stage within a day could be up to two meters due to the upstream dam operations. In shallow water along the shoreline, vertical thermal profiles measured by self-recording thermistors were combined with time series of hydraulic gradient derived from river stage and water level at in-land wells to estimate the hyporheic flux rate. For the deep section, a high resolution computational fluid dynamics (CFD) modeling framework was developed to characterize the spatial distribution of flux rates at the river bed and the residence time of hyporheic flow at different river flow conditions. Our modeling results show that the rates of hyporheic exchange and residence time are controlled by (1) hydrostatic pressure induced by river stage fluctuations, and (2) hydrodynamic drivers
Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

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

2010-01-01

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

NASA Astrophysics Data System (ADS)

Tao, Laifa; Lu, Chen; Noktehdan, Azadeh

2015-10-01

Battery capacity estimation is a significant recent challenge given the complex physical and chemical processes that occur within batteries and the restrictions on the accessibility of capacity degradation data. In this study, we describe an approach called dynamic spatial time warping, which is used to determine the similarities of two arbitrary curves. Unlike classical dynamic time warping methods, this approach can maintain the invariance of curve similarity to the rotations and translations of curves, which is vital in curve similarity search. Moreover, it utilizes the online charging or discharging data that are easily collected and do not require special assumptions. The accuracy of this approach is verified using NASA battery datasets. Results suggest that the proposed approach provides a highly accurate means of estimating battery capacity at less time cost than traditional dynamic time warping methods do for different individuals and under various operating conditions.
Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo

PubMed Central

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

2013-01-01

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

We study daily surface air temperature (SAT) reanalysis in a grid over the Earth's surface to identify and quantify changes in SAT dynamics during the period 1979-2016. By analysing the Hilbert amplitude and frequency we identify the regions where relative variations are most pronounced (larger than ±50 % for the amplitude and ±100 % for the frequency). Amplitude variations are interpreted as due to changes in precipitation or ice melting, while frequency variations are interpreted as due to a northward shift of the inter-tropical convergence zone (ITCZ) and to a widening of the rainfall band in the western Pacific Ocean. The ITCZ is the ascending branch of the Hadley cell, and thus by affecting the tropical atmospheric circulation, ITCZ migration has far-reaching climatic consequences. As the methodology proposed here can be applied to many other geophysical time series, our work will stimulate new research that will advance the understanding of climate change impacts.
Nuclear markers reveal that inter-lake cichlids' similar morphologies do not reflect similar genealogy.

PubMed

Kassam, Daud; Seki, Shingo; Horic, Michio; Yamaoka, Kosaku

2006-08-01

The apparent inter-lake morphological similarity among East African Great Lakes' cichlid species/genera has left evolutionary biologists asking whether such similarity is due to sharing of common ancestor or mere convergent evolution. In order to answer such question, we first used Geometric Morphometrics, GM, to quantify morphological similarity and then subsequently used Amplified Fragment Length Polymorphism, AFLP, to determine if similar morphologies imply shared ancestry or convergent evolution. GM revealed that not all presumed morphological similar pairs were indeed similar, and the dendrogram generated from AFLP data indicated distinct clusters corresponding to each lake and not inter-lake morphological similar pairs. Such results imply that the morphological similarity is due to convergent evolution and not shared ancestry. The congruency of GM and AFLP generated dendrograms imply that GM is capable of picking up phylogenetic signal, and thus GM can be potential tool in phylogenetic systematics.
Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

DOE PAGES

Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

2015-04-01

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

PubMed

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

2015-05-21

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

PubMed Central

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Harries, Rebekah; Kirstein, Linda; Whittaker, Alex; Attal, Mikael; Peralta, Silvio

2017-04-01

considering factors such as climate storminess and degree of glacial cover in having a dominant control on the variance of sediment released. These findings have significant implications for our ability to invert the fluvial stratigraphy for climatically driven changes in discharge and highlight a need to quantify the impact of sediment dynamics on modern systems so that we may better understand the limitations in applying quantitative models to ancient stratigraphy.
Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

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

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to
Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to

Generalized sample entropy analysis for traffic signals based on similarity measure

NASA Astrophysics Data System (ADS)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.
Fluctuation of similarity (FLUS) to detect transitions between distinct dynamical regimes in short time series

PubMed Central

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2016-01-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [1], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In the present work, we describe the details of the analytical relationships between this newly introduced measure and the well known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method’s robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the U.S. crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980’s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980’s and early 1990’s, leading to increase in the dynamical complexity of these rates. PMID:25019852
Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

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

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.
Quantifying forest LAI succession in sub-tropical forests using time-series of Landsat data, 1987 -2015

NASA Astrophysics Data System (ADS)

Wu, Q.; Song, J.; Wang, J.; Chen, S.; Yu, B.; Liao, L.

2016-12-01

Monitoring the dynamics of leaf area index (LAI) throughout the life-cycle of forests (from seeding to maturity) is vital for simulating forest growth and quantifying carbon sequestration. However, all current global LAI produts show extremely low accuracy in forests and the coarse spatial resolution(nearly 1-km) mismatch with the spatial scale of forest inventory plots (nearly 26m*26m). To date, several studies have explored the possibility of satellite data to classify forest succession or predict stand age. And a few studies have explored the potential of using long term Landsat data to monitor the growing trend of forests, but no studies have quantified the inter-annual and intra-annual LAI dynamics along with forest succession. Vegetation indexes are not perfect variables in quantifying forest foliage dynamics. Hallet (1995) suggested remote sensing of biophysical characteristics should shift away from direct inference from vegetation indices toward more physically based algorithms. This work intends to be a pioneer example for improving the accuracy of forests LAI and providing temporal-spatial matching LAI datasets for monitoring forest processes. We integrates the Geometric-Optical and Radiative Transfer (GORT) model with the Physiological Principles Predicting Growth (3-PG) model to improve the estimation of the forest canopy LAI dynamics. Reflectance time-series data from 1987 to 2015 were collected and preprocessed for forests in southern China, using all available Landsat data (with <80% cloud). Effective LAI and true LAI were field measured to validate our results using various instruments, including digital hemispheric photographs (DHP), LAI-2000 Plant Canopy Analyzer (LI-COR), and Tracing radiation and Architecture of Canopies (TRAC). Results show that the relationship between spectral metrics of satellite images and forest LAI is clear in early stages before maturity. 3-PG provide accurate inter-annual trend of forest LAI, while satellite images
Quantifying suspended sediment dynamics in mega deltas using remote sensing data: A case study of the Mekong floodplains

NASA Astrophysics Data System (ADS)

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

2018-06-01

Temporal and spatial concentrations of suspended sediment in floodplains are difficult to quantify because in situ measurements can be logistically complex, time consuming and costly. In this research, satellite imagery with long temporal and large spatial coverage (Landsat TM/ETM+) was used to complement in situ suspended sediment measurements to reflect sediment dynamics in a large (70,000 km2) floodplain. Instead of using a single spectral band from Landsat, a Principal Component Analysis was applied to obtain uncorrelated reflectance values for five bands of Landsat TM/ETM+. Significant correlations between the scores of the 1st principal component and the values of continuously gauged suspended sediment concentration, shown via high coefficients of determination of sediment rating curves (R2 ranging from 0.66 to 0.92), permit the application of satellite images to quantify spatial and temporal sediment variation in the Mekong floodplains. Estimated suspended sediment maps show that hydraulic regimes at Chaktomuk (Cambodia), where the Mekong, Bassac, and Tonle Sap rivers diverge, determine the amount of seasonal sediment supplies to the Mekong Delta. The development of flood prevention systems to allow for three rice crops a year in the Vietnam Mekong Delta significantly reduces localized flooding, but also prevents sediment (source of nutrients) from entering fields. A direct consequence of this is the need to apply more artificial fertilizers to boost agricultural productivity, which may trigger environmental problems. Overall, remote sensing is shown to be an effective tool to understand temporal and spatial sediment dynamics in large floodplains.
Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging.

PubMed

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

2014-09-01

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

NASA Astrophysics Data System (ADS)

Hu, Xiaohu; Hong, Liang; Dean Smith, Micholas; Neusius, Thomas; Cheng, Xiaolin; Smith, Jeremy C.

2016-02-01

Internal motions of proteins are essential to their function. The time dependence of protein structural fluctuations is highly complex, manifesting subdiffusive, non-exponential behaviour with effective relaxation times existing over many decades in time, from ps up to ~102 s (refs ,,,). Here, using molecular dynamics simulations, we show that, on timescales from 10-12 to 10-5 s, motions in single proteins are self-similar, non-equilibrium and exhibit ageing. The characteristic relaxation time for a distance fluctuation, such as inter-domain motion, is observation-time-dependent, increasing in a simple, power-law fashion, arising from the fractal nature of the topology and geometry of the energy landscape explored. Diffusion over the energy landscape follows a non-ergodic continuous time random walk. Comparison with single-molecule experiments suggests that the non-equilibrium self-similar dynamical behaviour persists up to timescales approaching the in vivo lifespan of individual protein molecules.
Integrating user profile in medical CBIR systems to answer perceptual similarity queries

NASA Astrophysics Data System (ADS)

Bugatti, Pedro H.; Kaster, Daniel S.; Ponciano-Silva, Marcelo; Traina, Agma J. M.; Traina, Caetano, Jr.

2011-03-01

Techniques for Content-Based Image Retrieval (CBIR) have been intensively explored due to the increase in the amount of captured images and the need of fast retrieval of them. The medical field is a specific example that generates a large flow of information, especially digital images employed for diagnosing. One issue that still remains unsolved deals with how to reach the perceptual similarity. That is, to achieve an effective retrieval, one must characterize and quantify the perceptual similarity regarding the specialist in the field. Therefore, the present paper was conceived to fill in this gap creating a consistent support to perform similarity queries over medical images, maintaining the semantics of a given query desired by the user. CBIR systems relying in relevance feedback techniques usually request the users to label relevant images. In this paper, we present a simple but highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The user profiles maintain the settings desired for each user, allowing tuning the similarity assessment, which encompasses dynamically changing the distance function employed through an interactive process. Experiments using computed tomography lung images show that the proposed approach is effective in capturing the users' perception.
Practical technique to quantify small, dense low-density lipoprotein cholesterol using dynamic light scattering

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

PubMed

Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph

2014-05-01

The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large.
Quantifying the uncertainty in heritability

PubMed Central

Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph

2014-01-01

The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large. PMID:24670270
Quantifying Proportional Variability

PubMed Central

Heath, Joel P.; Borowski, Peter

2013-01-01

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

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

Sprott, J. C.; Xiong, Anda

2015-08-15

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

DOE PAGES

Hu, Xiaohu; Hong, Liang; Smith, Micholas Dean; ...

2015-11-23

Here, internal motions of proteins are essential to their function. The time dependence of protein structural fluctuations is highly complex, manifesting subdiffusive, non-exponential behavior with effective relaxation times existing over many decades in time, from ps up to ~10 2s (refs 1-4). Here, using molecular dynamics simulations, we show that, on timescales from 10 –12 to 10 –5s, motions in single proteins are self-similar, non-equilibrium and exhibit ageing. The characteristic relaxation time for a distance fluctuation, such as inter-domain motion, is observation-time-dependent, increasing in a simple, power-law fashion, arising from the fractal nature of the topology and geometry of themore » energy landscape explored. Diffusion over the energy landscape follows a non-ergodic continuous time random walk. Comparison with single-molecule experiments suggests that the non-equilibrium self-similar dynamical behavior persists up to timescales approaching the in vivo lifespan of individual protein molecules.« less
Quantifying coordination among the rearfoot, midfoot, and forefoot segments during running.

PubMed

Takabayashi, Tomoya; Edama, Mutsuaki; Yokoyama, Erika; Kanaya, Chiaki; Kubo, Masayoshi

2018-03-01

Because previous studies have suggested that there is a relationship between injury risk and inter-segment coordination, quantifying coordination between the segments is essential. Even though the midfoot and forefoot segments play important roles in dynamic tasks, previous studies have mostly focused on coordination between the shank and rearfoot segments. This study aimed to quantify coordination among rearfoot, midfoot, and forefoot segments during running. Eleven healthy young men ran on a treadmill. The coupling angle, representing inter-segment coordination, was calculated using a modified vector coding technique. The coupling angle was categorised into four coordination patterns. During the absorption phase, rearfoot-midfoot coordination in the frontal planes was mostly in-phase (rearfoot and midfoot eversion with similar amplitudes). The present study found that the eversion of the midfoot with respect to the rearfoot was comparable in magnitude to the eversion of the rearfoot with respect to the shank. A previous study has suggested that disruption of the coordination between the internal rotation of the shank and eversion of the rearfoot leads to running injuries such as anterior knee pain. Thus, these data might be used in the future to compare to individuals with foot deformities or running injuries.
Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging

PubMed Central

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

2014-01-01

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

PubMed Central

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

2015-01-01

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

PubMed

Moretto, P; Bisiaux, M; Lafortune, M A

2007-01-01

The purpose of this study was to determine if using similar walking velocities obtained from fractions of the Froude number (N(Fr)) and leg length can lead to kinematic and kinetic similarities and lower variability. Fifteen male subjects walked on a treadmill at 0.83 (VS(1)) and 1.16ms(-1) (VS(2)) and then at two similar velocities (V(Sim27) and V(Sim37)) determined from two fractions of the N(Fr) (0.27 and 0.37) so that the average group velocity remained unchanged in both conditions (VS(1)=V (Sim27)andVS(2)=V (Sim37)). N(Fr) can theoretically be used to determine walking velocities proportional to leg lengths and to establish dynamic similarities between subjects. This study represents the first attempt at using this approach to examine plantar pressure. The ankle and knee joint angles were studied in the sagittal plane and the plantar pressure distribution was assessed with an in-shoe measurement device. The similarity ratios were computed from anthropometric parameters and plantar pressure peaks. Dynamically similar conditions caused a 25% reduction in leg joint angles variation and a 10% significant decrease in dimensionless pressure peak variability on average of five footprint locations. It also lead to heel and under-midfoot pressure peaks proportional to body mass and to an increase in the number of under-forefoot plantar pressure peaks proportional to body mass and/or leg length. The use of walking velocities derived from N(Fr) allows kinematic and plantar pressure similarities between subjects to be observed and leads to a lower inter-subject variability. In-shoe pressure measurements have proven to be valuable for the understanding of lower extremity function. Set walking velocities used for clinical assessment mask the effects of body size and individual gait mechanics. The anthropometric scaling of walking velocities (fraction of N(Fr)) should improve identification of unique walking strategies and pathological foot functions.
Universal self-similar dynamics of relativistic and nonrelativistic field theories near nonthermal fixed points

NASA Astrophysics Data System (ADS)

Piñeiro Orioli, Asier; Boguslavski, Kirill; Berges, Jürgen

2015-07-01

We investigate universal behavior of isolated many-body systems far from equilibrium, which is relevant for a wide range of applications from ultracold quantum gases to high-energy particle physics. The universality is based on the existence of nonthermal fixed points, which represent nonequilibrium attractor solutions with self-similar scaling behavior. The corresponding dynamic universality classes turn out to be remarkably large, encompassing both relativistic as well as nonrelativistic quantum and classical systems. For the examples of nonrelativistic (Gross-Pitaevskii) and relativistic scalar field theory with quartic self-interactions, we demonstrate that infrared scaling exponents as well as scaling functions agree. We perform two independent nonperturbative calculations, first by using classical-statistical lattice simulation techniques and second by applying a vertex-resummed kinetic theory. The latter extends kinetic descriptions to the nonperturbative regime of overoccupied modes. Our results open new perspectives to learn from experiments with cold atoms aspects about the dynamics during the early stages of our universe.
Effects of Lipid Composition on Bilayer Membranes Quantified by All-Atom Molecular Dynamics.

PubMed

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

2015-12-10

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

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

NASA Astrophysics Data System (ADS)

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

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.
Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes

PubMed Central

Tiwari, Sandhya P.; Reuter, Nathalie

2016-01-01

The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design. PMID:27015412
Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

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

2017-01-01

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

PubMed Central

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

2017-01-01

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

PubMed

Valet, Jean-Pierre; Fournier, Alexandre; Courtillot, Vincent; Herrero-Bervera, Emilio

2012-10-04

No consensus has been reached so far on the properties of the geomagnetic field during reversals or on the main features that might reveal its dynamics. A main characteristic of the reversing field is a large decrease in the axial dipole and the dominant role of non-dipole components. Other features strongly depend on whether they are derived from sedimentary or volcanic records. Only thermal remanent magnetization of lava flows can capture faithful records of a rapidly varying non-dipole field, but, because of episodic volcanic activity, sequences of overlying flows yield incomplete records. Here we show that the ten most detailed volcanic records of reversals can be matched in a very satisfactory way, under the assumption of a common duration, revealing common dynamical characteristics. We infer that the reversal process has remained unchanged, with the same time constants and durations, at least since 180 million years ago. We propose that the reversing field is characterized by three successive phases: a precursory event, a 180° polarity switch and a rebound. The first and third phases reflect the emergence of the non-dipole field with large-amplitude secular variation. They are rarely both recorded at the same site owing to the rapidly changing field geometry and last for less than 2,500 years. The actual transit between the two polarities does not last longer than 1,000 years and might therefore result from mechanisms other than those governing normal secular variation. Such changes are too brief to be accurately recorded by most sediments.
Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

NASA Astrophysics Data System (ADS)

Xu, Qing

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

PubMed

Allen, Jenny A; Murray, Anita; Noad, Michael J; Dunlop, Rebecca A; Garland, Ellen C

2017-10-01

Classification of vocal signals can be undertaken using a wide variety of qualitative and quantitative techniques. Using east Australian humpback whale song from 2002 to 2014, a subset of vocal signals was acoustically measured and then classified using a Self-Organizing Map (SOM). The SOM created (1) an acoustic dictionary of units representing the song's repertoire, and (2) Cartesian distance measurements among all unit types (SOM nodes). Utilizing the SOM dictionary as a guide, additional song recordings from east Australia were rapidly (manually) transcribed. To assess the similarity in song sequences, the Cartesian distance output from the SOM was applied in Levenshtein distance similarity analyses as a weighting factor to better incorporate unit similarity in the calculation (previously a qualitative process). SOMs provide a more robust and repeatable means of categorizing acoustic signals along with a clear quantitative measurement of sound type similarity based on acoustic features. This method can be utilized for a wide variety of acoustic databases especially those containing very large datasets and can be applied across the vocalization research community to help address concerns surrounding inconsistency in manual classification.
Graph-based similarity concepts in virtual screening.

PubMed

Hutter, Michael C

2011-03-01

Applying similarity for finding new promising compounds is a key issue in drug design. Conversely, quantifying similarity between molecules has remained a difficult task despite the numerous approaches. Here, some general aspects along with recent developments regarding similarity criteria are collected. For the purpose of virtual screening, the compounds have to be encoded into a computer-readable format that permits a comparison, according to given similarity criteria, comprising the use of the 3D structure, fingerprints, graph-based and alignment-based approaches. Whereas finding the most common substructures is the most obvious method, more recent approaches take into account chemical modifications that appear throughout existing drugs, from various therapeutic categories and targets.
Similarity of Symbol Frequency Distributions with Heavy Tails

NASA Astrophysics Data System (ADS)

Gerlach, Martin; Font-Clos, Francesc; Altmann, Eduardo G.

2016-04-01

Quantifying the similarity between symbolic sequences is a traditional problem in information theory which requires comparing the frequencies of symbols in different sequences. In numerous modern applications, ranging from DNA over music to texts, the distribution of symbol frequencies is characterized by heavy-tailed distributions (e.g., Zipf's law). The large number of low-frequency symbols in these distributions poses major difficulties to the estimation of the similarity between sequences; e.g., they hinder an accurate finite-size estimation of entropies. Here, we show analytically how the systematic (bias) and statistical (fluctuations) errors in these estimations depend on the sample size N and on the exponent γ of the heavy-tailed distribution. Our results are valid for the Shannon entropy (α =1 ), its corresponding similarity measures (e.g., the Jensen-Shanon divergence), and also for measures based on the generalized entropy of order α . For small α 's, including α =1 , the errors decay slower than the 1 /N decay observed in short-tailed distributions. For α larger than a critical value α*=1 +1 /γ ≤2 , the 1 /N decay is recovered. We show the practical significance of our results by quantifying the evolution of the English language over the last two centuries using a complete α spectrum of measures. We find that frequent words change more slowly than less frequent words and that α =2 provides the most robust measure to quantify language change.
Cross-linguistic patterns in the acquisition of quantifiers.

PubMed

Katsos, Napoleon; Cummins, Chris; Ezeizabarrena, Maria-José; Gavarró, Anna; Kuvač Kraljević, Jelena; Hrzica, Gordana; Grohmann, Kleanthes K; Skordi, Athina; Jensen de López, Kristine; Sundahl, Lone; van Hout, Angeliek; Hollebrandse, Bart; Overweg, Jessica; Faber, Myrthe; van Koert, Margreet; Smith, Nafsika; Vija, Maigi; Zupping, Sirli; Kunnari, Sari; Morisseau, Tiffany; Rusieshvili, Manana; Yatsushiro, Kazuko; Fengler, Anja; Varlokosta, Spyridoula; Konstantzou, Katerina; Farby, Shira; Guasti, Maria Teresa; Vernice, Mirta; Okabe, Reiko; Isobe, Miwa; Crosthwaite, Peter; Hong, Yoonjee; Balčiūnienė, Ingrida; Ahmad Nizar, Yanti Marina; Grech, Helen; Gatt, Daniela; Cheong, Win Nee; Asbjørnsen, Arve; Torkildsen, Janne von Koss; Haman, Ewa; Miękisz, Aneta; Gagarina, Natalia; Puzanova, Julia; Anđelković, Darinka; Savić, Maja; Jošić, Smiljana; Slančová, Daniela; Kapalková, Svetlana; Barberán, Tania; Özge, Duygu; Hassan, Saima; Chan, Cecilia Yuet Hung; Okubo, Tomoya; van der Lely, Heather; Sauerland, Uli; Noveck, Ira

2016-08-16

Learners of most languages are faced with the task of acquiring words to talk about number and quantity. Much is known about the order of acquisition of number words as well as the cognitive and perceptual systems and cultural practices that shape it. Substantially less is known about the acquisition of quantifiers. Here, we consider the extent to which systems and practices that support number word acquisition can be applied to quantifier acquisition and conclude that the two domains are largely distinct in this respect. Consequently, we hypothesize that the acquisition of quantifiers is constrained by a set of factors related to each quantifier's specific meaning. We investigate competence with the expressions for "all," "none," "some," "some…not," and "most" in 31 languages, representing 11 language types, by testing 768 5-y-old children and 536 adults. We found a cross-linguistically similar order of acquisition of quantifiers, explicable in terms of four factors relating to their meaning and use. In addition, exploratory analyses reveal that language- and learner-specific factors, such as negative concord and gender, are significant predictors of variation.
Quantifying vocal fatigue recovery: Dynamic vocal recovery trajectories after a vocal loading exercise

PubMed Central

Hunter, Eric J.; Titze, Ingo R.

2012-01-01

Objectives To quantify the recovery of voice following a 2-hour vocal loading exercise (oral reading). Methods 86 adult participants tracked their voice recovery using short vocal tasks and perceptual ratings after an initial vocal loading exercise and for the following two days. Results Short-term recovery was apparent with 90% recovery within 4-6 hours and full recovery at 12-18 hours. Recovery was shown to be similar to a dermal wound healing trajectory. Conclusions The new recovery trajectory highlighted by the vocal loading exercise in the current study is called a vocal recovery trajectory. By comparing vocal fatigue to dermal wound healing, this trajectory is parallel to a chronic wound healing trajectory (as opposed to an acute wound healing trajectory). This parallel suggests that vocal fatigue from the daily use of the voice could be treated as a chronic wound, with the healing and repair mechanisms in a state of constant repair. In addition, there is likely a vocal fatigue threshold at which point the level of tissue damage would shift the chronic healing trajectory to an acute healing trajectory. PMID:19663377
The many faces of graph dynamics

NASA Astrophysics Data System (ADS)

Pignolet, Yvonne Anne; Roy, Matthieu; Schmid, Stefan; Tredan, Gilles

2017-06-01

The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is known today about the network dynamics: indeed, complex networks in reality are not static, but rather dynamically evolve over time. Our paper is motivated by the empirical observation that network evolution patterns seem far from random, but exhibit structure. Moreover, the specific patterns appear to depend on the network type, contradicting the existence of a ‘one fits it all’ model. However, we still lack observables to quantify these intuitions, as well as metrics to compare graph evolutions. Such observables and metrics are needed for extrapolating or predicting evolutions, as well as for interpolating graph evolutions. To explore the many faces of graph dynamics and to quantify temporal changes, this paper suggests to build upon the concept of centrality, a measure of node importance in a network. In particular, we introduce the notion of centrality distance, a natural similarity measure for two graphs which depends on a given centrality, characterizing the graph type. Intuitively, centrality distances reflect the extent to which (non-anonymous) node roles are different or, in case of dynamic graphs, have changed over time, between two graphs. We evaluate the centrality distance approach for five evolutionary models and seven real-world social and physical networks. Our results empirically show the usefulness of centrality distances for characterizing graph dynamics compared to a null-model of random evolution, and highlight the differences between the considered scenarios. Interestingly, our approach allows us to compare the dynamics of very different networks, in terms of scale and evolution speed.
Recent advances quantifying the large wood dynamics in river basins: New methods and remaining challenges

NASA Astrophysics Data System (ADS)

Ruiz-Villanueva, Virginia; Piégay, Hervé; Gurnell, Angela A.; Marston, Richard A.; Stoffel, Markus

2016-09-01

Large wood is an important physical component of woodland rivers and significantly influences river morphology. It is also a key component of stream ecosystems. However, large wood is also a source of risk for human activities as it may damage infrastructure, block river channels, and induce flooding. Therefore, the analysis and quantification of large wood and its mobility are crucial for understanding and managing wood in rivers. As the amount of large-wood-related studies by researchers, river managers, and stakeholders increases, documentation of commonly used and newly available techniques and their effectiveness has also become increasingly relevant as well. Important data and knowledge have been obtained from the application of very different approaches and have generated a significant body of valuable information representative of different environments. This review brings a comprehensive qualitative and quantitative summary of recent advances regarding the different processes involved in large wood dynamics in fluvial systems including wood budgeting and wood mechanics. First, some key definitions and concepts are introduced. Second, advances in quantifying large wood dynamics are reviewed; in particular, how measurements and modeling can be combined to integrate our understanding of how large wood moves through and is retained within river systems. Throughout, we present a quantitative and integrated meta-analysis compiled from different studies and geographical regions. Finally, we conclude by highlighting areas of particular research importance and their likely future trajectories, and we consider a particularly underresearched area so as to stress the future challenges for large wood research.
Dynamic Cross-Entropy.

PubMed

Aur, Dorian; Vila-Rodriguez, Fidel

2017-01-01

Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems. We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures. Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain. To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy. The applied technique may offer new approaches to better understand nonlinear brain activity. Copyright Â© 2016 Elsevier B.V. All rights reserved.
Quantifying Potential Groundwater Recharge In South Texas

NASA Astrophysics Data System (ADS)

Basant, S.; Zhou, Y.; Leite, P. A.; Wilcox, B. P.

2015-12-01

Groundwater in South Texas is heavily relied on for human consumption and irrigation for food crops. Like most of the south west US, woody encroachment has altered the grassland ecosystems here too. While brush removal has been widely implemented in Texas with the objective of increasing groundwater recharge, the linkage between vegetation and groundwater recharge in South Texas is still unclear. Studies have been conducted to understand plant-root-water dynamics at the scale of plants. However, little work has been done to quantify the changes in soil water and deep percolation at the landscape scale. Modeling water flow through soil profiles can provide an estimate of the total water flowing into deep percolation. These models are especially powerful with parameterized and calibrated with long term soil water data. In this study we parameterize the HYDRUS soil water model using long term soil water data collected in Jim Wells County in South Texas. Soil water was measured at every 20 cm intervals up to a depth of 200 cm. The parameterized model will be used to simulate soil water dynamics under a variety of precipitation regimes ranging from well above normal to severe drought conditions. The results from the model will be compared with the changes in soil moisture profile observed in response to vegetation cover and treatments from a study in a similar. Comparative studies like this can be used to build new and strengthen existing hypotheses regarding deep percolation and the role of soil texture and vegetation in groundwater recharge.
A space-efficient algorithm for local similarities.

PubMed

Huang, X Q; Hardison, R C; Miller, W

1990-10-01

Existing dynamic-programming algorithms for identifying similar regions of two sequences require time and space proportional to the product of the sequence lengths. Often this space requirement is more limiting than the time requirement. We describe a dynamic-programming local-similarity algorithm that needs only space proportional to the sum of the sequence lengths. The method can also find repeats within a single long sequence. To illustrate the algorithm's potential, we discuss comparison of a 73,360 nucleotide sequence containing the human beta-like globin gene cluster and a corresponding 44,594 nucleotide sequence for rabbit, a problem well beyond the capabilities of other dynamic-programming software.
Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice.

PubMed

Fernandez, Laura M J; Lecci, Sandro; Cardis, Romain; Vantomme, Gil; Béard, Elidie; Lüthi, Anita

2017-08-02

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders. We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to
Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

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

Lee, Danny; Pollock, Sean; Keall, Paul, E-mail: paul.keall@sydney.edu.au

2016-05-15

Purpose: The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale)more » respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic
Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method.

PubMed

Lee, Danny; Greer, Peter B; Pollock, Sean; Kim, Taeho; Keall, Paul

2016-05-01

The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity

Inferring Characteristics of Sensorimotor Behavior by Quantifying Dynamics of Animal Locomotion

NASA Astrophysics Data System (ADS)

Leung, KaWai

Locomotion is one of the most well-studied topics in animal behavioral studies. Many fundamental and clinical research make use of the locomotion of an animal model to explore various aspects in sensorimotor behavior. In the past, most of these studies focused on population average of a specific trait due to limitation of data collection and processing power. With recent advance in computer vision and statistical modeling techniques, it is now possible to track and analyze large amounts of behavioral data. In this thesis, I present two projects that aim to infer the characteristics of sensorimotor behavior by quantifying the dynamics of locomotion of nematode Caenorhabditis elegans and fruit fly Drosophila melanogaster, shedding light on statistical dependence between sensing and behavior. In the first project, I investigate the possibility of inferring noxious sensory information from the behavior of Caenorhabditis elegans. I develop a statistical model to infer the heat stimulus level perceived by individual animals from their stereotyped escape responses after stimulation by an IR laser. The model allows quantification of analgesic-like effects of chemical agents or genetic mutations in the worm. At the same time, the method is able to differentiate perturbations of locomotion behavior that are beyond affecting the sensory system. With this model I propose experimental designs that allows statistically significant identification of analgesic-like effects. In the second project, I investigate the relationship of energy budget and stability of locomotion in determining the walking speed distribution of Drosophila melanogaster during aging. The locomotion stability at different age groups is estimated from video recordings using Floquet theory. I calculate the power consumption of different locomotion speed using a biomechanics model. In conclusion, the power consumption, not stability, predicts the locomotion speed distribution at different ages.
Dyslexic and Skilled Reading Dynamics Are Self-Similar

ERIC Educational Resources Information Center

Holden, John G.; Greijn, Lieke T.; van Rooij, Marieke M. J. W.; Wijnants, Maarten L.; Bosman, Anna M. T.

2014-01-01

The shape of a word pronunciation time distribution supplies information about the dynamic interactions that support reading performance. Speeded word-naming pronunciation and response time distributions were collected from 20 sixth grade Dutch students with dyslexia and 23 age-matched controls. The participants' pronunciation times were modeled…
Geometrical Similarity Transformations in Dynamic Geometry Environment Geogebra

ERIC Educational Resources Information Center

Andraphanova, Natalia V.

2015-01-01

The subject of the article is usage of modern computer technologies through the example of interactive geometry environment Geogebra as an innovative technology of representing and studying of geometrical material which involves such didactical opportunities as vizualisation, simulation and dynamics. There is shown a classification of geometric…
Multi-Scale Scattering Transform in Music Similarity Measuring

NASA Astrophysics Data System (ADS)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.
From structure to function, via dynamics

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

PubMed

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G; Milosevic, Michael; Hedley, David W; Jaffray, David A

2016-11-21

Compared to FDG, the signal of 18 F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties-well-perfused without substantial necrosis or partitioning-for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in 'inter-corporal' transport properties-blood volume and clearance rate-as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3 , a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.
Quantifying hypoxia in human cancers using static PET imaging

NASA Astrophysics Data System (ADS)

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G.; Milosevic, Michael; Hedley, David W.; Jaffray, David A.

2016-11-01

Compared to FDG, the signal of 18F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties—well-perfused without substantial necrosis or partitioning—for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in ‘inter-corporal’ transport properties—blood volume and clearance rate—as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3, a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.
Quantifying the Incoming Jet Past Heart Valve Prostheses Using Vortex Formation Dynamics

NASA Astrophysics Data System (ADS)

Pierrakos, Olga

2005-11-01

Heart valve (HV) replacement prostheses are associated with hemodynamic compromises compared to their native counterparts. Traditionally, HV performance and hemodynamics have been quantified using effective orifice size and pressure gradients. However, quality and direction of flow are also important aspects of HV function and relate to HV design, implantation technique, and orientation. The flow past any HV is governed by the generation of shear layers followed by the formation and shedding of organized flow structures in the form of vortex rings (VR). For the first time, vortex formation (VF) in the LV is quantified. Vortex energy measurements allow for calculation of the critical formation number (FN), which is the time at which the VR reaches its maximum strength. Inefficiencies in HV function result in critical FN decrease. This study uses the concept of FN to compare mitral HV prostheses in an in-vitro model (a silicone LV model housed in a piston-driven heart simulator) using Time-resolved Digital Particle Image Velocimetry. Two HVs were studied: a porcine HV and bileaflet MHV, which was tested in an anatomic and non-anatomic orientation. The results suggest that HV orientation and design affect the critical FN. We propose that the critical FN, which is contingent on the HV design, orientation, and physical flow characteristics, serve as a parameter to quantify the incoming jet and the efficiency of the HV.
Perspective: Defining and quantifying the role of dynamics in enzyme catalysis

PubMed Central

Warshel, Arieh; Bora, Ram Prasad

2016-01-01

Enzymes control chemical reactions that are key to life processes, and allow them to take place on the time scale needed for synchronization between the relevant reaction cycles. In addition to general interest in their biological roles, these proteins present a fundamental scientific puzzle, since the origin of their tremendous catalytic power is still unclear. While many different hypotheses have been put forward to rationalize this, one of the proposals that has become particularly popular in recent years is the idea that dynamical effects contribute to catalysis. Here, we present a critical review of the dynamical idea, considering all reasonable definitions of what does and does not qualify as a dynamical effect. We demonstrate that no dynamical effect (according to these definitions) has ever been experimentally shown to contribute to catalysis. Furthermore, the existence of non-negligible dynamical contributions to catalysis is not supported by consistent theoretical studies. Our review is aimed, in part, at readers with a background in chemical physics and biophysics, and illustrates that despite a substantial body of experimental effort, there has not yet been any study that consistently established a connection between an enzyme’s conformational dynamics and a significant increase in the catalytic contribution of the chemical step. We also make the point that the dynamical proposal is not a semantic issue but a well-defined scientific hypothesis with well-defined conclusions. PMID:27179464
Perspective: Defining and quantifying the role of dynamics in enzyme catalysis.

PubMed

Warshel, Arieh; Bora, Ram Prasad

2016-05-14

Enzymes control chemical reactions that are key to life processes, and allow them to take place on the time scale needed for synchronization between the relevant reaction cycles. In addition to general interest in their biological roles, these proteins present a fundamental scientific puzzle, since the origin of their tremendous catalytic power is still unclear. While many different hypotheses have been put forward to rationalize this, one of the proposals that has become particularly popular in recent years is the idea that dynamical effects contribute to catalysis. Here, we present a critical review of the dynamical idea, considering all reasonable definitions of what does and does not qualify as a dynamical effect. We demonstrate that no dynamical effect (according to these definitions) has ever been experimentally shown to contribute to catalysis. Furthermore, the existence of non-negligible dynamical contributions to catalysis is not supported by consistent theoretical studies. Our review is aimed, in part, at readers with a background in chemical physics and biophysics, and illustrates that despite a substantial body of experimental effort, there has not yet been any study that consistently established a connection between an enzyme's conformational dynamics and a significant increase in the catalytic contribution of the chemical step. We also make the point that the dynamical proposal is not a semantic issue but a well-defined scientific hypothesis with well-defined conclusions.
Quantifying the spatio-temporal pattern of the ground impact of space weather events using dynamical networks formed from the SuperMAG database of ground based magnetometer stations.

NASA Astrophysics Data System (ADS)

Dods, Joe; Chapman, Sandra; Gjerloev, Jesper

2016-04-01

Quantitative understanding of the full spatial-temporal pattern of space weather is important in order to estimate the ground impact. Geomagnetic indices such as AE track the peak of a geomagnetic storm or substorm, but cannot capture the full spatial-temporal pattern. Observations by the ~100 ground based magnetometers in the northern hemisphere have the potential to capture the detailed evolution of a given space weather event. We present the first analysis of the full available set of ground based magnetometer observations of substorms using dynamical networks. SuperMAG offers a database containing ground station magnetometer data at a cadence of 1min from 100s stations situated across the globe. We use this data to form dynamic networks which capture spatial dynamics on timescales from the fast reconfiguration seen in the aurora, to that of the substorm cycle. Windowed linear cross-correlation between pairs of magnetometer time series along with a threshold is used to determine which stations are correlated and hence connected in the network. Variations in ground conductivity and differences in the response functions of magnetometers at individual stations are overcome by normalizing to long term averages of the cross-correlation. These results are tested against surrogate data in which phases have been randomised. The network is then a collection of connected points (ground stations); the structure of the network and its variation as a function of time quantify the detailed dynamical processes of the substorm. The network properties can be captured quantitatively in time dependent dimensionless network parameters and we will discuss their behaviour for examples of 'typical' substorms and storms. The network parameters provide a detailed benchmark to compare data with models of substorm dynamics, and can provide new insights on the similarities and differences between substorms and how they correlate with external driving and the internal state of the
Quantifying time-of-flight-resolved optical field dynamics in turbid media with interferometric near-infrared spectroscopy (iNIRS) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Borycki, Dawid; Kholiqov, Oybek; Zhou, Wenjun; Srinivasan, Vivek J.

2017-03-01

Sensing and imaging methods based on the dynamic scattering of coherent light, including laser speckle, laser Doppler, and diffuse correlation spectroscopy quantify scatterer motion using light intensity (speckle) fluctuations. The underlying optical field autocorrelation (OFA), rather than being measured directly, is typically inferred from the intensity autocorrelation (IA) through the Siegert relationship, by assuming that the scattered field obeys Gaussian statistics. In this work, we demonstrate interferometric near-infrared spectroscopy (iNIRS) for measurement of time-of-flight (TOF) resolved field and intensity autocorrelations in fluid tissue phantoms and in vivo. In phantoms, we find a breakdown of the Siegert relationship for short times-of-flight due to a contribution from static paths whose optical field does not decorrelate over experimental time scales, and demonstrate that eliminating such paths by polarization gating restores the validity of the Siegert relationship. Inspired by these results, we developed a method, called correlation gating, for separating the OFA into static and dynamic components. Correlation gating enables more precise quantification of tissue dynamics. To prove this, we show that iNIRS and correlation gating can be applied to measure cerebral hemodynamics of the nude mouse in vivo using dynamically scattered (ergodic) paths and not static (non-ergodic) paths, which may not be impacted by blood. More generally, correlation gating, in conjunction with TOF resolution, enables more precise separation of diffuse and non-diffusive contributions to OFA than is possible with TOF resolution alone. Finally, we show that direct measurements of OFA are statistically more efficient than indirect measurements based on IA.
Children's interpretations of general quantifiers, specific quantifiers, and generics

PubMed Central

Gelman, Susan A.; Leslie, Sarah-Jane; Was, Alexandra M.; Koch, Christina M.

2014-01-01

Recently, several scholars have hypothesized that generics are a default mode of generalization, and thus that young children may at first treat quantifiers as if they were generic in meaning. To address this issue, the present experiment provides the first in-depth, controlled examination of the interpretation of generics compared to both general quantifiers ("all Xs", "some Xs") and specific quantifiers ("all of these Xs", "some of these Xs"). We provided children (3 and 5 years) and adults with explicit frequency information regarding properties of novel categories, to chart when "some", "all", and generics are deemed appropriate. The data reveal three main findings. First, even 3-year-olds distinguish generics from quantifiers. Second, when children make errors, they tend to be in the direction of treating quantifiers like generics. Third, children were more accurate when interpreting specific versus general quantifiers. We interpret these data as providing evidence for the position that generics are a default mode of generalization, especially when reasoning about kinds. PMID:25893205
Quantifying evolutionary dynamics from variant-frequency time series

NASA Astrophysics Data System (ADS)

Khatri, Bhavin S.

2016-09-01

From Kimura’s neutral theory of protein evolution to Hubbell’s neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher’s angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.
Quantifying evolutionary dynamics from variant-frequency time series.

PubMed

Khatri, Bhavin S

2016-09-12

From Kimura's neutral theory of protein evolution to Hubbell's neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher's angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.
Quantifying the Influence of Dynamics Across Scales on Regional Climate Uncertainty in Western North America

NASA Astrophysics Data System (ADS)

Goldenson, Naomi L.

Uncertainties in climate projections at the regional scale are inevitably larger than those for global mean quantities. Here, focusing on western North American regional climate, several approaches are taken to quantifying uncertainties starting with the output of global climate model projections. Internal variance is found to be an important component of the projection uncertainty up and down the west coast. To quantify internal variance and other projection uncertainties in existing climate models, we evaluate different ensemble configurations. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find internal variability can be quantified consistently using a large ensemble or an ensemble of opportunity that includes small ensembles from multiple models and climate scenarios. The latter offers the advantage of also producing estimates of uncertainty due to model differences. We conclude that climate projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible. We then conduct a small single-model ensemble of simulations using the Model for Prediction Across Scales with physics from the Community Atmosphere Model Version 5 (MPAS-CAM5) and prescribed historical sea surface temperatures. In the global variable resolution domain, the finest resolution (at 30 km) is in our region of interest over western North America and upwind over the northeast Pacific. In the finer-scale region, extreme precipitation from atmospheric rivers (ARs) is connected to tendencies in seasonal snowpack in mountains of the Northwest United States and California. In most of the Cascade Mountains, winters with more AR days are associated with less snowpack, in contrast to the northern Rockies and California's Sierra Nevadas. In snowpack observations and reanalysis of the atmospheric circulation, we find similar relationships between frequency of AR events and winter
Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

USGS Publications Warehouse

Wedding, L.M.; Christopher, L.A.; Pittman, S.J.; Friedlander, A.M.; Jorgensen, S.

2011-01-01

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change. ?? Inter-Research 2011.
Quantifying non-ergodic dynamics of force-free granular gases.

PubMed

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

2015-09-14

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

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Cross-Linguistic Comparison of Rhythmic and Phonotactic Similarity

ERIC Educational Resources Information Center

Stojanovic, Diana

2013-01-01

Literature on speech rhythm has been focused on three major questions: whether languages have rhythms that can be classified into a small number of types, what the criteria are for the membership in each class, and whether the perceived rhythmic similarity between languages can be quantified based on properties found in the speech signal. Claims…
Detecting similarities among distant homologous proteins by comparison of domain flexibilities.

PubMed

Pandini, Alessandro; Mauri, Giancarlo; Bordogna, Annalisa; Bonati, Laura

2007-06-01

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable.
Cross-linguistic patterns in the acquisition of quantifiers

PubMed Central

Cummins, Chris; Gavarró, Anna; Kuvač Kraljević, Jelena; Hrzica, Gordana; Grohmann, Kleanthes K.; Skordi, Athina; Jensen de López, Kristine; Sundahl, Lone; van Hout, Angeliek; Hollebrandse, Bart; Overweg, Jessica; Faber, Myrthe; van Koert, Margreet; Smith, Nafsika; Vija, Maigi; Zupping, Sirli; Kunnari, Sari; Morisseau, Tiffany; Rusieshvili, Manana; Yatsushiro, Kazuko; Fengler, Anja; Varlokosta, Spyridoula; Konstantzou, Katerina; Farby, Shira; Guasti, Maria Teresa; Vernice, Mirta; Okabe, Reiko; Isobe, Miwa; Crosthwaite, Peter; Hong, Yoonjee; Balčiūnienė, Ingrida; Ahmad Nizar, Yanti Marina; Grech, Helen; Gatt, Daniela; Cheong, Win Nee; Asbjørnsen, Arve; Torkildsen, Janne von Koss; Haman, Ewa; Miękisz, Aneta; Gagarina, Natalia; Puzanova, Julia; Anđelković, Darinka; Savić, Maja; Jošić, Smiljana; Slančová, Daniela; Kapalková, Svetlana; Barberán, Tania; Özge, Duygu; Hassan, Saima; Chan, Cecilia Yuet Hung; Okubo, Tomoya; van der Lely, Heather; Sauerland, Uli; Noveck, Ira

2016-01-01

Learners of most languages are faced with the task of acquiring words to talk about number and quantity. Much is known about the order of acquisition of number words as well as the cognitive and perceptual systems and cultural practices that shape it. Substantially less is known about the acquisition of quantifiers. Here, we consider the extent to which systems and practices that support number word acquisition can be applied to quantifier acquisition and conclude that the two domains are largely distinct in this respect. Consequently, we hypothesize that the acquisition of quantifiers is constrained by a set of factors related to each quantifier’s specific meaning. We investigate competence with the expressions for “all,” “none,” “some,” “some…not,” and “most” in 31 languages, representing 11 language types, by testing 768 5-y-old children and 536 adults. We found a cross-linguistically similar order of acquisition of quantifiers, explicable in terms of four factors relating to their meaning and use. In addition, exploratory analyses reveal that language- and learner-specific factors, such as negative concord and gender, are significant predictors of variation. PMID:27482119
Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.
Quantifying Ciliary Dynamics during Assembly Reveals Step-wise Waveform Maturation in Airway Cells.

PubMed

Oltean, Alina; Schaffer, Andrew J; Bayly, Philip V; Brody, Steven L

2018-05-31

Motile cilia are essential for clearance of particulates and pathogens from airways. For effective transport, ciliary motor proteins and axonemal structures interact to generate the rhythmic, propulsive bending, but the mechanisms that produce a dynamic waveform remain incompletely understood. Biomechanical measures of human cilia motion and their relationships to cilia assembly are needed to illuminate the biophysics of normal cilia function, and to quantify dysfunction in ciliopathies. To these ends, we analyzed cilia motion from high-speed video microscopy of ciliated cells sampled from human lung airways compared to primary-culture cells that undergo ciliogenesis in vitro. Quantitative assessment of waveform parameters showed variations in waveform shape between individual cilia; however, general trends in waveform parameters emerged, associated with progression of cilia length and stage of differentiation. When cilia emerged from cultured cells, beat frequency was initially elevated, then fell and remained stable as cilia lengthened. In contrast, the average bending amplitude and the ability to generate force gradually increased and eventually approached values observed in ex vivo samples. Dynein arm motor proteins DNAH5, DNAH9, DNAH11, and DNAH6 were localized within specific regions of the axoneme in the ex vivo cells; however distinct stages of in vitro waveform development identified by biomechanical features were associated with the progressive movement of dyneins to the appropriate proximal or distal sections of the cilium. These observations suggest that the step-wise variation in waveform development during ciliogenesis is dependent on cilia length and potentially outer dynein arm assembly.
87Sr/86Sr as a quantitative geochemical proxy for 14C reservoir age in dynamic, brackish waters: assessing applicability and quantifying uncertainties.

NASA Astrophysics Data System (ADS)

Lougheed, Bryan; van der Lubbe, Jeroen; Davies, Gareth

2016-04-01

Accurate geochronologies are crucial for reconstructing the sensitivity of brackish and estuarine environments to rapidly changing past external impacts. A common geochronological method used for such studies is radiocarbon (14C) dating, but its application in brackish environments is severely limited by an inability to quantify spatiotemporal variations in 14C reservoir age, or R(t), due to dynamic interplay between river runoff and marine water. Additionally, old carbon effects and species-specific behavioural processes also influence 14C ages. Using the world's largest brackish water body (the estuarine Baltic Sea) as a test-bed, combined with a comprehensive approach that objectively excludes both old carbon and species-specific effects, we demonstrate that it is possible to use 87Sr/86Sr ratios to quantify R(t) in ubiquitous mollusc shell material, leading to almost one order of magnitude increase in Baltic Sea 14C geochronological precision over the current state-of-the-art. We propose that this novel proxy method can be developed for other brackish water bodies worldwide, thereby improving geochronological control in these climate sensitive, near-coastal environments.
Similarities between principal components of protein dynamics and random diffusion

NASA Astrophysics Data System (ADS)

Hess, Berk

2000-12-01

Principal component analysis, also called essential dynamics, is a powerful tool for finding global, correlated motions in atomic simulations of macromolecules. It has become an established technique for analyzing molecular dynamics simulations of proteins. The first few principal components of simulations of large proteins often resemble cosines. We derive the principal components for high-dimensional random diffusion, which are almost perfect cosines. This resemblance between protein simulations and noise implies that for many proteins the time scales of current simulations are too short to obtain convergence of collective motions.
Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

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

ERIC Educational Resources Information Center

Rausch, Tobias; Karing, Constance; Dörfler, Tobias; Artelt, Cordula

2016-01-01

This study examined personality similarity between teachers and their students and its impact on teacher judgement of student achievement in the domains of reading comprehension and mathematics. Personality similarity was quantified through intraclass correlations between personality characteristics of 409 dyads of German teachers and their…
Quantifying the impact of the Three Gorges Dam on the thermal dynamics of the Yangtze River

NASA Astrophysics Data System (ADS)

Cai, Huayang; Piccolroaz, Sebastiano; Huang, Jingzheng; Liu, Zhiyong; Liu, Feng; Toffolon, Marco

2018-05-01

This study examines the impact of the world’s largest dam, the Three Gorges Dam (TGD), on the thermal dynamics of the Yangtze River (China). The analysis uses long-term observations of river water temperature (RWT) in four stations and reconstructs the RWT that would have occurred in absence of the TGD. Relative to pre-TGD conditions, RWT consistently warmed in the region due to air temperature (AT) increase. In addition, the analysis demonstrates that the TGD significantly affected RWT in the downstream reach. At the closest downstream station (Yichang) to the TGD, the annual cycle of RWT experienced a damped response to AT and a marked seasonal alteration: warming during all seasons except for spring and early summer which were characterized by cooling. Both effects were a direct consequence of the larger thermal inertia of the massive water volume stored in the TGD reservoir, causing the downstream reach to be more thermally resilient. The approach used here to quantify the separate contributions of climate and human interventions on RWT can be used to set scientific guidelines for river management and conservation planning strategies.
Differential Variance Analysis: a direct method to quantify and visualize dynamic heterogeneities

NASA Astrophysics Data System (ADS)

Pastore, Raffaele; Pesce, Giuseppe; Caggioni, Marco

2017-03-01

Many amorphous materials show spatially heterogenous dynamics, as different regions of the same system relax at different rates. Such a signature, known as Dynamic Heterogeneity, has been crucial to understand the nature of the jamming transition in simple model systems and is currently considered very promising to characterize more complex fluids of industrial and biological relevance. Unfortunately, measurements of dynamic heterogeneities typically require sophisticated experimental set-ups and are performed by few specialized groups. It is now possible to quantitatively characterize the relaxation process and the emergence of dynamic heterogeneities using a straightforward method, here validated on video microscopy data of hard-sphere colloidal glasses. We call this method Differential Variance Analysis (DVA), since it focuses on the variance of the differential frames, obtained subtracting images at different time-lags. Moreover, direct visualization of dynamic heterogeneities naturally appears in the differential frames, when the time-lag is set to the one corresponding to the maximum dynamic susceptibility. This approach opens the way to effectively characterize and tailor a wide variety of soft materials, from complex formulated products to biological tissues.
Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an Internet social network.

PubMed

Little, Max; Wicks, Paul; Vaughan, Timothy; Pentland, Alex

2013-01-24

Parkinson's disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson's Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Online self-reported data was validated against the gold standard Parkinson's Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of
Quantifying the transmission potential of pandemic influenza

NASA Astrophysics Data System (ADS)

Chowell, Gerardo; Nishiura, Hiroshi

2008-03-01

This article reviews quantitative methods to estimate the basic reproduction number of pandemic influenza, a key threshold quantity to help determine the intensity of interventions required to control the disease. Although it is difficult to assess the transmission potential of a probable future pandemic, historical epidemiologic data is readily available from previous pandemics, and as a reference quantity for future pandemic planning, mathematical and statistical analyses of historical data are crucial. In particular, because many historical records tend to document only the temporal distribution of cases or deaths (i.e. epidemic curve), our review focuses on methods to maximize the utility of time-evolution data and to clarify the detailed mechanisms of the spread of influenza. First, we highlight structured epidemic models and their parameter estimation method which can quantify the detailed disease dynamics including those we cannot observe directly. Duration-structured epidemic systems are subsequently presented, offering firm understanding of the definition of the basic and effective reproduction numbers. When the initial growth phase of an epidemic is investigated, the distribution of the generation time is key statistical information to appropriately estimate the transmission potential using the intrinsic growth rate. Applications of stochastic processes are also highlighted to estimate the transmission potential using similar data. Critically important characteristics of influenza data are subsequently summarized, followed by our conclusions to suggest potential future methodological improvements.
Quantifying non-Markovianity of continuous-variable Gaussian dynamical maps

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

Vasile, Ruggero; Maniscalco, Sabrina; Paris, Matteo G. A.

2011-11-15

We introduce a non-Markovianity measure for continuous-variable open quantum systems based on the idea put forward in H.-P. Breuer et al.[Phys. Rev. Lett. 103, 210401 (2009);], that is, by quantifying the flow of information from the environment back to the open system. Instead of the trace distance we use here the fidelity to assess distinguishability of quantum states. We employ our measure to evaluate non-Markovianity of two paradigmatic Gaussian channels: the purely damping channel and the quantum Brownian motion channel with Ohmic environment. We consider different classes of Gaussian states and look for pairs of states maximizing the backflow ofmore » information. For coherent states we find simple analytical solutions, whereas for squeezed states we provide both exact numerical and approximate analytical solutions in the weak coupling limit.« less
Quantifying carbon stores and decomposition in dead wood: A review

Treesearch

Matthew B. Russell; Shawn Fraver; Tuomas Aakala; Jeffrey H. Gove; Christopher W. Woodall; Anthony W. D’Amato; Mark J. Ducey

2015-01-01

The amount and dynamics of forest dead wood (both standing and downed) has been quantified by a variety of approaches throughout the forest science and ecology literature. Differences in the sampling and quantification of dead wood can lead to differences in our understanding of forests and their role in the sequestration and emissions of CO2, as...
Text-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients.

PubMed

Saklatvala, Jake R; Dand, Nick; Simpson, Michael A

2018-05-01

The genetic diagnosis of rare monogenic diseases using exome/genome sequencing requires the true causal variant(s) to be identified from tens of thousands of observed variants. Typically a virtual gene panel approach is taken whereby only variants in genes known to cause phenotypes resembling the patient under investigation are considered. With the number of known monogenic gene-disease pairs exceeding 5,000, manual curation of personalized virtual panels using exhaustive knowledge of the genetic basis of the human monogenic phenotypic spectrum is challenging. We present improved probabilistic methods for estimating phenotypic similarity based on Human Phenotype Ontology annotation. A limitation of existing methods for evaluating a disease's similarity to a reference set is that reference diseases are typically represented as a series of binary (present/absent) observations of phenotypic terms. We evaluate a quantified disease reference set, using term frequency in phenotypic text descriptions to approximate term relevance. We demonstrate an improved ability to identify related diseases through the use of a quantified reference set, and that vector space similarity measures perform better than established information content-based measures. These improvements enable the generation of bespoke virtual gene panels, facilitating more accurate and efficient interpretation of genomic variant profiles from individuals with rare Mendelian disorders. These methods are available online at https://atlas.genetics.kcl.ac.uk/~jake/cgi-bin/patient_sim.py. © 2018 Wiley Periodicals, Inc.
Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099
In vitro assembled plant microtubules exhibit a high state of dynamic instability.

PubMed

Moore, R C; Zhang, M; Cassimeris, L; Cyr, R J

1997-01-01

Higher plants possess four distinct microtubule arrays. One of these, the cortical array, is involved in orienting the deposition of cellulose microfibrils. This plant interphase array is also notable because it contains exceptionally dynamic microtubules. Although the primary sequence of plant and animal tubulin is similar (79-87% amino acid identity overall) there are some regions of divergence. Thus, one possible explanation for the high state of polymer assembly and turnover that is observed in plant interphase arrays is that the tubulins have evolved differently and possess a higher intrinsic dynamic character than their animal counterparts. This hypothesis was tested using highly purified plant tubulin assembled in vitro. Using high-resolution DIC video-enhanced microscopy, we quantified the four characteristic parameters of dynamic instability of plant microtubules and compared them with animal microtubules. The elongation velocities between plant and animal microtubules are similar, but plant microtubules undergo catastrophes more frequently, do not exhibit any rescues, and have an average shortening velocity of 195 microm/min (compared with 21 microm/min for animal microtubules). These data support the hypothesis that plant tubulin forms microtubules that are intrinsically more dynamic than those of animals.
Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

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

PubMed

Angeler, David G; Allen, Craig R; Garmestani, Ahjond S; Gunderson, Lance H; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Quantifying the adaptive cycle

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.
Quantifying Intracranial Aneurysm Wall Permeability for Risk Assessment Using Dynamic Contrast-Enhanced MRI: A Pilot Study.

PubMed

Vakil, P; Ansari, S A; Cantrell, C G; Eddleman, C S; Dehkordi, F H; Vranic, J; Hurley, M C; Batjer, H H; Bendok, B R; Carroll, T J

2015-05-01

Pathological changes in the intracranial aneurysm wall may lead to increases in its permeability; however the clinical significance of such changes has not been explored. The purpose of this pilot study was to quantify intracranial aneurysm wall permeability (K(trans), VL) to contrast agent as a measure of aneurysm rupture risk and compare these parameters against other established measures of rupture risk. We hypothesized K(trans) would be associated with intracranial aneurysm rupture risk as defined by various anatomic, imaging, and clinical risk factors. Twenty-seven unruptured intracranial aneurysms in 23 patients were imaged with dynamic contrast-enhanced MR imaging, and wall permeability parameters (K(trans), VL) were measured in regions adjacent to the aneurysm wall and along the paired control MCA by 2 blinded observers. K(trans) and VL were evaluated as markers of rupture risk by comparing them against established clinical (symptomatic lesions) and anatomic (size, location, morphology, multiplicity) risk metrics. Interobserver agreement was strong as shown in regression analysis (R(2) > 0.84) and intraclass correlation (intraclass correlation coefficient >0.92), indicating that the K(trans) can be reliably assessed clinically. All intracranial aneurysms had a pronounced increase in wall permeability compared with the paired healthy MCA (P < .001). Regression analysis demonstrated a significant trend toward an increased K(trans) with increasing aneurysm size (P < .001). Logistic regression showed that K(trans) also predicted risk in anatomic (P = .02) and combined anatomic/clinical (P = .03) groups independent of size. We report the first evidence of dynamic contrast-enhanced MR imaging-modeled contrast permeability in intracranial aneurysms. We found that contrast agent permeability across the aneurysm wall correlated significantly with both aneurysm size and size-independent anatomic risk factors. In addition, K(trans) was a significant and size
Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach.

PubMed

Rosso, O A; Zunino, L; Pérez, D G; Figliola, A; Larrondo, H A; Garavaglia, M; Martín, M T; Plastino, A

2007-12-01

By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martín-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises.
Timing of transients: quantifying reaching times and transient behavior in complex systems

NASA Astrophysics Data System (ADS)

Kittel, Tim; Heitzig, Jobst; Webster, Kevin; Kurths, Jürgen

2017-08-01

In dynamical systems, one may ask how long it takes for a trajectory to reach the attractor, i.e. how long it spends in the transient phase. Although for a single trajectory the mathematically precise answer may be infinity, it still makes sense to compare different trajectories and quantify which of them approaches the attractor earlier. In this article, we categorize several problems of quantifying such transient times. To treat them, we propose two metrics, area under distance curve and regularized reaching time, that capture two complementary aspects of transient dynamics. The first, area under distance curve, is the distance of the trajectory to the attractor integrated over time. It measures which trajectories are ‘reluctant’, i.e. stay distant from the attractor for long, or ‘eager’ to approach it right away. Regularized reaching time, on the other hand, quantifies the additional time (positive or negative) that a trajectory starting at a chosen initial condition needs to approach the attractor as compared to some reference trajectory. A positive or negative value means that it approaches the attractor by this much ‘earlier’ or ‘later’ than the reference, respectively. We demonstrated their substantial potential for application with multiple paradigmatic examples uncovering new features.
Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris

PubMed Central

Merkle, Conrad W.; Leahy, Conor; Srinivasan, Vivek J.

2016-01-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo. DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution. PMID:27867732
Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris.

PubMed

Merkle, Conrad W; Leahy, Conor; Srinivasan, Vivek J

2016-10-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo . DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution.
Evaluation of two methods for quantifying passeriform lice

PubMed Central

Koop, Jennifer A. H.; Clayton, Dale H.

2013-01-01

Two methods commonly used to quantify ectoparasites on live birds are visual examination and dust-ruffling. Visual examination provides an estimate of ectoparasite abundance based on an observer’s timed inspection of various body regions on a bird. Dust-ruffling involves application of insecticidal powder to feathers that are then ruffled to dislodge ectoparasites onto a collection surface where they can then be counted. Despite the common use of these methods in the field, the proportion of actual ectoparasites they account for has only been tested with Rock Pigeons (Columba livia), a relatively large-bodied species (238–302 g) with dense plumage. We tested the accuracy of the two methods using European Starlings (Sturnus vulgaris; ~75 g). We first quantified the number of lice (Brueelia nebulosa) on starlings using visual examination, followed immediately by dust-ruffling. Birds were then euthanized and the proportion of lice accounted for by each method was compared to the total number of lice on each bird as determined with a body-washing method. Visual examination and dust-ruffling each accounted for a relatively small proportion of total lice (14% and 16%, respectively), but both were still significant predictors of abundance. The number of lice observed by visual examination accounted for 68% of the variation in total abundance. Similarly, the number of lice recovered by dust-ruffling accounted for 72% of the variation in total abundance. Our results show that both methods can be used to reliably quantify the abundance of lice on European Starlings and other similar-sized passerines. PMID:24039328
Relativistic self-similar dynamic gravitational collapses of a quasi-spherical general polytropic magnetofluid

NASA Astrophysics Data System (ADS)

Lou, Yu-Qing; Xia, Yu-Kai

2017-05-01

We study magnetohydrodynamic (MHD) self-similar collapses and void evolution, with or without shocks, of a general polytropic quasi-spherical magnetofluid permeated by random transverse magnetic fields under the Paczynski-Wiita gravity that captures essential general relativistic effects of a Schwarzschild black hole (BH) with a growing mass. Based on the derived set of non-linear MHD ordinary differential equations, we obtain various asymptotic MHD solutions, the geometric and analytical properties of the magnetosonic critical curve (MSCC) and MHD shock jump conditions. Novel asymptotic MHD solution behaviours near the rim of central expanding voids are derived analytically. By exploring numerical global MHD solutions, we identify allowable boundary conditions at large radii that accommodate a smooth solution and show that a reasonable amount of magnetization significantly increases the mass accretion rate in the expansion-wave-collapse solution scenario. We also construct the counterparts of envelope-expansion-core-collapse solutions that cross the MSCC twice, which are found to be closely paired with a sequence of global smooth solutions satisfying a novel type of central MHD behaviours. MHD shocks with static outer and various inner flow profiles are also examined. Astrophysical applications include dynamic core collapses of magnetized massive stars and compact objects as well as formation of supermassive, hypermassive, dark matter and mixed matter BHs in the Universe, including the early Universe. Such gigantic BHs can be detected in X-ray/gamma-ray sources, quasars, ultraluminous infrared galaxies or extremely luminous infrared galaxies and dark matter overwhelmingly dominated elliptical galaxies as well as massive dark matter halos, etc. Gravitational waves and electromagnetic wave emissions in broad band (including e.g., gamma-ray bursts and fast radio bursts) can result from this type of dynamic collapses of forming BHs involving magnetized media.
Dynamics of an elastic sphere containing a thin creeping region and immersed in an acoustic region for similar viscous-elastic and acoustic time- and length-scales

NASA Astrophysics Data System (ADS)

Gat, Amir; Friedman, Yonathan

2017-11-01

The characteristic time of low-Reynolds number fluid-structure interaction scales linearly with the ratio of fluid viscosity to solid Young's modulus. For sufficiently large values of Young's modulus, both time- and length-scales of the viscous-elastic dynamics may be similar to acoustic time- and length-scales. However, the requirement of dominant viscous effects limits the validity of such regimes to micro-configurations. We here study the dynamics of an acoustic plane wave impinging on the surface of a layered sphere, immersed within an inviscid fluid, and composed of an inner elastic sphere, a creeping fluid layer and an external elastic shell. We focus on configurations with similar viscous-elastic and acoustic time- and length-scales, where the viscous-elastic speed of interaction between the creeping layer and the elastic regions is similar to the speed of sound. By expanding the linearized spherical Reynolds equation into the relevant spectral series solution for the hyperbolic elastic regions, a global stiffness matrix of the layered elastic sphere was obtained. This work relates viscous-elastic dynamics to acoustic scattering and may pave the way to the design of novel meta-materials with unique acoustic properties. ISF 818/13.
Quantifiers more or less quantify online: ERP evidence for partial incremental interpretation

PubMed Central

Urbach, Thomas P.; Kutas, Marta

2010-01-01

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

NASA Astrophysics Data System (ADS)

Avila, Karina E.

Our current understanding of the dynamics of supercooled liquids and other similar slowly evolving (glassy) systems is rather limited. One aspect that is particularly poorly understood is the origin and behavior of the strong non trivial fluctuations that appear in the relaxation process toward equilibrium. Glassy systems and granular systems both present regions of particles moving cooperatively and at different rates from other regions. This phenomenon is known as spatially heterogeneous dynamics. A detailed explanation of this phenomenon may lead to a better understanding of the slow relaxation process, and perhaps it could even help to explain the presence of the glass transition. This dissertation concentrates on studying dynamical heterogeneity by analyzing simulation data for models of granular materials and structural glasses. For dissipative granular fluids, the growing behavior of dynamical heterogeneities is studied for different densities and different degrees of inelasticity in the particle collisions. The correlated regions are found to grow rapidly as the system approaches dynamical arrest. Their geometry is conserved even when probing at different cutoff length in the correlation function or when the energy dissipation in the system is increased. For structural glasses, I test a theoretical framework that models dynamical heterogeneity as originated in the presence of Goldstone modes, which emerge from a broken continuous time reparametrization symmetry. This analysis is based on quantifying the size and the spatial correlations of fluctuations in the time variable and of other kinds of fluctuations. The results obtained here agree with the predictions of the hypothesis. In particular, the fluctuations associated to the time reparametrization invariance become stronger for low temperatures, long timescales, and large coarse graining lengths. Overall, this research points to dynamical heterogeneity to be described for granular systems similarly than
Incorporating both physical and kinetic limitations in quantifying dissolved oxygen flux to aquatic sediments

USGS Publications Warehouse

O'Connor, B.L.; Hondzo, Miki; Harvey, J.W.

2009-01-01

Traditionally, dissolved oxygen (DO) fluxes have been calculated using the thin-film theory with DO microstructure data in systems characterized by fine sediments and low velocities. However, recent experimental evidence of fluctuating DO concentrations near the sediment-water interface suggests that turbulence and coherent motions control the mass transfer, and the surface renewal theory gives a more mechanistic model for quantifying fluxes. Both models involve quantifying the mass transfer coefficient (k) and the relevant concentration difference (??C). This study compared several empirical models for quantifying k based on both thin-film and surface renewal theories, as well as presents a new method for quantifying ??C (dynamic approach) that is consistent with the observed DO concentration fluctuations near the interface. Data were used from a series of flume experiments that includes both physical and kinetic uptake limitations of the flux. Results indicated that methods for quantifying k and ??C using the surface renewal theory better estimated the DO flux across a range of fluid-flow conditions. ?? 2009 ASCE.
Live cell interferometry quantifies dynamics of biomass partitioning during cytokinesis.

PubMed

Zangle, Thomas A; Teitell, Michael A; Reed, Jason

2014-01-01

The equal partitioning of cell mass between daughters is the usual and expected outcome of cytokinesis for self-renewing cells. However, most studies of partitioning during cell division have focused on daughter cell shape symmetry or segregation of chromosomes. Here, we use live cell interferometry (LCI) to quantify the partitioning of daughter cell mass during and following cytokinesis. We use adherent and non-adherent mouse fibroblast and mouse and human lymphocyte cell lines as models and show that, on average, mass asymmetries present at the time of cleavage furrow formation persist through cytokinesis. The addition of multiple cytoskeleton-disrupting agents leads to increased asymmetry in mass partitioning which suggests the absence of active mass partitioning mechanisms after cleavage furrow positioning.
Using seismic arrays to quantify the physics of a glacial outburst flood and its legacy on upland river dynamics

NASA Astrophysics Data System (ADS)

Gimbert, Florent; Cook, Kristen; Andermann, Christoff; Hovius, Niels; Turowski, Jens

2017-04-01

In the Himalayas fluvial erosion is thought to be controlled by the intense annual Indian Summer Monsoon precipitation. However, this region is also exposed to catastrophic floods generated by the sudden failure of landslides or moraine dams. These floods are rare and particularly devastating. Thus they have a strong impact on rivers and adjacent hillslopes, and they represent a hazard for local populations. Due to the difficulties to observe these floods and quantify their physics using traditional methods, their importance for the long-term evolution of Himalayan Rivers remains largely unknown, and no consistent early warning system exists to anticipate these events, especially in trans-boundary regions. Here we show that seismic arrays can be used to (i) reliably anticipate outburst floods and to (ii) quantify multiple and key fluvial processes associated with their propagation and their lasting impacts on upland river dynamics. We report unique seismic observations of a glacial lake outburst flood event that occurred the 5th of July 2016 in the Bhote Koshi River (Central Nepal). Precursory seismic signals are identified from the onset of the lake drainage event such that an early warning alarm may be turned on about an hour before the outburst flood wave reaches areas with an exposed population. Using our network of stations we observe for the first time that the outburst flood wave is in fact made of two distinct waves, namely a water flow wave and a bedload sediment wave. As expected these two waves travel at different speeds. We find that the ratio between the two wave speeds matches with that previously found at much smaller scales in flume laboratory experiments. Based on the physical modelling of both water-flow- and bedload- induced seismic noise we provide estimates of flow depth and bedload transport characteristics (flux, moving grains sizes) prior, during and after the flood. In particular we show that bedload sediment flux is enhanced by up to a
SIMILARITY PROPERTIES AND SCALING LAWS OF RADIATION HYDRODYNAMIC FLOWS IN LABORATORY ASTROPHYSICS

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

Falize, E.; Bouquet, S.; Michaut, C., E-mail: emeric.falize@cea.fr

The spectacular recent development of modern high-energy density laboratory facilities which concentrate more and more energy in millimetric volumes allows the astrophysical community to reproduce and to explore, in millimeter-scale targets and during very short times, astrophysical phenomena where radiation and matter are strongly coupled. The astrophysical relevance of these experiments can be checked from the similarity properties and especially scaling law establishment, which constitutes the keystone of laboratory astrophysics. From the radiating optically thin regime to the so-called optically thick radiative pressure regime, we present in this paper, for the first time, a complete analysis of the main radiatingmore » regimes that we encountered in laboratory astrophysics with the same formalism based on Lie group theory. The use of the Lie group method appears to be a systematic method which allows us to construct easily and systematically the scaling laws of a given problem. This powerful tool permits us to unify the recent major advances on scaling laws and to identify new similarity concepts that we discuss in this paper, and suggests important applications for present and future laboratory astrophysics experiments. All these results enable us to demonstrate theoretically that astrophysical phenomena in such radiating regimes can be explored experimentally thanks to powerful facilities. Consequently, the results presented here are a fundamental tool for the high-energy density laboratory astrophysics community in order to quantify the astrophysics relevance and justify laser experiments. Moreover, relying on Lie group theory, this paper constitutes the starting point of any analysis of the self-similar dynamics of radiating fluids.« less
Exploring information from the topology beneath the Gene Ontology terms to improve semantic similarity measures.

PubMed

Zhang, Shu-Bo; Lai, Jian-Huang

2016-07-15

Measuring the similarity between pairs of biological entities is important in molecular biology. The introduction of Gene Ontology (GO) provides us with a promising approach to quantifying the semantic similarity between two genes or gene products. This kind of similarity measure is closely associated with the GO terms annotated to biological entities under consideration and the structure of the GO graph. However, previous works in this field mainly focused on the upper part of the graph, and seldom concerned about the lower part. In this study, we aim to explore information from the lower part of the GO graph for better semantic similarity. We proposed a framework to quantify the similarity measure beneath a term pair, which takes into account both the information two ancestral terms share and the probability that they co-occur with their common descendants. The effectiveness of our approach was evaluated against seven typical measurements on public platform CESSM, protein-protein interaction and gene expression datasets. Experimental results consistently show that the similarity derived from the lower part contributes to better semantic similarity measure. The promising features of our approach are the following: (1) it provides a mirror model to characterize the information two ancestral terms share with respect to their common descendant; (2) it quantifies the probability that two terms co-occur with their common descendant in an efficient way; and (3) our framework can effectively capture the similarity measure beneath two terms, which can serve as an add-on to improve traditional semantic similarity measure between two GO terms. The algorithm was implemented in Matlab and is freely available from http://ejl.org.cn/bio/GOBeneath/. Copyright © 2016 Elsevier B.V. All rights reserved.
Non-stationary dynamics in the bouncing ball: A wavelet perspective

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

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in; Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding tomore » neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.« less
Quantifying light-dependent circadian disruption in humans and animal models.

PubMed

Rea, Mark S; Figueiro, Mariana G

2014-12-01

Although circadian disruption is an accepted term, little has been done to develop methods to quantify the degree of disruption or entrainment individual organisms actually exhibit in the field. A variety of behavioral, physiological and hormonal responses vary in amplitude over a 24-h period and the degree to which these circadian rhythms are synchronized to the daily light-dark cycle can be quantified with a technique known as phasor analysis. Several studies have been carried out using phasor analysis in an attempt to measure circadian disruption exhibited by animals and by humans. To perform these studies, species-specific light measurement and light delivery technologies had to be developed based upon a fundamental understanding of circadian phototransduction mechanisms in the different species. When both nocturnal rodents and diurnal humans, experienced different species-specific light-dark shift schedules, they showed, based upon phasor analysis of the light-dark and activity-rest patterns, similar levels of light-dependent circadian disruption. Indeed, both rodents and humans show monotonically increasing and quantitatively similar levels of light-dependent circadian disruption with increasing shift-nights per week. Thus, phasor analysis provides a method for quantifying circadian disruption in the field and in the laboratory as well as a bridge between ecological measurements of circadian entrainment in humans and parametric studies of circadian disruption in animal models, including nocturnal rodents.
Spatiotemporal dynamics of similarity-based neural representations of facial identity.

PubMed

Vida, Mark D; Nestor, Adrian; Plaut, David C; Behrmann, Marlene

2017-01-10

Humans' remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level "image-based" and higher level "identity-based" model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise.
Spatiotemporal dynamics of similarity-based neural representations of facial identity

PubMed Central

Vida, Mark D.; Nestor, Adrian; Plaut, David C.; Behrmann, Marlene

2017-01-01

Humans’ remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level “image-based” and higher level “identity-based” model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise. PMID:28028220

Exploiting Data Similarity to Reduce Memory Footprints

DTIC Science & Technology

2011-01-01

leslie3d Fortran Computational Fluid Dynamics (CFD) application 122. tachyon C Parallel Ray Tracing application 128.GAPgeofem C and Fortran Simulates...benefits most from SBLLmalloc; LAMMPS, which shows moderate similarity from primarily zero pages; and 122. tachyon , a parallel ray- tracing application...similarity across MPI tasks. They primarily are zero- pages although a small fraction (≈10%) are non-zero pages. 122. tachyon is an image rendering
Quantifying climate feedbacks in polar regions.

PubMed

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

2018-05-15

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

PubMed

Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe

2016-07-01

Space-time dependencies among monitoring network stations have been investigated to detect and quantify similarity relationships among gauging stations. In this work, besides the well-known rank correlation index, two new similarity indices have been defined and applied to compute the similarity matrix related to the Apulian meteo-climatic monitoring network. The similarity matrices can be applied to address reliably the issue of missing data in space-time series. In order to establish the effectiveness of the similarity indices, a simulation test was then designed and performed with the aim of estimating missing monthly rainfall rates in a suitably selected gauging station. The results of the simulation allowed us to evaluate the effectiveness of the proposed similarity indices. Finally, the multiple imputation by chained equations method was used as a benchmark to have an absolute yardstick for comparing the outcomes of the test. In conclusion, the new proposed multiplicative similarity index resulted at least as reliable as the selected benchmark.
A stochastic approach for quantifying immigrant integration: the Spanish test case

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Contucci, Pierluigi; Sandell, Richard; Vernia, Cecilia

2014-10-01

We apply stochastic process theory to the analysis of immigrant integration. Using a unique and detailed data set from Spain, we study the relationship between local immigrant density and two social and two economic immigration quantifiers for the period 1999-2010. As opposed to the classic time-series approach, by letting immigrant density play the role of ‘time’ and the quantifier the role of ‘space,’ it becomes possible to analyse the behavior of the quantifiers by means of continuous time random walks. Two classes of results are then obtained. First, we show that social integration quantifiers evolve following diffusion law, while the evolution of economic quantifiers exhibits ballistic dynamics. Second, we make predictions of best- and worst-case scenarios taking into account large local fluctuations. Our stochastic process approach to integration lends itself to interesting forecasting scenarios which, in the hands of policy makers, have the potential to improve political responses to integration problems. For instance, estimating the standard first-passage time and maximum-span walk reveals local differences in integration performance for different immigration scenarios. Thus, by recognizing the importance of local fluctuations around national means, this research constitutes an important tool to assess the impact of immigration phenomena on municipal budgets and to set up solid multi-ethnic plans at the municipal level as immigration pressures build.
Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling
Quantifying space-time dynamics of flood event types

NASA Astrophysics Data System (ADS)

Viglione, Alberto; Chirico, Giovanni Battista; Komma, Jürgen; Woods, Ross; Borga, Marco; Blöschl, Günter

2010-11-01

SummaryA generalised framework of space-time variability in flood response is used to characterise five flood events of different type in the Kamp area in Austria: one long-rain event, two short-rain events, one rain-on-snow event and one snowmelt event. Specifically, the framework quantifies the contributions of the space-time variability of rainfall/snowmelt, runoff coefficient, hillslope and channel routing to the flood runoff volume and the delay and spread of the resulting hydrograph. The results indicate that the components obtained by the framework clearly reflect the individual processes which characterise the event types. For the short-rain events, temporal, spatial and movement components can all be important in runoff generation and routing, which would be expected because of their local nature in time and, particularly, in space. For the long-rain event, the temporal components tend to be more important for runoff generation, because of the more uniform spatial coverage of rainfall, while for routing the spatial distribution of the produced runoff, which is not uniform, is also important. For the rain-on-snow and snowmelt events, the spatio-temporal variability terms typically do not play much role in runoff generation and the spread of the hydrograph is mainly due to the duration of the event. As an outcome of the framework, a dimensionless response number is proposed that represents the joint effect of runoff coefficient and hydrograph peakedness and captures the absolute magnitudes of the observed flood peaks.
Observation and numerical modeling of tidal dune dynamics

NASA Astrophysics Data System (ADS)

Doré, Arnaud; Bonneton, Philippe; Marieu, Vincent; Garlan, Thierry

2018-05-01

Tidal sand dune dynamics is observed for two tidal cycles in the Arcachon tidal inlet, southwest France. An array of instruments is deployed to measure bathymetric and current variations along dune profiles. Based on the measurements, dune crest horizontal and vertical displacements are quantified and show important dynamics in phase with tidal currents. We observed superimposed ripples on the dune stoss side and front, migrating and changing polarity as tidal currents reverse. A 2D RANS numerical model is used to simulate the morphodynamic evolution of a flat non-cohesive sand bed submitted to a tidal current. The model reproduces the bed evolution until a field of sand bedforms is obtained that are comparable with observed superimposed ripples in terms of geometrical dimensions and dynamics. The model is then applied to simulate the dynamics of a field of large sand dunes of similar size as the dunes observed in situ. In both cases, simulation results compare well with measurements qualitatively and quantitatively. This research allows for a better understanding of tidal sand dune and superimposed ripple morphodynamics and opens new perspectives for the use of numerical models to predict their evolution.
Stability of similarity measurements for bipartite networks

PubMed Central

Liu, Jian-Guo; Hou, Lei; Pan, Xue; Guo, Qiang; Zhou, Tao

2016-01-01

Similarity is a fundamental measure in network analyses and machine learning algorithms, with wide applications ranging from personalized recommendation to socio-economic dynamics. We argue that an effective similarity measurement should guarantee the stability even under some information loss. With six bipartite networks, we investigate the stabilities of fifteen similarity measurements by comparing the similarity matrixes of two data samples which are randomly divided from original data sets. Results show that, the fifteen measurements can be well classified into three clusters according to their stabilities, and measurements in the same cluster have similar mathematical definitions. In addition, we develop a top-n-stability method for personalized recommendation, and find that the unstable similarities would recommend false information to users, and the performance of recommendation would be largely improved by using stable similarity measurements. This work provides a novel dimension to analyze and evaluate similarity measurements, which can further find applications in link prediction, personalized recommendation, clustering algorithms, community detection and so on. PMID:26725688
Stability of similarity measurements for bipartite networks.

PubMed

Liu, Jian-Guo; Hou, Lei; Pan, Xue; Guo, Qiang; Zhou, Tao

2016-01-04

Similarity is a fundamental measure in network analyses and machine learning algorithms, with wide applications ranging from personalized recommendation to socio-economic dynamics. We argue that an effective similarity measurement should guarantee the stability even under some information loss. With six bipartite networks, we investigate the stabilities of fifteen similarity measurements by comparing the similarity matrixes of two data samples which are randomly divided from original data sets. Results show that, the fifteen measurements can be well classified into three clusters according to their stabilities, and measurements in the same cluster have similar mathematical definitions. In addition, we develop a top-n-stability method for personalized recommendation, and find that the unstable similarities would recommend false information to users, and the performance of recommendation would be largely improved by using stable similarity measurements. This work provides a novel dimension to analyze and evaluate similarity measurements, which can further find applications in link prediction, personalized recommendation, clustering algorithms, community detection and so on.
Quantifying utricular stimulation during natural behavior

PubMed Central

Rivera, Angela R. V.; Davis, Julian; Grant, Wally; Blob, Richard W.; Peterson, Ellengene; Neiman, Alexander B.; Rowe, Michael

2012-01-01

The use of natural stimuli in neurophysiological studies has led to significant insights into the encoding strategies used by sensory neurons. To investigate these encoding strategies in vestibular receptors and neurons, we have developed a method for calculating the stimuli delivered to a vestibular organ, the utricle, during natural (unrestrained) behaviors, using the turtle as our experimental preparation. High-speed digital video sequences are used to calculate the dynamic gravito-inertial (GI) vector acting on the head during behavior. X-ray computed tomography (CT) scans are used to determine the orientation of the otoconial layer (OL) of the utricle within the head, and the calculated GI vectors are then rotated into the plane of the OL. Thus, the method allows us to quantify the spatio-temporal structure of stimuli to the OL during natural behaviors. In the future, these waveforms can be used as stimuli in neurophysiological experiments to understand how natural signals are encoded by vestibular receptors and neurons. We provide one example of the method which shows that turtle feeding behaviors can stimulate the utricle at frequencies higher than those typically used in vestibular studies. This method can be adapted to other species, to other vestibular end organs, and to other methods of quantifying head movements. PMID:22753360
Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network

PubMed Central

Wicks, Paul; Vaughan, Timothy; Pentland, Alex

2013-01-01

Background Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom
Disordered crystals from first principles I: Quantifying the configuration space

NASA Astrophysics Data System (ADS)

Kühne, Thomas D.; Prodan, Emil

2018-04-01

This work represents the first chapter of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures. We are interested in the range of temperatures, where most electronic components operate, that is, room temperature and above. The aim is a predictive first-principle formalism that combines ab-initio molecular dynamics and a finite-temperature Kubo-formula for homogeneous thermodynamic phases. The input for this formula is the ergodic dynamical system (Ω , G , dP) defining the thermodynamic crystalline phase, where Ω is the configuration space for the atomic degrees of freedom, G is the space group acting on Ω and dP is the ergodic Gibbs measure relative to the G-action. The present work develops an algorithmic method for quantifying (Ω , G , dP) from first principles. Using the silicon crystal as a working example, we find the Gibbs measure to be extremely well characterized by a multivariate normal distribution, which can be quantified using a small number of parameters. The latter are computed at various temperatures and communicated in the form of a table. Using this table, one can generate large and accurate thermally-disordered atomic configurations to serve, for example, as input for subsequent simulations of the electronic degrees of freedom.
Spatially quantifying and attributing 17 years of land cover change to examine post-agricultural forest transition in Hawai`i

NASA Astrophysics Data System (ADS)

Lucas, M.; Trauernicht, C.; Carlson, K. M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

2017-12-01

results directly link land management history to land cover outcomes using an innovative approach to quantify change. It is also the first study to quantify forest transition dynamics in Hawaii and points to the need for similar assessments in post-agricultural landscapes on other oceanic islands.
Dynamics of ecosystem services provided by subtropical ...

EPA Pesticide Factsheets

The trends in the provision of ecosystem services during restoration and succession of subtropical forests and plantations were quantified, in terms of both receiver and donor values, based on a case study of a 3-step secondary succession series that included a 400-year-old subtropical forest and a 23-year history of growth on 3 subtropical forest plantations in Southeastern China. The ‘People's Republic of China Forestry Standard: Forest Ecosystem Service Valuation Norms’ was revised and applied to quantify the receiver values of ecosystem services, which were then compared with the emergy-based, donor values of the services. The results revealed that the efficiencies of subtropical forests and plantations in providing ecosystem services were 2 orders of magnitude higher than similar services provided by the current China economic system, and these efficiencieskept increasing over the course of succession. As a result, we conclude that afforestation is an efficient way to accelerate both the ability and efficiency of subtropical forests to provide ecosystem services. This paper is significant because it examines the dynamics of the provision of ecosystem services by forests over a succession series that spans 400 years. The paper also examines the rate of increase of services during forest restoration over a period of 23 years. The emergy used in ecosystem services provision is compared to the provision of similar services by economic means in the Chinese e
Self-similar dynamics of air film entrained by a solid disk in confined space: A simple prototype of topological transitions

NASA Astrophysics Data System (ADS)

Nakazato, Hana; Yamagishi, Yuki; Okumura, Ko

2018-05-01

In hydrodynamic topological transitions, one mass of fluid breaks into two or two merge into one. For example, in honey-drop formation when honey is dripping from a spoon, honey is extended to separate into two masses as the liquid neck bridging them thins down to the micron scale. At the moment when the topology changes due to the breakup, physical observables such as surface curvature locally diverge. Such singular dynamics has widely attracted physicists, revealing universality in self-similar dynamics, which shares much in common with critical phenomena in thermodynamics. Many experimental examples have been found, including an electric spout and vibration-induced jet eruption. However, only a few cases have been physically understood on the basis of equations that govern the singular dynamics and even in such a case the physical understanding is mathematically complicated, inevitably involving delicate numerical calculations. Here we study the breakup of air film entrained by a solid disk into viscous liquid in a confined space, which leads to formation, thinning, and breakup of the neck of air. As a result, we unexpectedly find that equations governing the neck dynamics can be solved analytically by virtue of two remarkable experimental features: Only a single length scale linearly dependent on time remains near the singularity and two universal scaling functions describing the singular neck shape and velocity field are both analytic. The present solvable case would be essential for a better understanding of the singular dynamics and will help reveal the physics of unresolved examples intimately related to daily-life phenomena and diverse practical applications.
Quantifying resilience

USGS Publications Warehouse

Allen, Craig R.; Angeler, David G.

2016-01-01

Several frameworks to operationalize resilience have been proposed. A decade ago, a special feature focused on quantifying resilience was published in the journal Ecosystems (Carpenter, Westley & Turner 2005). The approach there was towards identifying surrogates of resilience, but few of the papers proposed quantifiable metrics. Consequently, many ecological resilience frameworks remain vague and difficult to quantify, a problem that this special feature aims to address. However, considerable progress has been made during the last decade (e.g. Pope, Allen & Angeler 2014). Although some argue that resilience is best kept as an unquantifiable, vague concept (Quinlan et al. 2016), to be useful for managers, there must be concrete guidance regarding how and what to manage and how to measure success (Garmestani, Allen & Benson 2013; Spears et al. 2015). Ideas such as ‘resilience thinking’ have utility in helping stakeholders conceptualize their systems, but provide little guidance on how to make resilience useful for ecosystem management, other than suggesting an ambiguous, Goldilocks approach of being just right (e.g. diverse, but not too diverse; connected, but not too connected). Here, we clarify some prominent resilience terms and concepts, introduce and synthesize the papers in this special feature on quantifying resilience and identify core unanswered questions related to resilience.
Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

PubMed

Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M

2016-11-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.
Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan

PubMed Central

Davison, Elizabeth N.; Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2016-01-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism—hypergraph cardinality—we investigate individual variations in two separate, complementary data sets. The first data set (“multi-task”) consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set (“age-memory”), in which 95 individuals, aged 18–75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain. PMID:27880785
Quantifying App Store Dynamics: Longitudinal Tracking of Mental Health Apps

PubMed Central

Nicholas, Jennifer; Christensen, Helen

2016-01-01

Background For many mental health conditions, mobile health apps offer the ability to deliver information, support, and intervention outside the clinical setting. However, there are difficulties with the use of a commercial app store to distribute health care resources, including turnover of apps, irrelevance of apps, and discordance with evidence-based practice. Objective The primary aim of this study was to quantify the longevity and rate of turnover of mental health apps within the official Android and iOS app stores. The secondary aim was to quantify the proportion of apps that were clinically relevant and assess whether the longevity of these apps differed from clinically nonrelevant apps. The tertiary aim was to establish the proportion of clinically relevant apps that included claims of clinical effectiveness. We performed additional subgroup analyses using additional data from the app stores, including search result ranking, user ratings, and number of downloads. Methods We searched iTunes (iOS) and the Google Play (Android) app stores each day over a 9-month period for apps related to depression, bipolar disorder, and suicide. We performed additional app-specific searches if an app no longer appeared within the main search Results On the Android platform, 50% of the search results changed after 130 days (depression), 195 days (bipolar disorder), and 115 days (suicide). Search results were more stable on the iOS platform, with 50% of the search results remaining at the end of the study period. Approximately 75% of Android and 90% of iOS apps were still available to download at the end of the study. We identified only 35.3% (347/982) of apps as being clinically relevant for depression, of which 9 (2.6%) claimed clinical effectiveness. Only 3 included a full citation to a published study. Conclusions The mental health app environment is volatile, with a clinically relevant app for depression becoming unavailable to download every 2.9 days. This poses
Adapting Document Similarity Measures for Ligand-Based Virtual Screening.

PubMed

Himmat, Mubarak; Salim, Naomie; Al-Dabbagh, Mohammed Mumtaz; Saeed, Faisal; Ahmed, Ali

2016-04-13

Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in virtual screening. In this work, we propose a similarity measure for ligand-based virtual screening, which has been derived from a text processing similarity measure. It has been adopted to be suitable for virtual screening; we called this proposed measure the Adapted Similarity Measure of Text Processing (ASMTP). For evaluating and testing the proposed ASMTP we conducted several experiments on two different benchmark datasets: the Maximum Unbiased Validation (MUV) and the MDL Drug Data Report (MDDR). The experiments have been conducted by choosing 10 reference structures from each class randomly as queries and evaluate them in the recall of cut-offs at 1% and 5%. The overall obtained results are compared with some similarity methods including the Tanimoto coefficient, which are considered to be the conventional and standard similarity coefficients for fingerprint-based similarity calculations. The achieved results show that the performance of ligand-based virtual screening is better and outperforms the Tanimoto coefficients and other methods.

Spiral Plating Method To Quantify the Six Major Non-O157 Escherichia coli Serogroups in Cattle Feces.

PubMed

Shridhar, Pragathi B; Noll, Lance W; Cull, Charley A; Shi, Xiaorong; Cernicchiaro, Natalia; Renter, David G; Bai, Jianfa; Nagaraja, T G

2017-04-17

Cattle are a major reservoir of the six major Shiga toxin-producing non-O157 Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) responsible for foodborne illnesses in humans. Besides prevalence in feces, the concentrations of STEC in cattle feces play a major role in their transmission dynamics. A subset of cattle, referred to as super shedders, shed E. coli O157 at high concentrations (≥4 log CFU/g of feces). It is not known whether a similar pattern of fecal shedding exists for non-O157. Our objectives were to initially validate the spiral plating method to quantify the six non-O157 E. coli serogroups with pure cultures and culture-spiked fecal samples and then determine the applicability of the method and compare it with multiplex quantitative PCR (mqPCR) assays for the quantification of the six non-O157 E. coli serogroups in cattle fecal samples collected from commercial feedlots. Quantification limits of the spiral plating method were 3 log, 3 to 4 log, and 3 to 5 log CFU/mL or CFU/g for individual cultures, pooled pure cultures, and cattle fecal samples spiked with pooled pure cultures, respectively. Of the 1,152 cattle fecal samples tested from eight commercial feedlots, 122 (10.6%) and 320 (27.8%) harbored concentrations ≥4 log CFU/g of one or more of the six serogroups of non-O157 by spiral plating and mqPCR methods, respectively. A majority of quantifiable samples, detected by either spiral plating (135 of 137, 98.5%) or mqPCR (239 of 320, 74.7%), were shedding only one serogroup. Only one of the quantifiable samples was positive for a serogroup carrying Shiga toxin (stx 1 ) and intimin (eae) genes; 38 samples were positive for serogroups carrying the intimin gene. In conclusion, the spiral plating method can be used to quantify non-O157 serogroups in cattle feces, and our study identified a subset of cattle that was super shedders of non-O157 E. coli . The method has the advantage of quantifying non-O157 STEC, unlike mqPCR that
A mathematical method for quantifying in vivo mechanical behaviour of heel pad under dynamic load.

PubMed

Naemi, Roozbeh; Chatzistergos, Panagiotis E; Chockalingam, Nachiappan

2016-03-01

Mechanical behaviour of the heel pad, as a shock attenuating interface during a foot strike, determines the loading on the musculoskeletal system during walking. The mathematical models that describe the force deformation relationship of the heel pad structure can determine the mechanical behaviour of heel pad under load. Hence, the purpose of this study was to propose a method of quantifying the heel pad stress-strain relationship using force-deformation data from an indentation test. The energy input and energy returned densities were calculated by numerically integrating the area below the stress-strain curve during loading and unloading, respectively. Elastic energy and energy absorbed densities were calculated as the sum of and the difference between energy input and energy returned densities, respectively. By fitting the energy function, derived from a nonlinear viscoelastic model, to the energy density-strain data, the elastic and viscous model parameters were quantified. The viscous and elastic exponent model parameters were significantly correlated with maximum strain, indicating the need to perform indentation tests at realistic maximum strains relevant to walking. The proposed method showed to be able to differentiate between the elastic and viscous components of the heel pad response to loading and to allow quantifying the corresponding stress-strain model parameters.
Quantifying climate feedbacks in polar regions

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

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

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

DOE PAGES

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

2018-05-15

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

PubMed

Kinoshita, Sachiko; Robidoux, Serje; Guilbert, Daniel; Norris, Dennis

2015-10-01

In visual word recognition tasks, digit primes that are visually similar to letter string targets (e.g., 4/A, 8/B) are known to facilitate letter identification relative to visually dissimilar digits (e.g., 6/A, 7/B); in contrast, with letter primes, visual similarity effects have been elusive. In the present study we show that the visual similarity effect with letter primes can be made to come and go, depending on whether it is necessary to discriminate between visually similar letters. The results support a Bayesian view which regards letter recognition not as a passive activation process driven by the fixed stimulus properties, but as a dynamic evidence accumulation process for a decision that is guided by the task context.
Scaling Relations and Self-Similarity of 3-Dimensional Reynolds-Averaged Navier-Stokes Equations.

PubMed

Ercan, Ali; Kavvas, M Levent

2017-07-25

Scaling conditions to achieve self-similar solutions of 3-Dimensional (3D) Reynolds-Averaged Navier-Stokes Equations, as an initial and boundary value problem, are obtained by utilizing Lie Group of Point Scaling Transformations. By means of an open-source Navier-Stokes solver and the derived self-similarity conditions, we demonstrated self-similarity within the time variation of flow dynamics for a rigid-lid cavity problem under both up-scaled and down-scaled domains. The strength of the proposed approach lies in its ability to consider the underlying flow dynamics through not only from the governing equations under consideration but also from the initial and boundary conditions, hence allowing to obtain perfect self-similarity in different time and space scales. The proposed methodology can be a valuable tool in obtaining self-similar flow dynamics under preferred level of detail, which can be represented by initial and boundary value problems under specific assumptions.
Quantifying hyporheic exchange dynamics in a highly regulated large river reach.

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

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

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

NASA Technical Reports Server (NTRS)

Pincus, S. M.; Goldberger, A. L.

1994-01-01

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity that appears to have potential application to a wide variety of physiological and clinical time-series data. The focus here is to provide a better understanding of ApEn to facilitate its proper utilization, application, and interpretation. After giving the formal mathematical description of ApEn, we provide a multistep description of the algorithm as applied to two contrasting clinical heart rate data sets. We discuss algorithm implementation and interpretation and introduce a general mathematical hypothesis of the dynamics of a wide class of diseases, indicating the utility of ApEn to test this hypothesis. We indicate the relationship of ApEn to variability measures, the Fourier spectrum, and algorithms motivated by study of chaotic dynamics. We discuss further mathematical properties of ApEn, including the choice of input parameters, statistical issues, and modeling considerations, and we conclude with a section on caveats to ensure correct ApEn utilization.
Actively heated high-resolution fiber-optic-distributed temperature sensing to quantify streambed flow dynamics in zones of strong groundwater upwelling

USGS Publications Warehouse

Briggs, Martin A.; Buckley, Sean F.; Bagtzoglou, Amvrossios C.; Werkema, Dale D.; Lane, John W.

2016-01-01

Zones of strong groundwater upwelling to streams enhance thermal stability and moderate thermal extremes, which is particularly important to aquatic ecosystems in a warming climate. Passive thermal tracer methods used to quantify vertical upwelling rates rely on downward conduction of surface temperature signals. However, moderate to high groundwater flux rates (>−1.5 m d−1) restrict downward propagation of diurnal temperature signals, and therefore the applicability of several passive thermal methods. Active streambed heating from within high-resolution fiber-optic temperature sensors (A-HRTS) has the potential to define multidimensional fluid-flux patterns below the extinction depth of surface thermal signals, allowing better quantification and separation of local and regional groundwater discharge. To demonstrate this concept, nine A-HRTS were emplaced vertically into the streambed in a grid with ∼0.40 m lateral spacing at a stream with strong upward vertical flux in Mashpee, Massachusetts, USA. Long-term (8–9 h) heating events were performed to confirm the dominance of vertical flow to the 0.6 m depth, well below the extinction of ambient diurnal signals. To quantify vertical flux, short-term heating events (28 min) were performed at each A-HRTS, and heat-pulse decay over vertical profiles was numerically modeled in radial two dimension (2-D) using SUTRA. Modeled flux values are similar to those obtained with seepage meters, Darcy methods, and analytical modeling of shallow diurnal signals. We also observed repeatable differential heating patterns along the length of vertically oriented sensors that may indicate sediment layering and hyporheic exchange superimposed on regional groundwater discharge.
Data Used in Quantified Reliability Models

NASA Technical Reports Server (NTRS)

DeMott, Diana; Kleinhammer, Roger K.; Kahn, C. J.

2014-01-01

Data is the crux to developing quantitative risk and reliability models, without the data there is no quantification. The means to find and identify reliability data or failure numbers to quantify fault tree models during conceptual and design phases is often the quagmire that precludes early decision makers consideration of potential risk drivers that will influence design. The analyst tasked with addressing a system or product reliability depends on the availability of data. But, where is does that data come from and what does it really apply to? Commercial industries, government agencies, and other international sources might have available data similar to what you are looking for. In general, internal and external technical reports and data based on similar and dissimilar equipment is often the first and only place checked. A common philosophy is "I have a number - that is good enough". But, is it? Have you ever considered the difference in reported data from various federal datasets and technical reports when compared to similar sources from national and/or international datasets? Just how well does your data compare? Understanding how the reported data was derived, and interpreting the information and details associated with the data is as important as the data itself.
Thermo-fluid-dynamics of natural convection around a heated vertical plate with a critical assessment of the standard similarity theory

NASA Astrophysics Data System (ADS)

Guha, Abhijit; Nayek, Subhajit

2017-10-01

A compulsory element of all textbooks on natural convection has been a detailed similarity analysis for laminar natural convection on a heated semi-infinite vertical plate and a routinely used boundary condition for such analysis is u = 0 at x = 0. The same boundary condition continues to be assumed in related theoretical analyses, even in recent publications. The present work examines the consequence of this long-held assumption, which appears to have never been questioned in the literature, on the fluid dynamics and heat transfer characteristics. The assessment has been made here by solving the Navier-Stokes equations numerically with two boundary conditions—one with constrained velocity at x = 0 to mimic the similarity analysis and the other with no such constraints simulating the case of a heated vertical plate in an infinite expanse of the quiescent fluid medium. It is found that the fluid flow field given by the similarity theory is drastically different from that given by the computational fluid dynamics (CFD) simulations with unconstrained velocity. This also reflects on the Nusselt number, the prediction of the CFD simulations with unconstrained velocity being quite close to the experimentally measured values at all Grashof and Prandtl numbers (this is the first time theoretically computed values of the average Nusselt number N u ¯ are found to be so close to the experimental values). The difference of the Nusselt number (Δ N u ¯ ) predicted by the similarity theory and that by the CFD simulations (as well as the measured values), both computed with a high degree of precision, can be very significant, particularly at low Grashof numbers and at Prandtl numbers far removed from unity. Computations show that within the range of investigations (104 ≤ GrL ≤ 108, 0.01 ≤ Pr ≤ 100), the maximum value of Δ N u ¯ may be of the order 50%. Thus, for quantitative predictions, the available theory (i.e., similarity analysis) can be rather inadequate. With
Quantifying the buildup in extent and complexity of free exploration in mice

PubMed Central

Benjamini, Yoav; Fonio, Ehud; Galili, Tal; Havkin, Gregor Z.; Golani, Ilan

2011-01-01

To obtain a perspective on an animal's own functional world, we study its behavior in situations that allow the animal to regulate the growth rate of its behavior and provide us with the opportunity to quantify its moment-by-moment developmental dynamics. Thus, we are able to show that mouse exploratory behavior consists of sequences of repeated motion: iterative processes that increase in extent and complexity, whose presumed function is a systematic active management of input acquired during the exploration of a novel environment. We use this study to demonstrate our approach to quantifying behavior: targeting aspects of behavior that are shown to be actively managed by the animal, and using measures that are discriminative across strains and treatments and replicable across laboratories. PMID:21383149
Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

PubMed Central

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

2013-01-01

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

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

Tiana-Alsina, J.; Torrent, M. C.; Masoller, C.

Low-frequency fluctuations (LFFs) represent a dynamical instability that occurs in semiconductor lasers when they are operated near the lasing threshold and subject to moderate optical feedback. LFFs consist of sudden power dropouts followed by gradual, stepwise recoveries. We analyze experimental time series of intensity dropouts and quantify the complexity of the underlying dynamics employing two tools from information theory, namely, Shannon's entropy and the Martin, Plastino, and Rosso statistical complexity measure. These measures are computed using a method based on ordinal patterns, by which the relative length and ordering of consecutive interdropout intervals (i.e., the time intervals between consecutive intensitymore » dropouts) are analyzed, disregarding the precise timing of the dropouts and the absolute durations of the interdropout intervals. We show that this methodology is suitable for quantifying subtle characteristics of the LFFs, and in particular the transition to fully developed chaos that takes place when the laser's pump current is increased. Our method shows that the statistical complexity of the laser does not increase continuously with the pump current, but levels off before reaching the coherence collapse regime. This behavior coincides with that of the first- and second-order correlations of the interdropout intervals, suggesting that these correlations, and not the chaotic behavior, are what determine the level of complexity of the laser's dynamics. These results hold for two different dynamical regimes, namely, sustained LFFs and coexistence between LFFs and steady-state emission.« less
A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Singh, Surya Prakash

2017-11-01

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10-30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine-cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.
The devil is in the detail: Quantifying vocal variation in a complex, multi-levelled, and rapidly evolving display.

PubMed

Garland, Ellen C; Rendell, Luke; Lilley, Matthew S; Poole, M Michael; Allen, Jenny; Noad, Michael J

2017-07-01

Identifying and quantifying variation in vocalizations is fundamental to advancing our understanding of processes such as speciation, sexual selection, and cultural evolution. The song of the humpback whale (Megaptera novaeangliae) presents an extreme example of complexity and cultural evolution. It is a long, hierarchically structured vocal display that undergoes constant evolutionary change. Obtaining robust metrics to quantify song variation at multiple scales (from a sound through to population variation across the seascape) is a substantial challenge. Here, the authors present a method to quantify song similarity at multiple levels within the hierarchy. To incorporate the complexity of these multiple levels, the calculation of similarity is weighted by measurements of sound units (lower levels within the display) to bridge the gap in information between upper and lower levels. Results demonstrate that the inclusion of weighting provides a more realistic and robust representation of song similarity at multiple levels within the display. This method permits robust quantification of cultural patterns and processes that will also contribute to the conservation management of endangered humpback whale populations, and is applicable to any hierarchically structured signal sequence.
Using nonlinear methods to quantify changes in infant limb movements and vocalizations.

PubMed

Abney, Drew H; Warlaumont, Anne S; Haussman, Anna; Ross, Jessica M; Wallot, Sebastian

2014-01-01

The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior.
Using nonlinear methods to quantify changes in infant limb movements and vocalizations

PubMed Central

Abney, Drew H.; Warlaumont, Anne S.; Haussman, Anna; Ross, Jessica M.; Wallot, Sebastian

2014-01-01

The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior. PMID:25161629
Investigation of injection dose and camera integration time on quantifying pharmacokinetics of a Cy5.5-GX1 probe with dynamic fluorescence imaging in vivo

NASA Astrophysics Data System (ADS)

Dai, Yunpeng; Chen, Xueli; Yin, Jipeng; Kang, Xiaoyu; Wang, Guodong; Zhang, Xianghan; Nie, Yongzhan; Wu, Kaichun; Liang, Jimin

2016-08-01

The aim of this article is to investigate the influence of a tracer injection dose (ID) and camera integration time (IT) on quantifying pharmacokinetics of Cy5.5-GX1 in gastric cancer BGC-823 cell xenografted mice. Based on three factors, including whether or not to inject free GX1, the ID of Cy5.5-GX1, and the camera IT, 32 mice were randomly divided into eight groups and received 60-min dynamic fluorescence imaging. Gurfinkel exponential model (GEXPM) and Lammertsma simplified reference tissue model (SRTM) combined with a singular value decomposition analysis were used to quantitatively analyze the acquired dynamic fluorescent images. The binding potential (Bp) and the sum of the pharmacokinetic rate constants (SKRC) of Cy5.5-GX1 were determined by the SRTM and EXPM, respectively. In the tumor region, the SKRC value exhibited an obvious trend with change in the tracer ID, but the Bp value was not sensitive to it. Both the Bp and SKRC values were independent of the camera IT. In addition, the ratio of the tumor-to-muscle region was correlated with the camera IT but was independent of the tracer ID. Dynamic fluorescence imaging in conjunction with a kinetic analysis may provide more quantitative information than static fluorescence imaging, especially for a priori information on the optimal ID of targeted probes for individual therapy.
Neural basis for generalized quantifier comprehension.

PubMed

McMillan, Corey T; Clark, Robin; Moore, Peachie; Devita, Christian; Grossman, Murray

2005-01-01

Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.

In vivo D2O labeling to quantify static and dynamic changes in cholesterol and cholesterol esters by high resolution LC/MS[S

PubMed Central

Castro-Perez, Jose; Previs, Stephen F.; McLaren, David G.; Shah, Vinit; Herath, Kithsiri; Bhat, Gowri; Johns, Douglas G.; Wang, Sheng-Ping; Mitnaul, Lyndon; Jensen, Kristian; Vreeken, Robert; Hankemeier, Thomas; Roddy, Thomas P.; Hubbard, Brian K.

2011-01-01

High resolution LC/MS-MS and LC/APPI-MS methods have been established for the quantitation of flux in the turnover of cholesterol and cholesterol ester. Attention was directed toward quantifying the monoisotopic mass (M0) and that of the singly deuterated labeled (M+1) isotope. A good degree of isotopic dynamic range has been achieved by LC/MS-MS ranging from 3-4 orders of magnitude. Correlation between the linearity of GC/MS and LC atmospheric pressure photoionization (APPI)-MS are complimentary (r2 = 0.9409). To prove the viability of this particular approach, male C57Bl/6 mice on either a high carbohydrate (HC) or a high fat (HF) diet were treated with 2H2O for 96 h. Gene expression analysis showed an increase in the activity of stearoyl-CoA desaturase (Scd1) in the HC diet up to 69-fold (P < 0.0008) compared with the HF diet. This result was supported by the quantitative flux measurement of the isotopic incorporation of 2H into the respective cholesterol and cholesterol ester (CE) pools. We concluded that it is possible to readily obtain static and dynamic measurement of cholesterol and CEs in vivo by coupling novel LC/MS methods with stable isotope-based protocols. PMID:20884843
Quantifying Variability in Growth and Thermal Inactivation Kinetics of Lactobacillus plantarum.

PubMed

Aryani, D C; den Besten, H M W; Zwietering, M H

2016-08-15

The presence and growth of spoilage organisms in food might affect the shelf life. In this study, the effects of experimental, reproduction, and strain variabilities were quantified with respect to growth and thermal inactivation using 20 Lactobacillus plantarum strains. Also, the effect of growth history on thermal resistance was quantified. The strain variability in μmax was similar (P > 0.05) to reproduction variability as a function of pH, aw, and temperature, while being around half of the reproduction variability (P < 0.05) as a function of undissociated lactic acid concentration [HLa]. The cardinal growth parameters were estimated for the L. plantarum strains, and the pHmin was between 3.2 and 3.5, the aw,min was between 0.936 and 0.953, the [HLamax], at pH 4.5, was between 29 and 38 mM, and the Tmin was between 3.4 and 8.3°C. The average D values ranged from 0.80 min to 19 min at 55°C, 0.22 to 3.9 min at 58°C, 3.1 to 45 s at 60°C, and 1.8 to 19 s at 63°C. In contrast to growth, the strain variability in thermal resistance was on average six times higher than the reproduction variability and more than ten times higher than the experimental variability. The strain variability was also 1.8 times higher (P < 0.05) than the effect of growth history. The combined effects of strain variability and growth history on D value explained all of the variability as found in the literature, although with bias. Based on an illustrative milk-processing chain, strain variability caused ∼2-log10 differences in growth between the most and least robust strains and >10-log10 differences after thermal treatment. Accurate control and realistic prediction of shelf life is complicated by the natural diversity among microbial strains, and limited information on microbiological variability is available for spoilage microorganisms. Therefore, the objectives of the present study were to quantify strain variability, reproduction (biological) variability, and experimental
Quantifying phalangeal curvature: an empirical comparison of alternative methods.

PubMed

Stern, J T; Jungers, W L; Susman, R L

1995-05-01

It has been generally assumed and theoretically argued that the curvature of finger and toe bones seen in some nonhuman primates is associated with cheiridial use in an arboreal setting. Assessment of such curvature in fossil primates has been used to infer the positional behavior of these animals. Several methods of quantifying curvature of bones have been proposed. The measure most commonly applied to phalanges is that of included angle, but this has come under some criticism. We consider various other approaches for quantifying phalangeal curvature, demonstrating that some are equivalent to use of included angle, but that one--normalized curvature moment arm (NCMA)--represents a true alternative. A comparison of NCMA to included angle, both calculated on manual and pedal proximal phalanges of humans, apes, some monkeys, and the Hadar fossils, revealed that these two different measures of curvature are highly correlated and result in very similar distributional patterns.
Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

PubMed Central

Bischofs, Ilka; Price, Gavin; Keasling, Jay; Arkin, Adam P.

2008-01-01

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy. PMID:18324309
The baryonic self similarity of dark matter

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

Alard, C., E-mail: alard@iap.fr

2014-06-20

The cosmological simulations indicates that dark matter halos have specific self-similar properties. However, the halo similarity is affected by the baryonic feedback. By using momentum-driven winds as a model to represent the baryon feedback, an equilibrium condition is derived which directly implies the emergence of a new type of similarity. The new self-similar solution has constant acceleration at a reference radius for both dark matter and baryons. This model receives strong support from the observations of galaxies. The new self-similar properties imply that the total acceleration at larger distances is scale-free, the transition between the dark matter and baryons dominatedmore » regime occurs at a constant acceleration, and the maximum amplitude of the velocity curve at larger distances is proportional to M {sup 1/4}. These results demonstrate that this self-similar model is consistent with the basics of modified Newtonian dynamics (MOND) phenomenology. In agreement with the observations, the coincidence between the self-similar model and MOND breaks at the scale of clusters of galaxies. Some numerical experiments show that the behavior of the density near the origin is closely approximated by a Einasto profile.« less
Quantifying the effects of land use and climate on Holocene vegetation in Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph M.; Jönsson, Anna Maria; Smith, Benjamin; Kaplan, Jed O.; Alenius, Teija; Birks, H. John B.; Bjune, Anne E.; Christiansen, Jörg; Dodson, John; Edwards, Kevin J.; Giesecke, Thomas; Herzschuh, Ulrike; Kangur, Mihkel; Koff, Tiiu; Latałowa, Małgorzata; Lechterbeck, Jutta; Olofsson, Jörgen; Seppä, Heikki

2017-09-01

Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen-based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming
Quantifying geomorphic controls on riparian forest dynamics using a linked physical-biological model: implications for river corridor conservation

NASA Astrophysics Data System (ADS)

Stella, J. C.; Harper, E. B.; Fremier, A. K.; Hayden, M. K.; Battles, J. J.

2009-12-01

In high-order alluvial river systems, physical factors of flooding and channel migration are particularly important drivers of riparian forest dynamics because they regulate habitat creation, resource fluxes of water, nutrients and light that are critical for growth, and mortality from fluvial disturbance. Predicting vegetation composition and dynamics at individual sites in this setting is challenging, both because of the stochastic nature of the flood regime and the spatial variability of flood events. Ecological models that correlate environmental factors with species’ occurrence and abundance (e.g., ’niche models’) often work well in infrequently-disturbed upland habitats, but are less useful in river corridors and other dynamic zones where environmental conditions fluctuate greatly and selection pressures on disturbance-adapted organisms are complex. In an effort to help conserve critical riparian forest habitat along the middle Sacramento River, CA, we are taking a mechanistic approach to quantify linkages between fluvial and biotic processes for Fremont cottonwood (Populus fremontii), a keystone pioneer tree in dryland rivers ecosystems of the U.S. Southwest. To predict the corridor-wide population effects of projected changes to the disturbance regime from flow regulation, climate change, and landscape modifications, we have coupled a physical model of channel meandering with a patch-based population model that incorporates the climatic, hydrologic, and topographic factors critical for tree recruitment and survival. We employed these linked simulations to study the relative influence of the two most critical habitat types--point bars and abandoned channels--in sustaining the corridor-wide cottonwood population over a 175-year period. The physical model uses discharge data and channel planform to predict the spatial distribution of new habitat patches; the population model runs on top of this physical template to track tree colonization and survival on
Quantifier Comprehension in Corticobasal Degeneration

ERIC Educational Resources Information Center

McMillan, Corey T.; Clark, Robin; Moore, Peachie; Grossman, Murray

2006-01-01

In this study, we investigated patients with focal neurodegenerative diseases to examine a formal linguistic distinction between classes of generalized quantifiers, like "some X" and "less than half of X." Our model of quantifier comprehension proposes that number knowledge is required to understand both first-order and higher-order quantifiers.…
Towards a unified description of the hydrogen bond network of liquid water: A dynamics based approach

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

Ozkanlar, Abdullah, E-mail: abdullah.ozkanlar@wsu.edu; Zhou, Tiecheng; Clark, Aurora E., E-mail: auclark@wsu.edu

2014-12-07

The definition of a hydrogen bond (H-bond) is intimately related to the topological and dynamic properties of the hydrogen bond network within liquid water. The development of a universal H-bond definition for water is an active area of research as it would remove many ambiguities in the network properties that derive from the fixed definition employed to assign whether a water dimer is hydrogen bonded. This work investigates the impact that an electronic-structure based definition, an energetic, and a geometric definition of the H-bond has upon both topological and dynamic network behavior of simulated water. In each definition, the usemore » of a cutoff (either geometric or energetic) to assign the presence of a H-bond leads to the formation of transiently bonded or broken dimers, which have been quantified within the simulation data. The relative concentration of transient species, and their duration, results in two of the three definitions sharing similarities in either topological or dynamic features (H-bond distribution, H-bond lifetime, etc.), however no two definitions exhibit similar behavior for both classes of network properties. In fact, two networks with similar local network topology (as indicated by similar average H-bonds) can have dramatically different global network topology (as indicated by the defect state distributions) and altered H-bond lifetimes. A dynamics based correction scheme is then used to remove artificially transient H-bonds and to repair artificially broken bonds within the network such that the corrected network exhibits the same structural and dynamic properties for two H-bond definitions (the properties of the third definition being significantly improved). The algorithm described represents a significant step forward in the development of a unified hydrogen bond network whose properties are independent of the original hydrogen bond definition that is employed.« less
Modular interdependency in complex dynamical systems.

PubMed

Watson, Richard A; Pollack, Jordan B

2005-01-01

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

EPA Pesticide Factsheets

.The Diesel Emissions Quantifier (Quantifier) is an interactive tool to estimate emission reductions and cost effectiveness. Publications EPA-420-F-13-008a (420f13008a), EPA-420-B-10-035 (420b10023), EPA-420-B-10-034 (420b10034)
Relational Agreement Measures for Similarity Searching of Cheminformatic Data Sets.

PubMed

Rivera-Borroto, Oscar Miguel; García-de la Vega, José Manuel; Marrero-Ponce, Yovani; Grau, Ricardo

2016-01-01

Research on similarity searching of cheminformatic data sets has been focused on similarity measures using fingerprints. However, nominal scales are the least informative of all metric scales, increasing the tied similarity scores, and decreasing the effectivity of the retrieval engines. Tanimoto's coefficient has been claimed to be the most prominent measure for this task. Nevertheless, this field is far from being exhausted since the computer science no free lunch theorem predicts that "no similarity measure has overall superiority over the population of data sets". We introduce 12 relational agreement (RA) coefficients for seven metric scales, which are integrated within a group fusion-based similarity searching algorithm. These similarity measures are compared to a reference panel of 21 proximity quantifiers over 17 benchmark data sets (MUV), by using informative descriptors, a feature selection stage, a suitable performance metric, and powerful comparison tests. In this stage, RA coefficients perform favourably with repect to the state-of-the-art proximity measures. Afterward, the RA-based method outperform another four nearest neighbor searching algorithms over the same data domains. In a third validation stage, RA measures are successfully applied to the virtual screening of the NCI data set. Finally, we discuss a possible molecular interpretation for these similarity variants.
Quantification of cardiorespiratory interactions based on joint symbolic dynamics.

PubMed

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

2011-10-01

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

NASA Astrophysics Data System (ADS)

Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Groussat, Mathieu; Brunagel, Pierre

2007-12-01

A new similarity measure, called SimilB, for time series analysis, based on the cross-[InlineEquation not available: see fulltext.]-energy operator (2004), is introduced. [InlineEquation not available: see fulltext.] is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED) or the Pearson correlation coefficient (CC), SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of [InlineEquation not available: see fulltext.] are presented. Particularly, we show that [InlineEquation not available: see fulltext.] as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.
Quantifying Transmission.

PubMed

Woolhouse, Mark

2017-07-01

Transmissibility is the defining characteristic of infectious diseases. Quantifying transmission matters for understanding infectious disease epidemiology and designing evidence-based disease control programs. Tracing individual transmission events can be achieved by epidemiological investigation coupled with pathogen typing or genome sequencing. Individual infectiousness can be estimated by measuring pathogen loads, but few studies have directly estimated the ability of infected hosts to transmit to uninfected hosts. Individuals' opportunities to transmit infection are dependent on behavioral and other risk factors relevant given the transmission route of the pathogen concerned. Transmission at the population level can be quantified through knowledge of risk factors in the population or phylogeographic analysis of pathogen sequence data. Mathematical model-based approaches require estimation of the per capita transmission rate and basic reproduction number, obtained by fitting models to case data and/or analysis of pathogen sequence data. Heterogeneities in infectiousness, contact behavior, and susceptibility can have substantial effects on the epidemiology of an infectious disease, so estimates of only mean values may be insufficient. For some pathogens, super-shedders (infected individuals who are highly infectious) and super-spreaders (individuals with more opportunities to transmit infection) may be important. Future work on quantifying transmission should involve integrated analyses of multiple data sources.
Quantifying the resilience of carbon dynamics in semi-arid biomes in the Southwestern U.S. to drought

NASA Astrophysics Data System (ADS)

Litvak, M. E.; Krofcheck, D. J.; Maurer, G.

2015-12-01

Semi-arid biomes in many parts of the Southwestern U.S. have experienced a range of precipitation over the last decade, ranging from wetter than average years 2006-2010 (relative to the 40-year PRISM mean), extreme drought years (2010-2011) and slightly dry-average precipitation years (2013-2015). While annual carbon uptake in semi-arid biomes of the Southwestern US is relatively low, compared to more temperate ecosystems, collectively these biomes store a significant amount of carbon on a regional scale. It is therefore of great interest to understand what impact this range in precipitation variability has on inter- and intra- annual variability in regional carbon dynamics. We use an 9 year record from 2007-2015 of continuous measurements of net ecosystem exchange of carbon (NEE) and its components (gross primary productivity (GPP) and ecosystem respiration (Re), made across a network of flux towers along an elevation/aridity gradient in New Mexico, the New Mexico Elevation Gradient (NMEG), to quantify biome-specific responses of carbon dynamics to climate variability over this time period. Biomes include a desert grassland, creosote shrubland, juniper savanna, piñon-juniper woodland, and ponderosa pine and subalpine mixed conifer forests. We compared daily, seasonal and annual NEP, GPP and Re means between pre-drought (2007-2010), drought (2011-2012), and post-drought years (2013-2015). All biomes sequestered less carbon in the drought years, compared to the pre-drought years (~30-40, 270 and 60 g C/m2 less in low and middle elevation biomes, ponderosa pine, and mixed conifer forest, respectively), as GPP in all biomes was more sensitive to the drought than Re. In the post-drought years, GPP was still only 80-90% what it was in the pre-drought years. Re, however, in all biomes except for the creosote shrubland, was 5-15% higher in the post-drought years compared to pre-drought. As a result, carbon sequestration in these biomes was 20-75% lower in the post
Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

NASA Astrophysics Data System (ADS)

Cox, Dana C.; Lo, Jane-Jane

2014-03-01

This study is focused on identifying and describing the reasoning patterns of middle grade students when examining potentially similar figures. Described here is a framework that includes 11 strategies that students used during clinical interview to differentiate similar and non-similar figures. Two factors were found to influence the strategies students selected: the complexity of the figures being compared and the type of distortion present in nonsimilar pairings. Data from this study support the theory that distortions are identified as a dominant property of figures and that students use the presence and absence of distortion to visually decide if two figures are similar. Furthermore, this study shows that visual reasoning is not as primitive or nonconstructive as represented in earlier literature and supports students who are developing numeric reasoning strategies. This illuminates possible pathways students may take when advancing from using visual and additive reasoning strategies to using multiplicative proportional reasoning on similarity tasks. In particular, distortion detection is a visual activity that enables students to reflect upon and evaluate the validity and accuracy of differentiation and quantify perceived relationships leading to ratio. This study has implications for curriculum developers as well as future research.
Quantifying the dynamic wing morphing of hovering hummingbird

PubMed Central

Nakata, Toshiyuki; Kitamura, Ikuo; Tanaka, Hiroto

2017-01-01

Animal wings are lightweight and flexible; hence, during flapping flight their shapes change. It has been known that such dynamic wing morphing reduces aerodynamic cost in insects, but the consequences in vertebrate flyers, particularly birds, are not well understood. We have developed a method to reconstruct a three-dimensional wing model of a bird from the wing outline and the feather shafts (rachides). The morphological and kinematic parameters can be obtained using the wing model, and the numerical or mechanical simulations may also be carried out. To test the effectiveness of the method, we recorded the hovering flight of a hummingbird (Amazilia amazilia) using high-speed cameras and reconstructed the right wing. The wing shape varied substantially within a stroke cycle. Specifically, the maximum and minimum wing areas differed by 18%, presumably due to feather sliding; the wing was bent near the wrist joint, towards the upward direction and opposite to the stroke direction; positive upward camber and the ‘washout’ twist (monotonic decrease in the angle of incidence from the proximal to distal wing) were observed during both half-strokes; the spanwise distribution of the twist was uniform during downstroke, but an abrupt increase near the wrist joint was found during upstroke. PMID:28989736
Self-similarity analysis of eubacteria genome based on weighted graph.

PubMed

Qi, Zhao-Hui; Li, Ling; Zhang, Zhi-Meng; Qi, Xiao-Qin

2011-07-07

We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome. In our model, each genome is attributed to a weighted graph, whose topology describes the similarity relationship among genes in the same genome. Based on the related weighted graph theory, we extract some quantified statistical variables from the topology, and give the distribution of some variables derived from the largest social structure in the topology. The 23 eubacteria recently studied by Sorimachi and Okayasu are markedly classified into two different groups by their double logarithmic point-plots describing the similarity relationship among genes of the largest social structure in genome. The results show that the proposed model may provide us with some new sights to understand the structures and evolution patterns determined from the complete genomes. Copyright © 2011 Elsevier Ltd. All rights reserved.

NaviGO: interactive tool for visualization and functional similarity and coherence analysis with gene ontology.

PubMed

Wei, Qing; Khan, Ishita K; Ding, Ziyun; Yerneni, Satwica; Kihara, Daisuke

2017-03-20

The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enable fast and automatic function annotation. With the well-defined structure and manual curation, Gene Ontology (GO) is the most frequently used vocabulary for representing gene functions. To understand relationship and similarity between GO annotations of genes, it is important to have a convenient pipeline that quantifies and visualizes the GO function analyses in a systematic fashion. NaviGO is a web-based tool for interactive visualization, retrieval, and computation of functional similarity and associations of GO terms and genes. Similarity of GO terms and gene functions is quantified with six different scores including protein-protein interaction and context based association scores we have developed in our previous works. Interactive navigation of the GO function space provides intuitive and effective real-time visualization of functional groupings of GO terms and genes as well as statistical analysis of enriched functions. We developed NaviGO, which visualizes and analyses functional similarity and associations of GO terms and genes. The NaviGO webserver is freely available at: http://kiharalab.org/web/navigo .
Quantifying nonhomogeneous colors in agricultural materials part I: method development.

PubMed

Balaban, M O

2008-11-01

Measuring the color of food and agricultural materials using machine vision (MV) has advantages not available by other measurement methods such as subjective tests or use of color meters. The perception of consumers may be affected by the nonuniformity of colors. For relatively uniform colors, average color values similar to those given by color meters can be obtained by MV. For nonuniform colors, various image analysis methods (color blocks, contours, and "color change index"[CCI]) can be applied to images obtained by MV. The degree of nonuniformity can be quantified, depending on the level of detail desired. In this article, the development of the CCI concept is presented. For images with a wide range of hue values, the color blocks method quantifies well the nonhomogeneity of colors. For images with a narrow hue range, the CCI method is a better indicator of color nonhomogeneity.
Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...
Earthquake Fingerprints: Representing Earthquake Waveforms for Similarity-Based Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2016-12-01

New earthquake detection methods, such as Fingerprint and Similarity Thresholding (FAST), use fast approximate similarity search to identify similar waveforms in long-duration data without templates (Yoon et al. 2015). These methods have two key components: fingerprint extraction and an efficient search algorithm. Fingerprint extraction converts waveforms into fingerprints, compact signatures that represent short-duration waveforms for identification and search. Earthquakes are detected using an efficient indexing and search scheme, such as locality-sensitive hashing, that identifies similar waveforms in a fingerprint database. The quality of the search results, and thus the earthquake detection results, is strongly dependent on the fingerprinting scheme. Fingerprint extraction should map similar earthquake waveforms to similar waveform fingerprints to ensure a high detection rate, even under additive noise and small distortions. Additionally, fingerprints corresponding to noise intervals should have mutually dissimilar fingerprints to minimize false detections. In this work, we compare the performance of multiple fingerprint extraction approaches for the earthquake waveform similarity search problem. We apply existing audio fingerprinting (used in content-based audio identification systems) and time series indexing techniques and present modified versions that are specifically adapted for seismic data. We also explore data-driven fingerprinting approaches that can take advantage of labeled or unlabeled waveform data. For each fingerprinting approach we measure its ability to identify similar waveforms in a low signal-to-noise setting, and quantify the trade-off between true and false detection rates in the presence of persistent noise sources. We compare the performance using known event waveforms from eight independent stations in the Northern California Seismic Network.
Effect of Glycerol Water Binary Mixtures on the Structure and Dynamics of Protein Solutions

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

Ghattyvenkatakrishna, Pavan K; Carri, Gustavo A.

We have performed 20ns of fully atomistic molecular dynamics simulations of Hen Egg-White Lysozyme in 0, 10, 20, 30 and 100% by weight of glycerol in water to better understand the microscopic physics behind the bioprotection offered by glycerol to naturally occuring biological systems. The sovlent exposure of protein surface residues changes when glycerol is introduced. The dynamic behavior of the protein, as quantified by the Incoherent Intermediate Scattering Function, shows a non-monotonic dependence on glycerol content. The fluctuations of the protein residues with respect to each other were found to be similar in all water containing solvents; but differentmore » from the pure glycerol case. The increase in the number of protein glycerol hydrogen bonds in glycerol water binary mixtures explains the slowing down of protein dynamics as the glycerol content increases. We also explored the dynamic behavior of the hydration layer. We show that the short-length scale dynamics of this layer are insenstive to glycerol concentration. However, the long-length scale behavior shows a significant dependence on glycerol content. We also provide insights into the behavior of bound and mobile water molecules.« less
A framework for quantifying and optimizing the value of seismic monitoring of infrastructure

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr

2017-04-01

This paper outlines a framework for quantifying and optimizing the value of information from structural health monitoring (SHM) technology deployed on large infrastructure, which may sustain damage in a series of earthquakes (the main and the aftershocks). The evolution of the damage state of the infrastructure without or with SHM is presented as a time-dependent, stochastic, discrete-state, observable and controllable nonlinear dynamical system. The pre-posterior Bayesian analysis and the decision tree are used for quantifying and optimizing the value of SHM information. An optimality problem is then formulated how to decide on the adoption of SHM and how to manage optimally the usage and operations of the possibly damaged infrastructure and its repair schedule using the information from SHM. The objective function to minimize is the expected total cost or risk.
Protein structure similarity from Principle Component Correlation analysis.

PubMed

Zhou, Xiaobo; Chou, James; Wong, Stephen T C

2006-01-25

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC) analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum eigenvalues can be highly effective in clustering structurally or
Fractal Dynamics of Heartbeat Interval Fluctuations in Health and Disease

NASA Astrophysics Data System (ADS)

Meyer, M.; Marconi, C.; Rahmel, A.; Grassi, B.; Ferretti, G.; Skinner, J. E.; Cerretelli, P.

The dynamics of heartbeat interval time series were studied by a modified random walk analysis recently introduced as Detrended Fluctuation Analysis. In this analysis, the intrinsic fractal long-range power-law correlation properties of beat-to-beat fluctuations generated by the dynamical system (i.e. cardiac rhythm generator), after decomposition from extrinsic uncorrelated sources, can be quantified by the scaling exponent which, in healthy subjects, is about 1.0. The finding of a scaling coefficient of 1.0, indicating scale-invariant long-range power-law correlations (1/ƒnoise) of heartbeat fluctuations, would reflect a genuinely self-similar fractal process that typically generates fluctuations on a wide range of time scales. Lack of a characteristic time scale suggests that the neuroautonomic system underlying the control of heart rate dynamics helps prevent excessive mode-locking (error tolerance) that would restrict its functional responsiveness (plasticity) to environmental stimuli. The 1/ƒ dynamics of heartbeat interval fluctuations are unaffected by exposure to chronic hypoxia suggesting that the neuroautonomic cardiac control system is preadapted to hypoxia. Functional (hypothermia, cardiac disease) and/or structural (cardiac transplantation, early cardiac development) inactivation of neuroautonomic control is associated with the breakdown or absence of fractal complexity reflected by anticorrelated random walk-like dynamics, indicating that in these conditions the heart is unadapted to its environment.
Quantifying uncertainties of climate signals related to the 11-year solar cycle

NASA Astrophysics Data System (ADS)

Kruschke, T.; Kunze, M.; Matthes, K. B.; Langematz, U.; Wahl, S.

2017-12-01

Although state-of-the-art reconstructions based on proxies and (semi-)empirical models converge in terms of total solar irradiance, they still significantly differ in terms of spectral solar irradiance (SSI) with respect to the mean spectral distribution of energy input and temporal variability. This study aims at quantifying uncertainties for the Earth's climate related to the 11-year solar cycle by forcing two chemistry-climate models (CCMs) - CESM1(WACCM) and EMAC - with five different SSI reconstructions (NRLSSI1, NRLSSI2, SATIRE-T, SATIRE-S, CMIP6-SSI) and the reference spectrum RSSV1-ATLAS3, derived from observations. We conduct a unique set of timeslice experiments. External forcings and boundary conditions are fixed and identical for all experiments, except for the solar forcing. The set of analyzed simulations consists of one solar minimum simulation, employing RSSV1-ATLAS3 and five solar maximum experiments. The latter are a result of adding the amplitude of solar cycle 22 according to the five reconstructions to RSSV1-ATLAS3. Our results show that the climate response to the 11y solar cycle is generally robust across CCMs and SSI forcings. However, analyzing the variance of the solar maximum ensemble by means of ANOVA-statistics reveals additional information on the uncertainties of the mean climate signals. The annual mean response agrees very well between the two CCMs for most parts of the lower and middle atmosphere. Only the upper mesosphere is subject to significant differences related to the choice of the model. However, the different SSI forcings lead to significant differences in ozone concentrations, shortwave heating rates, and temperature throughout large parts of the mesosphere and upper stratosphere. Regarding the seasonal evolution of the climate signals, our findings for short wave heating rates, and temperature are similar to the annual means with respect to the relative importance of the choice of the model or the SSI forcing for the
Dynamics of Individual cilia to external loading- A simple one dimensional picture

NASA Astrophysics Data System (ADS)

Swaminathan, Vinay; Hill, David; Superfine, R.

2008-10-01

From being called the cellular janitors to swinging debauchers, cilia have captured the fascinations of researchers for over 200 years. In cystic fibrosis and chronic obstructive pulmonary disease where the cilia loses it's function, the protective mucus layer in the lung thickens and mucociliary clearance breaks down, leading to inflammation along the airways and an increased rate of infection. The mechanistic understanding of mucus clearance depends on a quantitative assessment of the axoneme dynamics and the maximum force the cilia are capable of generating and imparting to the mucus layer. Similar to the situation in molecular motors, detailed quantitative measurements of dynamics under applied load conditions are expected to be essential in developing predictive models. Based on our measurements of the dynamics of individual ciliary motion in the human bronchial epithelial cell under the application of an applied load, we present a simple one dimensional model for the axoneme dynamics and quantify the axoneme stiffness, the internal force generated by the axoneme, the stall force and show how the dynamics sheds insight on the time dependence of the internal force generation. The internal force generated by the axoneme is related to the ability of cilia to propel fluids and to their potential role in force sensing.
The Fallacy of Quantifying Risk

DTIC Science & Technology

2012-09-01

Defense AT&L: September–October 2012 18 The Fallacy of Quantifying Risk David E. Frick, Ph.D. Frick is a 35-year veteran of the Department of...a key to risk analysis was “choosing the right technique” of quantifying risk . The weakness in this argument stems not from the assertion that one...of information about the enemy), yet achiev- ing great outcomes. Attempts at quantifying risk are not, in and of themselves, objectionable. Prudence
Quantifying climate changes of the Common Era for Finland

NASA Astrophysics Data System (ADS)

Luoto, Tomi P.; Nevalainen, Liisa

2017-10-01

In this study, we aim to quantify summer air temperatures from sediment records from Southern, Central and Northern Finland over the past 2000 years. We use lake sediment archives to estimate paleotemperatures applying fossil Chironomidae assemblages and the transfer function approach. The used enhanced Chironomidae-based temperature calibration set was validated in a 70-year high-resolution sediment record against instrumentally measured temperatures. Since the inferred and observed temperatures showed close correlation, we deduced that the new calibration model is reliable for reconstructions beyond the monitoring records. The 700-year long temperature reconstructions from three sites at multi-decadal temporal resolution showed similar trends, although they had differences in timing of the cold Little Ice Age (LIA) and the initiation of recent warming. The 2000-year multi-centennial reconstructions from three different sites showed resemblance with each other having clear signals of the Medieval Climate Anomaly (MCA) and LIA, but with differences in their timing. The influence of external forcing on climate of the southern and central sites appeared to be complex at the decadal scale, but the North Atlantic Oscillation (NAO) was closely linked to the temperature development of the northern site. Solar activity appears to be synchronous with the temperature fluctuations at the multi-centennial scale in all the sites. The present study provides new insights into centennial and decadal variability in air temperature dynamics in Northern Europe and on the external forcing behind these trends. These results are particularly useful in comparing regional responses and lags of temperature trends between different parts of Scandinavia.
Experimental Investigation of Hysteretic Dynamic Capillarity Effect in Unsaturated Flow

PubMed Central

Zhuang, Luwen; Qin, Chao‐Zhong; de Waal, Arjen

2017-01-01

Abstract The difference between average pressures of two immiscible fluids is commonly assumed to be the same as macroscopic capillary pressure, which is considered to be a function of saturation only. However, under transient conditions, a dependence of this pressure difference on the time rate of saturation change has been observed by many researchers. This is commonly referred to as dynamic capillarity effect. As a first‐order approximation, the dynamic term is assumed to be linearly dependent on the time rate of change of saturation, through a material coefficient denoted by τ. In this study, a series of laboratory experiments were carried out to quantify the dynamic capillarity effect in an unsaturated sandy soil. Primary, main, and scanning drainage experiments, under both static and dynamic conditions, were performed on a sandy soil in a small cell. The value of the dynamic capillarity coefficient τ was calculated from the air‐water pressure differences and average saturation values during static and dynamic drainage experiments. We found a dependence of τ on saturation, which showed a similar trend for all drainage conditions. However, at any given saturation, the value of τ for primary drainage was larger than the value for main drainage and that was in turn larger than the value for scanning drainage. Each data set was fit a simple log‐linear equation, with different values of fitting parameters. This nonuniqueness of the relationship between τ and saturation and possible causes is discussed. PMID:29398729
Experimental Investigation of Hysteretic Dynamic Capillarity Effect in Unsaturated Flow

NASA Astrophysics Data System (ADS)

Zhuang, Luwen; Hassanizadeh, S. Majid; Qin, Chao-Zhong; de Waal, Arjen

2017-11-01

The difference between average pressures of two immiscible fluids is commonly assumed to be the same as macroscopic capillary pressure, which is considered to be a function of saturation only. However, under transient conditions, a dependence of this pressure difference on the time rate of saturation change has been observed by many researchers. This is commonly referred to as dynamic capillarity effect. As a first-order approximation, the dynamic term is assumed to be linearly dependent on the time rate of change of saturation, through a material coefficient denoted by τ. In this study, a series of laboratory experiments were carried out to quantify the dynamic capillarity effect in an unsaturated sandy soil. Primary, main, and scanning drainage experiments, under both static and dynamic conditions, were performed on a sandy soil in a small cell. The value of the dynamic capillarity coefficient τ was calculated from the air-water pressure differences and average saturation values during static and dynamic drainage experiments. We found a dependence of τ on saturation, which showed a similar trend for all drainage conditions. However, at any given saturation, the value of τ for primary drainage was larger than the value for main drainage and that was in turn larger than the value for scanning drainage. Each data set was fit a simple log-linear equation, with different values of fitting parameters. This nonuniqueness of the relationship between τ and saturation and possible causes is discussed.
Simultaneous dynamic optical and electrical properties of endothelial cell attachment on indium tin oxide bioelectrodes.

PubMed

Choi, Chang K; English, Anthony E; Kihm, Kenneth D; Margraves, Charles H

2007-01-01

This study quantifies the dynamic attachment and spreading of porcine pulmonary artery endothelial cells (PPAECs) on optically thin, indium tin oxide (ITO) biosensors using simultaneous differential interference contrast microscopy (DICM) and electrical microimpedance spectroscopy. A lock-in amplifier circuit monitored the impedance of PPAECs cultivated on the transparent ITO bioelectrodes as a function of frequency between 10 Hz and 100 kHz and as a function of time, while DICM images were simultaneously acquired. A digital image processing algorithm quantified the cell-covered electrode area as a function of time. The results of this study show that the fraction of the cell-covered electrode area is in qualitative agreement with the electrical impedance during the attachment phase following the cell settling on the electrode surface. The possibility of several distinctly different states of electrode coverage and cellular attachment giving rise to similar impedance signals is discussed.
Chemical dynamics between wells across a time-dependent barrier: Self-similarity in the Lagrangian descriptor and reactive basins.

PubMed

Junginger, Andrej; Duvenbeck, Lennart; Feldmaier, Matthias; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

2017-08-14

In chemical or physical reaction dynamics, it is essential to distinguish precisely between reactants and products for all times. This task is especially demanding in time-dependent or driven systems because therein the dividing surface (DS) between these states often exhibits a nontrivial time-dependence. The so-called transition state (TS) trajectory has been seen to define a DS which is free of recrossings in a large number of one-dimensional reactions across time-dependent barriers and thus, allows one to determine exact reaction rates. A fundamental challenge to applying this method is the construction of the TS trajectory itself. The minimization of Lagrangian descriptors (LDs) provides a general and powerful scheme to obtain that trajectory even when perturbation theory fails. Both approaches encounter possible breakdowns when the overall potential is bounded, admitting the possibility of returns to the barrier long after the trajectories have reached the product or reactant wells. Such global dynamics cannot be captured by perturbation theory. Meanwhile, in the LD-DS approach, it leads to the emergence of additional local minima which make it difficult to extract the optimal branch associated with the desired TS trajectory. In this work, we illustrate this behavior for a time-dependent double-well potential revealing a self-similar structure of the LD, and we demonstrate how the reflections and side-minima can be addressed by an appropriate modification of the LD associated with the direct rate across the barrier.
Similar but Different: Dynamic Social Network Analysis Highlights Fundamental Differences between the Fission-Fusion Societies of Two Equid Species, the Onager and Grevy’s Zebra

PubMed Central

Rubenstein, Daniel I.; Sundaresan, Siva R.; Fischhoff, Ilya R.; Tantipathananandh, Chayant; Berger-Wolf, Tanya Y.

2015-01-01

Understanding why animal societies take on the form that they do has benefited from insights gained by applying social network analysis to patterns of individual associations. Such analyses typically aggregate data over long time periods even though most selective forces that shape sociality have strong temporal elements. By explicitly incorporating the temporal signal in social interaction data we re-examine the network dynamics of the social systems of the evolutionarily closely-related Grevy’s zebras and wild asses that show broadly similar social organizations. By identifying dynamic communities, previously hidden differences emerge: Grevy’s zebras show more modularity than wild asses and in wild asses most communities consist of solitary individuals; and in Grevy’s zebras, lactating females show a greater propensity to switch communities than non-lactating females and males. Both patterns were missed by static network analyses and in general, adding a temporal dimension provides insights into differences associated with the size and persistence of communities as well as the frequency and synchrony of their formation. Dynamic network analysis provides insights into the functional significance of these social differences and highlights the way dynamic community analysis can be applied to other species. PMID:26488598
Using Eddy Covariance to Quantify Methane Emissions from a Dynamic Heterogeneous Area

EPA Science Inventory

Measuring emissions of CH4, CO2, H2O, and other greenhouse gases from heterogeneous land area sources is challenging. Dynamic changes within the source area as well as changing environmental conditions make individual point measurements less informative than desired, especially w...
Using Eddy Covariance to Quantify Methane Emission from a Dynamic Heterogeneous Area

EPA Science Inventory

Measuring emissions of CH4, CO2, H2O, and other greenhouse gases from heterogeneous land area sources is challenging. Dynamic changes within the source area as well as changing environmental conditions make individual point measurements less informative than desired, especially w...
Quantifying Cancer Risk from Radiation.

PubMed

Keil, Alexander P; Richardson, David B

2017-12-06

Complex statistical models fitted to data from studies of atomic bomb survivors are used to estimate the human health effects of ionizing radiation exposures. We describe and illustrate an approach to estimate population risks from ionizing radiation exposure that relaxes many assumptions about radiation-related mortality. The approach draws on developments in methods for causal inference. The results offer a different way to quantify radiation's effects and show that conventional estimates of the population burden of excess cancer at high radiation doses are driven strongly by projecting outside the range of current data. Summary results obtained using the proposed approach are similar in magnitude to those obtained using conventional methods, although estimates of radiation-related excess cancers differ for many age, sex, and dose groups. At low doses relevant to typical exposures, the strength of evidence in data is surprisingly weak. Statements regarding human health effects at low doses rely strongly on the use of modeling assumptions. © 2017 Society for Risk Analysis.

Role of density modulation in the spatially resolved dynamics of strongly confined liquids

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

Saw, Shibu, E-mail: shibu.saw@sydney.edu.au; Dasgupta, Chandan, E-mail: cdgupta@physics.iisc.ernet.in

Confinement by walls usually produces a strong modulation in the density of dense liquids near the walls. Using molecular dynamics simulations, we examine the effects of the density modulation on the spatially resolved dynamics of a liquid confined between two parallel walls, using a resolution of a fraction of the interparticle distance in the liquid. The local dynamics is quantified by the relaxation time associated with the temporal autocorrelation function of the local density. We find that this local relaxation time varies in phase with the density modulation. The amplitude of the spatial modulation of the relaxation time can bemore » quite large, depending on the characteristics of the wall and thermodynamic parameters of the liquid. To disentangle the effects of confinement and density modulation on the spatially resolved dynamics, we compare the dynamics of a confined liquid with that of an unconfined one in which a similar density modulation is induced by an external potential. We find several differences indicating that density modulation alone cannot account for all the features seen in the spatially resolved dynamics of confined liquids. We also examine how the dynamics near a wall depends on the separation between the two walls and show that the features seen in our simulations persist in the limit of large wall separation.« less
A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

NASA Astrophysics Data System (ADS)

Koorehdavoudi, Hana; Bogdan, Paul

2016-06-01

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

PubMed Central

Koorehdavoudi, Hana; Bogdan, Paul

2016-01-01

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

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a
Quantifying mantle structure and dynamics using plume tracing in seismic tomography

NASA Astrophysics Data System (ADS)

O'Farrell, K. A.; Eakin, C. M.; Jackson, M. G.; Jones, T. D.; Lekic, V.; Lithgow-Bertelloni, C. R.

2017-12-01

Directly linking deep mantle processes with surface features and dynamics is a complex problem. Hotspot volcanism gives us surface observables of mantle signatures, but the depth and source of the mantle plumes feeding these hotspots are highly debated. To address these issues, it is necessary to consider the entire journey of a plume through the mantle. By analyzing the behavior of mantle plumes we can constrain the vigor of mantle convection, the net rotation of the mantle and the role of thermal versus chemical anomalies as well as the bulk physical properties such as the viscosity profile. To do this, we developed a new algorithm to trace plume-like features in shear-wave (Vs) seismic tomography models based on picking local minima in the velocity and searching for continuous features with depth. We applied this method to recent tomographic models and find 60+ continuous plume conduits that are > 750 km long. Approximately a third of these can be associated with known hotspots at the surface. We analyze the morphology of these continuous conduits and infer large scale mantle flow patterns and properties. We find the largest lateral deflections in the conduits occur near the base of the lower mantle and in the upper mantle (near the thermal boundary layers). The preferred orientation of the plume deflections show large variability at all depths and indicate no net mantle rotation. Plate by plate analysis shows little agreement in deflection below particular plates, indicating these deflected features might be long lived and not caused by plate shearing. Changes in the gradient of plume deflection are inferred to correspond with viscosity contrasts in the mantle and found below the transition zone as well as at 1000 km depth. From this inferred viscosity structure, we explore the dynamics of a plume through these viscosity jumps. We also retrieve the Vs profiles for the conduits and compare with the velocity profiles predicted for different mantle adiabat
Multiscale contact mechanics model for RF-MEMS switches with quantified uncertainties

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

PubMed Central

2013-01-01

Background Microbial ecologists often employ methods from classical community ecology to analyze microbial community diversity. However, these methods have limitations because microbial communities differ from macro-organismal communities in key ways. This study sought to quantify microbial diversity using methods that are better suited for data spanning multiple domains of life and dimensions of diversity. Diversity profiles are one novel, promising way to analyze microbial datasets. Diversity profiles encompass many other indices, provide effective numbers of diversity (mathematical generalizations of previous indices that better convey the magnitude of differences in diversity), and can incorporate taxa similarity information. To explore whether these profiles change interpretations of microbial datasets, diversity profiles were calculated for four microbial datasets from different environments spanning all domains of life as well as viruses. Both similarity-based profiles that incorporated phylogenetic relatedness and naïve (not similarity-based) profiles were calculated. Simulated datasets were used to examine the robustness of diversity profiles to varying phylogenetic topology and community composition. Results Diversity profiles provided insights into microbial datasets that were not detectable with classical univariate diversity metrics. For all datasets analyzed, there were key distinctions between calculations that incorporated phylogenetic diversity as a measure of taxa similarity and naïve calculations. The profiles also provided information about the effects of rare species on diversity calculations. Additionally, diversity profiles were used to examine thousands of simulated microbial communities, showing that similarity-based and naïve diversity profiles only agreed approximately 50% of the time in their classification of which sample was most diverse. This is a strong argument for incorporating similarity information and calculating diversity
Heuristic reusable dynamic programming: efficient updates of local sequence alignment.

PubMed

Hong, Changjin; Tewfik, Ahmed H

2009-01-01

Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm.
A conceptual model for quantifying connectivity using graph theory and cellular (per-pixel) approach

NASA Astrophysics Data System (ADS)

Singh, Manudeo; Sinha, Rajiv; Tandon, Sampat K.

2016-04-01

The concept of connectivity is being increasingly used for understanding hydro-geomorphic processes at all spatio-temporal scales. Connectivity is defined as the potential for energy and material flux (water, sediments, nutrients, heat, etc.) to navigate within or between the landscape systems and has two components, structural connectivity and dynamic connectivity. Structural connectivity is defined by the spatially connected features (physical linkages) through which energy and materials flow. Dynamic connectivity is a process defined connectivity component. These two connectivity components also interact with each other by forming a feedback system. This study attempts to explore a method to quantify structural and dynamic connectivity. In fluvial transport systems, sediment and water can flow in either a diffused manner or in a channelized way. At all the scales, hydrological and sediment fluxes can be tracked using a cellular (per-pixel) approach and can be quantified using graphical approach. The material flux, slope and LULC (Land Use Land Cover) weightage factors of a pixel together determine if it will contribute towards connectivity of the landscape/system. In a graphical approach, all the contributing pixels will form a node at their centroid and this node will be connected to the next 'down-node' via a directed edge with 'least cost path'. The length of the edge will depend on the desired spatial scale and its path direction will depend on the traversed pixel's slope and the LULC (weightage) factors. The weightage factors will lie in-between 0 to 1. This value approaches 1 for the LULC factors which promote connectivity. For example, in terms of sediment connectivity, the weightage could be RUSLE (Revised Universal Soil Loss Equation) C-factors with bare unconsolidated surfaces having values close to 1. This method is best suited for areas with low slopes, where LULC can be a deciding as well as dominating factor. The degree of connectivity and its
Quantifying and Monetizing Potential Climate Change Policy Impacts on Terrestrial Ecosystem Carbon Storage and Wildfires in the United States

EPA Science Inventory

This paper quantifies and monetizes climate change impacts on carbon stored in terrestrial vegetation and wildfire incidence in the contiguous United States to assess the benefits of alternative mitigation policies. The MC-1 dynamic global vegetation model was used to develop int...
Predicting the performance of fingerprint similarity searching.

PubMed

Vogt, Martin; Bajorath, Jürgen

2011-01-01

Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.
Quantifying Dynamic Deformity After Dual Plane Breast Augmentation.

PubMed

Cheffe, Marcelo Recondo; Valentini, Jorge Diego; Collares, Marcus Vinicius Martins; Piccinini, Pedro Salomão; da Silva, Jefferson Luis Braga

2018-06-01

Dynamic breast deformity (DBD) is characterized by visible distortion and deformity of the breast due to contraction of the pectoralis major muscle after submuscular breast augmentation; fortunately, in most cases, this is not a clinically significant complaint from patients. The purpose of this study is to present a simple method for objectively measuring DBD in patients submitted to dual plane breast augmentation (DPBA). We studied 32 women, between 18 and 50 years old, who underwent primary DPBA with at least 1 year of follow-up. Anthropometric landmarks of the breast were marked, creating linear segments. Standardized photographs were obtained both during no pectoralis contraction (NPC) and during maximum pectoralis muscle contraction (MPC); measurements of the linear segments were taken through ImageJ imaging software, and both groups were compared. We found statistically significant differences in all analyzed segments when comparing measurements of the breasts during NPC and MPC (p < 0.001). Our study proposes a novel, standardized method for measuring DBD after DPBA. This technique is reproducible, allowing for objective quantification of the deformity in any patient, which can be valuable for both patients and surgeons, as it allows for a more thorough discussion on DBD, both pre- and postoperatively, and may help both patients and surgeons to make more informed decisions regarding potential animation deformities after breast augmentation. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
Modified DTW for a quantitative estimation of the similarity between rainfall time series

NASA Astrophysics Data System (ADS)

Djallel Dilmi, Mohamed; Barthès, Laurent; Mallet, Cécile; Chazottes, Aymeric

2017-04-01

The Precipitations are due to complex meteorological phenomenon and can be described as intermittent process. The spatial and temporal variability of this phenomenon is significant and covers large scales. To analyze and model this variability and / or structure, several studies use a network of rain gauges providing several time series of precipitation measurements. To compare these different time series, the authors compute for each time series some parameters (PDF, rain peak intensity, occurrence, amount, duration, intensity …). However, and despite the calculation of these parameters, the comparison of the parameters between two series of measurements remains qualitative. Due to the advection processes, when different sensors of an observation network measure precipitation time series identical in terms of intermitency or intensities, there is a time lag between the different measured series. Analyzing and extracting relevant information on physical phenomena from these precipitation time series implies the development of automatic analytical methods capable of comparing two time series of precipitation measured by different sensors or at two different locations and thus quantifying the difference / similarity. The limits of the Euclidean distance to measure the similarity between the time series of precipitation have been well demonstrated and explained (eg the Euclidian distance is indeed very sensitive to the effects of phase shift : between two identical but slightly shifted time series, this distance is not negligible). To quantify and analysis these time lag, the correlation functions are well established, normalized and commonly used to measure the spatial dependences that are required by many applications. However, authors generally observed that there is always a considerable scatter of the inter-rain gauge correlation coefficients obtained from the individual pairs of rain gauges. Because of a substantial dispersion of estimated time lag, the
Quantifying the behavior of price dynamics at opening time in stock market

NASA Astrophysics Data System (ADS)

Ochiai, Tomoshiro; Takada, Hideyuki; Nacher, Jose C.

2014-11-01

The availability of huge volume of financial data has offered the possibility for understanding the markets as a complex system characterized by several stylized facts. Here we first show that the time evolution of the Japan’s Nikkei stock average index (Nikkei 225) futures follows the resistance and breaking-acceleration effects when the complete time series data is analyzed. However, in stock markets there are periods where no regular trades occur between the close of the market on one day and the next day’s open. To examine these time gaps we decompose the time series data into opening time and intermediate time. Our analysis indicates that for the intermediate time, both the resistance and the breaking-acceleration effects are still observed. However, for the opening time there are almost no resistance and breaking-acceleration effects, and volatility is always constantly high. These findings highlight unique dynamic differences between stock markets and forex market and suggest that current risk management strategies may need to be revised to address the absence of these dynamic effects at the opening time.
Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

PubMed Central

Yang, Albert C.; Tsai, Shih-Jen; Hong, Chen-Jee; Wang, Cynthia; Chen, Tai-Jui; Liou, Ying-Jay; Peng, Chung-Kang

2011-01-01

Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. PMID:21573230
Quantifying the chiral magnetic effect from anomalous-viscous fluid dynamics

NASA Astrophysics Data System (ADS)

Jiang, Yin; Shi, Shuzhe; Yin, Yi; Liao, Jinfeng

2018-01-01

The Chiral Magnetic Effect (CME) is a macroscopic manifestation of fundamental chiral anomaly in a many-body system of chiral fermions, and emerges as an anomalous transport current in the fluid dynamics framework. Experimental observation of the CME is of great interest and has been reported in Dirac and Weyl semimetals. Significant efforts have also been made to look for the CME in heavy ion collisions. Critically needed for such a search is the theoretical prediction for the CME signal. In this paper we report a first quantitative modeling framework, Anomalous Viscous Fluid Dynamics (AVFD), which computes the evolution of fermion currents on top of realistic bulk evolution in heavy ion collisions and simultaneously accounts for both anomalous and normal viscous transport effects. AVFD allows a quantitative understanding of the generation and evolution of CME-induced charge separation during the hydrodynamic stage, as well as its dependence on theoretical ingredients. With reasonable estimates of key parameters, the AVFD simulations provide the first phenomenologically successful explanation of the measured signal in 200 AGeV AuAu collisions. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, within the framework of the Beam Energy Scan Theory (BEST) Topical Collaboration. The work is also supported in part by the National Science Foundation under Grant No. PHY-1352368 (SS and JL), by the National Science Foundation of China under Grant No. 11735007 (JL) and by the U.S. Department of Energy under grant Contract Number No. DE- SC0012704 (BNL)/DE-SC0011090 (MIT) (YY). JL is grateful to the Institute for Nuclear Theory for hospitality during the INT-16-3 Program. The computation of this research was performed on IU’s Big Red II cluster, supported in part by Lilly Endowment, Inc. (through its support for the Indiana University Pervasive Technology Institute) and in part by the Indiana METACyt
Branch length similarity entropy-based descriptors for shape representation

NASA Astrophysics Data System (ADS)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.
Quantifying complexity in translational research: an integrated approach.

PubMed

Munoz, David A; Nembhard, Harriet Black; Kraschnewski, Jennifer L

2014-01-01

The purpose of this paper is to quantify complexity in translational research. The impact of major operational steps and technical requirements is calculated with respect to their ability to accelerate moving new discoveries into clinical practice. A three-phase integrated quality function deployment (QFD) and analytic hierarchy process (AHP) method was used to quantify complexity in translational research. A case study in obesity was used to usability. Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, the authors found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice. As the method is mainly based on subjective opinion, some argue that the results may be biased. However, a consistency ratio is calculated and used as a guide to subjectivity. Alternatively, a larger sample may be incorporated to reduce bias. The integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects. Current conceptual models in translational research provide little or no clue to assess complexity. The proposed method aimed to fill this gap. Additionally, the literature review includes various features that have not been explored in translational research.
Quantifying complexity in translational research: an integrated approach

PubMed Central

Munoz, David A.; Nembhard, Harriet Black; Kraschnewski, Jennifer L.

2014-01-01

Purpose This article quantifies complexity in translational research. The impact of major operational steps and technical requirements (TR) is calculated with respect to their ability to accelerate moving new discoveries into clinical practice. Design/Methodology/Approach A three-phase integrated Quality Function Deployment (QFD) and Analytic Hierarchy Process (AHP) method was used to quantify complexity in translational research. A case study in obesity was used to usability. Findings Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, we found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice. Research limitations/implications As the method is mainly based on subjective opinion, some argue that the results may be biased. However, a consistency ratio is calculated and used as a guide to subjectivity. Alternatively, a larger sample may be incorporated to reduce bias. Practical implications The integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects. Originality/value Current conceptual models in translational research provide little or no clue to assess complexity. The proposed method aimed to fill this gap. Additionally, the literature review includes various features that have not been explored in translational research. PMID:25417380
Common ecology quantifies human insurgency.

PubMed

Bohorquez, Juan Camilo; Gourley, Sean; Dixon, Alexander R; Spagat, Michael; Johnson, Neil F

2009-12-17

Many collective human activities, including violence, have been shown to exhibit universal patterns. The size distributions of casualties both in whole wars from 1816 to 1980 and terrorist attacks have separately been shown to follow approximate power-law distributions. However, the possibility of universal patterns ranging across wars in the size distribution or timing of within-conflict events has barely been explored. Here we show that the sizes and timing of violent events within different insurgent conflicts exhibit remarkable similarities. We propose a unified model of human insurgency that reproduces these commonalities, and explains conflict-specific variations quantitatively in terms of underlying rules of engagement. Our model treats each insurgent population as an ecology of dynamically evolving, self-organized groups following common decision-making processes. Our model is consistent with several recent hypotheses about modern insurgency, is robust to many generalizations, and establishes a quantitative connection between human insurgency, global terrorism and ecology. Its similarity to financial market models provides a surprising link between violent and non-violent forms of human behaviour.

Modeling Unsteady Cavitation and Dynamic Loads in Turbopumps

NASA Technical Reports Server (NTRS)

Hosangadi, Ashvin; Ahuja, Vineet; Ungewitter, Ronald; Dash, Sanford M.

2009-01-01

A computational fluid dynamics (CFD) model that includes representations of effects of unsteady cavitation and associated dynamic loads has been developed to increase the accuracy of simulations of the performances of turbopumps. Although the model was originally intended to serve as a means of analyzing preliminary designs of turbopumps that supply cryogenic propellant liquids to rocket engines, the model could also be applied to turbopumping of other liquids: this can be considered to have been already demonstrated, in that the validation of the model was performed by comparing results of simulations performed by use of the model with results of sub-scale experiments in water. The need for this or a similar model arises as follows: Cavitation instabilities in a turbopump are generated as inlet pressure drops and vapor cavities grow on inducer blades, eventually becoming unsteady. The unsteady vapor cavities lead to rotation cavitation, in which the cavities detach from the blades and become part of a fluid mass that rotates relative to the inducer, thereby generating a fluctuating load. Other instabilities (e.g., surge instabilities) can couple with cavitation instabilities, thereby compounding the deleterious effects of unsteadiness on other components of the fluid-handling system of which the turbopump is a part and thereby, further, adversely affecting the mechanical integrity and safety of the system. Therefore, an ability to predict cavitation- instability-induced dynamic pressure loads on the blades, the shaft, and other pump parts would be valuable in helping to quantify safe margins of inducer operation and in contributing to understanding of design compromises. Prior CFD models do not afford this ability. Heretofore, the primary parameter used in quantifying cavitation performance of a turbopump inducer has been the critical suction specific speed at which head breakdown occurs. This parameter is a mean quantity calculated on the basis of assumed steady
Quantifying the Adaptive Cycle | Science Inventory | US EPA

EPA Pesticide Factsheets

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and
Visual Reconciliation of Alternative Similarity Spaces in Climate Modeling.

PubMed

Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher R; Huntzinger, Deborah N; Cook, Robert; Bertini, Enrico; Silva, Claudio T

2014-12-01

Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses additional challenges. In this paper we define visual reconciliation as the problem of reconciling multiple alternative similarity spaces through visualization and interaction. We derive this problem from our work on model comparison in climate science where climate modelers are faced with the challenge of making sense of alternative ways to describe their models: one through the output they generate, another through the large set of properties that describe them. Ideally, they want to understand whether groups of models with similar spatio-temporal behaviors share similar sets of criteria or, conversely, whether similar criteria lead to similar behaviors. We propose a visual analytics solution based on linked views, that addresses this problem by allowing the user to dynamically create, modify and observe the interaction among groupings, thereby making the potential explanations apparent. We present case studies that demonstrate the usefulness of our technique in the area of climate science.
Measuring abnormal movements in free-swimming fish with accelerometers: implications for quantifying tag and parasite load.

PubMed

Broell, Franziska; Burnell, Celene; Taggart, Christopher T

2016-03-01

Animal-borne data loggers allow movement, associated behaviours and energy expenditure in fish to be quantified without direct observations. As with any tagging, tags that are attached externally may adversely affect fish behaviour, swimming efficiency and survival. We report on free-swimming wild Atlantic cod (Gadus morhua) held in a large mesocosm that exhibited distinctly aberrant rotational swimming (scouring) when externally tagged with accelerometer data loggers. To quantify the phenomenon, the cod were tagged with two sizes of loggers (18 and 6 g; <2% body mass) that measured tri-axial acceleration at 50 Hz. An automated algorithm, based on body angular rotation, was designed to extract the scouring movements from the acceleration signal (98% accuracy). The algorithm also identified the frequency pattern and associated energy expenditure of scouring in relation to tag load (% body weight). The average per cent time spent scouring (5%) was independent of tag load. The vector of the dynamic body acceleration (VeDBA), used as a proxy for energy expenditure, increased with tag load (r(2)=0.51), and suggests that fish with large tags spent more energy when scouring than fish with small tags. The information allowed us to determine potential detrimental effects of an external tag on fish behaviour and how these effects may be mitigated by tag size. The algorithm can potentially identify similar rotational movements associated with spawning, courtship, feeding and parasite-load shedding in the wild. The results infer a more careful interpretation of data derived from external tags and the careful consideration of tag type, drag, buoyancy and placement, as well as animal buoyancy and species. © 2016. Published by The Company of Biologists Ltd.
Community detection in sequence similarity networks based on attribute clustering

DOE PAGES

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

2017-07-24

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less
Community detection in sequence similarity networks based on attribute clustering

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

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less
Integrating Stomach Content and Stable Isotope Analyses to Quantify the Diets of Pygoscelid Penguins

PubMed Central

Polito, Michael J.; Trivelpiece, Wayne Z.; Karnovsky, Nina J.; Ng, Elizabeth; Patterson, William P.; Emslie, Steven D.

2011-01-01

Stomach content analysis (SCA) and more recently stable isotope analysis (SIA) integrated with isotopic mixing models have become common methods for dietary studies and provide insight into the foraging ecology of seabirds. However, both methods have drawbacks and biases that may result in difficulties in quantifying inter-annual and species-specific differences in diets. We used these two methods to simultaneously quantify the chick-rearing diet of Chinstrap (Pygoscelis antarctica) and Gentoo (P. papua) penguins and highlight methods of integrating SCA data to increase accuracy of diet composition estimates using SIA. SCA biomass estimates were highly variable and underestimated the importance of soft-bodied prey such as fish. Two-source, isotopic mixing model predictions were less variable and identified inter-annual and species-specific differences in the relative amounts of fish and krill in penguin diets not readily apparent using SCA. In contrast, multi-source isotopic mixing models had difficulty estimating the dietary contribution of fish species occupying similar trophic levels without refinement using SCA-derived otolith data. Overall, our ability to track inter-annual and species-specific differences in penguin diets using SIA was enhanced by integrating SCA data to isotopic mixing modes in three ways: 1) selecting appropriate prey sources, 2) weighting combinations of isotopically similar prey in two-source mixing models and 3) refining predicted contributions of isotopically similar prey in multi-source models. PMID:22053199
Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.
Quantumness-generating capability of quantum dynamics

NASA Astrophysics Data System (ADS)

Li, Nan; Luo, Shunlong; Mao, Yuanyuan

2018-04-01

We study quantumness-generating capability of quantum dynamics, where quantumness refers to the noncommutativity between the initial state and the evolving state. In terms of the commutator of the square roots of the initial state and the evolving state, we define a measure to quantify the quantumness-generating capability of quantum dynamics with respect to initial states. Quantumness-generating capability is absent in classical dynamics and hence is a fundamental characteristic of quantum dynamics. For qubit systems, we present an analytical form for this measure, by virtue of which we analyze several prototypical dynamics such as unitary dynamics, phase damping dynamics, amplitude damping dynamics, and random unitary dynamics (Pauli channels). Necessary and sufficient conditions for the monotonicity of quantumness-generating capability are also identified. Finally, we compare these conditions for the monotonicity of quantumness-generating capability with those for various Markovianities and illustrate that quantumness-generating capability and quantum Markovianity are closely related, although they capture different aspects of quantum dynamics.
Popularity versus similarity in growing networks

NASA Astrophysics Data System (ADS)

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, Mariangeles; Boguna, Marian

2012-02-01

Preferential attachment is a powerful mechanism explaining the emergence of scaling in growing networks. If new connections are established preferentially to more popular nodes in a network, then the network is scale-free. Here we show that not only popularity but also similarity is a strong force shaping the network structure and dynamics. We develop a framework where new connections, instead of preferring popular nodes, optimize certain trade-offs between popularity and similarity. The framework admits a geometric interpretation, in which preferential attachment emerges from local optimization processes. As opposed to preferential attachment, the optimization framework accurately describes large-scale evolution of technological (Internet), social (web of trust), and biological (E.coli metabolic) networks, predicting the probability of new links in them with a remarkable precision. The developed framework can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.
The dependence of crowding on flanker complexity and target-flanker similarity

PubMed Central

Bernard, Jean-Baptiste; Chung, Susana T.L.

2013-01-01

We examined the effects of the spatial complexity of flankers and target-flanker similarity on the performance of identifying crowded letters. On each trial, observers identified the middle character of random strings of three characters (“trigrams”) briefly presented at 10° below fixation. We tested the 26 lowercase letters of the Times-Roman and Courier fonts, a set of 79 characters (letters and non-letters) of the Times-Roman font, and the uppercase letters of two highly complex ornamental fonts, Edwardian and Aristocrat. Spatial complexity of characters was quantified by the length of the morphological skeleton of each character, and target-flanker similarity was defined based on a psychometric similarity matrix. Our results showed that (1) letter identification error rate increases with flanker complexity up to a certain value, beyond which error rate becomes independent of flanker complexity; (2) the increase of error rate is slower for high-complexity target letters; (3) error rate increases with target-flanker similarity; and (4) mislocation error rate increases with target-flanker similarity. These findings, combined with the current understanding of the faulty feature integration account of crowding, provide some constraints of how the feature integration process could cause perceptual errors. PMID:21730225
Statistical similarities of pre-earthquake electromagnetic emissions to biological and economic extreme events

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Contoyiannis, Yiannis; Kopanas, John; Kalimeris, Anastasios; Antonopoulos, George; Peratzakis, Athanasios; Eftaxias, Konstantinos; Nomicos, Costantinos

2014-05-01

When one considers a phenomenon that is "complex" refers to a system whose phenomenological laws that describe the global behavior of the system, are not necessarily directly related to the "microscopic" laws that regulate the evolution of its elementary parts. The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe disparate problems ranging from particle physics to economies of societies. Several authors have suggested that earthquake (EQ) dynamics can be analyzed within similar mathematical frameworks with economy dynamics, and neurodynamics. A central property of the EQ preparation process is the occurrence of coherent large-scale collective behavior with a very rich structure, resulting from repeated nonlinear interactions among the constituents of the system. As a result, nonextensive statistics is an appropriate, physically meaningful, tool for the study of EQ dynamics. Since the fracture induced electromagnetic (EM) precursors are observable manifestations of the underlying EQ preparation process, the analysis of a fracture induced EM precursor observed prior to the occurrence of a large EQ can also be conducted within the nonextensive statistics framework. Within the frame of the investigation for universal principles that may hold for different dynamical systems that are related to the genesis of extreme events, we present here statistical similarities of the pre-earthquake EM emissions related to an EQ, with the pre-ictal electrical brain activity related to an epileptic seizure, and with the pre-crisis economic observables related to the collapse of a share. It is demonstrated the all three dynamical systems' observables can be analyzed in the frame of nonextensive statistical mechanics, while the frequency-size relations of appropriately defined "events" that precede the extreme event related to each one of these different systems present striking quantitative
Talker-specificity and adaptation in quantifier interpretation

PubMed Central

Yildirim, Ilker; Degen, Judith; Tanenhaus, Michael K.; Jaeger, T. Florian

2015-01-01

Linguistic meaning has long been recognized to be highly context-dependent. Quantifiers like many and some provide a particularly clear example of context-dependence. For example, the interpretation of quantifiers requires listeners to determine the relevant domain and scale. We focus on another type of context-dependence that quantifiers share with other lexical items: talker variability. Different talkers might use quantifiers with different interpretations in mind. We used a web-based crowdsourcing paradigm to study participants’ expectations about the use of many and some based on recent exposure. We first established that the mapping of some and many onto quantities (candies in a bowl) is variable both within and between participants. We then examined whether and how listeners’ expectations about quantifier use adapts with exposure to talkers who use quantifiers in different ways. The results demonstrate that listeners can adapt to talker-specific biases in both how often and with what intended meaning many and some are used. PMID:26858511
Intrastorm scale rainfall interception dynamics in a mature coniferous forest stand

NASA Astrophysics Data System (ADS)

Iida, Shin'ichi; Levia, Delphis F.; Shimizu, Akira; Shimizu, Takanori; Tamai, Koji; Nobuhiro, Tatsuhiko; Kabeya, Naoki; Noguchi, Shoji; Sawano, Shinji; Araki, Makoto

2017-05-01

Canopy interception of rainfall is an important process in the water balance of forests. The intrastorm dynamics of canopy interception is less well understood than event scale interception. Accordingly, armed with measurements of hourly interception intensity (i) from the field, this study is among the first to examine the differences in canopy interception dynamics between the first and second halves of rainfall events to quantify dynamic storage values for a coniferous forest in Japan. At this site, experimental results demonstrated that: (1) the relationship between interception loss (I) and gross rainfall (GR) at the event scale is better explained by a parabolic curve than a linear relationship, and there is a low correlation between rainfall intensity (gr) and i; (2) the ratio of accumulated i during the first half (IF) to that of gr (GRF) was larger than the second half (IS/GRS), with no significant correlations between potential evaporation during first half (PEF) vs IF or the second half (PES) vs IS; and (3) water storage capacity was similar to the magnitude of maximum I. By emphasizing the comparison between IF and IS, this study concludes that the water storage on tree surface is more important than losses by wet canopy evaporation and splash during rain. This study also adds insights into intrastorm interception dynamics of coniferous forests which are necessary to better model and forecast interception losses.
Quantification of causal couplings via dynamical effects: A unifying perspective

NASA Astrophysics Data System (ADS)

Smirnov, Dmitry A.

2014-12-01

Quantitative characterization of causal couplings from time series is crucial in studies of complex systems of different origin. Various statistical tools for that exist and new ones are still being developed with a tendency to creating a single, universal, model-free quantifier of coupling strength. However, a clear and generally applicable way of interpreting such universal characteristics is lacking. This work suggests a general conceptual framework for causal coupling quantification, which is based on state space models and extends the concepts of virtual interventions and dynamical causal effects. Namely, two basic kinds of interventions (state space and parametric) and effects (orbital or transient and stationary or limit) are introduced, giving four families of coupling characteristics. The framework provides a unifying view of apparently different well-established measures and allows us to introduce new characteristics, always with a definite "intervention-effect" interpretation. It is shown that diverse characteristics cannot be reduced to any single coupling strength quantifier and their interpretation is inevitably model based. The proposed set of dynamical causal effect measures quantifies different aspects of "how the coupling manifests itself in the dynamics," reformulating the very question about the "causal coupling strength."
Broad-Band Pump-Probe Spectroscopy Quantifies Ultrafast Solvation Dynamics of Proteins and Molecules.

PubMed

Jumper, Chanelle C; Arpin, Paul C; Turner, Daniel B; McClure, Scott D; Rafiq, Shahnawaz; Dean, Jacob C; Cina, Jeffrey A; Kovac, Philip A; Mirkovic, Tihana; Scholes, Gregory D

2016-11-17

In this work, we demonstrate the use of broad-band pump-probe spectroscopy to measure femtosecond solvation dynamics. We report studies of a rhodamine dye in methanol and cryptophyte algae light-harvesting proteins in aqueous suspension. Broad-band impulsive excitation generates a vibrational wavepacket that oscillates on the excited-state potential energy surface, destructively interfering with itself at the minimum of the surface. This destructive interference gives rise to a node at a certain probe wavelength that varies with time. This reveals the Gibbs free-energy changes of the excited-state potential energy surface, which equates to the solvation time correlation function. This method captures the inertial solvent response of water (∼40 fs) and the bimodal inertial response of methanol (∼40 and ∼150 fs) and reveals how protein-buried chromophores are sensitive to the solvent dynamics inside and outside of the protein environment.
Dynamical diagnostics of the SST annual cycle in the eastern equatorial Pacific: part I a linear coupled framework

NASA Astrophysics Data System (ADS)

Chen, Ying-Ying; Jin, Fei-Fei

2018-03-01

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

PubMed

Gorai, Biswajit; Prabhavadhni, Arasu; Sivaraman, Thirunavukkarasu

2015-09-01

Unfolding stabilities of two homologous proteins, cardiotoxin III and short-neurotoxin (SNTX) belonging to three-finger toxin (TFT) superfamily, have been probed by means of molecular dynamics (MD) simulations. Combined analysis of data obtained from steered MD and all-atom MD simulations at various temperatures in near physiological conditions on the proteins suggested that overall structural stabilities of the two proteins were different from each other and the MD results are consistent with experimental data of the proteins reported in the literature. Rationalization for the differential structural stabilities of the structurally similar proteins has been chiefly attributed to the differences in the structural contacts between C- and N-termini regions in their three-dimensional structures, and the findings endorse the 'CN network' hypothesis proposed to qualitatively analyse the thermodynamic stabilities of proteins belonging to TFT superfamily of snake venoms. Moreover, the 'CN network' hypothesis has been revisited and the present study suggested that 'CN network' should be accounted in terms of 'structural contacts' and 'structural strengths' in order to precisely describe order of structural stabilities of TFTs.
Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.
Quantifying stream nutrient uptake from ambient to saturation with instantaneous tracer additions

NASA Astrophysics Data System (ADS)

Covino, T. P.; McGlynn, B. L.; McNamara, R.

2009-12-01

Stream nutrient tracer additions and spiraling metrics are frequently used to quantify stream ecosystem behavior. However, standard approaches limit our understanding of aquatic biogeochemistry. Specifically, the relationship between in-stream nutrient concentration and stream nutrient spiraling has not been characterized. The standard constant rate (steady-state) approach to stream spiraling parameter estimation, either through elevating nutrient concentration or adding isotopically labeled tracers (e.g. 15N), provides little information regarding the stream kinetic curve that represents the uptake-concentration relationship analogous to the Michaelis-Menten curve. These standard approaches provide single or a few data points and often focus on estimating ambient uptake under the conditions at the time of the experiment. Here we outline and demonstrate a new method using instantaneous nutrient additions and dynamic analyses of breakthrough curve (BTC) data to characterize the full relationship between spiraling metrics and nutrient concentration. We compare the results from these dynamic analyses to BTC-integrated, and standard steady-state approaches. Our results indicate good agreement between these three approaches but we highlight the advantages of our dynamic method. Specifically, our new dynamic method provides a cost-effective and efficient approach to: 1) characterize full concentration-spiraling metric curves; 2) estimate ambient spiraling metrics; 3) estimate Michaelis-Menten parameters maximum uptake (Umax) and the half-saturation constant (Km) from developed uptake-concentration kinetic curves, and; 4) measure dynamic nutrient spiraling in larger rivers where steady-state approaches are impractical.

Developing stochastic epidemiological models to quantify the dynamics of infectious diseases in domestic livestock.

PubMed

MacKenzie, K; Bishop, S C

2001-08-01

A stochastic model describing disease transmission dynamics for a microparasitic infection in a structured domestic animal population is developed and applied to hypothetical epidemics on a pig farm. Rational decision making regarding appropriate control strategies for infectious diseases in domestic livestock requires an understanding of the disease dynamics and risk profiles for different groups of animals. This is best achieved by means of stochastic epidemic models. Methodologies are presented for 1) estimating the probability of an epidemic, given the presence of an infected animal, whether this epidemic is major (requires intervention) or minor (dies out without intervention), and how the location of the infected animal on the farm influences the epidemic probabilities; 2) estimating the basic reproductive ratio, R0 (i.e., the expected number of secondary cases on the introduction of a single infected animal) and the variability of the estimate of this parameter; and 3) estimating the total proportion of animals infected during an epidemic and the total proportion infected at any point in time. The model can be used for assessing impact of altering farm structure on disease dynamics, as well as disease control strategies, including altering farm structure, vaccination, culling, and genetic selection.
Using LTI Dynamics to Identify the Influential Nodes in a Network

PubMed Central

Jorswieck, Eduard; Scheunert, Christian

2016-01-01

Networks are used for modeling numerous technical, social or biological systems. In order to better understand the system dynamics, it is a matter of great interest to identify the most important nodes within the network. For a large set of problems, whether it is the optimal use of available resources, spreading information efficiently or even protection from malicious attacks, the most important node is the most influential spreader, the one that is capable of propagating information in the shortest time to a large portion of the network. Here we propose the Node Imposed Response (NiR), a measure which accurately evaluates node spreading power. It outperforms betweenness, degree, k-shell and h-index centrality in many cases and shows the similar accuracy to dynamics-sensitive centrality. We utilize the system-theoretic approach considering the network as a Linear Time-Invariant system. By observing the system response we can quantify the importance of each node. In addition, our study provides a robust tool set for various protective strategies. PMID:28030548
Cardiovascular dynamics during space sickness and deconditioning

NASA Technical Reports Server (NTRS)

Goldberger, Ary L.; Rigney, David R.

1991-01-01

We are currently funded by NASA for the project, 'Cardiovascular Dynamics During Space Sickness and Deconditioning.' NASA has given priority to the investigation of two problems encountered in the long-term space flights currently being planned: (1) space motion sickness; and (2) cardiovascular deconditioning. We have proposed to use spectral and nonlinear dynamical analysis of heart rate data to quantify the presence of these problems and to evaluate countermeasures against them.
Quantifying Contemporary Terrestrial Carbon Sources and Sinks in the Conterminous United States

NASA Astrophysics Data System (ADS)

Liu, S.; Loveland, T.

2003-12-01

U.S. land likely accounts for a significant portion of the unidentified global carbon sink, although the magnitude is highly uncertain. The ultimate goal of this study is to quantify the contemporary temporal and spatial patterns of carbon sources and sinks in the conterminous United States from the early 1970s to 2000, and to explain the mechanisms that cause the variability and changes. Because of the difficulty and massive cost for developing land cover change databases for the conterminous United States, we adopt an ecoregion-based sampling approach. Carbon dynamics within thousands of 20 km by 20 km or 10 km by 10 km sampling blocks, stratified by Omernik Level III ecoregions, are simulated using the General Ensemble Biogeochemical Modeling System at the spatial resolution of 60 m by 60 m. The land use change data, providing unprecedented accuracy and consistency, are derived from Landsat imagery for five time points (nominally 1972, 1980, 1986, 1992, and 2000). Mechanisms have been implemented to assimilate data from key national benchmark databases (including the USDA Forest Service_s Forest Inventory and Analysis data and the USDA_s agricultural census data). The dynamics of carbon stocks in vegetation, soil, and harvested wood materials are quantified. Results from three ecoregions (i.e., Southeastern Plains, Piedmont, and Northern Piedmont) indicated that the carbon sink strength has been decreasing from the 1970s to 2000. The relative contribution of biomass accumulation to the sink decreased during this period, while those of soil organic carbon and harvested wood materials increased.
Post-fire reconstructions of fire intensity from fire severity data: quantifying the role of spatial variability of fire intensity on forest dynamics

NASA Astrophysics Data System (ADS)

Baker, Patrick; Oborne, Lisa

2015-04-01

Large, high-intensity fires have direct and long-lasting effects on forest ecosystems and present a serious threat to human life and property. However, even within the most catastrophic fires there is important variability in local-scale intensity that has important ramifications for forest mortality and regeneration. Quantifying this variability is difficult due to the rarity of catastrophic fire events, the extreme conditions at the time of the fires, and their large spatial extent. Instead fire severity is typically measured or estimated from observed patterns of vegetation mortality; however, differences in species- and size-specific responses to fires often makes fire severity a poor proxy for fire intensity. We developed a statistical method using simple, plot-based measurements of individual tree mortality to simultaneously estimate plot-level fire intensity and species-specific mortality patterns as a function of tree size. We applied our approach to an area of forest burned in the catastrophic Black Saturday fires that occurred near Melbourne, Australia, in February 2009. Despite being the most devastating fire in the past 70 years and our plots being located in the area that experienced some of the most intense fires in the 350,000 ha fire complex, we found that the estimated fire intensity was highly variable at multiple spatial scales. All eight tree species in our study differed in their susceptibility to fire-induced mortality, particularly among the largest size classes. We also found that seedling height and species richness of the post-fire seedling communities were both positively correlated with fire intensity. Spatial variability in disturbance intensity has important, but poorly understood, consequences for the short- and long-term dynamics of forests in the wake of catastrophic wildfires. Our study provides a tool to estimate fire intensity after a fire has passed, allowing new opportunities for linking spatial variability in fire intensity to
Observation and quantification of the quantum dynamics of a strong-field excited multi-level system.

PubMed

Liu, Zuoye; Wang, Quanjun; Ding, Jingjie; Cavaletto, Stefano M; Pfeifer, Thomas; Hu, Bitao

2017-01-04

The quantum dynamics of a V-type three-level system, whose two resonances are first excited by a weak probe pulse and subsequently modified by another strong one, is studied. The quantum dynamics of the multi-level system is closely related to the absorption spectrum of the transmitted probe pulse and its modification manifests itself as a modulation of the absorption line shape. Applying the dipole-control model, the modulation induced by the second strong pulse to the system's dynamics is quantified by eight intensity-dependent parameters, describing the self and inter-state contributions. The present study opens the route to control the quantum dynamics of multi-level systems and to quantify the quantum-control process.
Using ultrasound to quantify tongue shape and movement characteristics.

PubMed

Zharkova, Natalia

2013-01-01

Objective : Previous experimental studies have demonstrated abnormal lingual articulatory patterns characterizing cleft palate speech. Most articulatory information to date has been collected using electropalatography, which records the location and size of tongue-palate contact but not the tongue shape. The latter type of data can be provided by ultrasound. The present paper aims to describe ultrasound tongue imaging as a potential tool for quantitative analysis of tongue function in speakers with cleft palate. A description of the ultrasound technique as applied to analyzing tongue movements is given, followed by the requirements for quantitative analysis. Several measures are described, and example calculations are provided. Measures : Two measures aim to quantify overuse of tongue dorsum in cleft palate articulations. Crucially for potential clinical applications, these measures do not require head-to-transducer stabilization because both are based on a single tongue curve. The other three measures compare sets of tongue curves, with the aim to quantify the dynamics of tongue displacement, token-to-token variability in tongue position, and the extent of separation between tongue curves for different speech sounds. Conclusions : All measures can be used to compare tongue function in speakers with cleft palate before and after therapy, as well as to assess their performance against that in typical speakers and to help in selecting more effective treatments.
A Hybrid Knowledge-Based and Data-Driven Approach to Identifying Semantically Similar Concepts

PubMed Central

Pivovarov, Rimma; Elhadad, Noémie

2012-01-01

An open research question when leveraging ontological knowledge is when to treat different concepts separately from each other and when to aggregate them. For instance, concepts for the terms "paroxysmal cough" and "nocturnal cough" might be aggregated in a kidney disease study, but should be left separate in a pneumonia study. Determining whether two concepts are similar enough to be aggregated can help build better datasets for data mining purposes and avoid signal dilution. Quantifying the similarity among concepts is a difficult task, however, in part because such similarity is context-dependent. We propose a comprehensive method, which computes a similarity score for a concept pair by combining data-driven and ontology-driven knowledge. We demonstrate our method on concepts from SNOMED-CT and on a corpus of clinical notes of patients with chronic kidney disease. By combining information from usage patterns in clinical notes and from ontological structure, the method can prune out concepts that are simply related from those which are semantically similar. When evaluated against a list of concept pairs annotated for similarity, our method reaches an AUC (area under the curve) of 92%. PMID:22289420
Do Behavioral Foraging Responses of Prey to Predators Function Similarly in Restored and Pristine Foodwebs?

PubMed Central

Madin, Elizabeth M. P.; Gaines, Steven D.; Madin, Joshua S.; Link, Anne-Katrin; Lubchenco, Peggy J.; Selden, Rebecca L.; Warner, Robert R.

2012-01-01

Efforts to restore top predators in human-altered systems raise the question of whether rebounds in predator populations are sufficient to restore pristine foodweb dynamics. Ocean ecosystems provide an ideal system to test this question. Removal of fishing in marine reserves often reverses declines in predator densities and size. However, whether this leads to restoration of key functional characteristics of foodwebs, especially prey foraging behavior, is unclear. The question of whether restored and pristine foodwebs function similarly is nonetheless critically important for management and restoration efforts. We explored this question in light of one important determinant of ecosystem function and structure – herbivorous prey foraging behavior. We compared these responses for two functionally distinct herbivorous prey fishes (the damselfish Plectroglyphidodon dickii and the parrotfish Chlorurus sordidus) within pairs of coral reefs in pristine and restored ecosystems in two regions of these species' biogeographic ranges, allowing us to quantify the magnitude and temporal scale of this key ecosystem variable's recovery. We demonstrate that restoration of top predator abundances also restored prey foraging excursion behaviors to a condition closely resembling those of a pristine ecosystem. Increased understanding of behavioral aspects of ecosystem change will greatly improve our ability to predict the cascading consequences of conservation tools aimed at ecological restoration, such as marine reserves. PMID:22403650
A Causal Relation between Bioluminescence and Oxygen to Quantify the Cell Niche

PubMed Central

Lambrechts, Dennis; Roeffaers, Maarten; Goossens, Karel; Hofkens, Johan; Van de Putte, Tom; Schrooten, Jan; Van Oosterwyck, Hans

2014-01-01

Bioluminescence imaging assays have become a widely integrated technique to quantify effectiveness of cell-based therapies by monitoring fate and survival of transplanted cells. To date these assays are still largely qualitative and often erroneous due to the complexity and dynamics of local micro-environments (niches) in which the cells reside. Here, we report, using a combined experimental and computational approach, on oxygen that besides being a critical niche component responsible for cellular energy metabolism and cell-fate commitment, also serves a primary role in regulating bioluminescent light kinetics. We demonstrate the potential of an oxygen dependent Michaelis-Menten relation in quantifying intrinsic bioluminescence intensities by resolving cell-associated oxygen gradients from bioluminescent light that is emitted from three-dimensional (3D) cell-seeded hydrogels. Furthermore, the experimental and computational data indicate a strong causal relation of oxygen concentration with emitted bioluminescence intensities. Altogether our approach demonstrates the importance of oxygen to evolve towards quantitative bioluminescence and holds great potential for future microscale measurement of oxygen tension in an easily accessible manner. PMID:24840204
A causal relation between bioluminescence and oxygen to quantify the cell niche.

PubMed

Lambrechts, Dennis; Roeffaers, Maarten; Goossens, Karel; Hofkens, Johan; Vande Velde, Greetje; Van de Putte, Tom; Schrooten, Jan; Van Oosterwyck, Hans

2014-01-01

Bioluminescence imaging assays have become a widely integrated technique to quantify effectiveness of cell-based therapies by monitoring fate and survival of transplanted cells. To date these assays are still largely qualitative and often erroneous due to the complexity and dynamics of local micro-environments (niches) in which the cells reside. Here, we report, using a combined experimental and computational approach, on oxygen that besides being a critical niche component responsible for cellular energy metabolism and cell-fate commitment, also serves a primary role in regulating bioluminescent light kinetics. We demonstrate the potential of an oxygen dependent Michaelis-Menten relation in quantifying intrinsic bioluminescence intensities by resolving cell-associated oxygen gradients from bioluminescent light that is emitted from three-dimensional (3D) cell-seeded hydrogels. Furthermore, the experimental and computational data indicate a strong causal relation of oxygen concentration with emitted bioluminescence intensities. Altogether our approach demonstrates the importance of oxygen to evolve towards quantitative bioluminescence and holds great potential for future microscale measurement of oxygen tension in an easily accessible manner.
Quantifying the ecological success of a community-based wildlife conservation area in Tanzania.

PubMed

Lee, Derek E; Bond, Monica L

2018-04-03

In Tanzania, community-based natural resource management of wildlife occurs through the creation of Wildlife Management Areas (WMAs). WMAs consist of multiple villages designating land for wildlife conservation, and sharing a portion of subsequent tourism revenues. Nineteen WMAs are currently operating, encompassing 7% of Tanzania's land area, with 19 more WMAs planned. The ecological success or failure of WMAs for wildlife conservation has yet to be quantified. We defined ecological success in this case as significantly greater densities of wildlife and significantly lower densities of livestock in the WMA relative to the control site, after the WMA was established. We used 4 years of distance sampling surveys conducted 6 times per year for wild and domestic ungulates to quantify wildlife and livestock densities before and after the establishment and implementation of management efforts at Randilen WMA, relative to a control site on adjacent land of similar vegetation and habitat types. We documented similarity between the sites before WMA establishment, when both sites were managed by the same authority. After WMA establishment, we documented significantly higher densities of resident wildlife (giraffes and dik-diks) and lower densities of cattle in the WMA, relative to the control site, indicating short-term ecological success. Continued monitoring is necessary to determine longer-term effects, and to evaluate management decisions.
Quantifying arm nonuse in individuals poststroke.

PubMed

Han, Cheol E; Kim, Sujin; Chen, Shuya; Lai, Yi-Hsuan; Lee, Jeong-Yoon; Osu, Rieko; Winstein, Carolee J; Schweighofer, Nicolas

2013-06-01

Arm nonuse, defined as the difference between what the individual can do when constrained to use the paretic arm and what the individual does when given a free choice to use either arm, has not yet been quantified in individuals poststroke. (1) To quantify nonuse poststroke and (2) to develop and test a novel, simple, objective, reliable, and valid instrument, the Bilateral Arm Reaching Test (BART), to quantify arm use and nonuse poststroke. First, we quantify nonuse with the Quality of Movement (QOM) subscale of the Actual Amount of Use Test (AAUT) by subtracting the AAUT QOM score in the spontaneous use condition from the AAUT QOM score in a subsequent constrained use condition. Second, we quantify arm use and nonuse with BART by comparing reaching performance to visual targets projected over a 2D horizontal hemi-work space in a spontaneous-use condition (in which participants are free to use either arm at each trial) with reaching performance in a constrained-use condition. All participants (N = 24) with chronic stroke and with mild to moderate impairment exhibited nonuse with the AAUT QOM. Nonuse with BART had excellent test-retest reliability and good external validity. BART is the first instrument that can be used repeatedly and practically in the clinic to quantify the effects of neurorehabilitation on arm use and nonuse and in the laboratory for advancing theoretical knowledge about the recovery of arm use and the development of nonuse and "learned nonuse" after stroke.
Similarity laws of lunar and terrestrial volcanic flows

NASA Technical Reports Server (NTRS)

Pai, S. I.; Hsu, Y.; Okeefe, J. A.

1977-01-01

A mathematical model of a one dimensional, steady duct flow of a mixture of a gas and small solid particles (rock) was analyzed and applied to the lunar and the terrestrial volcanic flows under geometrically and dynamically similar conditions. Numerical results for the equilibrium two phase flows of lunar and terrestrial volcanoes under similar conditions are presented. The study indicates that: (1) the lunar crater is much larger than the corresponding terrestrial crater; (2) the exit velocity from the lunar volcanic flow may be higher than the lunar escape velocity but the exit velocity of terrestrial volcanic flow is much less than that of the lunar case; and (3) the thermal effects on the lunar volcanic flow are much larger than those of the terrestrial case.
Coordinated Approaches to Quantify Long-Term Ecosystem dynamics in Response to Global Change

USDA-ARS?s Scientific Manuscript database

Climate change and its impact on ecosystems are usually assessed at decadal and century time scales. Ecological responses to climate change at those scales are strongly regulated by long-term processes, such as changes in species composition, carbon dynamics in soil and by big trees, and nutrient r...
The Heterogeneous Dynamics of Economic Complexity

PubMed Central

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312
The heterogeneous dynamics of economic complexity.

PubMed

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.
Data quantile-quantile plots: quantifying the time evolution of space climatology

NASA Astrophysics Data System (ADS)

Tindale, Elizabeth; Chapman, Sandra

2017-04-01

The solar wind is inherently variable across a wide range of spatio-temporal scales; embedded in the flow are the signatures of distinct non-linear physical processes from evolving turbulence to the dynamical solar corona. In-situ satellite observations of solar wind magnetic field and velocity are at minute and below time resolution and now extend over several solar cycles. Each solar cycle is unique, and the space climatology challenge is to quantify how solar wind variability changes within, and across, each distinct solar cycle, and how this in turn drives space weather at earth. We will demonstrate a novel statistical method, that of data-data quantile-quantile (DQQ) plots, which quantifies how the underlying statistical distribution of a given observable is changing in time. Importantly this method does not require any assumptions concerning the underlying functional form of the distribution and can identify multi-component behaviour that is changing in time. This can be used to determine when a sub-range of a given observable is undergoing a change in statistical distribution, or where the moments of the distribution only are changing and the functional form of the underlying distribution is not changing in time. The method is quite general; for this application we use data from the WIND satellite to compare the solar wind across the minima and maxima of solar cycles 23 and 24 [1], and how these changes are manifest in parameters that quantify coupling to the earth's magnetosphere. [1] Tindale, E., and S.C. Chapman (2016), Geophys. Res. Lett., 43(11), doi: 10.1002/2016GL068920.
Short-term dynamic behavior of Escherichia coli in response to successive glucose pulses on glucose-limited chemostat cultures.

PubMed

Sunya, Sirichai; Bideaux, Carine; Molina-Jouve, Carole; Gorret, Nathalie

2013-04-15

The effect of repeated glucose perturbations on dynamic behavior of Escherichia coli DPD2085, yciG::LuxCDABE reporter strain, was studied and characterized on a short-time scale using glucose-limited chemostat cultures at dilution rates close to 0.18h(-1). The substrate disturbances were applied on independent steady-state cultures, firstly using a single glucose pulse under different aeration conditions and secondly using repeated glucose pulses under fully aerobic condition. The dynamic responses of E. coli to a single glucose pulse of different intensities (0.25 and 0.6gL(-1)) were significantly similar at macroscopic level, revealing the independency of the macroscopic microbial behavior to the perturbation intensity in the range of tested glucose concentrations. The dynamic responses of E. coli to repeated glucose pulses to simulate fluctuating environments between glucose-limited and glucose-excess conditions were quantified; similar behavior regarding respiration and by-product formations was observed, except for the first perturbation denoted by an overshoot of the specific oxygen uptake rate in the first minutes after the pulse. In addition, transcriptional induction of yciG promoter gene involved in general stress response, σ(S), was monitored through the bioluminescent E. coli strain. This study aims to provide and compare short-term quantitative kinetics data describing the dynamic behavior of E. coli facing repeated transient substrate conditions. Copyright © 2013 Elsevier B.V. All rights reserved.
Chaotic dynamics of Comet 1P/Halley: Lyapunov exponent and survival time expectancy

NASA Astrophysics Data System (ADS)

Muñoz-Gutiérrez, M. A.; Reyes-Ruiz, M.; Pichardo, B.

2015-03-01

The orbital elements of Comet Halley are known to a very high precision, suggesting that the calculation of its future dynamical evolution is straightforward. In this paper we seek to characterize the chaotic nature of the present day orbit of Comet Halley and to quantify the time-scale over which its motion can be predicted confidently. In addition, we attempt to determine the time-scale over which its present day orbit will remain stable. Numerical simulations of the dynamics of test particles in orbits similar to that of Comet Halley are carried out with the MERCURY 6.2 code. On the basis of these we construct survival time maps to assess the absolute stability of Halley's orbit, frequency analysis maps to study the variability of the orbit, and we calculate the Lyapunov exponent for the orbit for variations in initial conditions at the level of the present day uncertainties in our knowledge of its orbital parameters. On the basis of our calculations of the Lyapunov exponent for Comet Halley, the chaotic nature of its motion is demonstrated. The e-folding time-scale for the divergence of initially very similar orbits is approximately 70 yr. The sensitivity of the dynamics on initial conditions is also evident in the self-similarity character of the survival time and frequency analysis maps in the vicinity of Halley's orbit, which indicates that, on average, it is unstable on a time-scale of hundreds of thousands of years. The chaotic nature of Halley's present day orbit implies that a precise determination of its motion, at the level of the present-day observational uncertainty, is difficult to predict on a time-scale of approximately 100 yr. Furthermore, we also find that the ejection of Halley from the Solar system or its collision with another body could occur on a time-scale as short as 10 000 yr.

Self-similar random process and chaotic behavior in serrated flow of high entropy alloys

DOE PAGES

Chen, Shuying; Yu, Liping; Ren, Jingli; ...

2016-07-20

Here, the statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al 0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, andmore » there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.« less
Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys.

PubMed

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K

2016-07-20

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.
Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys

PubMed Central

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K.

2016-01-01

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk. PMID:27435922
Observations and analysis of self-similar branching topology in glacier networks

USGS Publications Warehouse

Bahr, D.B.; Peckham, S.D.

1996-01-01

Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.
Quantifying T Lymphocyte Turnover

PubMed Central

De Boer, Rob J.; Perelson, Alan S.

2013-01-01

Peripheral T cell populations are maintained by production of naive T cells in the thymus, clonal expansion of activated cells, cellular self-renewal (or homeostatic proliferation), and density dependent cell life spans. A variety of experimental techniques have been employed to quantify the relative contributions of these processes. In modern studies lymphocytes are typically labeled with 5-bromo-2′-deoxyuridine (BrdU), deuterium, or the fluorescent dye carboxy-fluorescein diacetate succinimidyl ester (CFSE), their division history has been studied by monitoring telomere shortening and the dilution of T cell receptor excision circles (TRECs) or the dye CFSE, and clonal expansion has been documented by recording changes in the population densities of antigen specific cells. Proper interpretation of such data in terms of the underlying rates of T cell production, division, and death has proven to be notoriously difficult and involves mathematical modeling. We review the various models that have been developed for each of these techniques, discuss which models seem most appropriate for what type of data, reveal open problems that require better models, and pinpoint how the assumptions underlying a mathematical model may influence the interpretation of data. Elaborating various successful cases where modeling has delivered new insights in T cell population dynamics, this review provides quantitative estimates of several processes involved in the maintenance of naive and memory, CD4+ and CD8+ T cell pools in mice and men. PMID:23313150
Coordinated approaches to quantify long-term ecosystem dynamics in response to global change

Treesearch

Yiqi Luo; Jerry Melillo; Shuli Niu; Claus Beier; James S. Clark; Aime E.T. Classen; Eric Dividson; Jeffrey S. Dukes; R. Dave Evans; Christopher B. Field; Claudia I. Czimczik; Michael Keller; Bruce A. Kimball; Lara M. Kueppers; Richard J. Norby; Shannon L. Pelini; Elise Pendall; Edward Rastetter; Johan Six; Melinda Smith; Mark G. Tjoelker; Margaret S. Torn

2011-01-01

Many serious ecosystem consequences of climate change will take decades or even centuries to emerge. Long-term ecological responses to global change are strongly regulated by slow processes, such as changes in species composition, carbon dynamics in soil and by long-lived plants, and accumulation of nutrient capitals. Understanding and predicting these processes...
New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

NASA Technical Reports Server (NTRS)

Ott, L.; Pawson, S.; Zhu, Z.; Nielsen, J. E.; Collatz, G. J.; Gregg, W. W.

2012-01-01

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.
Using atmospheric fallout to date organic horizon layers and quantify metal dynamics during decomposition

NASA Astrophysics Data System (ADS)

Kaste, James M.; Bostick, Benjamin C.; Heimsath, Arjun M.; Steinnes, Eiliv; Friedland, Andrew J.

2011-03-01

High concentrations of metals in organic matter can inhibit decomposition and limit nutrient availability in ecosystems, but the long-term fate of metals bound to forest litter is poorly understood. Controlled experiments indicate that during the first few years of litter decay, Al, Fe, Pb, and other metals that form stable complexes with organic matter are naturally enriched by several hundred percent as carbon is oxidized. The transformation of fresh litter to humus takes decades, however, such that current datasets describing the accumulation and release of metals in decomposing organic matter are timescale limited. Here we use atmospheric 210Pb to quantify the fate of metals in canopy-derived litter during burial and decay in coniferous forests in New England and Norway where decomposition rates are slow and physical soil mixing is minimal. We measure 210Pb inventories in the O horizon and mineral soil and calculate a 60-630 year timescale for the production of mobile organo-metallic colloids from the decomposition of fresh forest detritus. This production rate is slowest at our highest elevation (˜1000 m) and highest latitude sites (>63°N) where decomposition rates are expected to be low. We calculate soil layer ages by assuming a constant supply of atmospheric 210Pb and find that they are consistent with the distribution of geochemical tracers from weapons fallout, air pollution, and a direct 207Pb application at one site. By quantifying a gradient of organic matter ages with depth in the O horizon, we describe the accumulation and loss of metals in the soil profile as organic matter transforms from fresh litter to humus. While decomposition experiments predict that Al and Fe concentrations increase during the initial few years of decay, we show here that these metals continue to accumulate in humus for decades, and that enrichment occurs at a rate higher than can be explained by quantitative retention during decomposition alone. Acid extractable Al and Fe
disLocate: tools to rapidly quantify local intermolecular structure to assess two-dimensional order in self-assembled systems.

PubMed

Bumstead, Matt; Liang, Kunyu; Hanta, Gregory; Hui, Lok Shu; Turak, Ayse

2018-01-24

Order classification is particularly important in photonics, optoelectronics, nanotechnology, biology, and biomedicine, as self-assembled and living systems tend to be ordered well but not perfectly. Engineering sets of experimental protocols that can accurately reproduce specific desired patterns can be a challenge when (dis)ordered outcomes look visually similar. Robust comparisons between similar samples, especially with limited data sets, need a finely tuned ensemble of accurate analysis tools. Here we introduce our numerical Mathematica package disLocate, a suite of tools to rapidly quantify the spatial structure of a two-dimensional dispersion of objects. The full range of tools available in disLocate give different insights into the quality and type of order present in a given dispersion, accessing the translational, orientational and entropic order. The utility of this package allows for researchers to extract the variation and confidence range within finite sets of data (single images) using different structure metrics to quantify local variation in disorder. Containing all metrics within one package allows for researchers to easily and rapidly extract many different parameters simultaneously, allowing robust conclusions to be drawn on the order of a given system. Quantifying the experimental trends which produce desired morphologies enables engineering of novel methods to direct self-assembly.
Centrifugal fans: Similarity, scaling laws, and fan performance

NASA Astrophysics Data System (ADS)

Sardar, Asad Mohammad

Centrifugal fans are rotodynamic machines used for moving air continuously against moderate pressures through ventilation and air conditioning systems. There are five major topics presented in this thesis: (1) analysis of the fan scaling laws and consequences of dynamic similarity on modelling; (2) detailed flow visualization studies (in water) covering the flow path starting at the fan blade exit to the evaporator core of an actual HVAC fan scroll-diffuser module; (3) mean velocity and turbulence intensity measurements (flow field studies) at the inlet and outlet of large scale blower; (4) fan installation effects on overall fan performance and evaluation of fan testing methods; (5) two point coherence and spectral measurements conducted on an actual HVAC fan module for flow structure identification of possible aeroacoustic noise sources. A major objective of the study was to identity flow structures within the HVAC module that are responsible for noise and in particular "rumble noise" generation. Possible mechanisms for the generation of flow induced noise in the automotive HVAC fan module are also investigated. It is demonstrated that different modes of HVAC operation represent very different internal flow characteristics. This has implications on both fan HVAC airflow performance and noise characteristics. It is demonstrated from principles of complete dynamic similarity that fan scaling laws require that Reynolds, number matching is a necessary condition for developing scale model fans or fan test facilities. The physical basis for the fan scaling laws derived was established from both pure dimensional analysis and also from the fundamental equations of fluid motion. Fan performance was measured in a three times scale model (large scale blower) in air of an actual forward curved automotive HVAC blower. Different fan testing methods (based on AMCA fan test codes) were compared on the basis of static pressure measurements. Also, the flow through an actual HVAC
Demonstrating vegetation dynamics using SIMPPLLE

Treesearch

Glenda Scott; Jimmie D. Chew

1997-01-01

Understanding vegetation dynamics, both spatially and temporally, is essential to the management of natural resources. SIMPPLLE has been designed to help us quantify and communicate these concepts: What levels of process, i.e., fire or insect and disease, to expect; how they spread; what the vegetative distribution and composition is over time; and how silvicultural...
Quantifying the dilution effect for models in ecological epidemiology.

PubMed

Roberts, M G; Heesterbeek, J A P

2018-03-01

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

PubMed Central

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

2015-01-01

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

PubMed

Strand, Julia F; Sommers, Mitchell S

2011-09-01

Much research has explored how spoken word recognition is influenced by the architecture and dynamics of the mental lexicon (e.g., Luce and Pisoni, 1998; McClelland and Elman, 1986). A more recent question is whether the processes underlying word recognition are unique to the auditory domain, or whether visually perceived (lipread) speech may also be sensitive to the structure of the mental lexicon (Auer, 2002; Mattys, Bernstein, and Auer, 2002). The current research was designed to test the hypothesis that both aurally and visually perceived spoken words are isolated in the mental lexicon as a function of their modality-specific perceptual similarity to other words. Lexical competition (the extent to which perceptually similar words influence recognition of a stimulus word) was quantified using metrics that are well-established in the literature, as well as a statistical method for calculating perceptual confusability based on the phi-square statistic. Both auditory and visual spoken word recognition were influenced by modality-specific lexical competition as well as stimulus word frequency. These findings extend the scope of activation-competition models of spoken word recognition and reinforce the hypothesis (Auer, 2002; Mattys et al., 2002) that perceptual and cognitive properties underlying spoken word recognition are not specific to the auditory domain. In addition, the results support the use of the phi-square statistic as a better predictor of lexical competition than metrics currently used in models of spoken word recognition. © 2011 Acoustical Society of America
Cluster dynamics transcending chemical dynamics toward nuclear fusion

PubMed Central

Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

2006-01-01

Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 1015–1020 W·cm−2). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C4+(D+)4)n and (D+I22+)n at IM = 1018 W·cm−2, that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D2)n, (HT)n, (CD4)n, (DI)n, (CD3I)n, and (CH3I)n clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D2)n clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., 12C(P,γ)13N driven by CE of (CH3I)n clusters, were explored. PMID:16740666
Cluster dynamics transcending chemical dynamics toward nuclear fusion.

PubMed

Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

2006-07-11

Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 10(15)-10(20) W.cm(-2)). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C(4+)(D(+))(4))(n) and (D(+)I(22+))(n) at I(M) = 10(18) W.cm(-2), that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D(2))(n), (HT)(n), (CD(4))(n), (DI)(n), (CD(3)I)(n), and (CH(3)I)(n) clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D(2))(n) clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., (12)C(P,gamma)(13)N driven by CE of (CH(3)I)(n) clusters, were explored.
Quantifying the radiative and microphysical impacts of fire aerosols on cloud dynamics in the tropics using temporally offset satellite observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O.

2013-12-01

Anthropogenic fires in Southeast Asia and Central America emit smoke that affects cloud dynamics, meteorology, and climate. We measured the cloud response to direct and indirect forcing from biomass burning aerosols using aerosol retrievals from the Multi-angle Imaging SpectroRadiometer (MISR) and non-synchronous cloud retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) from collocated morning and afternoon overpasses. Level 2 data from thirty-one individual scenes acquired between 2006 and 2010 were used to quantify changes in cloud fraction, cloud droplet size, cloud optical depth and cloud top temperature from morning (10:30am local time) to afternoon (1:30pm local time) in the presence of varying aerosol burdens. We accounted for large-scale meteorological differences between scenes by normalizing observed changes to the mean difference per individual scene. Elevated AODs reduced cloud fraction and cloud droplet size and increased cloud optical depths in both Southeast Asia and Central America. In mostly cloudy regions, aerosols significantly reduced cloud fraction and cloud droplet sizes, but in clear skies, cloud fraction, cloud optical thickness and cloud droplet sizes increased. In clouds with vertical development, aerosols reduced cloud fraction via semi-direct effects but spurred cloud growth via indirect effects. These results imply a positive feedback loop between anthropogenic burning and cloudiness in both Central America and Southeast Asia, and are consistent with previous studies linking smoke aerosols to both cloud reduction and convective invigoration.
Similar star formation rate and metallicity variability time-scales drive the fundamental metallicity relation

NASA Astrophysics Data System (ADS)

Torrey, Paul; Vogelsberger, Mark; Hernquist, Lars; McKinnon, Ryan; Marinacci, Federico; Simcoe, Robert A.; Springel, Volker; Pillepich, Annalisa; Naiman, Jill; Pakmor, Rüdiger; Weinberger, Rainer; Nelson, Dylan; Genel, Shy

2018-06-01

The fundamental metallicity relation (FMR) is a postulated correlation between galaxy stellar mass, star formation rate (SFR), and gas-phase metallicity. At its core, this relation posits that offsets from the mass-metallicity relation (MZR) at a fixed stellar mass are correlated with galactic SFR. In this Letter, we use hydrodynamical simulations to quantify the time-scales over which populations of galaxies oscillate about the average SFR and metallicity values at fixed stellar mass. We find that Illustris and IllustrisTNG predict that galaxy offsets from the star formation main sequence and MZR oscillate over similar time-scales, are often anticorrelated in their evolution, evolve with the halo dynamical time, and produce a pronounced FMR. Our models indicate that galaxies oscillate about equilibrium SFR and metallicity values - set by the galaxy's stellar mass - and that SFR and metallicity offsets evolve in an anticorrelated fashion. This anticorrelated variability of the metallicity and SFR offsets drives the existence of the FMR in our models. In contrast to Illustris and IllustrisTNG, we speculate that the SFR and metallicity evolution tracks may become decoupled in galaxy formation models dominated by feedback-driven globally bursty SFR histories, which could weaken the FMR residual correlation strength. This opens the possibility of discriminating between bursty and non-bursty feedback models based on the strength and persistence of the FMR - especially at high redshift.
Quantifying the Geomorphic Dynamics of the Extensively Impacted Lower Yuba River

NASA Astrophysics Data System (ADS)

Wyrick, J. R.; Pasternack, G. B.; Carley, J. K.; Barker, R.; Massa, D.; Bratovich, P.; Reedy, G.; Johnson, T.

2010-12-01

Traditionally it is has been thought that rivers possess the capability of adjusting their attributes to accommodate varying flow and sediment transport regimes so that sediment in- and out-fluxes are balanced and landform conditions are “stable”. In reality, however, geomorphic drivers and boundary conditions are much more independently dynamic than classically envisioned, such that landforms may always be in a state of adjustment that is normal and appropriate. Rather than thinking of landforms as stable, it is more appropriate to think of them, and the ecosystem services with which they are associated, as resilient in response to change. Knowledge of historic, pre-human baseline conditions or regional reference conditions is limited and may not be as applicable in understanding natural geomorphic and ecosystem services as once envisioned. In light of this natural complexity, a geomorphic assessment of conditions after a large dam or other facility is built and operated may not be as simple as documenting geomorphic instability and attributing that to human impacts relative to the presumed stable baseline conditions. Rather than compare anthropogenically-impacted conditions to theoretical baseline or reference conditions, a more effective approach is to deduce the geomorphic processes in a system under different regimes and evaluate the implications for resiliency of ecosystem services. Through a mechanistic understanding of environmental systems, it may be possible to rationally rehabilitate an ecosystem to achieve resiliency in cases where it has been lost or is desirable to instill, even if it was not historically present. This analytic paradigm is being used to assess the history and on-going geomorphic dynamism of the lower Yuba River (LYR) in northern California. Despite a legacy of massive hydraulic mining waste deposition, dredger re-working of the river valley, dam construction, and flow regulation, the river has been described as lacking the
Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

PubMed

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term.
Similarity from Multi-Dimensional Scaling: Solving the Accuracy and Diversity Dilemma in Information Filtering

PubMed Central

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term. PMID:25343243
Processing of Numerical and Proportional Quantifiers

ERIC Educational Resources Information Center

Shikhare, Sailee; Heim, Stefan; Klein, Elise; Huber, Stefan; Willmes, Klaus

2015-01-01

Quantifier expressions like "many" and "at least" are part of a rich repository of words in language representing magnitude information. The role of numerical processing in comprehending quantifiers was studied in a semantic truth value judgment task, asking adults to quickly verify sentences about visual displays using…
Risk assessment by dynamic representation of vulnerability, exploitation, and impact

NASA Astrophysics Data System (ADS)

Cam, Hasan

2015-05-01

Assessing and quantifying cyber risk accurately in real-time is essential to providing security and mission assurance in any system and network. This paper presents a modeling and dynamic analysis approach to assessing cyber risk of a network in real-time by representing dynamically its vulnerabilities, exploitations, and impact using integrated Bayesian network and Markov models. Given the set of vulnerabilities detected by a vulnerability scanner in a network, this paper addresses how its risk can be assessed by estimating in real-time the exploit likelihood and impact of vulnerability exploitation on the network, based on real-time observations and measurements over the network. The dynamic representation of the network in terms of its vulnerabilities, sensor measurements, and observations is constructed dynamically using the integrated Bayesian network and Markov models. The transition rates of outgoing and incoming links of states in hidden Markov models are used in determining exploit likelihood and impact of attacks, whereas emission rates help quantify the attack states of vulnerabilities. Simulation results show the quantification and evolving risk scores over time for individual and aggregated vulnerabilities of a network.
On the Mediterranean Sea inter-basin exchanges and nutrient dynamics

NASA Astrophysics Data System (ADS)

Rupolo, V.; Ribera D'Alcalà, M.; Iudicone, D.; Artale, V.

2009-04-01

The Mediterranean Sea is an evaporative basin in which the deficit of water is supplied by the inflow from the Gibraltar Strait of Atlantic Water. The net result of the air sea interactions in the entire basin is an outflow at Gibraltar of a salty water that is mainly constituted by the Levantin Intermediate Water, formed in the eastern part of the basin. Despite this simplified pattern, the circulation in the Mediterranean is rather complex. Most of the Mediterranean sub-basins are characterized by water mass formation processes and the presence of sills and straits strongly influence both the spreading and the mixing of intermediate and deep waters. In this context a Lagrangian diagnostics applied to numerical results was used to quantify mass transport in the main pathways of the upper and lower cells of the Mediterranean thermohaline circulation as they results from OGCM simulations. Lagrangian diagnostics reveals to be very useful to quantify both transports between different regions and the associated spectrum of transit times by means of pdf distribution of particles transit times between the different regions of the basin. This method is very effective to estimate the contribution of different water masses in isopycnal and diapycnal transformation processes and in reconstructing the fate of tracers. We use here these previous results on the basin circulation for better understanding the nutrient dynamics within the basin where the inputs from the different sources (atmosphere, runoff and open ocean) have similar order of magnitude. This, to the aim of building scenarios on the impact of climate driven changes in elemental fluxes to the basin on the internal nutrient dynamics.
Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

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

Li, Minjing; Gao, Yuqian; Qian, Wei-Jun

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different frommore » that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.« less
Velocity-strengthening friction significantly affects interfacial dynamics, strength and dissipation

PubMed Central

Bar-Sinai, Yohai; Spatschek, Robert; Brener, Efim A.; Bouchbinder, Eran

2015-01-01

Frictional interfaces abound in natural and man-made systems, yet their dynamics are not well-understood. Recent extensive experimental data have revealed that velocity-strengthening friction, where the steady-state frictional resistance increases with sliding velocity over some range, is a generic feature of such interfaces. This physical behavior has very recently been linked to slow stick-slip motion. Here we elucidate the importance of velocity-strengthening friction by theoretically studying three variants of a realistic friction model, all featuring identical logarithmic velocity-weakening friction at small sliding velocities, but differ in their higher velocity behaviors. By quantifying energy partition (e.g. radiation and dissipation), the selection of interfacial rupture fronts and rupture arrest, we show that the presence or absence of strengthening significantly affects the global interfacial resistance and the energy release during frictional instabilities. Furthermore, we show that different forms of strengthening may result in events of similar magnitude, yet with dramatically different dissipation and radiation rates. This happens because the events are mediated by rupture fronts with vastly different propagation velocities, where stronger velocity-strengthening friction promotes slower rupture. These theoretical results may have significant implications on our understanding of frictional dynamics. PMID:25598161
Alignment of dynamic networks

PubMed Central

Vijayan, V.; Critchlow, D.; Milenković, T.

2017-01-01

Abstract Motivation: Network alignment (NA) aims to find a node mapping that conserves similar regions between compared networks. NA is applicable to many fields, including computational biology, where NA can guide the transfer of biological knowledge from well- to poorly-studied species across aligned network regions. Existing NA methods can only align static networks. However, most complex real-world systems evolve over time and should thus be modeled as dynamic networks. We hypothesize that aligning dynamic network representations of evolving systems will produce superior alignments compared to aligning the systems’ static network representations, as is currently done. Results: For this purpose, we introduce the first ever dynamic NA method, DynaMAGNA ++. This proof-of-concept dynamic NA method is an extension of a state-of-the-art static NA method, MAGNA++. Even though both MAGNA++ and DynaMAGNA++ optimize edge as well as node conservation across the aligned networks, MAGNA++ conserves static edges and similarity between static node neighborhoods, while DynaMAGNA++ conserves dynamic edges (events) and similarity between evolving node neighborhoods. For this purpose, we introduce the first ever measure of dynamic edge conservation and rely on our recent measure of dynamic node conservation. Importantly, the two dynamic conservation measures can be optimized with any state-of-the-art NA method and not just MAGNA++. We confirm our hypothesis that dynamic NA is superior to static NA, on synthetic and real-world networks, in computational biology and social domains. DynaMAGNA++ is parallelized and has a user-friendly graphical interface. Availability and implementation: http://nd.edu/∼cone/DynaMAGNA++/. Contact: tmilenko@nd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881980
Scalar Quantifiers: Logic, Acquisition, and Processing

ERIC Educational Resources Information Center

Geurts, Bart; Katsos, Napoleon; Cummins, Chris; Moons, Jonas; Noordman, Leo

2010-01-01

Superlative quantifiers ("at least 3", "at most 3") and comparative quantifiers ("more than 2", "fewer than 4") are traditionally taken to be interdefinable: the received view is that "at least n" and "at most n" are equivalent to "more than n-1" and "fewer than n+1",…
Potential and flux field landscape theory. I. Global stability and dynamics of spatially dependent non-equilibrium systems.

PubMed

Wu, Wei; Wang, Jin

2013-09-28

We established a potential and flux field landscape theory to quantify the global stability and dynamics of general spatially dependent non-equilibrium deterministic and stochastic systems. We extended our potential and flux landscape theory for spatially independent non-equilibrium stochastic systems described by Fokker-Planck equations to spatially dependent stochastic systems governed by general functional Fokker-Planck equations as well as functional Kramers-Moyal equations derived from master equations. Our general theory is applied to reaction-diffusion systems. For equilibrium spatially dependent systems with detailed balance, the potential field landscape alone, defined in terms of the steady state probability distribution functional, determines the global stability and dynamics of the system. The global stability of the system is closely related to the topography of the potential field landscape in terms of the basins of attraction and barrier heights in the field configuration state space. The effective driving force of the system is generated by the functional gradient of the potential field alone. For non-equilibrium spatially dependent systems, the curl probability flux field is indispensable in breaking detailed balance and creating non-equilibrium condition for the system. A complete characterization of the non-equilibrium dynamics of the spatially dependent system requires both the potential field and the curl probability flux field. While the non-equilibrium potential field landscape attracts the system down along the functional gradient similar to an electron moving in an electric field, the non-equilibrium flux field drives the system in a curly way similar to an electron moving in a magnetic field. In the small fluctuation limit, the intrinsic potential field as the small fluctuation limit of the potential field for spatially dependent non-equilibrium systems, which is closely related to the steady state probability distribution functional, is
Intergroup Variation of Social Relationships in Wild Vervet Monkeys: A Dynamic Network Approach.

PubMed

Borgeaud, Christèle; Sosa, Sebastian; Bshary, Redouan; Sueur, Cédric; van de Waal, Erica

2016-01-01

Social network analysis is a powerful tool that enables us to describe and quantify relationships between individuals. So far most of the studies rely on the analyses of various network snapshots, but do not capture changes over time. Here we use a stochastic actor-oriented model (SAOM) to test both the structure and the dynamics of relationships of three groups of wild vervet monkeys. We found that triadic closure (i.e., the friend of a friend is a friend) was significant in all three groups while degree popularity (i.e., the willingness to associate with individuals with high degree of connections) was significant in only two groups (AK, BD). The structure and dynamics of relationships according to the attributes of sex, matrilineand age differed significantly among groups. With respect to the structure, when analyzing the likelihood of bonds according to the different attributes, we found that individuals associate themselves preferably to individuals of the same sex only in two groups (AK, NH), while significant results for attachment to individuals of the same matriline were found also in two groups (BD, NH). With respect to the dynamics, i.e., how quickly relationships are modified, we found in two groups (AK, BD) that females' relationships were more prone to variation than males.' In the BD group, relationships within high-ranking matrilines were less stable than low-ranking ones while in the NH group, juveniles' relationships were also less stable than adults' ones. The intergroup variation indicates that establishing species-specific or even population specific characteristics of social networks for later between-species comparisons will be challenging. Although, such variation could also indicate some methodological issue, we are quite confident that data was collected similarly within the different groups. Our study therefore provides a potential new method to quantify social complexity according to natural demographic variation.
Using expert opinion to quantify unmeasured confounding bias parameters.

PubMed

Navadeh, Soodabeh; Mirzazadeh, Ali; McFarland, Willi; Woolf-King, Sarah; Mansournia, Mohammad Ali

2016-06-27

To develop and apply a method to quantify bias parameters in the case example of the association between alcohol use and HIV-serodiscordant condomless anal sex with potential confounding by sensation seeking among men who have sex with men (MSM), using expert opinion as an external data source. Through an online survey, we sought the input of 41 epidemiologist and behavioural scientists to quantify six parameters in the population of MSM: the proportion of high sensation seeking among heavy-drinking MSM, the proportion of sensation seeking among low-level drinking MSM, and the risk ratio (RR) of the association between sensation seeking and condomless anal sex, for HIV-positive and HIV-negative MSM. Eleven experts responded. For HIV-positive heavy drinkers, the proportion of high sensation seeking was 53.6% (beta distribution [α=5.50, β=4.78]), and 41.1% (beta distribution [α=3.10, β=4.46]) in HIV-negative heavy drinkers. In HIV-positive low-level alcohol drinkers, high sensation seeking was 26.9% (beta distribution [α=1.81, β=4.92]), similar to high sensation seeking among HIV-negative low-level alcohol drinkers (25.3%) (beta distribution [α=2.00, β=5.89]). The lnRR for the association between sensation seeking and condomless anal sex was ln(2.4) (normal distribution [μ=0.889, σ=0.438]) in HIV-positive and ln(1.5) (normal distribution [μ=0.625, σ=0.391]) in HIV-negative MSM. Expert opinion can be a simple and efficient method for deriving bias parameters to quantify and adjust for hypothesized confounding. In this test case, expert opinion confirmed sensation seeking as a confounder for the effect of alcohol on condomless anal sex and provided the parameters necessary for probabilistic bias analysis.
Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

PubMed

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.
Quantifying the abnormal hemodynamics of sickle cell anemia

NASA Astrophysics Data System (ADS)

Lei, Huan; Karniadakis, George

2012-02-01

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

NASA Astrophysics Data System (ADS)

Rosenblum, Michael; Kralemann, Bjoern; Pikovsky, Arkady

2013-03-01

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

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Han, Feng; Sun, Bo

2012-08-01

In this study, we employ a dynamic time warping method to study the topology of similarity networks among 35 major currencies in international foreign exchange (FX) markets, measured by the minimal spanning tree (MST) approach, which is expected to overcome the synchronous restriction of the Pearson correlation coefficient. In the empirical process, firstly, we subdivide the analysis period from June 2005 to May 2011 into three sub-periods: before, during, and after the US sub-prime crisis. Secondly, we choose NZD (New Zealand dollar) as the numeraire and then, analyze the topology evolution of FX markets in terms of the structure changes of MSTs during the above periods. We also present the hierarchical tree associated with the MST to study the currency clusters in each sub-period. Our results confirm that USD and EUR are the predominant world currencies. But USD gradually loses the most central position while EUR acts as a stable center in the MST passing through the crisis. Furthermore, an interesting finding is that, after the crisis, SGD (Singapore dollar) becomes a new center currency for the network.
Controlling Interfacial Dynamics: Covalent Bonding versus Physical Adsorption in Polymer Nanocomposites

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

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

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

DOE PAGES

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

2016-06-23

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

PubMed Central

Lee, Derek E

2018-01-01

Abstract In Tanzania, community-based natural resource management of wildlife occurs through the creation of Wildlife Management Areas (WMAs). WMAs consist of multiple villages designating land for wildlife conservation, and sharing a portion of subsequent tourism revenues. Nineteen WMAs are currently operating, encompassing 7% of Tanzania’s land area, with 19 more WMAs planned. The ecological success or failure of WMAs for wildlife conservation has yet to be quantified. We defined ecological success in this case as significantly greater densities of wildlife and significantly lower densities of livestock in the WMA relative to the control site, after the WMA was established. We used 4 years of distance sampling surveys conducted 6 times per year for wild and domestic ungulates to quantify wildlife and livestock densities before and after the establishment and implementation of management efforts at Randilen WMA, relative to a control site on adjacent land of similar vegetation and habitat types. We documented similarity between the sites before WMA establishment, when both sites were managed by the same authority. After WMA establishment, we documented significantly higher densities of resident wildlife (giraffes and dik-diks) and lower densities of cattle in the WMA, relative to the control site, indicating short-term ecological success. Continued monitoring is necessary to determine longer-term effects, and to evaluate management decisions. PMID:29867255

Modeling malaria and typhoid fever co-infection dynamics.

PubMed

Mutua, Jones M; Wang, Feng-Bin; Vaidya, Naveen K

2015-06-01

Malaria and typhoid are among the most endemic diseases, and thus, of major public health concerns in tropical developing countries. In addition to true co-infection of malaria and typhoid, false diagnoses due to similar signs and symptoms and false positive results in testing methods, leading to improper controls, are the major challenges on managing these diseases. In this study, we develop novel mathematical models describing the co-infection dynamics of malaria and typhoid. Through mathematical analyses of our models, we identify distinct features of typhoid and malaria infection dynamics as well as relationships associated to their co-infection. The global dynamics of typhoid can be determined by a single threshold (the typhoid basic reproduction number, R0(T)) while two thresholds (the malaria basic reproduction number, R0(M), and the extinction index, R0(MM)) are needed to determine the global dynamics of malaria. We demonstrate that by using efficient simultaneous prevention programs, the co-infection basic reproduction number, R0, can be brought down to below one, thereby eradicating the diseases. Using our model, we present illustrative numerical results with a case study in the Eastern Province of Kenya to quantify the possible false diagnosis resulting from this co-infection. In Kenya, despite having higher prevalence of typhoid, malaria is more problematic in terms of new infections and disease deaths. We find that false diagnosis-with higher possible cases for typhoid than malaria-cause significant devastating impacts on Kenyan societies. Our results demonstrate that both diseases need to be simultaneously managed for successful control of co-epidemics. Copyright © 2015 Elsevier Inc. All rights reserved.
Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach

USGS Publications Warehouse

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

2013-01-01

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

NASA Astrophysics Data System (ADS)

Caniza, Horacio; Romero, Alfonso E.; Paccanaro, Alberto

2015-12-01

We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure.
Spike Train Similarity Space (SSIMS) Method Detects Effects of Obstacle Proximity and Experience on Temporal Patterning of Bat Biosonar

PubMed Central

Accomando, Alyssa W.; Vargas-Irwin, Carlos E.; Simmons, James A.

2018-01-01

Bats emit biosonar pulses in complex temporal patterns that change to accommodate dynamic surroundings. Efforts to quantify these patterns have included analyses of inter-pulse intervals, sonar sound groups, and changes in individual signal parameters such as duration or frequency. Here, the similarity in temporal structure between trains of biosonar pulses is assessed. The spike train similarity space (SSIMS) algorithm, originally designed for neural activity pattern analysis, was applied to determine which features of the environment influence temporal patterning of pulses emitted by flying big brown bats, Eptesicus fuscus. In these laboratory experiments, bats flew down a flight corridor through an obstacle array. The corridor varied in width (100, 70, or 40 cm) and shape (straight or curved). Using a relational point-process framework, SSIMS was able to discriminate between echolocation call sequences recorded from flights in each of the corridor widths. SSIMS was also able to tell the difference between pulse trains recorded during flights where corridor shape through the obstacle array matched the previous trials (fixed, or expected) as opposed to those recorded from flights with randomized corridor shape (variable, or unexpected), but only for the flight path shape in which the bats had previous training. The results show that experience influences the temporal patterns with which bats emit their echolocation calls. It is demonstrated that obstacle proximity to the bat affects call patterns more dramatically than flight path shape. PMID:29472848
Spike Train Similarity Space (SSIMS) Method Detects Effects of Obstacle Proximity and Experience on Temporal Patterning of Bat Biosonar.

PubMed

Accomando, Alyssa W; Vargas-Irwin, Carlos E; Simmons, James A

2018-01-01

Bats emit biosonar pulses in complex temporal patterns that change to accommodate dynamic surroundings. Efforts to quantify these patterns have included analyses of inter-pulse intervals, sonar sound groups, and changes in individual signal parameters such as duration or frequency. Here, the similarity in temporal structure between trains of biosonar pulses is assessed. The spike train similarity space (SSIMS) algorithm, originally designed for neural activity pattern analysis, was applied to determine which features of the environment influence temporal patterning of pulses emitted by flying big brown bats, Eptesicus fuscus . In these laboratory experiments, bats flew down a flight corridor through an obstacle array. The corridor varied in width (100, 70, or 40 cm) and shape (straight or curved). Using a relational point-process framework, SSIMS was able to discriminate between echolocation call sequences recorded from flights in each of the corridor widths. SSIMS was also able to tell the difference between pulse trains recorded during flights where corridor shape through the obstacle array matched the previous trials (fixed, or expected) as opposed to those recorded from flights with randomized corridor shape (variable, or unexpected), but only for the flight path shape in which the bats had previous training. The results show that experience influences the temporal patterns with which bats emit their echolocation calls. It is demonstrated that obstacle proximity to the bat affects call patterns more dramatically than flight path shape.
Adaptation to extreme environments: macromolecular dynamics in bacteria compared in vivo by neutron scattering

PubMed Central

Tehei, Moeava; Franzetti, Bruno; Madern, Dominique; Ginzburg, Margaret; Ginzburg, Ben Z; Giudici-Orticoni, Marie-Thérèse; Bruschi, Mireille; Zaccai, Giuseppe

2004-01-01

Mean macromolecular dynamics was quantified in vivo by neutron scattering in psychrophile, mesophile, thermophile and hyperthermophile bacteria. Root mean square atomic fluctuation amplitudes determining macromolecular flexibility were found to be similar for each organism at its physiological temperature (∼1 Å in the 0.1 ns timescale). Effective force constants determining the mean macromolecular resilience were found to increase with physiological temperature from 0.2 N/m for the psychrophiles, which grow at 4°C, to 0.6 N/m for the hyperthermophiles (85°C), indicating that the increase in stabilization free energy is dominated by enthalpic rather than entropic terms. Larger resilience allows macromolecular stability at high temperatures, while maintaining flexibility within acceptable limits for biological activity. PMID:14710189
Breeding Birds of Late-Rotation Pine Hardwood Stands: Community Characteristics and Similarity to Other Regional Pine Forests

Treesearch

Daniel R. Petit; Lisa J. Petit; Thomas E. Martin; others

1994-01-01

The relative abundances of bird species and the ecological characteristics of the overall avian community were quantified within 20 late-rotation pine-hardwood sites in the Ouschitn and Ozark National Forests in Arkansas and Oklahoma during 1992 and 1993. In addition, similarities in species composition and guild representation were compared with those of forest...
Panarchy: discontinuities reval similarities in the dynamic system structure of ecological and social systems

EPA Science Inventory

Debates on the organization, structure and dynamics of ecosystems across scales of space and time have waxed and waned in the literature for a century. From successional theory to ecosystem theories of resilience and robustness, from hierarchy to ascendency to panarchy theory, e...
Similarity of the ruminal bacteria across individual lactating cows.

PubMed

Jami, Elie; Mizrahi, Itzhak

2012-06-01

Dairy cattle hold enormous significance for man as a source of milk and meat. Their remarkable ability to convert indigestible plant mass into these digestible food products resides in the rumen - an anaerobic chambered compartment - in the bovine digestive system. The rumen houses a complex microbiota which is responsible for the degradation of plant material, consequently enabling the conversion of plant fibers into milk and meat and determining their quality and quantity. Hence, an understanding of this complex ecosystem has major economic implications. One important question that is yet to be addressed is the degree of conservation of rumen microbial composition across individual animals. Here we quantified the degree of similarity between rumen bacterial populations of 16 individual cows. We used real-time PCR to determine the variance of specific ruminal bacterial species with different metabolic functions, revealing that while some bacterial strains vary greatly across animals, others show only very low variability. This variance could not be linked to the metabolic traits of these bacteria. We examined the degree of similarity in the dominant bacterial populations across all animals using automated ribosomal intergenic spacer analysis (ARISA), and identified a bacterial community consisting of 32% operational taxonomic units (OTUs) shared by at least 90% of the animals and 19% OTUs shared by 100% of the animals. Looking only at the presence or absence of each OTU gave an average similarity of 75% between each cow pair. When abundance of each OTU was added to the analysis, this similarity decreased to an average of less than 60%. Thus, as suggested in similar recent studies of the human gut, a bovine rumen core microbiome does exist, but taxa abundance may vary greatly across animals. Copyright © 2012 Elsevier Ltd. All rights reserved.
Effective time closures: quantifying the conservation benefits of input control for the Pacific chub mackerel fishery.

PubMed

Ichinokawa, Momoko; Okamura, Hiroshi; Watanabe, Chikako; Kawabata, Atsushi; Oozeki, Yoshioki

2015-09-01

Restricting human access to a specific wildlife species, community, or ecosystem, i.e., input control, is one of the most popular tools to control human impacts for natural resource management and wildlife conservation. However, quantitative evaluations of input control are generally difficult, because it is unclear how much human impacts can actually be reduced by the control. We present a model framework to quantify the effectiveness of input control using day closures to reduce actual fishing impact by considering the observed fishery dynamics. The model framework was applied to the management of the Pacific stock of the chub mackerel (Scomber japonicus) fishery, in which fishing was suspended for one day following any day when the total mackerel catch exceeded a threshold level. We evaluated the management measure according to the following steps: (1) we fitted the daily observed catch and fishing effort data to a generalized linear model (GLM) or generalized autoregressive state-space model (GASSM), (2) we conducted population dynamics simulations based on annual catches randomly generated from the parameters estimated in the first step, (3) we quantified the effectiveness of day closures by comparing the results of two simulation scenarios with and without day closures, and (4) we conducted additional simulations based on different sets of explanatory variables and statistical models (sensitivity analysis). In the first step, we found that the GASSM explained the observed data far better than the simple GLM. The model parameterized with the estimates from the GASSM demonstrated that the day closures implemented from 2004 to 2009 would have decreased exploitation fractions by ~10% every year and increased the 2009 stock biomass by 37-46% (median), relative to the values without day closures. The sensitivity analysis revealed that the effectiveness of day closures was particularly influenced by autoregressive processes in the fishery data and by positive
Quantifying the propagation of distress and mental disorders in social networks.

PubMed

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

2018-03-22

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

PubMed Central

Morrow, Melissa M.; Rankin, Jeffery W.; Neptune, Richard R.; Kaufman, Kenton R.

2014-01-01

The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4 % Fmax error in the middle deltoid) to good (6.4 % Fmax error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation-supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction. PMID:25282075
Equivalence classes of Fibonacci lattices and their similarity properties

NASA Astrophysics Data System (ADS)

Lo Gullo, N.; Vittadello, L.; Bazzan, M.; Dell'Anna, L.

2016-08-01

We investigate, theoretically and experimentally, the properties of Fibonacci lattices with arbitrary spacings. Different from periodic structures, the reciprocal lattice and the dynamical properties of Fibonacci lattices depend strongly on the lengths of their lattice parameters, even if the sequence of long and short segment, the Fibonacci string, is the same. In this work we show that by exploiting a self-similarity property of Fibonacci strings under a suitable composition rule, it is possible to define equivalence classes of Fibonacci lattices. We show that the diffraction patterns generated by Fibonacci lattices belonging to the same equivalence class can be rescaled to a common pattern of strong diffraction peaks thus giving to this classification a precise meaning. Furthermore we show that, through the gap labeling theorem, gaps in the energy spectra of Fibonacci crystals belonging to the same class can be labeled by the same momenta (up to a proper rescaling) and that the larger gaps correspond to the strong peaks of the diffraction spectra. This observation makes the definition of equivalence classes meaningful also for the spectral and therefore dynamical and thermodynamical properties of quasicrystals. Our results apply to the more general class of quasiperiodic lattices for which similarity under a suitable deflation rule is in order.
Alignment of dynamic networks.

PubMed

Vijayan, V; Critchlow, D; Milenkovic, T

2017-07-15

Network alignment (NA) aims to find a node mapping that conserves similar regions between compared networks. NA is applicable to many fields, including computational biology, where NA can guide the transfer of biological knowledge from well- to poorly-studied species across aligned network regions. Existing NA methods can only align static networks. However, most complex real-world systems evolve over time and should thus be modeled as dynamic networks. We hypothesize that aligning dynamic network representations of evolving systems will produce superior alignments compared to aligning the systems' static network representations, as is currently done. For this purpose, we introduce the first ever dynamic NA method, DynaMAGNA ++. This proof-of-concept dynamic NA method is an extension of a state-of-the-art static NA method, MAGNA++. Even though both MAGNA++ and DynaMAGNA++ optimize edge as well as node conservation across the aligned networks, MAGNA++ conserves static edges and similarity between static node neighborhoods, while DynaMAGNA++ conserves dynamic edges (events) and similarity between evolving node neighborhoods. For this purpose, we introduce the first ever measure of dynamic edge conservation and rely on our recent measure of dynamic node conservation. Importantly, the two dynamic conservation measures can be optimized with any state-of-the-art NA method and not just MAGNA++. We confirm our hypothesis that dynamic NA is superior to static NA, on synthetic and real-world networks, in computational biology and social domains. DynaMAGNA++ is parallelized and has a user-friendly graphical interface. http://nd.edu/∼cone/DynaMAGNA++/ . tmilenko@nd.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Water dynamics in protein hydration shells: the molecular origins of the dynamical perturbation.

PubMed

Fogarty, Aoife C; Laage, Damien

2014-07-17

Protein hydration shell dynamics play an important role in biochemical processes including protein folding, enzyme function, and molecular recognition. We present here a comparison of the reorientation dynamics of individual water molecules within the hydration shell of a series of globular proteins: acetylcholinesterase, subtilisin Carlsberg, lysozyme, and ubiquitin. Molecular dynamics simulations and analytical models are used to access site-resolved information on hydration shell dynamics and to elucidate the molecular origins of the dynamical perturbation of hydration shell water relative to bulk water. We show that all four proteins have very similar hydration shell dynamics, despite their wide range of sizes and functions, and differing secondary structures. We demonstrate that this arises from the similar local surface topology and surface chemical composition of the four proteins, and that such local factors alone are sufficient to rationalize the hydration shell dynamics. We propose that these conclusions can be generalized to a wide range of globular proteins. We also show that protein conformational fluctuations induce a dynamical heterogeneity within the hydration layer. We finally address the effect of confinement on hydration shell dynamics via a site-resolved analysis and connect our results to experiments via the calculation of two-dimensional infrared spectra.
Water Dynamics in Protein Hydration Shells: The Molecular Origins of the Dynamical Perturbation

PubMed Central

2014-01-01

Protein hydration shell dynamics play an important role in biochemical processes including protein folding, enzyme function, and molecular recognition. We present here a comparison of the reorientation dynamics of individual water molecules within the hydration shell of a series of globular proteins: acetylcholinesterase, subtilisin Carlsberg, lysozyme, and ubiquitin. Molecular dynamics simulations and analytical models are used to access site-resolved information on hydration shell dynamics and to elucidate the molecular origins of the dynamical perturbation of hydration shell water relative to bulk water. We show that all four proteins have very similar hydration shell dynamics, despite their wide range of sizes and functions, and differing secondary structures. We demonstrate that this arises from the similar local surface topology and surface chemical composition of the four proteins, and that such local factors alone are sufficient to rationalize the hydration shell dynamics. We propose that these conclusions can be generalized to a wide range of globular proteins. We also show that protein conformational fluctuations induce a dynamical heterogeneity within the hydration layer. We finally address the effect of confinement on hydration shell dynamics via a site-resolved analysis and connect our results to experiments via the calculation of two-dimensional infrared spectra. PMID:24479585
Using transfer functions to quantify El Niño Southern Oscillation dynamics in data and models.

PubMed

MacMartin, Douglas G; Tziperman, Eli

2014-09-08

Transfer function tools commonly used in engineering control analysis can be used to better understand the dynamics of El Niño Southern Oscillation (ENSO), compare data with models and identify systematic model errors. The transfer function describes the frequency-dependent input-output relationship between any pair of causally related variables, and can be estimated from time series. This can be used first to assess whether the underlying relationship is or is not frequency dependent, and if so, to diagnose the underlying differential equations that relate the variables, and hence describe the dynamics of individual subsystem processes relevant to ENSO. Estimating process parameters allows the identification of compensating model errors that may lead to a seemingly realistic simulation in spite of incorrect model physics. This tool is applied here to the TAO array ocean data, the GFDL-CM2.1 and CCSM4 general circulation models, and to the Cane-Zebiak ENSO model. The delayed oscillator description is used to motivate a few relevant processes involved in the dynamics, although any other ENSO mechanism could be used instead. We identify several differences in the processes between the models and data that may be useful for model improvement. The transfer function methodology is also useful in understanding the dynamics and evaluating models of other climate processes.
Quantifying renewable groundwater stress with GRACE

NASA Astrophysics Data System (ADS)

Richey, Alexandra S.; Thomas, Brian F.; Lo, Min-Hui; Reager, John T.; Famiglietti, James S.; Voss, Katalyn; Swenson, Sean; Rodell, Matthew

2015-07-01

Groundwater is an increasingly important water supply source globally. Understanding the amount of groundwater used versus the volume available is crucial to evaluate future water availability. We present a groundwater stress assessment to quantify the relationship between groundwater use and availability in the world's 37 largest aquifer systems. We quantify stress according to a ratio of groundwater use to availability, which we call the Renewable Groundwater Stress ratio. The impact of quantifying groundwater use based on nationally reported groundwater withdrawal statistics is compared to a novel approach to quantify use based on remote sensing observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. Four characteristic stress regimes are defined: Overstressed, Variable Stress, Human-dominated Stress, and Unstressed. The regimes are a function of the sign of use (positive or negative) and the sign of groundwater availability, defined as mean annual recharge. The ability to mitigate and adapt to stressed conditions, where use exceeds sustainable water availability, is a function of economic capacity and land use patterns. Therefore, we qualitatively explore the relationship between stress and anthropogenic biomes. We find that estimates of groundwater stress based on withdrawal statistics are unable to capture the range of characteristic stress regimes, especially in regions dominated by sparsely populated biome types with limited cropland. GRACE-based estimates of use and stress can holistically quantify the impact of groundwater use on stress, resulting in both greater magnitudes of stress and more variability of stress between regions.
Quantifying renewable groundwater stress with GRACE

PubMed Central

Richey, Alexandra S.; Thomas, Brian F.; Lo, Min‐Hui; Reager, John T.; Voss, Katalyn; Swenson, Sean; Rodell, Matthew

2015-01-01

Abstract Groundwater is an increasingly important water supply source globally. Understanding the amount of groundwater used versus the volume available is crucial to evaluate future water availability. We present a groundwater stress assessment to quantify the relationship between groundwater use and availability in the world's 37 largest aquifer systems. We quantify stress according to a ratio of groundwater use to availability, which we call the Renewable Groundwater Stress ratio. The impact of quantifying groundwater use based on nationally reported groundwater withdrawal statistics is compared to a novel approach to quantify use based on remote sensing observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. Four characteristic stress regimes are defined: Overstressed, Variable Stress, Human‐dominated Stress, and Unstressed. The regimes are a function of the sign of use (positive or negative) and the sign of groundwater availability, defined as mean annual recharge. The ability to mitigate and adapt to stressed conditions, where use exceeds sustainable water availability, is a function of economic capacity and land use patterns. Therefore, we qualitatively explore the relationship between stress and anthropogenic biomes. We find that estimates of groundwater stress based on withdrawal statistics are unable to capture the range of characteristic stress regimes, especially in regions dominated by sparsely populated biome types with limited cropland. GRACE‐based estimates of use and stress can holistically quantify the impact of groundwater use on stress, resulting in both greater magnitudes of stress and more variability of stress between regions. PMID:26900185
Quantifying Qualitative Learning.

ERIC Educational Resources Information Center

Bogus, Barbara

1995-01-01

A teacher at an alternative school for at-risk students discusses the development of student assessment that increases students' self-esteem, convinces students that learning is fun, and prepares students to return to traditional school settings. She found that allowing students to participate in the assessment process successfully quantified the…

Comparing landscape scale vegetation dynamics following recent disturbance in climatically similar sites in California and the Mediterranean basin

Treesearch

Yohay Carmel; Curtis H. Flather

2004-01-01

A long line of inquiry on the notion of ecological convergence has compared ecosystem structure and function between areas that are evolutionarily unrelated but under the same climate regime. Much of this literature has focused on quantifying the degree to which animal morphology or plant physiognomy is alike between disjunct areas. An important property of ecosystems...
Theory of activated glassy dynamics in randomly pinned fluids.

PubMed

Phan, Anh D; Schweizer, Kenneth S

2018-02-07

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.
Theory of activated glassy dynamics in randomly pinned fluids

NASA Astrophysics Data System (ADS)

Phan, Anh D.; Schweizer, Kenneth S.

2018-02-01

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.
Quantifying exciton hopping in disordered media with quenching sites: Application to arrays of quantum dots

NASA Astrophysics Data System (ADS)

Miyazaki, Jun

2013-10-01

We present an analytical method for quantifying exciton hopping in an energetically disordered system with quenching sites. The method is subsequently used to provide a quantitative understanding of exciton hopping in a quantum dot (QD) array. Several statistical quantities that characterize the dynamics (survival probability, average number of distinct sites visited, average hopping distance, and average hopping rate in the initial stage) are obtained experimentally by measuring time-resolved fluorescence intensities at various temperatures. The time evolution of these quantities suggests in a quantitative way that at low temperature an exciton tends to be trapped at a local low-energy site, while at room temperature, exciton hopping occurs repeatedly, leading to a large hopping distance. This method will serve to facilitate highly efficient optoelectronic devices using QDs such as photovoltaic cells and light-emitting diodes, since exciton hopping is considered to strongly influence their operational parameters. The presence of a dark QD (quenching site) that exhibits fast decay is also quantified.
Developments in dynamic MR elastography for in vitro biomechanical assessment of hyaline cartilage under high-frequency cyclical shear.

PubMed

Lopez, Orlando; Amrami, Kimberly K; Manduca, Armando; Rossman, Phillip J; Ehman, Richard L

2007-02-01

The design, construction, and evaluation of a customized dynamic magnetic resonance elastography (MRE) technique for biomechanical assessment of hyaline cartilage in vitro are described. For quantification of the dynamic shear properties of hyaline cartilage by dynamic MRE, mechanical excitation and motion sensitization were performed at frequencies in the kilohertz range. A custom electromechanical actuator and a z-axis gradient coil were used to generate and image shear waves throughout cartilage at 1000-10,000 Hz. A radiofrequency (RF) coil was also constructed for high-resolution imaging. The technique was validated at 4000 and 6000 Hz by quantifying differences in shear stiffness between soft ( approximately 200 kPa) and stiff ( approximately 300 kPa) layers of 5-mm-thick bilayered phantoms. The technique was then used to quantify the dynamic shear properties of bovine and shark hyaline cartilage samples at frequencies up to 9000 Hz. The results demonstrate that one can obtain high-resolution shear stiffness measurements of hyaline cartilage and small, stiff, multilayered phantoms at high frequencies by generating robust mechanical excitations and using large magnetic field gradients. Dynamic MRE can potentially be used to directly quantify the dynamic shear properties of hyaline and articular cartilage, as well as other cartilaginous materials and engineered constructs. (c) 2007 Wiley-Liss, Inc.
Design criteria for portable timber bridge systems : static versus dynamic loads

Treesearch

John M. Franklin; S. E. Taylor; Paul A. Morgan; M. A. Ritter

1999-01-01

Design criteria are needed specifically for portable bridges to insure that they are safe and cost effective. This paper discusses different portable bridge categories and their general design criteria. Specific emphasis is given to quantifying the effects of dynamic live loads on portable bridge design. Results from static and dynamic load tests of two portable timber...
A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics.

PubMed

Kumar, Rakesh; Jade, Dhananjay; Gupta, Dinesh

2018-03-05

5-HydroxyTriptamine 2A antagonists are potential targets for treatment of various cerebrovascular and cardiovascular disorders. In this study, we have developed and performed a unique screening pipeline for filtering ZINC database compounds on the basis of similarities to known antagonists to determine novel small molecule antagonists of 5-HydroxyTriptamine 2A. The screening pipeline is based on 2D similarity, 3D dissimilarity and a combination of 2D/3D similarity. The shortlisted compounds were docked to a 5-HydroxyTriptamine 2A homology-based model, and complexes with low binding energies (287 complexes) were selected for molecular dynamics (MD) simulations in a lipid bilayer. The MD simulations of the shortlisted compounds in complex with 5-HydroxyTriptamine 2A confirmed the stability of the complexes and revealed novel interaction insights. The receptor residues S239, N343, S242, S159, Y370 and D155 predominantly participate in hydrogen bonding. π-π stacking is observed in F339, F340, F234, W151 and W336, whereas hydrophobic interactions are observed amongst V156, F339, F234, V362, V366, F340, V235, I152 and W151. The known and potential antagonists shortlisted by us have similar overlapping molecular interaction patterns. The 287 potential 5-HydroxyTriptamine 2A antagonists may be experimentally verified.
Quantifying non-linear dynamics of mass-springs in series oscillators via asymptotic approach

NASA Astrophysics Data System (ADS)

Starosta, Roman; Sypniewska-Kamińska, Grażyna; Awrejcewicz, Jan

2017-05-01

Dynamical regular response of an oscillator with two serially connected springs with nonlinear characteristics of cubic type and governed by a set of differential-algebraic equations (DAEs) is studied. The classical approach of the multiple scales method (MSM) in time domain has been employed and appropriately modified to solve the governing DAEs of two systems, i.e. with one- and two degrees-of-freedom. The approximate analytical solutions have been verified by numerical simulations.
Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

PubMed

Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

2017-11-13

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.
Quantifying Evaporation in a Permeable Pavement System

EPA Science Inventory

Studies quantifying evaporation from permeable pavement systems are limited to a few laboratory studies and one field application. This research quantifies evaporation for a larger-scale field application by measuring the water balance from lined permeable pavement sections. Th...
Determination of Dynamic Fracture Toughness Properties of Rail Steels

DOT National Transportation Integrated Search

1987-11-01

Motivated by the occurrence of a long-running rail web fracture in service, dynamic fracture mechanics research was undertaken to (1) quantify the crack driving force due to the residual stresses induced by roller straightening operations, (2) determ...
Investigation of Rossby-number similarity in the neutral boundary layer using large-eddy simulation

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

Ohmstede, W.D.; Cederwall, R.T.; Meyers, R.E.

One special case of particular interest, especially to theoreticians, is the steady-state, horizontally homogeneous, autobarotropic (PLB), hereafter referred to as the neutral boundary layer (NBL). The NBL is in fact a 'rare' atmospheric phenomenon, generally associated with high-wind situations. Nevertheless, there is a disproportionate interest in this problem because Rossby-number similarity theory provides a sound approach for addressing this issue. Rossby-number similarity theory has rather wide acceptance, but because of the rarity of the 'true' NBL state, there remains an inadequate experimental database for quantifying constants associated with the Rossby-number similarity concept. Although it remains a controversial issue, it hasmore » been proposed that large-eddy simulation (LES) is an alternative to physical experimentation for obtaining basic atmospherc 'data'. The objective of the study reported here is to investigate Rossby-number similarity in the NBL using LES. Previous studies have not addressed Rossby-number similarity explicitly, although they made use of it in the interpretation of their results. The intent is to calculate several sets of NBL solutions that are ambiguous relative to the their respective Rossby numbers and compare the results for similarity, or the lack of it. 14 refs., 1 fig.« less
Application of spectral methods for high-frequency financial data to quantifying states of market participants

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2008-06-01

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional time series with spectral distances introduced in [A.-H. Sato, Physica A 382 (2007) 258-270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation of the earth, and that the similarities among best quotation rates are associated with those among quotation frequencies. Furthermore, it is shown that the Jensen-Shannon spectral divergence is proportional to a mean of the Kullback-Leibler spectral distance both empirically and numerically. It is confirmed that these spectral distances are connected with distributions for behavioural parameters of the market participants from numerical simulation. This concludes that spectral distances of representative quantities of financial markets are related into diversification of behavioural parameters of the market participants.
Quantifying selective pressures driving bacterial evolution using lineage analysis

PubMed Central

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population’s rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages –i.e. the life-histories of individuals and their ancestors– to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to E. coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life-history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection, and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems. PMID:26213639
Quantifying Selective Pressures Driving Bacterial Evolution Using Lineage Analysis

NASA Astrophysics Data System (ADS)

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population's rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages—i.e., the life histories of individuals and their ancestors—to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to Escherichia coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems.
Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257
Ocean Dynamics: Vietnam DRI

DTIC Science & Technology

2014-09-30

floor. OBJECTIVES To identify the phenomena involved in the cascade of energy from mesoscales to turbulent scales. In particular, we wish to quantify the...data from the profiler to the surface buoy. The WW Iridium telemetry system was tested on the WW moored over the continental shelf. Telemetry...2580 email: ajlucas@ucsd.edu Award: N00014-12-1-0635 LONG-TERM GOALS To gain a more complete understanding of ocean dynamical processes
A common neural code for similar conscious experiences in different individuals

PubMed Central

Naci, Lorina; Cusack, Rhodri; Anello, Mimma; Owen, Adrian M.

2014-01-01

The interpretation of human consciousness from brain activity, without recourse to speech or action, is one of the most provoking and challenging frontiers of modern neuroscience. We asked whether there is a common neural code that underpins similar conscious experiences, which could be used to decode these experiences in the absence of behavior. To this end, we used richly evocative stimulation (an engaging movie) portraying real-world events to elicit a similar conscious experience in different people. Common neural correlates of conscious experience were quantified and related to measurable, quantitative and qualitative, executive components of the movie through two additional behavioral investigations. The movie’s executive demands drove synchronized brain activity across healthy participants’ frontal and parietal cortices in regions known to support executive function. Moreover, the timing of activity in these regions was predicted by participants’ highly similar qualitative experience of the movie’s moment-to-moment executive demands, suggesting that synchronization of activity across participants underpinned their similar experience. Thus we demonstrate, for the first time to our knowledge, that a neural index based on executive function reliably predicted every healthy individual’s similar conscious experience in response to real-world events unfolding over time. This approach provided strong evidence for the conscious experience of a brain-injured patient, who had remained entirely behaviorally nonresponsive for 16 y. The patient’s executive engagement and moment-to-moment perception of the movie content were highly similar to that of every healthy participant. These findings shed light on the common basis of human consciousness and enable the interpretation of conscious experience in the absence of behavior. PMID:25225384
Network Physiology: How Organ Systems Dynamically Interact

PubMed Central

Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073
Quantifying and Modelling Long Term Sediment Dynamics in Catchments in Western Europe

NASA Astrophysics Data System (ADS)

Notebaert, B.; De Brue, H.; Verstraeten, G.; Broothaerts, N.

2015-12-01

Quantification of sediment dynamics allows to get insight in driving forces and internal dynamics of the sediment cascade system. A useful tool to achieve this is the sediment budget approach, which encompasses the quantification of different sinks and sources. A Holocene time-differentiated sediment budget has been constructed for the Belgian Dijle River catchment (720 km²), based on a large set of field data. The results show how soil erosion is driven by land use changes over longer timescales. Sediment redistribution and the relative importance of the different sinks also vary over time, mainly as a result of changing land use and related landscape connectivity. However, the coarse temporal resolution typically associated with Holocene studies complicates the understanding of sub-millennial scale processes. In a second step, the field-based sediment budget was combined with a modeling approach using Watem/Sedem, a spatially distributed model that simulates soil erosion and colluvial deposition. After validation of the model calibration against the sediment budget, the model was used in a sensitivity analysis. Results confirm the overwhelming influence of human land use on both soil erosion and landscape connectivity, whereas the climatic impact is comparatively small. In addition to catchment-wide simulations, the model also served to test the relative importance of lynchets and dry valleys in different environments. Finally, the geomorphic model was used to simulate past land use, taking into account equifinality. For this purpose, a large series of hypothetical time-independent land use maps of the Dijle catchment were modeled based on a multi-objective allocation algorithm, and applied in Watem/Sedem. Modeled soil erosion and sediment deposition outcomes for each scenario were subsequently compared with the field-based record, taking into account uncertainties. As such, the model allows to evaluate and select realistic land use scenarios for the Holocene.

Quantifying stream thermal regimes at management-pertinent scales: combining thermal infrared and stationary stream temperature data in a novel modeling framework.

USGS Publications Warehouse

Vatland, Shane J.; Gresswell, Robert E.; Poole, Geoffrey C.

2015-01-01

Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.
Dynamics Simulation Model for Space Tethers

NASA Technical Reports Server (NTRS)

Levin, E. M.; Pearson, J.; Oldson, J. C.

2006-01-01

This document describes the development of an accurate model for the dynamics of the Momentum Exchange Electrodynamic Reboost (MXER) system. The MXER is a rotating tether about 100-km long in elliptical Earth orbit designed to catch payloads in low Earth orbit and throw them to geosynchronous orbit or to Earth escape. To ensure successful rendezvous between the MXER tip catcher and a payload, a high-fidelity model of the system dynamics is required. The model developed here quantifies the major environmental perturbations, and can predict the MXER tip position to within meters over one orbit.
Phylodynamics with Migration: A Computational Framework to Quantify Population Structure from Genomic Data.

PubMed

Kühnert, Denise; Stadler, Tanja; Vaughan, Timothy G; Drummond, Alexei J

2016-08-01

When viruses spread, outbreaks can be spawned in previously unaffected regions. Depending on the time and mode of introduction, each regional outbreak can have its own epidemic dynamics. The migration and phylodynamic processes are often intertwined and need to be taken into account when analyzing temporally and spatially structured virus data. In this article, we present a fully probabilistic approach for the joint reconstruction of phylodynamic history in structured populations (such as geographic structure) based on a multitype birth-death process. This approach can be used to quantify the spread of a pathogen in a structured population. Changes in epidemic dynamics through time within subpopulations are incorporated through piecewise constant changes in transmission parameters.We analyze a global human influenza H3N2 virus data set from a geographically structured host population to demonstrate how seasonal dynamics can be inferred simultaneously with the phylogeny and migration process. Our results suggest that the main migration path among the northern, tropical, and southern region represented in the sample analyzed here is the one leading from the tropics to the northern region. Furthermore, the time-dependent transmission dynamics between and within two HIV risk groups, heterosexuals and injecting drug users, in the Latvian HIV epidemic are investigated. Our analyses confirm that the Latvian HIV epidemic peaking around 2001 was mainly driven by the injecting drug user risk group. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Two complementary approaches to quantify variability in heat resistance of spores of Bacillus subtilis.

PubMed

den Besten, Heidy M W; Berendsen, Erwin M; Wells-Bennik, Marjon H J; Straatsma, Han; Zwietering, Marcel H

2017-07-17

Realistic prediction of microbial inactivation in food requires quantitative information on variability introduced by the microorganisms. Bacillus subtilis forms heat resistant spores and in this study the impact of strain variability on spore heat resistance was quantified using 20 strains. In addition, experimental variability was quantified by using technical replicates per heat treatment experiment, and reproduction variability was quantified by using two biologically independent spore crops for each strain that were heat treated on different days. The fourth-decimal reduction times and z-values were estimated by a one-step and two-step model fitting procedure. Grouping of the 20 B. subtilis strains into two statistically distinguishable groups could be confirmed based on their spore heat resistance. The reproduction variability was higher than experimental variability, but both variabilities were much lower than strain variability. The model fitting approach did not significantly affect the quantification of variability. Remarkably, when strain variability in spore heat resistance was quantified using only the strains producing low-level heat resistant spores, then this strain variability was comparable with the previously reported strain variability in heat resistance of vegetative cells of Listeria monocytogenes, although in a totally other temperature range. Strains that produced spores with high-level heat resistance showed similar temperature range for growth as strains that produced low-level heat resistance. Strain variability affected heat resistance of spores most, and therefore integration of this variability factor in modelling of spore heat resistance will make predictions more realistic. Copyright © 2017. Published by Elsevier B.V.
Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

NASA Astrophysics Data System (ADS)

Demin, S. A.; Yulmetyev, R. M.; Panischev, O. Yu.; Hänggi, Peter

2008-03-01

On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO - control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.
Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

PubMed

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.
Quantifying quantum coherence with quantum Fisher information.

PubMed

Feng, X N; Wei, L F

2017-11-14

Quantum coherence is one of the old but always important concepts in quantum mechanics, and now it has been regarded as a necessary resource for quantum information processing and quantum metrology. However, the question of how to quantify the quantum coherence has just been paid the attention recently (see, e.g., Baumgratz et al. PRL, 113. 140401 (2014)). In this paper we verify that the well-known quantum Fisher information (QFI) can be utilized to quantify the quantum coherence, as it satisfies the monotonicity under the typical incoherent operations and the convexity under the mixing of the quantum states. Differing from most of the pure axiomatic methods, quantifying quantum coherence by QFI could be experimentally testable, as the bound of the QFI is practically measurable. The validity of our proposal is specifically demonstrated with the typical phase-damping and depolarizing evolution processes of a generic single-qubit state, and also by comparing it with the other quantifying methods proposed previously.
Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

NASA Astrophysics Data System (ADS)

Francisco, C. P. F.; da Silveira, I. C. A.; Campos, E. J. D.

2011-03-01

In this work, we investigated the mesoscale dynamics of the Brazil-Malvinas Confluence (BMC) region. Particularly, we were interested in the role of geophysical instability in the formation and development of the mesoscale features commonly observed in this region. We dynamically analyzed the results of numerical simulations of the BMC region conducted with 'Hybrid Coordinate Ocean Model' (HYCOM). We quantified the effect of barotropic and baroclinic energy conversions in the modeled flow and showed the dominance of the latter in the region.
Using NASA`s Airborne Topographic Mapper IV to Quantify Geomorphic Change in Arid Southwestern Stream Systems

NASA Astrophysics Data System (ADS)

Finnegan, D. C.; Krabill, W.; Lichvar, R. W.; Ericsson, M. P.; Frederick, E.; Manizade, S.; Yungel, J.; Sonntag, J.; Swift, R.

2005-12-01

Understanding how arid stream systems respond to individual climatic events is often difficult given the dynamic and `flashy' nature of most watersheds and the unpredictable nature of individual storm events. Until recently conventional methods for quantifying change dictated the use of stream gauge measurements coupled with periodic cross-section measurements to quantify changes in large-scale channel geometry. Using this approach to quantify change across large areas often proves to be impractical and unattainable given the laborious nature of most surveying techniques including modern GPS systems. Alternately, airborne laser technologies such as NASA's Airborne Topographic Mapper (ATM) are capable of quantifying small-scale changes (~5-10cm) across large-scale terrain rapidly and accurately. The ATM was developed at the NASA-GSFC Wallops Flight Facility. Its current version, ATM-4, measures topography 5,000 times per second across a 45-degree swath below the aircraft by transmitting a 532nm (green) laser pulse and receiving the backscattered signal in a high-speed waveform digitizer. The laser range measurements are combined with aircraft location from GPS and attitude from an inertial navigation system (INS) to provide a precise XYZ coordinate for each (~1-meter diameter) laser footprint on the ground. Our work focuses on the use of airborne laser altimetry to quantify the nature of individual surfaces and the geomorphic change that occurs within small arid stream systems during significant storm events. In September of 2003 and 2005 acquisition surveys using NASA's ATM-IV were flown over Mission Creek, a small arid stream system in Southern California's Mojave Desert with a relatively long gauging history (>40yrs), allowing us to quantify the geomorphic change occurring within the channel as a result of the record storm events during the winter of 2004-2005. Preliminary results associated with our work are encouraging and lead us to believe that when compared
Development of device for quantifying magnetic nanoparticle tracers accumulating in sentinel lymph nodes

NASA Astrophysics Data System (ADS)

Kuwahata, Akihiro; Kaneko, Miki; Chikaki, Shinichi; Kusakabe, Moriaki; Sekino, Masaki

2018-05-01

The developed device with electromagnetic coils and small permanent magnets quantifies the iron contents of superparamagnetic iron oxide nanoparticles for sentinel lymph node (SLN) biopsy. To remove diamagnetic and paramagnetic components and detect only superparamagnetic components, a 2nd harmonics signal is detected by a gradiometer under a moderate AC magnetic field (1-2 mT) with the fundamental frequency (2.944 kHz) of the coils and DC magnetic field (1-2 mT) of the magnets. The detection limit with a signal-to-noise ratio of 5 is approximately 0.28 μg of iron, and the device has a wide dynamic range of 104, 0.28 μg-2.8 mg. Additional coils and permanent magnets play an important role producing the optimum distribution of AC/DC magnetic fields for an iron distribution-independent and SLN size-independent quantification. We demonstrated the quantification of the iron in phantoms, which have a size of 3-20 mm with varied iron distributions and contain magnetic nanoparticles numerically. These results indicate that the developed device is useful for quantifying the magnetic nanoparticles accumulating in SLNs.
A compact clinical instrument for quantifying suppression.

PubMed

Black, Joanne M; Thompson, Benjamin; Maehara, Goro; Hess, Robert F

2011-02-01

We describe a compact and convenient clinical apparatus for the measurement of suppression based on a previously reported laboratory-based approach. In addition, we report and validate a novel, rapid psychophysical method for measuring suppression using this apparatus, which makes the technique more applicable to clinical practice. By using a Z800 dual pro head-mounted display driven by a MAC laptop, we provide dichoptic stimulation. Global motion stimuli composed of arrays of moving dots are presented to each eye. One set of dots move in a coherent direction (termed signal) whereas another set of dots move in a random direction (termed noise). To quantify performance, we measure the signal/noise ratio corresponding to a direction-discrimination threshold. Suppression is quantified by assessing the extent to which it matters which eye sees the signal and which eye sees the noise. A space-saving, head-mounted display using current video technology offers an ideal solution for clinical practice. In addition, our optimized psychophysical method provided results that were in agreement with those produced using the original technique. We made measures of suppression on a group of nine adult amblyopic participants using this apparatus with both the original and new psychophysical paradigms. All participants had measurable suppression ranging from mild to severe. The two different psychophysical methods gave a strong correlation for the strength of suppression (rho = -0.83, p = 0.006). Combining the new apparatus and new psychophysical method creates a convenient and rapid technique for parametric measurement of interocular suppression. In addition, this apparatus constitutes the ideal platform for suppressors to combine information between their eyes in a similar way to binocularly normal people. This provides a convenient way for clinicians to implement the newly proposed binocular treatment of amblyopia that is based on antisuppression training.
Scale-Similar Models for Large-Eddy Simulations

NASA Technical Reports Server (NTRS)

Sarghini, F.

1999-01-01

Scale-similar models employ multiple filtering operations to identify the smallest resolved scales, which have been shown to be the most active in the interaction with the unresolved subgrid scales. They do not assume that the principal axes of the strain-rate tensor are aligned with those of the subgrid-scale stress (SGS) tensor, and allow the explicit calculation of the SGS energy. They can provide backscatter in a numerically stable and physically realistic manner, and predict SGS stresses in regions that are well correlated with the locations where large Reynolds stress occurs. In this paper, eddy viscosity and mixed models, which include an eddy-viscosity part as well as a scale-similar contribution, are applied to the simulation of two flows, a high Reynolds number plane channel flow, and a three-dimensional, nonequilibrium flow. The results show that simulations without models or with the Smagorinsky model are unable to predict nonequilibrium effects. Dynamic models provide an improvement of the results: the adjustment of the coefficient results in more accurate prediction of the perturbation from equilibrium. The Lagrangian-ensemble approach [Meneveau et al., J. Fluid Mech. 319, 353 (1996)] is found to be very beneficial. Models that included a scale-similar term and a dissipative one, as well as the Lagrangian ensemble averaging, gave results in the best agreement with the direct simulation and experimental data.
Similarity in volatile communities leads to increased herbivory and greater tropical forest diversity.

PubMed

Massad, Tara J; Martins de Moraes, Marcílio; Philbin, Casey; Oliveira, Celso; Cebrian Torrejon, Gerardo; Fumiko Yamaguchi, Lydia; Jeffrey, Christopher S; Dyer, Lee A; Richards, Lora A; Kato, Massuo J

2017-07-01

A longstanding paradigm in ecology is that there are positive associations between herbivore diversity, specialization, and plant species diversity, with a focus on taxonomic diversity. However, phytochemical diversity is also an informative metric, as insect herbivores interact with host plants not as taxonomic entities, but as sources of nutrients, primary metabolites, and mixtures of attractant and repellant chemicals. The present research examines herbivore responses to phytochemical diversity measured as volatile similarity in the tropical genus Piper. We quantified associations between naturally occurring volatile variation and herbivory by specialist and generalist insects. Intraspecific similarity of volatile compounds across individuals was associated with greater overall herbivory. A structural equation model supported the hypothesis that plot level volatile similarity caused greater herbivory by generalists, but not specialists, which led to increased understory plant richness. These results demonstrate that using volatiles as a functional diversity metric is informative for understanding tropical forest diversity and indicate that generalist herbivores contribute to the maintenance of diversity. © 2017 by the Ecological Society of America.
Approaches for evaluating the effects of bivalve filter feeding on nutrient dynamics in Puget Sound, Washington

USGS Publications Warehouse

Konrad, Christopher P.

2014-01-01

Marine bivalves such as clams, mussels, and oysters are an important component of the food web, which influence nutrient dynamics and water quality in many estuaries. The role of bivalves in nutrient dynamics and, particularly, the contribution of commercial shellfish activities, are not well understood in Puget Sound, Washington. Numerous approaches have been used in other estuaries to quantify the effects of bivalves on nutrient dynamics, ranging from simple nutrient budgeting to sophisticated numerical models that account for tidal circulation, bioenergetic fluxes through food webs, and biochemical transformations in the water column and sediment. For nutrient management in Puget Sound, it might be possible to integrate basic biophysical indicators (residence time, phytoplankton growth rates, and clearance rates of filter feeders) as a screening tool to identify places where nutrient dynamics and water quality are likely to be sensitive to shellfish density and, then, apply more sophisticated methods involving in-situ measurements and simulation models to quantify those dynamics.
Gains and Pitfalls of Quantifier Elimination as a Teaching Tool

ERIC Educational Resources Information Center

Oldenburg, Reinhard

2015-01-01

Quantifier Elimination is a procedure that allows simplification of logical formulas that contain quantifiers. Many mathematical concepts are defined in terms of quantifiers and especially in calculus their use has been identified as an obstacle in the learning process. The automatic deduction provided by quantifier elimination thus allows…
Contrasting lexical similarity and formal definitions in SNOMED CT: consistency and implications.

PubMed

Agrawal, Ankur; Elhanan, Gai

2014-02-01

To quantify the presence of and evaluate an approach for detection of inconsistencies in the formal definitions of SNOMED CT (SCT) concepts utilizing a lexical method. Utilizing SCT's Procedure hierarchy, we algorithmically formulated similarity sets: groups of concepts with similar lexical structure of their fully specified name. We formulated five random samples, each with 50 similarity sets, based on the same parameter: number of parents, attributes, groups, all the former as well as a randomly selected control sample. All samples' sets were reviewed for types of formal definition inconsistencies: hierarchical, attribute assignment, attribute target values, groups, and definitional. For the Procedure hierarchy, 2111 similarity sets were formulated, covering 18.1% of eligible concepts. The evaluation revealed that 38 (Control) to 70% (Different relationships) of similarity sets within the samples exhibited significant inconsistencies. The rate of inconsistencies for the sample with different relationships was highly significant compared to Control, as well as the number of attribute assignment and hierarchical inconsistencies within their respective samples. While, at this time of the HITECH initiative, the formal definitions of SCT are only a minor consideration, in the grand scheme of sophisticated, meaningful use of captured clinical data, they are essential. However, significant portion of the concepts in the most semantically complex hierarchy of SCT, the Procedure hierarchy, are modeled inconsistently in a manner that affects their computability. Lexical methods can efficiently identify such inconsistencies and possibly allow for their algorithmic resolution. Copyright © 2013 Elsevier Inc. All rights reserved.
The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence.

PubMed

Stayton, C Tristan

2015-08-01

Convergent evolution is an important phenomenon in the history of life. Despite this, there is no common definition of convergence used by biologists. Instead, several conceptually different definitions are employed. The primary dichotomy is between pattern-based definitions, where independently evolved similarity is sufficient for convergence, and process-based definitions, where convergence requires a certain process to produce this similarity. The unacknowledged diversity of definitions can lead to problems in evolutionary research. Process-based definitions may bias researchers away from studying or recognizing other sources of independently evolved similarity, or lead researchers to interpret convergent patterns as necessarily caused by a given process. Thus, pattern-based definitions are recommended. Existing measures of convergence are reviewed, and two new measures are developed. Both are pattern based and conceptually minimal, quantifying nothing but independently evolved similarity. One quantifies the amount of phenotypic distance between two lineages that is closed by subsequent evolution; the other simply counts the number of lineages entering a region of phenotypic space. The behavior of these measures is explored in simulations; both show acceptable Type I and Type II error. The study of convergent evolution will be facilitated if researchers are explicit about working definitions of convergence and adopt a standard toolbox of convergence measures. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Deaf Learners' Knowledge of English Universal Quantifiers

ERIC Educational Resources Information Center

Berent, Gerald P.; Kelly, Ronald R.; Porter, Jeffrey E.; Fonzi, Judith

2008-01-01

Deaf and hearing students' knowledge of English sentences containing universal quantifiers was compared through their performance on a 50-item, multiple-picture task that required students to decide whether each of five pictures represented a possible meaning of a target sentence. The task assessed fundamental knowledge of quantifier sentences,…
Quantifying the Relationship between Curvature and Electric Potential in Lipid Bilayers.

PubMed

Bruhn, Dennis S; Lomholt, Michael A; Khandelia, Himanshu

2016-06-02

Cellular membranes mediate vital cellular processes by being subject to curvature and transmembrane electrical potentials. Here we build upon the existing theory for flexoelectricity in liquid crystals to quantify the coupling between lipid bilayer curvature and membrane potentials. Using molecular dynamics simulations, we show that headgroup dipole moments, the lateral pressure profile across the bilayer, and spontaneous curvature all systematically change with increasing membrane potentials. In particular, there is a linear dependence between the bending moment (the product of bending rigidity and spontaneous curvature) and the applied membrane potentials. We show that biologically relevant membrane potentials can induce biologically relevant curvatures corresponding to radii of around 500 nm. The implications of flexoelectricity in lipid bilayers are thus likely to be of considerable consequence both in biology and in model lipid bilayer systems.

CARBON DYNAMICS OF THE CONSERVATION AND WETLAND RESERVE PROGRAMS

EPA Science Inventory

Data from the Conservation (CRP) and Wetland (WRP) Reserve Programs were analyzed to quantify the carbon (C) dynamics of associated cropland converted to grassland or forestland. Land-area enrollments were multiplied by grassland- and forestland-C densities to calculate C pools a...
Validation of a new device to quantify groundwater-surface water exchange

NASA Astrophysics Data System (ADS)

Cremeans, Mackenzie M.; Devlin, J. F.

2017-11-01

Distributions of flow across the groundwater-surface water interface should be expected to be as complex as the geologic deposits associated with stream or lake beds and their underlying aquifers. In these environments, the conventional Darcy-based method of characterizing flow systems (near streams) has significant limitations, including reliance on parameters with high uncertainties (e.g., hydraulic conductivity), the common use of drilled wells in the case of streambank investigations, and potentially lengthy measurement times for aquifer characterization and water level measurements. Less logistically demanding tools for quantifying exchanges across streambeds have been developed and include drive-point mini-piezometers, seepage meters, and temperature profiling tools. This project adds to that toolbox by introducing the Streambed Point Velocity Probe (SBPVP), a reusable tool designed to quantify groundwater-surface water interactions (GWSWI) at the interface with high density sampling, which can effectively, rapidly, and accurately complement conventional methods. The SBPVP is a direct push device that measures in situ water velocities at the GWSWI with a small-scale tracer test on the probe surface. Tracer tests do not rely on hydraulic conductivity or gradient information, nor do they require long equilibration times. Laboratory testing indicated that the SBPVP has an average accuracy of ± 3% and an average precision of ± 2%. Preliminary field testing, conducted in the Grindsted Å in Jutland, Denmark, yielded promising agreement between groundwater fluxes determined by conventional methods and those estimated from the SBPVP tests executed at similar scales. These results suggest the SBPVP is a viable tool to quantify groundwater-surface water interactions in high definition in sandy streambeds.
Space Suit Thermal Dynamics

NASA Technical Reports Server (NTRS)

Campbell, Anthony B.; Nair, Satish S.; Miles, John B.; Iovine, John V.; Lin, Chin H.

1998-01-01

The present NASA space suit (the Shuttle EMU) is a self-contained environmental control system, providing life support, environmental protection, earth-like mobility, and communications. This study considers the thermal dynamics of the space suit as they relate to astronaut thermal comfort control. A detailed dynamic lumped capacitance thermal model of the present space suit is used to analyze the thermal dynamics of the suit with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The observations from this study are being utilized in two future design efforts, automatic thermal comfort control design for the present space suit and design of future space suit systems for Space Station, Lunar, and Martian missions.
A new method for quantifying and modeling large scale surface water inundation dynamics and key drivers using multiple time series of Earth observation and river flow data. A case study for Australia's Murray-Darling Basin

NASA Astrophysics Data System (ADS)

Heimhuber, Valentin; Tulbure, Mirela G.; Broich, Mark

2017-04-01

Periodically inundated surface water (SW) areas such as floodplains are hotspots of biodiversity and provide a broad range of ecosystem services but have suffered alarming declines in recent history. Large scale flooding events govern the dynamics of these areas and are a critical component of the terrestrial water cycle, but their propagation through river systems and the corresponding long term SW dynamics remain poorly quantified on continental or global scales. In this research, we used an unprecedented Landsat-based time series of SW maps (1986-2011), to develop statistical inundation models and quantify the role of driver variables across the Murray-Darling Basin (MDB) (1 million square-km), which is Australia's bread basket and subject to competing demands over limited water resources. We fitted generalized additive models (GAM) between SW extent as the dependent variable and river flow data from 68 gauges, spatial time series of rainfall (P; interpolated gauge data), evapotranspiration (ET; AWRA-L land surface model) and soil moisture (SM; active passive microwave satellite remote sensing) as predictor variables. We used a fully directed and connected river network (Australian Geofabric) in combination with ancillary data, to develop a spatial modeling framework consisting of 18,521 individual modeling units. We then fitted individual models for all modeling units, which were made up of 10x10 km grid cells split into floodplain, floodplain-lake and non-floodplain areas, depending on the type of water body and its hydrologic connectivity to a gauged river. We applied the framework to quantify flood propagation times for all major river and floodplain systems across the MDB, which were in good accordance with observed travel times. After incorporating these flow lag times into the models, average goodness of fit was high across floodplains and floodplain-lake modeling units (r-squared > 0.65), which were primarily driven by river flow, and lower for non
Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.
Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.
Unifying dynamical and structural stability of equilibria

NASA Astrophysics Data System (ADS)

Arnoldi, Jean-François; Haegeman, Bart

2016-09-01

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

PubMed

Arnoldi, Jean-François; Haegeman, Bart

2016-09-01

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

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Kumar, Rohini; Samaniego, Luis; Barthel, Roland

2016-04-01

Within the classification framework for groundwater systems that aims for identifying similarity of hydrogeological systems and transferring information from a well-observed to an ungauged system (Haaf and Barthel, 2015; Haaf and Barthel, 2016), we propose a copula-based method for describing groundwater-systems similarity. Copulas are an emerging method in hydrological sciences that make it possible to model the dependence structure of two groundwater level time series, independently of the effects of their marginal distributions. This study is based on Samaniego et al. (2010), which described an approach calculating dissimilarity measures from bivariate empirical copula densities of streamflow time series. Subsequently, streamflow is predicted in ungauged basins by transferring properties from similar catchments. The proposed approach is innovative because copula-based similarity has not yet been applied to groundwater systems. Here we estimate the pairwise dependence structure of 600 wells in Southern Germany using 10 years of weekly groundwater level observations. Based on these empirical copulas, dissimilarity measures are estimated, such as the copula's lower- and upper corner cumulated probability, copula-based Spearman's rank correlation - as proposed by Samaniego et al. (2010). For the characterization of groundwater systems, copula-based metrics are compared with dissimilarities obtained from precipitation signals corresponding to the presumed area of influence of each groundwater well. This promising approach provides a new tool for advancing similarity-based classification of groundwater system dynamics. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs EGU General Assembly
A nonlinear dynamical system for combustion instability in a pulse model combustor

NASA Astrophysics Data System (ADS)

Takagi, Kazushi; Gotoda, Hiroshi

2016-11-01

We theoretically and numerically study the bifurcation phenomena of nonlinear dynamical system describing combustion instability in a pulse model combustor on the basis of dynamical system theory and complex network theory. The dynamical behavior of pressure fluctuations undergoes a significant transition from steady-state to deterministic chaos via the period-doubling cascade process known as Feigenbaum scenario with decreasing the characteristic flow time. Recurrence plots and recurrence networks analysis we adopted in this study can quantify the significant changes in dynamic behavior of combustion instability that cannot be captured in the bifurcation diagram.
Dynamic and rheological properties of soft biological cell suspensions

PubMed Central

Yazdani, Alireza; Li, Xuejin

2016-01-01

Quantifying dynamic and rheological properties of suspensions of soft biological particles such as vesicles, capsules, and red blood cells (RBCs) is fundamentally important in computational biology and biomedical engineering. In this review, recent studies on dynamic and rheological behavior of soft biological cell suspensions by computer simulations are presented, considering both unbounded and confined shear flow. Furthermore, the hemodynamic and hemorheological characteristics of RBCs in diseases such as malaria and sickle cell anemia are highlighted. PMID:27540271
Using heteroclinic orbits to quantify topological entropy in fluid flows

NASA Astrophysics Data System (ADS)

Sattari, Sulimon; Chen, Qianting; Mitchell, Kevin A.

2016-03-01

Topological approaches to mixing are important tools to understand chaotic fluid flows, ranging from oceanic transport to the design of micro-mixers. Typically, topological entropy, the exponential growth rate of material lines, is used to quantify topological mixing. Computing topological entropy from the direct stretching rate is computationally expensive and sheds little light on the source of the mixing. Earlier approaches emphasized that topological entropy could be viewed as generated by the braiding of virtual, or "ghost," rods stirring the fluid in a periodic manner. Here, we demonstrate that topological entropy can also be viewed as generated by the braiding of ghost rods following heteroclinic orbits instead. We use the machinery of homotopic lobe dynamics, which extracts symbolic dynamics from finite-length pieces of stable and unstable manifolds attached to fixed points of the fluid flow. As an example, we focus on the topological entropy of a bounded, chaotic, two-dimensional, double-vortex cavity flow. Over a certain parameter range, the topological entropy is primarily due to the braiding of a period-three orbit. However, this orbit does not explain the topological entropy for parameter values where it does not exist, nor does it explain the excess of topological entropy for the entire range of its existence. We show that braiding by heteroclinic orbits provides an accurate computation of topological entropy when the period-three orbit does not exist, and that it provides an explanation for some of the excess topological entropy when the period-three orbit does exist. Furthermore, the computation of symbolic dynamics using heteroclinic orbits has been automated and can be used to compute topological entropy for a general 2D fluid flow.
Density Scaling of Glassy Dynamics and Dynamic Heterogeneities in Glass-forming Liquids.

NASA Astrophysics Data System (ADS)

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

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

PubMed

Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.
StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

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

Zemla, A; Lang, D; Kostova, T

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitatemore » the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or
Quantifying fossil fuel CO2 from continuous measurements of APO: a novel approach

NASA Astrophysics Data System (ADS)

Pickers, Penelope; Manning, Andrew C.; Forster, Grant L.; van der Laan, Sander; Wilson, Phil A.; Wenger, Angelina; Meijer, Harro A. J.; Oram, David E.; Sturges, William T.

2016-04-01

Using atmospheric measurements to accurately quantify CO2 emissions from fossil fuel sources requires the separation of biospheric and anthropogenic CO2 fluxes. The ability to quantify the fossil fuel component of CO2 (ffCO2) from atmospheric measurements enables more accurate 'top-down' verification of CO2 emissions inventories, which frequently have large uncertainty. Typically, ffCO2 is quantified (in ppm units) from discrete atmospheric measurements of Δ14CO2, combined with higher resolution atmospheric CO measurements, and with knowledge of CO:ffCO2 ratios. In the United Kingdom (UK), however, measurements of Δ14CO2 are often significantly biased by nuclear power plant influences, which limit the use of this approach. We present a novel approach for quantifying ffCO2 using measurements of APO (Atmospheric Potential Oxygen; a tracer derived from concurrent measurements of CO2 and O2) from two measurement sites in Norfolk, UK. Our approach is similar to that used for quantifying ffCO2 from CO measurements (ffCO2(CO)), whereby ffCO2(APO) = (APOmeas - APObg)/RAPO, where (APOmeas - APObg) is the APO deviation from the background, and RAPO is the APO:CO2 combustion ratio for fossil fuel. Time varying values of RAPO are calculated from the global gridded COFFEE (CO2 release and Oxygen uptake from Fossil Fuel Emission Estimate) dataset, combined with NAME (Numerical Atmospheric-dispersion Modelling Environment) transport model footprints. We compare our ffCO2(APO) results to results obtained using the ffCO2(CO) method, using CO:CO2 fossil fuel emission ratios (RCO) from the EDGAR (Emission Database for Global Atmospheric Research) database. We find that the APO ffCO2 quantification method is more precise than the CO method, owing primarily to a smaller range of possible APO:CO2 fossil fuel emission ratios, compared to the CO:CO2 emission ratio range. Using a long-term dataset of atmospheric O2, CO2, CO and Δ14CO2 from Lutjewad, The Netherlands, we examine the
An efficient approach to the analysis of rail surface irregularities accounting for dynamic train-track interaction and inelastic deformations

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

NASA Astrophysics Data System (ADS)

Roy, Sukesh; Hua, Jia-Chen; Barnhill, Will; Gunaratne, Gemunu H.; Gord, James R.

2015-01-01

Analytical and computational studies of reacting flows are extremely challenging due in part to nonlinearities of the underlying system of equations and long-range coupling mediated by heat and pressure fluctuations. However, many dynamical features of the flow can be inferred through low-order models if the flow constituents (e.g., eddies or vortices) and their symmetries, as well as the interactions among constituents, are established. Modal decompositions of high-frequency, high-resolution imaging, such as measurements of species-concentration fields through planar laser-induced florescence and of velocity fields through particle-image velocimetry, are the first step in the process. A methodology is introduced for deducing the flow constituents and their dynamics following modal decomposition. Proper orthogonal (POD) and dynamic mode (DMD) decompositions of two classes of problems are performed and their strengths compared. The first problem involves a cellular state generated in a flat circular flame front through symmetry breaking. The state contains two rings of cells that rotate clockwise at different rates. Both POD and DMD can be used to deconvolve the state into the two rings. In POD the contribution of each mode to the flow is quantified using the energy. Each DMD mode can be associated with an energy as well as a unique complex growth rate. Dynamic modes with the same spatial symmetry but different growth rates are found to be combined into a single POD mode. Thus, a flow can be approximated by a smaller number of POD modes. On the other hand, DMD provides a more detailed resolution of the dynamics. Two classes of reacting flows behind symmetric bluff bodies are also analyzed. In the first, symmetric pairs of vortices are released periodically from the two ends of the bluff body. The second flow contains von Karman vortices also, with a vortex being shed from one end of the bluff body followed by a second shedding from the opposite end. The way in which
Similar call signs

DOT National Transportation Integrated Search

2010-08-18

This presentation was given at the Partnership for Safety Meeting in Washington, DC. It examines the similarities that are found when calls signs are visually similar or similar sounding. Visually similar call signs increase the chances of controller...
The dynamics of correlated novelties.

PubMed

Tria, F; Loreto, V; Servedio, V D P; Strogatz, S H

2014-07-31

Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called "expanding the adjacent possible". The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the adjacent possible and its role in biological, cultural, and technological evolution.

The dynamics of correlated novelties

NASA Astrophysics Data System (ADS)

Tria, F.; Loreto, V.; Servedio, V. D. P.; Strogatz, S. H.

2014-07-01

Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called ``expanding the adjacent possible''. The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the adjacent possible and its role in biological, cultural, and technological evolution.
The dynamics of correlated novelties

PubMed Central

Tria, F.; Loreto, V.; Servedio, V. D. P.; Strogatz, S. H.

2014-01-01

Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called “expanding the adjacent possible”. The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the adjacent possible and its role in biological, cultural, and technological evolution. PMID:25080941
Quantifying Variations In Multi-parameter Models With The Photon Clean Method (PCM) And Bootstrap Methods

NASA Astrophysics Data System (ADS)

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

2007-05-01

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

NASA Astrophysics Data System (ADS)

Kolodrubetz, Michael; Katz, Emanuel; Polkovnikov, Anatoli

2015-02-01

The study of dynamics in closed quantum systems has been revitalized by the emergence of experimental systems that are well-isolated from their environment. In this paper, we consider the closed-system dynamics of an archetypal model: spins driven across a second-order quantum critical point, which are traditionally described by the Kibble-Zurek mechanism. Imbuing the driving field with Newtonian dynamics, we find that the full closed system exhibits a robust new phenomenon—dynamic critical trapping—in which the system is self-trapped near the critical point due to efficient absorption of field kinetic energy by heating the quantum spins. We quantify limits in which this phenomenon can be observed and generalize these results by developing a Kibble-Zurek scaling theory that incorporates the dynamic field. Our findings can potentially be interesting in the context of early universe physics, where the role of the driving field is played by the inflaton or a modulus field.
Quantifying selective elbow movements during an exergame in children with neurological disorders: a pilot study.

PubMed

van Hedel, Hubertus J A; Häfliger, Nadine; Gerber, Corinna N

2016-10-21

It is difficult to distinguish between restorative and compensatory mechanisms underlying (pediatric) neurorehabilitation, as objective measures assessing selective voluntary motor control (SVMC) are scarce. We aimed to quantify SVMC of elbow movements in children with brain lesions. Children played an airplane game with the glove-based YouGrabber system. Participants were instructed to steer an airplane on a screen through a cloud-free path by correctly applying bilateral elbow flexion and extension movements. Game performance measures were (i) % time on the correct path and (ii) similarity between the ideal flight path and the actually flown path. SVMC was quantified by calculating a correlation coefficient between the derivative of the ideal path and elbow movements. A therapist scored whether the child had used compensatory movements. Thirty-three children with brain lesions (11 girls; 12.6 ± 3.6 years) participated. Clinical motor and cognitive scores correlated moderately with SVMC (0.50-0.74). Receiver Operating Characteristics analyses showed that SVMC could differentiate well and better than clinical and game performance measures between compensatory and physiological movements. We conclude that a simple measure assessed while playing a game appears promising in quantifying SVMC. We propose how to improve the methodology, and how this approach can be easily extended to other joints.
Cordilleran forest scaling dynamics and disturbance regimes quantified by aerial lidar

NASA Astrophysics Data System (ADS)

Swetnam, Tyson L.

Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my coauthors and I apply metabolic scaling theory (MST) to examine scaling behavior and structural patterns of semi-arid conifer forests in Arizona and New Mexico. We conceptualize a linkage to mechanistic drivers of forest assembly that incorporates the effects of low-intensity disturbance, and physiologic and resource limitations as an extension of MST. We use both aerial LiDAR data and field observations to quantify changes in forest structure from the sub-meter to landscape scales. We found: (1) semi-arid forest structure exhibits MST-predicted behaviors regardless of disturbance and that MST can help to quantitatively measure the level of disturbance intensity in a forest, (2) the application of a power law to a forest overstory frequency distribution can help predict understory presence/absence, (3) local indicators of spatial association can help to define first order effects (e.g. topographic changes) and map where recent disturbances (e.g. logging and fire) have altered forest structure. Lastly, we produced a comprehensive set of above-ground biomass and carbon models for five distinct forest types and ten common species of the southwestern US that are meant for use in aerial LiDAR forest inventory projects. This dissertation presents both a conceptual framework and applications for investigating local scales (stands of trees) up to entire ecosystems for diagnosis of current carbon balances, levels of departure from historical norms, and ecological stability. These tools and models will become more important as we prepare our ecosystems for a future characterized by increased climatic variability
Investigating Forest Harvest Effects on DOC Concentration and Quality: An In Situ, High Resolution Approach to Quantifying DOC Export Dynamics

NASA Astrophysics Data System (ADS)

Jollymore, A. J.; Johnson, M. S.; Hawthorne, I.

2013-12-01

the months following harvest. A major advantage of this study is the use of in situ measurements, allowing for high temporal resolution of DOC dynamics occurring within specific hydrologic events. For example, concentration-discharge relationships for both the pre- and post-logging periods demonstrate similar clockwise hysteresis during individual storm events, while the magnitude of change dramatically increased during the post-logging period. However, in situ measurements of SUVA over this period suggest that DOC quality may be less affected by forest harvest than overall DOC concentration, where high frequency data also allows for the observation of SUVA and spectral slope responses to specific hydrologic events during the pre- and post- harvest period.
Applications of high resolution rainfall radar data to quantify water temperature dynamics in urban catchments

NASA Astrophysics Data System (ADS)

Croghan, Danny; Van Loon, Anne; Bradley, Chris; Sadler, Jon; Hannnah, David

2017-04-01

Studies relating rainfall events to river water quality are frequently hindered by the lack of high resolution rainfall data. Local studies are particularly vulnerable due to the spatial variability of precipitation, whilst studies in urban environments require precipitation data at high spatial and temporal resolutions. The use of point-source data makes identifying causal effects of storms on water quality problematic and can lead to erroneous interpretations. High spatial and temporal resolution rainfall radar data offers great potential to address these issues. Here we use rainfall radar data with a 1km spatial resolution and 5 minute temporal resolution sourced from the UK Met Office Nimrod system to study the effects of storm events on water temperature (WTemp) in Birmingham, UK. 28 WTemp loggers were placed over 3 catchments on a rural-urban land use gradient to identify trends in WTemp during extreme events within urban environments. Using GIS, the catchment associated with each logger was estimated, and 5 min. rainfall totals and intensities were produced for each sub-catchment. Comparisons of rainfall radar data to meteorological stations in the same grid cell revealed the high accuracy of rainfall radar data in our catchments (<5% difference for studied months). The rainfall radar data revealed substantial differences in rainfall quantity between the three adjacent catchments. The most urban catchment generally received more rainfall, with this effect greatest in the highest intensity storms, suggesting the possibility of urban heat island effects on precipitation dynamics within the catchment. Rainfall radar data provided more accurate sub-catchment rainfall totals allowing better modelled estimates of storm flow, whilst spatial fluctuations in both discharge and WTemp can be simply related to precipitation intensity. Storm flow inputs for each sub-catchment were estimated and linked to changes in WTemp. WTemp showed substantial fluctuations (>1 �
Understanding wheel dynamics.

PubMed

Proffitt, D R; Kaiser, M K; Whelan, S M

1990-07-01

In five experiments, assessments were made of people's understandings about the dynamics of wheels. It was found that undergraduates make highly erroneous dynamical judgments about the motions of this commonplace event, both in explicit problem-solving contexts and when viewing ongoing events. These problems were also presented to bicycle racers and high-school physics teachers; both groups were found to exhibit misunderstandings similar to those of naive undergraduates. Findings were related to our account of dynamical event complexity. The essence of this account is that people encounter difficulties when evaluating the dynamics of any mechanical system that has more than one dynamically relevant object parameter. A rotating wheel is multidimensional in this respect: in addition to the motion of its center of mass, its mass distribution is also of dynamical relevance. People do not spontaneously form the essential multidimensional quantities required to adequately evaluate wheel dynamics.
Similarity of the Jovian satellite footprints: Spots multiplicity and dynamics

NASA Astrophysics Data System (ADS)

Bonfond, B.; Grodent, D.; Badman, S. V.; Saur, J.; Gérard, J.-C.; Radioti, A.

2017-08-01

In the magnetospheres of Jupiter and Saturn, the intense interaction of the satellites Io, Europa, Ganymede and Enceladus with their surrounding plasma environment leaves a signature in the aurora of the planet. Called satellite footprints, these auroral features appear either as a single spot (Europa and Enceladus) or as multiple spots (Io and Ganymede). Moreover, they can be followed by extended trailing tails in the case of Io and Europa, while no tail has been reported for Ganymede and Enceladus, yet. Here we show that all Jovian footprints can be made of several spots. Furthermore, the footprints all experience brightness variations on timescale of 2-3 min. We also demonstrate that the satellite location relative to the plasma sheet is not the only driver for the footprint brightness, but that the plasma environment and the magnetic field strength also play a role. These new findings demonstrate that the Europa and Ganymede footprints are very similar to the Io footprint. As a consequence, the processes expected to take place at Io, such as the bi-directional electron acceleration by Alfvén waves or the partial reflection of these waves on plasma density gradients, can most likely be extended to the other footprints, suggesting that they are indeed universal processes.
Kernel approach to molecular similarity based on iterative graph similarity.

PubMed

Rupp, Matthias; Proschak, Ewgenij; Schneider, Gisbert

2007-01-01

Similarity measures for molecules are of basic importance in chemical, biological, and pharmaceutical applications. We introduce a molecular similarity measure defined directly on the annotated molecular graph, based on iterative graph similarity and optimal assignments. We give an iterative algorithm for the computation of the proposed molecular similarity measure, prove its convergence and the uniqueness of the solution, and provide an upper bound on the required number of iterations necessary to achieve a desired precision. Empirical evidence for the positive semidefiniteness of certain parametrizations of our function is presented. We evaluated our molecular similarity measure by using it as a kernel in support vector machine classification and regression applied to several pharmaceutical and toxicological data sets, with encouraging results.
Dynamic balance during walking adaptability tasks in individuals post-stroke.

PubMed

Vistamehr, Arian; Balasubramanian, Chitralakshmi K; Clark, David J; Neptune, Richard R; Fox, Emily J

2018-06-06

Maintaining dynamic balance during community ambulation is a major challenge post-stroke. Community ambulation requires performance of steady-state level walking as well as tasks that require walking adaptability. Prior studies on balance control post-stroke have mainly focused on steady-state walking, but walking adaptability tasks have received little attention. The purpose of this study was to quantify and compare dynamic balance requirements during common walking adaptability tasks post-stroke and in healthy adults and identify differences in underlying mechanisms used for maintaining dynamic balance. Kinematic data were collected from fifteen individuals with post-stroke hemiparesis during steady-state forward and backward walking, obstacle negotiation, and step-up tasks. In addition, data from ten healthy adults provided the basis for comparison. Dynamic balance was quantified using the peak-to-peak range of whole-body angular-momentum in each anatomical plane during the paretic, nonparetic and healthy control single-leg-stance phase of the gait cycle. To understand differences in some of the key underlying mechanisms for maintaining dynamic balance, foot placement and plantarflexor muscle activation were examined. Individuals post-stroke had significant dynamic balance deficits in the frontal plane across most tasks, particularly during the paretic single-leg-stance. Frontal plane balance deficits were associated with wider paretic foot placement, elevated body center-of-mass, and lower soleus activity. Further, the obstacle negotiation task imposed a higher balance requirement, particularly during the trailing leg single-stance. Thus, improving paretic foot placement and ankle plantarflexor activity, particularly during obstacle negotiation, may be important rehabilitation targets to enhance dynamic balance during post-stroke community ambulation. Copyright © 2018 Elsevier Ltd. All rights reserved.
Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.

PubMed

Sullivan, David C; Lim, Carmay

2006-08-24

Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.
Successional dynamics in Neotropical forests are as uncertain as they are predictable

PubMed Central

Norden, Natalia; Angarita, Héctor A.; Bongers, Frans; Martínez-Ramos, Miguel; Granzow-de la Cerda, Iñigo; van Breugel, Michiel; Lebrija-Trejos, Edwin; Meave, Jorge A.; Vandermeer, John; Williamson, G. Bruce; Finegan, Bryan; Mesquita, Rita; Chazdon, Robin L.

2015-01-01

Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes—stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration. PMID:26080411
Successional dynamics in Neotropical forests are as uncertain as they are predictable.

PubMed

Norden, Natalia; Angarita, Héctor A; Bongers, Frans; Martínez-Ramos, Miguel; Granzow-de la Cerda, Iñigo; van Breugel, Michiel; Lebrija-Trejos, Edwin; Meave, Jorge A; Vandermeer, John; Williamson, G Bruce; Finegan, Bryan; Mesquita, Rita; Chazdon, Robin L

2015-06-30

Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes--stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.
Measuring Clearance Mechanics Based on Dynamic Leg Length

ERIC Educational Resources Information Center

Khamis, Sam; Danino, Barry; Hayek, Shlomo; Carmeli, Eli

2018-01-01

The aim of this study was to quantify clearance mechanics during gait. Seventeen children diagnosed with hemiplegic cerebral palsy underwent a three-dimensional gait analysis evaluation. Dynamic leg lengths were measured from the hip joint center to the heel, to the ankle joint center and to the forefoot throughout the gait cycle. Significant…
Protein stability and dynamics influenced by ligands in extremophilic complexes - a molecular dynamics investigation.

PubMed

Khan, Sara; Farooq, Umar; Kurnikova, Maria

2017-08-22

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

NASA Astrophysics Data System (ADS)

van der Elst, N.; Page, M. T.

2017-12-01

The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity
STABLE ISOTOPES AS INDICATORS OF SOIL WATER DYNAMICS IN WATERSHEDS

EPA Science Inventory

Stream water quality and quantity depend on discharge rates of water and nutrients from soils. However, soil-water storage is very dynamic and strongly influenced by plants. We analyzed stable isotopes of oxygen and hydrogen to quantify spatial and temporal changes in evaporati...
Morphological similarities between DBM and a microeconomic model of sprawl

NASA Astrophysics Data System (ADS)

Caruso, Geoffrey; Vuidel, Gilles; Cavailhès, Jean; Frankhauser, Pierre; Peeters, Dominique; Thomas, Isabelle

2011-03-01

We present a model that simulates the growth of a metropolitan area on a 2D lattice. The model is dynamic and based on microeconomics. Households show preferences for nearby open spaces and neighbourhood density. They compete on the land market. They travel along a road network to access the CBD. A planner ensures the connectedness and maintenance of the road network. The spatial pattern of houses, green spaces and road network self-organises, emerging from agents individualistic decisions. We perform several simulations and vary residential preferences. Our results show morphologies and transition phases that are similar to Dieletric Breakdown Models (DBM). Such similarities were observed earlier by other authors, but we show here that it can be deducted from the functioning of the land market and thus explicitly connected to urban economic theory.

Decomposition and nitrogen dynamics of 15N-labeled leaf, root, and twig litter in temperate coniferous forests

USGS Publications Warehouse

van Huysen, Tiff L.; Harmon, Mark E.; Perakis, Steven S.; Chen, Hua

2013-01-01

Litter nutrient dynamics contribute significantly to biogeochemical cycling in forest ecosystems. We examined how site environment and initial substrate quality influence decomposition and nitrogen (N) dynamics of multiple litter types. A 2.5-year decomposition study was installed in the Oregon Coast Range and West Cascades using 15N-labeled litter from Acer macrophyllum, Picea sitchensis, and Pseudotsuga menziesii. Mass loss for leaf litter was similar between the two sites, while root and twig litter exhibited greater mass loss in the Coast Range. Mass loss was greatest from leaves and roots, and species differences in mass loss were more prominent in the Coast Range. All litter types and species mineralized N early in the decomposition process; only A. macrophyllum leaves exhibited a net N immobilization phase. There were no site differences with respect to litter N dynamics despite differences in site N availability, and litter N mineralization patterns were species-specific. For multiple litter × species combinations, the difference between gross and net N mineralization was significant, and gross mineralization was 7–20 % greater than net mineralization. The mineralization results suggest that initial litter chemistry may be an important driver of litter N dynamics. Our study demonstrates that greater amounts of N are cycling through these systems than may be quantified by only measuring net mineralization and challenges current leaf-based biogeochemical theory regarding patterns of N immobilization and mineralization.
Quantifying Dynamic Changes in Plantar Pressure Gradient in Diabetics with Peripheral Neuropathy.

PubMed

Lung, Chi-Wen; Hsiao-Wecksler, Elizabeth T; Burns, Stephanie; Lin, Fang; Jan, Yih-Kuen

2016-01-01

Diabetic foot ulcers remain one of the most serious complications of diabetes. Peak plantar pressure (PPP) and peak pressure gradient (PPG) during walking have been shown to be associated with the development of diabetic foot ulcers. To gain further insight into the mechanical etiology of diabetic foot ulcers, examination of the pressure gradient angle (PGA) has been recently proposed. The PGA quantifies directional variation or orientation of the pressure gradient during walking and provides a measure of whether pressure gradient patterns are concentrated or dispersed along the plantar surface. We hypothesized that diabetics at risk of foot ulceration would have smaller PGA in key plantar regions, suggesting less movement of the pressure gradient over time. A total of 27 participants were studied, including 19 diabetics with peripheral neuropathy and 8 non-diabetic control subjects. A foot pressure measurement system was used to measure plantar pressures during walking. PPP, PPG, and PGA were calculated for four foot regions - first toe (T1), first metatarsal head (M1), second metatarsal head (M2), and heel (HL). Consistent with prior studies, PPP and PPG were significantly larger in the diabetic group compared with non-diabetic controls in the T1 and M1 regions, but not M2 or HL. For example, PPP was 165% (P = 0.02) and PPG was 214% (P < 0.001) larger in T1. PGA was found to be significantly smaller in the diabetic group in T1 (46%, P = 0.04), suggesting a more concentrated pressure gradient pattern under the toe. The proposed PGA may improve our understanding of the role of pressure gradient on the risk of diabetic foot ulcers.
Quantifying flood duration controls on chute cutoff formation in a wandering gravel-bed river

NASA Astrophysics Data System (ADS)

Sawyer, A.; Wilcox, A. C.

2014-12-01

Chute cutoffs, which occur when a bypass or "chute" channel incises across a point or braid bar, distribute water and sediment, regulate sinuosity, and create off-channel habitat in wandering gravel-bed rivers. Cutoffs have been hypothesized to occur by progressive migration preparing a bend for cutoff, after which overbank flow events provide a trigger to excavate new channels. This trigger may depend on the magnitude and duration of floods and their associated sediment fluxes. Here we investigated how overbank flow duration impacts cutoff formation in a wandering gravel-bed river. To explore this, we applied a two-dimensional hydrodynamic model to a recently reconstructed reach of the Clark Fork River in western Montana that experienced chute cutoffs during a long-duration flood event in 2011. Hydrographs exceeding bankfull and with varying durations were simulated to constrain the role of overbank flow duration on erosional work in chute cutoff channels. For each magnitude-frequency-duration combination, cumulative excess shear stress (i.e., above the threshold of sediment mobilization) was quantified for in-channel and overbank areas. Locations of shear stress divergence associated with morphological change were identified along chute pathways. Preliminary results suggest that overbank areas containing concentrated flowpaths such as swales follow cumulative excess shear stress curve patterns similar to in-channel areas. This work describes a dynamic system characteristic of wandering gravel-bed rivers in the Pacific Northwest, and has implications for understanding morphodynamic evolution, river restoration targeting off-channel habitat for fish, and geomorphic flow regime management in regulated rivers.
Quantifying the influence of the terrestrial biosphere on glacial-interglacial climate dynamics

NASA Astrophysics Data System (ADS)

Davies-Barnard, Taraka; Ridgwell, Andy; Singarayer, Joy; Valdes, Paul

2017-10-01

The terrestrial biosphere is thought to be a key component in the climatic variability seen in the palaeo-record. It has a direct impact on surface temperature through changes in surface albedo and evapotranspiration (so-called biogeophysical effects) and, in addition, has an important indirect effect through changes in vegetation and soil carbon storage (biogeochemical effects) and hence modulates the concentrations of greenhouse gases in the atmosphere. The biogeochemical and biogeophysical effects generally have opposite signs, meaning that the terrestrial biosphere could potentially have played only a very minor role in the dynamics of the glacial-interglacial cycles of the late Quaternary. Here we use a fully coupled dynamic atmosphere-ocean-vegetation general circulation model (GCM) to generate a set of 62 equilibrium simulations spanning the last 120 kyr. The analysis of these simulations elucidates the relative importance of the biogeophysical versus biogeochemical terrestrial biosphere interactions with climate. We find that the biogeophysical effects of vegetation account for up to an additional -0.91 °C global mean cooling, with regional cooling as large as -5 °C, but with considerable variability across the glacial-interglacial cycle. By comparison, while opposite in sign, our model estimates of the biogeochemical impacts are substantially smaller in magnitude. Offline simulations show a maximum of +0.33 °C warming due to an increase of 25 ppm above our (pre-industrial) baseline atmospheric CO2 mixing ratio. In contrast to shorter (century) timescale projections of future terrestrial biosphere response where direct and indirect responses may at times cancel out, we find that the biogeophysical effects consistently and strongly dominate the biogeochemical effect over the inter-glacial cycle. On average across the period, the terrestrial biosphere has a -0.26 °C effect on temperature, with -0.58 °C at the Last Glacial Maximum. Depending on
Quantifying gaze and mouse interactions on spatial visual interfaces with a new movement analytics methodology.

PubMed

Demšar, Urška; Çöltekin, Arzu

2017-01-01

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

PubMed Central

2017-01-01

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

PubMed

Ramos-Cordoba, Eloy; Matito, Eduard

2017-06-13

Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.
The stochastic dynamics of tethered microcantilevers in a viscous fluid

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

Robbins, Brian A.; Paul, Mark R.; Radiom, Milad

2014-10-28

We explore and quantify the coupled dynamics of a pair of micron scale cantilevers immersed in a viscous fluid that are also directly tethered to one another at their tips by a spring force. The spring force, for example, could represent the molecular stiffness or elasticity of a biomolecule or material tethered between the cantilevers. We use deterministic numerical simulations with the fluctuation-dissipation theorem to compute the stochastic dynamics of the cantilever pair for the conditions of experiment when driven only by Brownian motion. We validate our approach by comparing directly with experimental measurements in the absence of the tethermore » which shows excellent agreement. Using numerical simulations, we quantify the correlated dynamics of the cantilever pair over a range of tether stiffness. Our results quantify the sensitivity of the auto- and cross-correlations of equilibrium fluctuations in cantilever displacement to the stiffness of the tether. We show that the tether affects the magnitude of the correlations which can be used in a measurement to probe the properties of an attached tethering substance. For the configurations of current interest using micron scale cantilevers in water, we show that the magnitude of the fluid coupling between the cantilevers is sufficiently small such that the influence of the tether can be significant. Our results show that the cross-correlation is more sensitive to tether stiffness than the auto-correlation indicating that a two-cantilever measurement has improved sensitivity when compared with a measurement using a single cantilever.« less
Quantifying noise in optical tweezers by allan variance.

PubMed

Czerwinski, Fabian; Richardson, Andrew C; Oddershede, Lene B

2009-07-20

Much effort is put into minimizing noise in optical tweezers experiments because noise and drift can mask fundamental behaviours of, e.g., single molecule assays. Various initiatives have been taken to reduce or eliminate noise but it has been difficult to quantify their effect. We propose to use Allan variance as a simple and efficient method to quantify noise in optical tweezers setups.We apply the method to determine the optimal measurement time, frequency, and detection scheme, and quantify the effect of acoustic noise in the lab. The method can also be used on-the-fly for determining optimal parameters of running experiments.
Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics

PubMed Central

Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert

2014-01-01

The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes two domains (patients and drugs) and encodes three relationships (patient similarity, drug similarity, and patient-drug prior associations). We describe a novel approach for performing a label propagation procedure to spread the label information representing the effectiveness of different drugs for different patients over this heterogeneous graph. The proposed method has been applied on a real-world EHR dataset to help identify personalized treatments for hypercholesterolemia. The experimental results demonstrate the effectiveness of the approach and suggest that the combination of appropriate patient similarity and drug similarity analytics could lead to actionable insights for personalized medicine. Particularly, by leveraging drug similarity in combination with patient similarity, our method could perform well even on new or rarely used drugs for which there are few records of known past performance. PMID:25717413
Word embeddings quantify 100 years of gender and ethnic stereotypes.

PubMed

Garg, Nikhil; Schiebinger, Londa; Jurafsky, Dan; Zou, James

2018-04-17

Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we develop a framework to demonstrate how the temporal dynamics of the embedding helps to quantify changes in stereotypes and attitudes toward women and ethnic minorities in the 20th and 21st centuries in the United States. We integrate word embeddings trained on 100 y of text data with the US Census to show that changes in the embedding track closely with demographic and occupation shifts over time. The embedding captures societal shifts-e.g., the women's movement in the 1960s and Asian immigration into the United States-and also illuminates how specific adjectives and occupations became more closely associated with certain populations over time. Our framework for temporal analysis of word embedding opens up a fruitful intersection between machine learning and quantitative social science.
An inter-comparison of similarity-based methods for organisation and classification of groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2018-04-01

Classification and similarity based methods, which have recently received major attention in the field of surface water hydrology, namely through the PUB (prediction in ungauged basins) initiative, have not yet been applied to groundwater systems. However, it can be hypothesised, that the principle of "similar systems responding similarly to similar forcing" applies in subsurface hydrology as well. One fundamental prerequisite to test this hypothesis and eventually to apply the principle to make "predictions for ungauged groundwater systems" is efficient methods to quantify the similarity of groundwater system responses, i.e. groundwater hydrographs. In this study, a large, spatially extensive, as well as geologically and geomorphologically diverse dataset from Southern Germany and Western Austria was used, to test and compare a set of 32 grouping methods, which have previously only been used individually in local-scale studies. The resulting groupings are compared to a heuristic visual classification, which serves as a baseline. A performance ranking of these classification methods is carried out and differences in homogeneity of grouping results were shown, whereby selected groups were related to hydrogeological indices and geological descriptors. This exploratory empirical study shows that the choice of grouping method has a large impact on the object distribution within groups, as well as on the homogeneity of patterns captured in groups. The study provides a comprehensive overview of a large number of grouping methods, which can guide researchers when attempting similarity-based groundwater hydrograph classification.
Quantifiers More or Less Quantify On-Line: ERP Evidence for Partial Incremental Interpretation

ERIC Educational Resources Information Center

Urbach, Thomas P.; Kutas, Marta

2010-01-01

Event-related brain potentials were recorded during RSVP reading to test the hypothesis that quantifier expressions are incrementally interpreted fully and immediately. In sentences tapping general knowledge ("Farmers grow crops/worms as their primary source of income"), Experiment 1 found larger N400s for atypical ("worms") than typical objects…
Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

2016-01-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.
Detailed Investigation of Self-Similarity of Strong Shock Reflection Phenomena

NASA Astrophysics Data System (ADS)

Kobayashi, Susumu; Adachi, Takashi

2012-04-01

This paper experimentally investigates the validity of self-similarity of strong shock reflection phenomena in a shock tube. The models used for the shock-tube experiment are ordinary wedges with various reflecting wedge angles. The triple-point trajectory is approximately a straight line through the wedge apex for each reflecting wedge. However, a detailed measurement of the angle made by the incident and reflected shocks shows that the wave angle varies as the incident shock proceeds. This means that the shock reflection configuration deviates from self-similarity. The most remarkable phenomenon is the dynamic transition from regular to Mach reflection during shock propagation, where the validity of self-similarity breaks down. The flow-field behind the Mach stem is subsonic with respect to the triple point, so the condition on the solid boundary can catch up with the triple point and affect the flow around it. We also explain why the discrepancy between theory and experiment has gone unnoticed for strong shock waves and demonstrate that it is due to the transport properties of the fluid, such as the viscosity.
Analysis to Quantify Significant Contribution

EPA Pesticide Factsheets

This Technical Support Document provides information that supports EPA’s analysis to quantify upwind state emissions that significantly contribute to nonattainment or interfere with maintenance of National Ambient Air Quality Standards in downwind states.
Computational hydrodynamic comparison of a mini vessel and a USP 2 dissolution testing system to predict the dynamic operating conditions for similarity of dissolution performance.

PubMed

Wang, Bing; Bredael, Gerard; Armenante, Piero M

2018-03-25

The hydrodynamic characteristics of a mini vessel and a USP 2 dissolution testing system were obtained and compared to predict the tablet-liquid mass transfer coefficient from velocity distributions near the tablet and establish the dynamic operating conditions under which dissolution in mini vessels could be conducted to generate concentration profiles similar to those in the USP 2. Velocity profiles were obtained experimentally using Particle Image Velocimetry (PIV). Computational Fluid Dynamics (CFD) was used to predict the velocity distribution and strain rate around a model tablet. A CFD-based mass transfer model was also developed. When plotted against strain rate, the predicted tablet-liquid mass transfer coefficient was found to be independent of the system where it was obtained, implying that a tablet would dissolve at the same rate in both systems provided that the concentration gradient between the tablet surface and the bulk is the same, the tablet surface area per unit liquid volume is identical, and the two systems are operated at the appropriate agitation speeds specified in this work. The results of this work will help dissolution scientists operate mini vessels so as to predict the dissolution profiles in the USP 2, especially during the early stages of drug development. Copyright © 2018 Elsevier B.V. All rights reserved.
Quantifying the extent of protected-area downgrading, downsizing, and degazettement in Australia.

PubMed

Cook, Carly N; Valkan, Rebecca S; Mascia, Michael B; McGeoch, Melodie A

2017-10-01

The use of total area protected as the predominant indicator of progress in building protected area (PA) networks is receiving growing criticism. Documenting the full dynamics of PA networks, both in terms of the gains and losses in protection, provides a much more informative approach to tracking progress. To this end, documentation of PA downgrading, downsizing, and degazettement (PADDD) has increased. Studies of PADDD events generally fail to place these losses in the context of gains in protection; therefore, they omit important elements of PA network dynamics. To address this limitation, we used a spatially explicit approach to identify every parcel of land added to and excised from the Australian terrestrial PA network and PAs that had their level of protection changed over 17 years (1997-2014). By quantifying changes in the spatial configuration of the PA network with time-series data (spatial layers for nine separate time steps), ours is the first assessment of the dynamics (increases and decreases in area and level of protection) of a PA network and the first comprehensive assessment of PADDD in a developed country. We found that the Australian network was highly dynamic; there were 5233 changes in area or level of protection over 17 years. Against a background of enormous increases in area protected, we identified over 1500 PADDD events, which affected over one-third of the network, which were largely the result of widespread downgrading of protection. We believe our approach provides a mechanism for robust tracking of trends in the world's PAs through the use of data from the World Database on Protected Areas. However, this will require greater transparency and improved data standards in reporting changes to PAs. © 2017 Society for Conservation Biology.
A probabilistic approach to quantifying hydrologic thresholds regulating migration of adult Atlantic salmon into spawning streams

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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