Dynamic Balance of Excitation and Inhibition in Human and Monkey Neocortex

NASA Astrophysics Data System (ADS)

Dehghani, Nima; Peyrache, Adrien; Telenczuk, Bartosz; Le van Quyen, Michel; Halgren, Eric; Cash, Sydney S.; Hatsopoulos, Nicholas G.; Destexhe, Alain

2016-03-01

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics of excitation and inhibition using dense multielectrode recordings in humans and monkeys. We found that in all states of the wake-sleep cycle, excitatory and inhibitory ensembles are well balanced, and co-fluctuate with slight instantaneous deviations from perfect balance, mostly in slow-wave sleep. Remarkably, these correlated fluctuations are seen for many different temporal scales. The similarity of these computational features with a network model of self-generated balanced states suggests that such balanced activity is essentially generated by recurrent activity in the local network and is not due to external inputs. Finally, we find that this balance breaks down during seizures, where the temporal correlation of excitatory and inhibitory populations is disrupted. These results show that balanced activity is a feature of normal brain activity, and break down of the balance could be an important factor to define pathological states.

Crown dynamics and wood production of Douglas-fir trees in an old-growth forest

Treesearch

H. Roaki Ishii; Stephen C. Sillett; Allyson L. Carroll

2017-01-01

Large trees are the most prominent structural features of old-growth forests, which are considered to be globally important carbon sinks. Because of their large size, estimates of biomass and growth of large trees are often based on ground-level measurements (e.g., diameter at breast height, DBH) and little is known about growth dynamics within the crown. As trees...

Structures composing protein domains.

PubMed

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel; Hudeček, Jiří

2013-08-01

This review summarizes available data concerning intradomain structures (IS) such as functionally important amino acid residues, short linear motifs, conserved or disordered regions, peptide repeats, broadly occurring secondary structures or folds, etc. IS form structural features (units or elements) necessary for interactions with proteins or non-peptidic ligands, enzyme reactions and some structural properties of proteins. These features have often been related to a single structural level (e.g. primary structure) mostly requiring certain structural context of other levels (e.g. secondary structures or supersecondary folds) as follows also from some examples reported or demonstrated here. In addition, we deal with some functionally important dynamic properties of IS (e.g. flexibility and different forms of accessibility), and more special dynamic changes of IS during enzyme reactions and allosteric regulation. Selected notes concern also some experimental methods, still more necessary tools of bioinformatic processing and clinically interesting relationships. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

The dynamics of Black Smokers: a heated-salty plume analog.

NASA Astrophysics Data System (ADS)

Maxworthy, Tony

2004-11-01

Experiments have been carried out on the dynamical processes that govern the evolution of hot, salty plumes injected into cold surroundings. Under the appropriate circumstances these are then used as an analoque system to understand some features of particle-laden, deep-ocean, hydrothermal plumes, e.g., Black Smokers. Details of the temperature distributions over a wide range of parameters are presented and these, coupled with flow visualization experiments, have yielded a fairly complete picture of the important features of the flow. As a result it has been concluded that cabelling processes are critical to an understanding of the flow reversals found in a certain parameter range and that double diffusive processes, though present, are of minor importance. As a final exercise an example is worked through in which the circumstances for flow reversal in deep-sea plumes have been estimated based on the best available knowledge of these interesting entities.

Designing attractive models via automated identification of chaotic and oscillatory dynamical regimes.

PubMed

Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Rose, Anna; Moon, Simon; Dallman, Margaret J; Stumpf, Michael P H

2011-10-04

Chaos and oscillations continue to capture the interest of both the scientific and public domains. Yet despite the importance of these qualitative features, most attempts at constructing mathematical models of such phenomena have taken an indirect, quantitative approach, for example, by fitting models to a finite number of data points. Here we develop a qualitative inference framework that allows us to both reverse-engineer and design systems exhibiting these and other dynamical behaviours by directly specifying the desired characteristics of the underlying dynamical attractor. This change in perspective from quantitative to qualitative dynamics, provides fundamental and new insights into the properties of dynamical systems.

On the relationship between the dynamic behavior and nanoscale staggered structure of the bone

NASA Astrophysics Data System (ADS)

Qwamizadeh, Mahan; Zhang, Zuoqi; Zhou, Kun; Zhang, Yong Wei

2015-05-01

Bone, a typical load-bearing biological material, composed of ordinary base materials such as organic protein and inorganic mineral arranged in a hierarchical architecture, exhibits extraordinary mechanical properties. Up to now, most of previous studies focused on its mechanical properties under static loading. However, failure of the bone occurs often under dynamic loading. An interesting question is: Are the structural sizes and layouts of the bone related or even adapted to the functionalities demanded by its dynamic performance? In the present work, systematic finite element analysis was performed on the dynamic response of nanoscale bone structures under dynamic loading. It was found that for a fixed mineral volume fraction and unit cell area, there exists a nanoscale staggered structure at some specific feature size and layout which exhibits the fastest attenuation of stress waves. Remarkably, these specific feature sizes and layouts are in excellent agreement with those experimentally observed in the bone at the same scale, indicating that the structural size and layout of the bone at the nanoscale are evolutionarily adapted to its dynamic behavior. The present work points out the importance of dynamic effect on the biological evolution of load-bearing biological materials.

The neural circuit and synaptic dynamics underlying perceptual decision-making

NASA Astrophysics Data System (ADS)

Liu, Feng

2015-03-01

Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.

The Transition Zone Chlorophyll Front updated: Advances from a decade of research

NASA Astrophysics Data System (ADS)

Polovina, Jeffrey J.; Howell, Evan A.; Kobayashi, Donald R.; Seki, Michael P.

2017-01-01

The dynamic ocean feature called the Transition Zone Chlorophyll Front (TZCF) was first described fifteen years ago based on an empirical association between the apparent habitat of loggerhead sea turtles and albacore tuna linked to a basin-wide chlorophyll front observed with remotely sensed ocean color data. Subsequent research has provided considerable evidence that the TZCF is an indicator for a dynamic ocean feature with important physical and biological characteristics. New insights into the seasonal dynamics of the TZCF suggest that in the summer it is located at the southern boundary of the subarctic gyre while its position in the winter and spring is defined by the extent of the southward transport of surface nutrients. While the TZCF is defined as the dynamic boundary between low and high surface chlorophyll, it appears to be a boundary between subtropical and subarctic phytoplankton communities. Furthermore, the TZCF is also characterized as supporting enhanced phytoplankton net community production throughout its seasonal migration. Lastly, the TZCF is important to the growth rate of neon flying squid and to the survival of monk seal pups in the northern atolls of the Hawaiian Archipelago. This paper reviews these and other findings that advance our current understanding of the physics and biology of the TZCF from research over the past decade.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

What shakes the FX tree? Understanding currency dominance, dependence, and dynamics (Keynote Address)

NASA Astrophysics Data System (ADS)

Johnson, Neil F.; McDonald, Mark; Suleman, Omer; Williams, Stacy; Howison, Sam

2005-05-01

There is intense interest in understanding the stochastic and dynamical properties of the global Foreign Exchange (FX) market, whose daily transactions exceed one trillion US dollars. This is a formidable task since the FX market is characterized by a web of fluctuating exchange rates, with subtle inter-dependencies which may change in time. In practice, traders talk of particular currencies being 'in play' during a particular period of time -- yet there is no established machinery for detecting such important information. Here we apply the construction of Minimum Spanning Trees (MSTs) to the FX market, and show that the MST can capture important features of the global FX dynamics. Moreover, we show that the MST can help identify momentarily dominant and dependent currencies.

MHD Instability and Turbulence in the Tachocline

NASA Technical Reports Server (NTRS)

Werne, Joe; Wagner, William J. (Technical Monitor)

2003-01-01

The focus of this project was to study the physical processes that govern tachocline dynamics and structure. Specific features explored included stratification, shear, waves, and toroidal and poloidal background fields. In order to address recent theoretical work on anisotropic mixing and dynamics in the tachocline, we were particularly interested in such anisotropic mixing for the specific tachocline processes studied. Transition to turbulence often shapes the largest-scale features that appear spontaneously in a flow during the development of turbulence. The resulting large-scale straining field can control the subsequent dynamics; therefore, anticipation of the large-scale straining field that results for individual realizations of the transition to turbulence can be important for subsequent dynamics, flow morphology, and transport characteristics. As a result, we paid particular attention to the development of turbulence in the stratified and sheared environment of the tachocline. This is complicated by the fact that the linearly stability of sheared MHD flows is non-self-adjoint, implying that normal asymptotic linear stability theory may not be relevant.

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

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.

Cortical processing of dynamic sound envelope transitions.

PubMed

Zhou, Yi; Wang, Xiaoqin

2010-12-08

Slow envelope fluctuations in the range of 2-20 Hz provide important segmental cues for processing communication sounds. For a successful segmentation, a neural processor must capture envelope features associated with the rise and fall of signal energy, a process that is often challenged by the interference of background noise. This study investigated the neural representations of slowly varying envelopes in quiet and in background noise in the primary auditory cortex (A1) of awake marmoset monkeys. We characterized envelope features based on the local average and rate of change of sound level in envelope waveforms and identified envelope features to which neurons were selective by reverse correlation. Our results showed that envelope feature selectivity of A1 neurons was correlated with the degree of nonmonotonicity in their static rate-level functions. Nonmonotonic neurons exhibited greater feature selectivity than monotonic neurons in quiet and in background noise. The diverse envelope feature selectivity decreased spike-timing correlation among A1 neurons in response to the same envelope waveforms. As a result, the variability, but not the average, of the ensemble responses of A1 neurons represented more faithfully the dynamic transitions in low-frequency sound envelopes both in quiet and in background noise.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

A stochastic spatial model of HIV dynamics with an asymmetric battle between the virus and the immune system

NASA Astrophysics Data System (ADS)

Lin, Hai; Shuai, J. W.

2010-04-01

A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.

Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.

PubMed

Ebrahimi, Farideh; Setarehdan, Seyed-Kamaledin; Ayala-Moyeda, Jose; Nazeran, Homer

2013-10-01

The conventional method for sleep staging is to analyze polysomnograms (PSGs) recorded in a sleep lab. The electroencephalogram (EEG) is one of the most important signals in PSGs but recording and analysis of this signal presents a number of technical challenges, especially at home. Instead, electrocardiograms (ECGs) are much easier to record and may offer an attractive alternative for home sleep monitoring. The heart rate variability (HRV) signal proves suitable for automatic sleep staging. Thirty PSGs from the Sleep Heart Health Study (SHHS) database were used. Three feature sets were extracted from 5- and 0.5-min HRV segments: time-domain features, nonlinear-dynamics features and time-frequency features. The latter was achieved by using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods. Normalized energies in important frequency bands of HRV signals were computed using time-frequency methods. ANOVA and t-test were used for statistical evaluations. Automatic sleep staging was based on HRV signal features. The ANOVA followed by a post hoc Bonferroni was used for individual feature assessment. Most features were beneficial for sleep staging. A t-test was used to compare the means of extracted features in 5- and 0.5-min HRV segments. The results showed that the extracted features means were statistically similar for a small number of features. A separability measure showed that time-frequency features, especially EMD features, had larger separation than others. There was not a sizable difference in separability of linear features between 5- and 0.5-min HRV segments but separability of nonlinear features, especially EMD features, decreased in 0.5-min HRV segments. HRV signal features were classified by linear discriminant (LD) and quadratic discriminant (QD) methods. Classification results based on features from 5-min segments surpassed those obtained from 0.5-min segments. The best result was obtained from features using 5-min HRV segments classified by the LD classifier. A combination of linear/nonlinear features from HRV signals is effective in automatic sleep staging. Moreover, time-frequency features are more informative than others. In addition, a separability measure and classification results showed that HRV signal features, especially nonlinear features, extracted from 5-min segments are more discriminative than those from 0.5-min segments in automatic sleep staging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Association between dynamic features of breast DCE-MR imaging and clinical response of neoadjuvant chemotherapy: a preliminary analysis

NASA Astrophysics Data System (ADS)

Huang, Lijuan; Fan, Ming; Li, Lihua; Zhang, Juan; Shao, Guoliang; Zheng, Bin

2016-03-01

Neoadjuvant chemotherapy (NACT) is being used increasingly in the management of patients with breast cancer for systemically reducing the size of primary tumor before surgery in order to improve survival. The clinical response of patients to NACT is correlated with reduced or abolished of their primary tumor, which is important for treatment in the next stage. Recently, the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used for evaluation of the response of patients to NACT. To measure this correlation, we extracted the dynamic features from the DCE- MRI and performed association analysis between these features and the clinical response to NACT. In this study, 59 patients are screened before NATC, of which 47 are complete or partial response, and 12 are no response. We segmented the breast areas depicted on each MR image by a computer-aided diagnosis (CAD) scheme, registered images acquired from the sequential MR image scan series, and calculated eighteen features extracted from DCE-MRI. We performed SVM with the 18 features for classification between patients of response and no response. Furthermore, 6 of the 18 features are selected to refine the classification by using Genetic Algorithm. The accuracy, sensitivity and specificity are 87%, 95.74% and 50%, respectively. The calculated area under a receiver operating characteristic (ROC) curve is 0.79+/-0.04. This study indicates that the features of DCE-MRI of breast cancer are associated with the response of NACT. Therefore, our method could be helpful for evaluation of NACT in treatment of breast cancer.

Modelling and mapping tick dynamics using volunteered observations.

PubMed

Garcia-Martí, Irene; Zurita-Milla, Raúl; van Vliet, Arnold J H; Takken, Willem

2017-11-14

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014. Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT. We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level. This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Pynamic: the Python Dynamic Benchmark

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

Lee, G L; Ahn, D H; de Supinksi, B R

2007-07-10

Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less

Dynamic Moss Observed with Hi-C

NASA Technical Reports Server (NTRS)

Alexander, Caroline; Winebarger, Amy; Morton, Richard; Savage, Sabrina

2014-01-01

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-­-C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Dynamic Moss Observed with Hi-C

NASA Technical Reports Server (NTRS)

Alexander, Caroline; Winebarger, Amy; Morton, Richard; Savage, Sabrina

2014-01-01

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Physical activity classification with dynamic discriminative methods.

PubMed

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

2018-06-19

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

Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons.

PubMed

Rubinov, Mikail; Sporns, Olaf; Thivierge, Jean-Philippe; Breakspear, Michael

2011-06-01

Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches) and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect their importance for neuronal information processing.

Dynamical network of residue–residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation

PubMed Central

Doshi, Urmi; Holliday, Michael J.; Eisenmesser, Elan Z.; Hamelberg, Donald

2016-01-01

Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue–residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general. PMID:27071107

Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model

EPA Science Inventory

A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...

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

DOE PAGES

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

2016-11-08

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

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

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

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

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

Optimal Dynamics of Intermittent Water Supply

NASA Astrophysics Data System (ADS)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2014-11-01

In many urban areas of the developing world, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability.

General theories and features of interfacial thermal transport

NASA Astrophysics Data System (ADS)

Zhou, Hangbo; Zhang, Gang

2018-03-01

A clear understanding and proper control of interfacial thermal transport is important in nanoscale device. In this review, we first discuss the theoretical methods to handle the interfacial thermal transport problem, such as the macroscopic model, molecular dynamics, lattice dynamics and modern quantum transport theories. Then we discuss various effects that can significantly affect the interfacial thermal transport, such as the formation of chemical bonds at interface, defects and interface roughness, strain and substrates, atomic species and mass ratios, structural orientations. Then importantly, we analyze the role of inelastic scatterings at the interface, and discuss its application in thermal rectifications. Finally, the challenges and promising directions are discussed.

Automated Extraction of Secondary Flow Features

NASA Technical Reports Server (NTRS)

Dorney, Suzanne M.; Haimes, Robert

2005-01-01

The use of Computational Fluid Dynamics (CFD) has become standard practice in the design and development of the major components used for air and space propulsion. To aid in the post-processing and analysis phase of CFD many researchers now use automated feature extraction utilities. These tools can be used to detect the existence of such features as shocks, vortex cores and separation and re-attachment lines. The existence of secondary flow is another feature of significant importance to CFD engineers. Although the concept of secondary flow is relatively understood there is no commonly accepted mathematical definition for secondary flow. This paper will present a definition for secondary flow and one approach for automatically detecting and visualizing secondary flow.

Symmetry breaking, mixing, instability, and low-frequency variability in a minimal Lorenz-like system.

PubMed

Lucarini, Valerio; Fraedrich, Klaus

2009-08-01

Starting from the classical Saltzman two-dimensional convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system which includes a decoupled generalized Lorenz system. The consideration of this process breaks an important symmetry and couples the dynamics of fast and slow variables, with the ensuing modifications to the structural properties of the attractor and of the spectral features. When the relevant nondimensional number (Eckert number Ec) is different from zero, an additional time scale of O(Ec(-1)) is introduced in the system, as shown with standard multiscale analysis and made clear by several numerical evidences. Moreover, the system is ergodic and hyperbolic, the slow variables feature long-term memory with 1/f(3/2) power spectra, and the fast variables feature amplitude modulation. Increasing the strength of the thermal-viscous feedback has a stabilizing effect, as both the metric entropy and the Kaplan-Yorke attractor dimension decrease monotonically with Ec. The analyzed system features very rich dynamics: it overcomes some of the limitations of the Lorenz system and might have prototypical value in relevant processes in complex systems dynamics, such as the interaction between slow and fast variables, the presence of long-term memory, and the associated extreme value statistics. This analysis shows how neglecting the coupling of slow and fast variables only on the basis of scale analysis can be catastrophic. In fact, this leads to spurious invariances that affect essential dynamical properties (ergodicity, hyperbolicity) and that cause the model losing ability in describing intrinsically multiscale processes.

Nonlinear dynamics, fractals, cardiac physiology and sudden death

NASA Technical Reports Server (NTRS)

Goldberger, Ary L.

1987-01-01

The authors propose a diametrically opposite viewpoint to the generally accepted tendency of equating healthy function with order and disease with chaos. With regard to the question of sudden cardiac death and chaos, it is suggested that certain features of dynamical chaos related to fractal structure and fractal dynamics may be important organizing principles in normal physiology and that certain pathologies, including ventricular fibrillation, represent a class of 'pathological periodicities'. Some laboratory work bearing on the relation of nonlinear analysis to physiological and pathophysiological data is briefly reviewed, with tentative theories and models described in reference to the mechanism of ventricular fibrillation.

The Coevolution of Digital Ecosystems

ERIC Educational Resources Information Center

SungYong, Um

2016-01-01

Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…

A Waved Journal Bearing Concept-Evaluating Steady-State and Dynamic Performance with a Potential Active Control Alternative

NASA Technical Reports Server (NTRS)

Dimofte, Florin

1993-01-01

Analysis of the waved journal bearing concept featuring a waved inner bearing diameter for use with a compressible lubricant (gas) is presented. The performance of generic waved bearings having either three or four waves is predicted for air lubricated bearings. Steady-state performance is discussed in terms of bearing load capacity, while the dynamic performance is discussed in terms of fluid film stability and dynamic coefficients. It was found that the bearing wave amplitude has an important influence on both the steady-state and the dynamic performance of the waved journal bearing. For a fixed eccentricity ratio, the bearing steady-state load capacity and direct dynamic stiffness coefficient increase as the wave amplitude increases.

Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials.

PubMed

Amsel, Ben D

2011-04-01

Empirically derived semantic feature norms categorized into different types of knowledge (e.g., visual, functional, auditory) can be summed to create number-of-feature counts per knowledge type. Initial evidence suggests several such knowledge types may be recruited during language comprehension. The present study provides a more detailed understanding of the timecourse and intensity of influence of several such knowledge types on real-time neural activity. A linear mixed-effects model was applied to single trial event-related potentials for 207 visually presented concrete words measured on total number of features (semantic richness), imageability, and number of visual motion, color, visual form, smell, taste, sound, and function features. Significant influences of multiple feature types occurred before 200ms, suggesting parallel neural computation of word form and conceptual knowledge during language comprehension. Function and visual motion features most prominently influenced neural activity, underscoring the importance of action-related knowledge in computing word meaning. The dynamic time courses and topographies of these effects are most consistent with a flexible conceptual system wherein temporally dynamic recruitment of representations in modal and supramodal cortex are a crucial element of the constellation of processes constituting word meaning computation in the brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Bioethical pluralism and complementarity.

PubMed

Grinnell, Frederick; Bishop, Jeffrey P; McCullough, Laurence B

2002-01-01

This essay presents complementarity as a novel feature of bioethical pluralism. First introduced by Neils Bohr in conjunction with quantum physics, complementarity in bioethics occurs when different perspectives account for equally important features of a situation but are mutually exclusive. Unlike conventional approaches to bioethical pluralism, which attempt in one fashion or another to isolate and choose between different perspectives, complementarity accepts all perspectives. As a result, complementarity results in a state of holistic, dynamic tension, rather than one that yields singular or final moral judgments.

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

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

Soner Yorgun, M.; Rood, Richard B.

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

DOE PAGES

Soner Yorgun, M.; Rood, Richard B.

2016-11-11

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

An inverse dynamics approach to trajectory optimization and guidance for an aerospace plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

The optimal ascent problem for an aerospace planes is formulated as an optimal inverse dynamic problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the optimal trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suited for onboard implementation. Robust ascent guidance is obtained by using combination of feedback compensation and onboard generation of control through the inverse dynamics approach. Accurate orbital insertion can be achieved with near-optimal control of the rocket through inverse dynamics even in the presence of disturbances.

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

PubMed

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

2016-01-01

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

Modeling time-series count data: the unique challenges facing political communication studies.

PubMed

Fogarty, Brian J; Monogan, James E

2014-05-01

This paper demonstrates the importance of proper model specification when analyzing time-series count data in political communication studies. It is common for scholars of media and politics to investigate counts of coverage of an issue as it evolves over time. Many scholars rightly consider the issues of time dependence and dynamic causality to be the most important when crafting a model. However, to ignore the count features of the outcome variable overlooks an important feature of the data. This is particularly the case when modeling data with a low number of counts. In this paper, we argue that the Poisson autoregressive model (Brandt and Williams, 2001) accurately meets the needs of many media studies. We replicate the analyses of Flemming et al. (1997), Peake and Eshbaugh-Soha (2008), and Ura (2009) and demonstrate that models missing some of the assumptions of the Poisson autoregressive model often yield invalid inferences. We also demonstrate that the effect of any of these models can be illustrated dynamically with estimates of uncertainty through a simulation procedure. The paper concludes with implications of these findings for the practical researcher. Copyright © 2013 Elsevier Inc. All rights reserved.

First-principles molecular dynamics simulation study on electrolytes for use in redox flow battery

NASA Astrophysics Data System (ADS)

Choe, Yoong-Kee; Tsuchida, Eiji; Tokuda, Kazuya; Ootsuka, Jun; Saito, Yoshihiro; Masuno, Atsunobu; Inoue, Hiroyuki

2017-11-01

Results of first-principles molecular dynamics simulations carried out to investigate structural aspects of electrolytes for use in a redox flow battery are reported. The electrolytes studied here are aqueous sulfuric acid solutions where its property is of importance for dissolving redox couples in redox flow battery. The simulation results indicate that structural features of the acid solutions depend on the concentration of sulfuric acid. Such dependency arises from increase of proton dissociation from sulfuric acid.

Kinetic modeling of particle dynamics in H- negative ion sources (invited)

NASA Astrophysics Data System (ADS)

Hatayama, A.; Shibata, T.; Nishioka, S.; Ohta, M.; Yasumoto, M.; Nishida, K.; Yamamoto, T.; Miyamoto, K.; Fukano, A.; Mizuno, T.

2014-02-01

Progress in the kinetic modeling of particle dynamics in H- negative ion source plasmas and their comparisons with experiments are reviewed, and discussed with some new results. Main focus is placed on the following two topics, which are important for the research and development of large negative ion sources and high power H- ion beams: (i) Effects of non-equilibrium features of EEDF (electron energy distribution function) on H- production, and (ii) extraction physics of H- ions and beam optics.

The features of chlorophyll concentration long-standing dynamics in the ocean surface layer (comparison of czcs and seawifs data)

NASA Astrophysics Data System (ADS)

Shevyrnogov, A.; Vysotskaya, G.

To preserve biosphere and make its utilization expedient makes imperative to comprehend in depth long-standing dynamics of the primary production process on our planet. Variability of chlorophyll concentration in the ocean is one of the most important components of this process. However, hard access and large size of the water surface make its investigation labor-consuming. Besides, the dependence of primary production on high variability of hydrophysical phenomena in the ocean (fluctuations of currents, frontal zones, etc.) makes the location of points for measuring the chlorophyll concentration dynamics significant. In this work the long-standing changes in chlorophyll concentration in the surface layer of the ocean have been analyzed on the basis of the CZCS data for 7.5 years and the SeaWiFS data from 1997 to 2003. It was shown that the average chlorophyll concentration calculated at all investigated area is varied moderately. However when analyzing spatially local trends, it was detected that areas exist with stable rise and fall of chlorophyll concentration. Some interesting features of the long-standing dynamics of chlorophyll concentration several interesting features were found. There are the various directions of long-term trends (constant increase or decrease) that cannot be explained only by large-scale hydrological phenomena in the ocean (currents, upwellings etc.). The next feature is a difference between the trends revealed by using the CZCS data and the trends based on the SeaWiFS data. Thus, the obtained results allow the possibility of identification of the ocean biota role in the global biospheric gas exchange.

Variability of total ozone at Arosa, Switzerland, since 1931 related to atmospheric circulation indices

NASA Astrophysics Data System (ADS)

Brönnimann, S.; Luterbacher, J.; Schmutz, C.; Wanner, H.; Staehelin, J.

2000-08-01

Atmospheric circulation determines to a considerable extent the variability of lower stratospheric ozone and can modulate its long-term trends in Europe and the North Atlantic Region. Due to dynamical stratosphere-troposphere coupling, important features of the variability of the surface pressure field are reflected in the long-term total ozone record from Arosa, Switzerland. Significant (p<0.01) correlations between total ozone and different atmospheric circulation indices (NAOI, AOI, EU1, EU2) are found in all months except for April, June, July, and November for the period 1931 to 1997. An analysis of geopotential heights for the period 1958 to 1997 shows that these circulation anomaly patterns have upper tropospheric features over the North Atlantic-European sector that are consistent with a dynamical influence on total ozone.

Dynamics of Whistler-mode Waves Below LHR Frequency: Application for the Equatorial Noise

NASA Astrophysics Data System (ADS)

Balikhin, M. A.; Shklyar, D. R.

2017-12-01

Plasma waves that are regularly observed in the vicinity of geomagnetic equator since 1970's are often referred to as "equatorial noise" or "equatorial magnetosonic" emission. Currently, it is accepted that these waves can have significant effects on both the processes of loss and acceleration of energetic electrons within the radiation belts. A model to explain the observed features of the equatorial noise is presented. It is assumed that the loss-cone instability of supra-thermal ions is the reason for their generation. It is argued that as these waves propagate their growth/damping rate changes and, therefore the integral wave amplification is more important to explain observed spectral features than the local growth rate. The qualitative correspondence of Cluster observations with dynamical spectra arising from the model is shown.

The relations between inadequate parent-child boundaries and borderline personality disorder in adolescence.

PubMed

Vanwoerden, Salome; Kalpakci, Allison; Sharp, Carla

2017-11-01

Borderline Personality Disorder (BPD) is a severe mental illness that onsets in adolescence. Research has demonstrated the central role of parent-child relationships for the development and maintenance of BPD although more research is necessary to clarify the specific dynamics that relate to BPD during adolescence. Based on preliminary research establishing the importance of parent-child boundaries for adolescent BPD, this study sought to evaluate the relations between different forms of inadequate boundaries and BPD in adolescence using a multi-method approach. To that end, 301 adolescents (65.1% female; ages 12-17) inpatients were recruited; parents and adolescents completed questionnaire- and interview-based measures of BPD features in adolescent children and a questionnaire-based measure of parent-child boundaries. Relations were found between parental guilt induction and psychological control with children's BPD features above and beyond relations with psychiatric severity and gender. Relations between parent reports of triangulation (when children are recruited to mediate parental marital conflict) and children's BPD were contingent on the level of children's perceptions of triangulation. Findings confirm previous research suggesting the relevance of inadequate parent-child boundaries to children's BPD features and have important implications for understanding the dynamics in families with adolescents with BPD, representing a relevant treatment target. Copyright © 2017 Elsevier B.V. All rights reserved.

Subduction, Extension, and a Mantle Plume in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Hawley, W. B.; Allen, R. M.; Richards, M. A.

2016-12-01

Subduction zones are some of the most important systems that control the dynamics and evolution of the earth. The Cascadia Subduction Zone offers a unique natural laboratory for understanding the subduction process, and how subduction interacts with other large-scale geodynamical phenomena. The small size of the Juan de Fuca (JdF) plate and the proximity of the system to the Yellowstone Hotspot and the extensional Basin and Range province allow for detailed study of the effects these important systems have on each other. We present both a P-wave and an S-wave tomographic model of the Pacific Northwestern United States using regional seismic arrays, including the amphibious Cascadia Initiative. These models share important features, such as the Yellowstone plume, the subducting JdF slab, a gap in the subducting slab, and a low-velocity feature beneath the shallowest portions of the slab. But subtle differences in these features between the models—the size of the gap in the subducting JdF slab and the shape of the Yellowstone plume shaft above the transition zone, for example—provide physical insight into the interpretation of these models. The physics that we infer from our seismic tomography and other studies of the region will refine our understanding of subduction zones worldwide, and will help to identify targets for future amphibious seismic array studies. The discovery of a pronounced low-velocity feature beneath the JdF slab as it subducts beneath the coastal Pacific Northwest is, thus far, the most surprising result from our imaging work, and implies a heretofore unanticipated regime of dynamical interaction between the sublithospheric oceanic asthenosphere and the subduction process. Such discoveries are made possible, and rendered interpretable, by ever-increasing resolution that the Cascadia Initiative affords seismic tomography models.

Dynamics of atmospheres with a non-dilute condensible component

PubMed Central

Ding, Feng

2016-01-01

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

Dynamics of atmospheres with a non-dilute condensible component.

PubMed

Pierrehumbert, Raymond T; Ding, Feng

2016-06-01

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

Field migration rates of tidal meanders recapitulate fluvial morphodynamics

NASA Astrophysics Data System (ADS)

Finotello, Alvise; Lanzoni, Stefano; Ghinassi, Massimiliano; Marani, Marco; Rinaldo, Andrea; D'Alpaos, Andrea

2018-02-01

The majority of tidal channels display marked meandering features. Despite their importance in oil-reservoir formation and tidal landscape morphology, questions remain on whether tidal-meander dynamics could be understood in terms of fluvial processes and theory. Key differences suggest otherwise, like the periodic reversal of landscape-forming tidal flows and the widely accepted empirical notion that tidal meanders are stable landscape features, in stark contrast with their migrating fluvial counterparts. On the contrary, here we show that, once properly normalized, observed migration rates of tidal and fluvial meanders are remarkably similar. Key to normalization is the role of tidal channel width that responds to the strong spatial gradients of landscape-forming flow rates and tidal prisms. We find that migration dynamics of tidal meanders agree with nonlinear theories for river meander evolution. Our results challenge the conventional view of tidal channels as stable landscape features and suggest that meandering tidal channels recapitulate many fluvial counterparts owing to large gradients of tidal prisms across meander wavelengths.

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

PubMed

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

2016-11-01

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

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

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

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

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

A Unified Model of Geostrophic Adjustment and Frontogenesis

NASA Astrophysics Data System (ADS)

Taylor, John; Shakespeare, Callum

2013-11-01

Fronts, or regions with strong horizontal density gradients, are ubiquitous and dynamically important features of the ocean and atmosphere. In the ocean, fronts are associated with enhanced air-sea fluxes, turbulence, and biological productivity, while atmospheric fronts are associated with some of the most extreme weather events. Here, we describe a new mathematical framework for describing the formation of fronts, or frontogenesis. This framework unifies two classical problems in geophysical fluid dynamics, geostrophic adjustment and strain-driven frontogenesis, and provides a number of important extensions beyond previous efforts. The model solutions closely match numerical simulations during the early stages of frontogenesis, and provide a means to describe the development of turbulence at mature fronts.

Face processing in autism: Reduced integration of cross-feature dynamics.

PubMed

Shah, Punit; Bird, Geoffrey; Cook, Richard

2016-02-01

Characteristic problems with social interaction have prompted considerable interest in the face processing of individuals with Autism Spectrum Disorder (ASD). Studies suggest that reduced integration of information from disparate facial regions likely contributes to difficulties recognizing static faces in this population. Recent work also indicates that observers with ASD have problems using patterns of facial motion to judge identity and gender, and may be less able to derive global motion percepts. These findings raise the possibility that feature integration deficits also impact the perception of moving faces. To test this hypothesis, we examined whether observers with ASD exhibit susceptibility to a new dynamic face illusion, thought to index integration of moving facial features. When typical observers view eye-opening and -closing in the presence of asynchronous mouth-opening and -closing, the concurrent mouth movements induce a strong illusory slowing of the eye transitions. However, we find that observers with ASD are not susceptible to this illusion, suggestive of weaker integration of cross-feature dynamics. Nevertheless, observers with ASD and typical controls were equally able to detect the physical differences between comparison eye transitions. Importantly, this confirms that observers with ASD were able to fixate the eye-region, indicating that the striking group difference has a perceptual, not attentional origin. The clarity of the present results contrasts starkly with the modest effect sizes and equivocal findings seen throughout the literature on static face perception in ASD. We speculate that differences in the perception of facial motion may be a more reliable feature of this condition. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Issues related to the detection of boundaries

Treesearch

M.-J. Fortin; Olson; R.J.; S. Ferson; L. Iverson; C. Hunsaker; G. Edwards; D. Levine; K. Butera; V. Klemas; V. Klemas

2000-01-01

Ecotones are inherent features of landscapes, transitional zones, and play more than one functional role in ecosystem dynamics. The delineation of ecotones and environmental boundaries is therefore an important step in land-use management planning. The delineation of ecotones depends on the phenomenon of interest and the statistical methods used as well as the...

The Ties That Bind: How Social Capital Is Forged and Forfeited in Teacher Communities

ERIC Educational Resources Information Center

Bridwell-Mitchell, E. N.; Cooc, North

2016-01-01

The effects of social capital on school improvement make it important to understand how teachers forge, maintain, or forfeit collegial relationships. Two common explanations focused on formal organizational features and individual characteristics do not address how social capital accrues from informal dynamics of teachers' interactions in…

The Oral Accentuation of Greek.

ERIC Educational Resources Information Center

Allen, W. Sidney

1967-01-01

A brief review of theory and traditional approaches to the problem of oral reading of Greek dating from the fall of Constantinople (1453) focuses on the importance of two major linguistic features of Byzantine pronunciation. The first examines the nature of the dynamic (stress) accent and the second is concerned with differences in vowel lengths…

Southern Appalachian hillslope erosion rates measured by soil and detrital radiocarbon in hollows

Treesearch

T.C. Hales; K.M. Scharer; R.M. Wooten

2012-01-01

Understanding the dynamics of sediment generation and transport on hillslopes provides important constraints on the rate of sediment output from orogenic systems. Hillslope sediment fluxes are recorded by organic material found in the deposits infilling unchanneled convergent topographic features called hollows. This study describes the first hollow infilling rates...

Serendipity in Teaching and Learning: The Importance of Critical Moments

ERIC Educational Resources Information Center

Giordano, Peter J.

2010-01-01

Can professors, through their casual, random remarks to students, alter lives and transform identities? The answer, based on two exploratory studies described in this article, appears to be yes. Drawing from constructive-developmental ideas of student maturation and from features of chaos theory as applied to the complex dynamic system of…

Conclusions and recommendations: Exploration of the Saturn system

NASA Technical Reports Server (NTRS)

Hunten, D. M.

1978-01-01

Saturn missions have the following principal goals, in order of importance: (1) Intensive investigation of the atmosphere of Saturn; (2) determination of regional surface chemistry and properties of the surface features of satellites and properties of ring particles; (3) intensive investigation of Titan; and (4) atmospheric dynamics and structure of Saturn satellites and Saturn rings.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

PubMed

Andrabi, Munazah; Hutchins, Andrew Paul; Miranda-Saavedra, Diego; Kono, Hidetoshi; Nussinov, Ruth; Mizuguchi, Kenji; Ahmad, Shandar

2017-06-22

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

Natural and bio-inspired underwater adhesives: Current progress and new perspectives

NASA Astrophysics Data System (ADS)

Cui, Mengkui; Ren, Susu; Wei, Shicao; Sun, Chengjun; Zhong, Chao

2017-11-01

Many marine organisms harness diverse protein molecules as underwater adhesives to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Natural underwater adhesion phenomena thus provide inspiration for engineering adhesive materials that can perform in water or high-moisture settings for biomedical and industrial applications. Here we review examples of biological adhesives to show the molecular features of natural adhesives and discuss how such knowledge serves as a heuristic guideline for the rational design of biologically inspired underwater adhesives. In view of future bio-inspired research, we propose several potential opportunities, either in improving upon current L-3, 4-dihydroxyphenylalanine-based and coacervates-enabled adhesives with new features or engineering conceptually new types of adhesives that recapitulate important characteristics of biological adhesives. We underline the importance of viewing natural adhesives as dynamic materials, which owe their outstanding performance to the cellular coordination of protein expression, delivery, deposition, assembly, and curing of corresponding components with spatiotemporal control. We envision that the emerging synthetic biology techniques will provide great opportunities for advancing both fundamental and application aspects of underwater adhesives.

Complexity in neuronal noise depends on network interconnectivity.

PubMed

Serletis, Demitre; Zalay, Osbert C; Valiante, Taufik A; Bardakjian, Berj L; Carlen, Peter L

2011-06-01

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e., 1/f(γ) noise and correlation dimension) and found evidence for complexity in neuronal NLA, ranging from high- to low-complexity dynamics. Importantly, these high- and low-complexity signal features were largely dependent on gap junction and chemical synaptic transmission. Progressive neuronal isolation from the surrounding local network via gap junction blockade (abolishing gap junction-dependent spikelets) and then chemical synaptic blockade (abolishing excitatory and inhibitory post-synaptic potentials), or the reverse order of these treatments, resulted in emergence of high-complexity NLA dynamics. Restoring local network interconnectivity via blockade washout resulted in resolution to low-complexity behavior. These results suggest that the observed increase in background NLA complexity is the result of reduced network interconnectivity, thereby highlighting the potential importance of the NLA signal to the study of network state transitions arising in normal and abnormal brain dynamics (such as in epilepsy, for example).

Probabilistic assessment of dynamic system performance. Part 3

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

Belhadj, Mohamed

1993-01-01

Accurate prediction of dynamic system failure behavior can be important for the reliability and risk analyses of nuclear power plants, as well as for their backfitting to satisfy given constraints on overall system reliability, or optimization of system performance. Global analysis of dynamic systems through investigating the variations in the structure of the attractors of the system and the domains of attraction of these attractors as a function of the system parameters is also important for nuclear technology in order to understand the fault-tolerance as well as the safety margins of the system under consideration and to insure a safemore » operation of nuclear reactors. Such a global analysis would be particularly relevant to future reactors with inherent or passive safety features that are expected to rely on natural phenomena rather than active components to achieve and maintain safe shutdown. Conventionally, failure and global analysis of dynamic systems necessitate the utilization of different methodologies which have computational limitations on the system size that can be handled. Using a Chapman-Kolmogorov interpretation of system dynamics, a theoretical basis is developed that unifies these methodologies as special cases and which can be used for a comprehensive safety and reliability analysis of dynamic systems.« less

Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.

PubMed

Karamzadeh, Razieh; Karimi-Jafari, Mohammad Hossein; Sharifi-Zarchi, Ali; Chitsaz, Hamidreza; Salekdeh, Ghasem Hosseini; Moosavi-Movahedi, Ali Akbar

2017-06-16

The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences in dynamics of redox states are extracted by statistical machine learning methods. Mapping the structural variations to time series of residue interaction networks also provides a holistic representation of the dynamical redox differences. With emphasizing on persistent long-lasting interactions, an approach is proposed that compiled these time series networks to a single dynamic residue interaction network (DRIN). Differential comparison of DRIN in oxidized and reduced states reveals chains of residue interactions that represent potential allosteric paths between catalytic and ligand binding sites of hPDI.

Structure and dynamics of ionic micelles: MD simulation and neutron scattering study.

PubMed

Aoun, B; Sharma, V K; Pellegrini, E; Mitra, S; Johnson, M; Mukhopadhyay, R

2015-04-16

Fully atomistic molecular dynamics (MD) simulations have been carried out on sodium dodecyl sulfate (SDS), an anionic micelle, and three cationic (CnTAB; n = 12, 14, 16) micelles, investigating the effects of size, the form of the headgroup, and chain length. They have been used to analyze neutron scattering data. MD simulations confirm the dynamical model of global motion of the whole micelle, segmental motion (headgroup and alkyl chain), and fast torsional motion associated with the surfactants that is used to analyze the experimental data. It is found that the solvent surrounding the headgroups results in their significant mobility, which exceeds that of the tails on the nanosecond time scale. The middle of the chain is found to be least mobile, consolidating the micellar configuration. This dynamical feature is similar for all the ionic micelles investigated and therefore independent of headgroup form and charge and chain length. Diffusion constants for global and segmental motion of the different micelles are consistent with experimentally obtained values as well as known structural features. This work provides a more realistic model of micelle dynamics and offers new insight into the strongly fluctuating surface of micelles which is important in understanding micelle dispersion and related functionality, like drug delivery.

Ab initio calculation of the ion feature in x-ray Thomson scattering.

PubMed

Plagemann, Kai-Uwe; Rüter, Hannes R; Bornath, Thomas; Shihab, Mohammed; Desjarlais, Michael P; Fortmann, Carsten; Glenzer, Siegfried H; Redmer, Ronald

2015-07-01

The spectrum of x-ray Thomson scattering is proportional to the dynamic structure factor. An important contribution is the ion feature which describes elastic scattering of x rays off electrons. We apply an ab initio method for the calculation of the form factor of bound electrons, the slope of the screening cloud of free electrons, and the ion-ion structure factor in warm dense beryllium. With the presented method we can calculate the ion feature from first principles. These results will facilitate a better understanding of x-ray scattering in warm dense matter and an accurate measurement of ion temperatures which would allow determining nonequilibrium conditions, e.g., along shock propagation.

Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.

Analysis of spike-wave discharges in rats using discrete wavelet transform.

PubMed

Ubeyli, Elif Derya; Ilbay, Gül; Sahin, Deniz; Ateş, Nurbay

2009-03-01

A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records.

Application of interactive computer graphics in wind-tunnel dynamic model testing

NASA Technical Reports Server (NTRS)

Doggett, R. V., Jr.; Hammond, C. E.

1975-01-01

The computer-controlled data-acquisition system recently installed for use with a transonic dynamics tunnel was described. This includes a discussion of the hardware/software features of the system. A subcritical response damping technique, called the combined randomdec/moving-block method, for use in windtunnel-model flutter testing, that has been implemented on the data-acquisition system, is described in some detail. Some results using the method are presented and the importance of using interactive graphics in applying the technique in near real time during wind-tunnel test operations is discussed.

Pulsatile Hormonal Signaling to Extracellular Signal-regulated Kinase

PubMed Central

Perrett, Rebecca M.; Voliotis, Margaritis; Armstrong, Stephen P.; Fowkes, Robert C.; Pope, George R.; Tsaneva-Atanasova, Krasimira; McArdle, Craig A.

2014-01-01

Gonadotropin-releasing hormone (GnRH) is secreted in brief pulses that stimulate synthesis and secretion of pituitary gonadotropin hormones and thereby mediate control of reproduction. It acts via G-protein-coupled receptors to stimulate effectors, including ERK. Information could be encoded in GnRH pulse frequency, width, amplitude, or other features of pulse shape, but the relative importance of these features is unknown. Here we examine this using automated fluorescence microscopy and mathematical modeling, focusing on ERK signaling. The simplest scenario is one in which the system is linear, and response dynamics are relatively fast (compared with the signal dynamics). In this case integrated system output (ERK activation or ERK-driven transcription) will be roughly proportional to integrated input, but we find that this is not the case. Notably, we find that relatively slow response kinetics lead to ERK activity beyond the GnRH pulse, and this reduces sensitivity to pulse width. More generally, we show that the slowing of response kinetics through the signaling cascade creates a system that is robust to pulse width. We, therefore, show how various levels of response kinetics synergize to dictate system sensitivity to different features of pulsatile hormone input. We reveal the mathematical and biochemical basis of a dynamic GnRH signaling system that is robust to changes in pulse amplitude and width but is sensitive to changes in receptor occupancy and frequency, precisely the features that are tightly regulated and exploited to exert physiological control in vivo. PMID:24482225

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

Player guild dynamics and evolution in massively multiplayer online games.

PubMed

Chen, Chien-Hsun; Sun, Chuen-Tsai; Hsieh, Jilung

2008-06-01

In the latest versions of massively multiplayer online games (MMOGs), developers have purposefully made guilds part of game environments. Guilds represent a powerful method for giving players a sense of online community, but there is little quantitative data on guild dynamics. To address this topic, we took advantage of a feature found in one of today's most popular MMOGs (World of Warcraft) to collect in-game data: user interfaces that players can modify and refine. In addition to collecting data on in-game player activities, we used this feature to observe and investigate how players join and leave guilds. Data were analyzed for the purpose of identifying factors that propel game-world guild dynamics and evolution. After collecting data for 641,805 avatars on 62 Taiwanese World of Warcraft game servers between February 10 and April 10, 2006, we created five guild type categories (small, large, elite, newbie, and unstable) that have different meanings in terms of in-game group dynamics. By viewing players as the most important resource affecting guild life cycles, it is possible to analyze game worlds as ecosystems consisting of evolving guilds and to study how guild life cycles reflect game world characteristics.

Low-angle dunes in the Changjiang (Yangtze) Estuary: Flow and sediment dynamics under tidal influence

NASA Astrophysics Data System (ADS)

Hu, Hao; Wei, Taoyuan; Yang, Zhongyong; Hackney, Christopher R.; Parsons, Daniel R.

2018-05-01

It has long been highlighted that important feedbacks exist between river bed morphology, sediment transport and the turbulent flow field and that these feedbacks change in response to forcing mechanisms. However, our current understanding of bedform dynamics is largely based on studies of steady flow environments and cohesionless bed conditions. Few investigations have been made under rapidly changing flows. Here, we examine flow and sediment dynamics over low-angle dunes in unsteady flows in the Changjiang (Yangtze) Estuary, China. Topography, flow and sediment data were collected over a reach ca 1.8 km long through a semi-diurnal tidal cycle in a moderate tide of flood season. The results show that: (1) roughness length derived from the upper flow changes little with the flow reversing and displays the same value on both the ebb and flood tide. Moreover, the variability of individual bedform features plays an important role in roughness length variation. (2) Shear stress over the crest of low-angle dunes roughly represents the total spatially averaged stress over dunes in this study area, which has significant implications for advancing numerical models. (3) Changes in morphology, flow and sediment dynamics over dunes through time reveal how low-angle dunes evolve within a tidal cycle. (4) The clockwise hysteresis loops between flow dynamics and bedform features (height and aspect ratio) are also observed. The combination of suspended sediment transport and bedload transport on dune transformation and migration attributes to the clockwise hysteresis. The specific sediment composition of the riverbed, in some extent, affects the mechanism of sediment transport related to the exchange between suspended sediment and riverbed, but further investigation is needed to figure out the mechanism behind this for extended series of tides, such as spring/neap tide and tides in flooding and dry season.

Icy Moon Absorption Signatures: Probes of Saturnian Magnetospheric Dynamics and Moon Activity

NASA Astrophysics Data System (ADS)

Roussos, E.; Krupp, N.; Jones, G. H.; Paranicas, C.; Mitchell, D. G.; Krimigis, S. M.; Motschmann, U.; Dougherty, M. K.; Lagg, A.; Woch, J.

2006-12-01

After the first flybys at the outer planets by the Pioneer and Voyager probes, it became evident that energetic charged particle absorption features in the radiation belts are important tracers of magnetospheric dynamical features and parameters. Absorption signatures are especially important for characterizing the Saturnian magnetosphere. Due to the spin and magnetic axes' near-alignment, losses of particles to the icy moon surfaces and rings are higher compared to the losses at other planetary magnetospheres. The refilling rate of these absorption features (termed "micorsignatures") can be associated with particle diffusion. In addition, as these microsignatures drift with the properties of the pre-depletion electrons, they provide us direct information on the drift shell structure in the radiation belts and the factors that influence their shape. The multiple icy moon L-shell crossings by the Cassini spacecraft during the first 2 years of the mission provided us with almost 100 electron absorption events by eight different moons, at various longitudinal separations from each one and at various electron energies. Their analysis seems to give a consistent picture of the electron diffusion source and puts aside a lot of inconsistencies that resulted from relevant Pioneer and Voyager studies. The presence of non-axisymmetric particle drift shells even down to the orbit of Enceladus (3.98 Rs), also revealed through this analysis, suggests either large ring current disturbances or the action of global or localized electric fields. Finally, despite these absorption signatures being observed far from the originating moons, they can give us hints on the nature of the local interaction between each moon and the magnetospheric plasma. It is, nevertheless, beyond any doubt that energetic charged particle absorption signatures are a very powerful tool that can be used to effectively probe a series of dynamical processes in the Saturnian magnetosphere.

Single neuron computation: from dynamical system to feature detector.

PubMed

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

2007-12-01

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

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Effects of landscape features on the distribution and sustainability of ungulate hunting in northern Congo

Treesearch

Miranda H. Mockrin; Robert F. Rockwell; Kent H. Redford; Nicholas S. Keuler

2011-01-01

Understanding the spatial dimensions of hunting and prey population dynamics is important in order to estimate the sustainability of hunting in tropical forests. We investigated how hunting offtake of vertebrates differed in mixed forest and monodominant forest (composed of Gilbertiodendron dewevrei) and over different spatial extents within the hunting catchment...

The Importance of "What": Infants Use Featural Information to Index Events

ERIC Educational Resources Information Center

Kirkham, Natasha Z.; Richardson, Daniel C.; Wu, Rachel; Johnson, Scott P.

2012-01-01

Dynamic spatial indexing is the ability to encode, remember, and track the location of complex events. For example, in a previous study, 6-month-old infants were familiarized to a toy making a particular sound in a particular location, and later they fixated that empty location when they heard the sound presented alone ("Journal of Experimental…

Modeling asthma: Pitfalls, promises, and the road ahead.

PubMed

Rosenberg, Helene F; Druey, Kirk M

2018-02-16

Asthma is a chronic, heterogeneous, and recurring inflammatory disease of the lower airways, with exacerbations that feature airway inflammation and bronchial hyperresponsiveness. Asthma has been modeled extensively via disease induction in both wild-type and genetically manipulated laboratory mice (Mus musculus). Antigen sensitization and challenge strategies have reproduced numerous important features of airway inflammation characteristic of human asthma, notably the critical roles of type 2 T helper cell cytokines. Recent models of disease induction have advanced to include physiologic aeroallergens with prolonged respiratory challenge without systemic sensitization; others incorporate tobacco, respiratory viruses, or bacteria as exacerbants. Nonetheless, differences in lung size, structure, and physiologic responses limit the degree to which airway dynamics measured in mice can be compared to human subjects. Other rodent allergic airways models, including those featuring the guinea pig (Cavia porcellus) might be considered for lung function studies. Finally, domestic cats (Feline catus) and horses (Equus caballus) develop spontaneous obstructive airway disorders with clinical and pathologic features that parallel human asthma. Information on pathogenesis and treatment of these disorders is an important resource. ©2018 Society for Leukocyte Biology.

Incorporating heterogeneity into the transmission dynamics of a waterborne disease model.

PubMed

Collins, O C; Govinder, K S

2014-09-07

We formulate a mathematical model that captures the essential dynamics of waterborne disease transmission to study the effects of heterogeneity on the spread of the disease. The effects of heterogeneity on some important mathematical features of the model such as the basic reproduction number, type reproduction number and final outbreak size are analysed accordingly. We conduct a real-world application of this model by using it to investigate the heterogeneity in transmission in the recent cholera outbreak in Haiti. By evaluating the measure of heterogeneity between the administrative departments in Haiti, we discover a significant difference in the dynamics of the cholera outbreak between the departments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic stall reattachment revisited

NASA Astrophysics Data System (ADS)

Mulleners, Karen

2017-11-01

Dynamic stall on pitching airfoils is an important practical problem that affects for example rotary wing aircraft and wind turbines. It also comprises a number of interesting fundamental fluid dynamical phenomena such as unsteady flow separation, vortex formation and shedding, unsteady flow reattachment, and dynamic hysteresis. Following up on past efforts focussing on the separation development, we now revisited the flow reattachment or stall recovery process. Experimental time-resolved velocity field and surface pressure data for a two-dimensional sinusoidally pitching airfoil with various reduced frequencies was analysed using different Eulerian, Lagrangian, and modal decomposition methods. This complementary analysis resulted in the identification of the chain of events that play a role in the flow reattachment process, a detailed description of that role, and characterisation of the individual events by the governing time-scales and flow features.

Predicting couple therapy outcomes based on speech acoustic features

PubMed Central

Nasir, Md; Baucom, Brian Robert; Narayanan, Shrikanth

2017-01-01

Automated assessment and prediction of marital outcome in couples therapy is a challenging task but promises to be a potentially useful tool for clinical psychologists. Computational approaches for inferring therapy outcomes using observable behavioral information obtained from conversations between spouses offer objective means for understanding relationship dynamics. In this work, we explore whether the acoustics of the spoken interactions of clinically distressed spouses provide information towards assessment of therapy outcomes. The therapy outcome prediction task in this work includes detecting whether there was a relationship improvement or not (posed as a binary classification) as well as discerning varying levels of improvement or decline in the relationship status (posed as a multiclass recognition task). We use each interlocutor’s acoustic speech signal characteristics such as vocal intonation and intensity, both independently and in relation to one another, as cues for predicting the therapy outcome. We also compare prediction performance with one obtained via standardized behavioral codes characterizing the relationship dynamics provided by human experts as features for automated classification. Our experiments, using data from a longitudinal clinical study of couples in distressed relations, showed that predictions of relationship outcomes obtained directly from vocal acoustics are comparable or superior to those obtained using human-rated behavioral codes as prediction features. In addition, combining direct signal-derived features with manually coded behavioral features improved the prediction performance in most cases, indicating the complementarity of relevant information captured by humans and machine algorithms. Additionally, considering the vocal properties of the interlocutors in relation to one another, rather than in isolation, showed to be important for improving the automatic prediction. This finding supports the notion that behavioral outcome, like many other behavioral aspects, is closely related to the dynamics and mutual influence of the interlocutors during their interaction and their resulting behavioral patterns. PMID:28934302

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

Emergence of Rich-Club Topology and Coordinated Dynamics in Development of Hippocampal Functional Networks In Vitro

PubMed Central

Charlesworth, Paul; Kitzbichler, Manfred G.; Paulsen, Ole

2015-01-01

Recent studies demonstrated that the anatomical network of the human brain shows a “rich-club” organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called “hub neurons”). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a “rich-get-richer” growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

FIR signature verification system characterizing dynamics of handwriting features

NASA Astrophysics Data System (ADS)

Thumwarin, Pitak; Pernwong, Jitawat; Matsuura, Takenobu

2013-12-01

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

Influence of High Energy Electromagnetic Pulses on the Dynamics of the Seismic Process Around the Bishkek Test Area (Central Asia)

NASA Astrophysics Data System (ADS)

Matcharashvili, Teimuraz N.; Chelidze, Tamaz L.; Zhukova, Natalia N.

2015-07-01

Investigation of dynamical features of the seismic process as well as the possible influence of different natural and man-made impacts on it remains one of the main interdisciplinary research challenges. The question of external influences (forcings) acquires new importance in the light of known facts on possible essential changes, which occur in the behavior of complex systems due to different relatively weak external impacts. Seismic processes in the complicated tectonic system are not an exclusion from this general rule. In the present research we continued the investigation of dynamical features of seismic activity in Central Asia around the Bishkek (Kyrgyzstan) test area, where strong electromagnetic (EM) soundings were performed in the 1980s. The unexpected result of these experiments was that they revealed the impact of strong electromagnetic discharges on the microseismic activity of investigated area. We used an earthquake catalogue of this area to investigate dynamical features of seismic activity in periods before, during, and after the mentioned man-made EM forcings. Different methods of modern time series analysis have been used, such as wavelet transformation, Hilbert Huang transformation, detrended fluctuation analysis, and recurrence quantification analysis. Namely, inter-event (waiting) time intervals, inter-earthquake distances and magnitude sequences, as well as time series of the number of daily occurring earthquakes have been analyzed. We concluded that man-made high-energy EM irradiation essentially affects dynamics of the seismic process in the investigated area in its temporal and spatial domains; namely, the extent of order in earthquake time and space distribution increase. At the same time, EM influence on the energetic distribution is not clear from the present analysis. It was also shown that the influence of EM impulses on dynamical features of seismicity differs in different areas of the examined territory around the test site. Clear changes have been indicated only in areas which, according to previous researches, have been characterized by anomalous increase of average rates of strain release and thus can be regarded as close to the critical state.

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

PubMed Central

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

2016-01-01

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

A Nonlinear Dynamic Subscale Model for Partially Resolved Numerical Simulation (PRNS)/Very Large Eddy Simulation (VLES) of Internal Non-Reacting Flows

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing; Liu, nan-Suey

2010-01-01

A brief introduction of the temporal filter based partially resolved numerical simulation/very large eddy simulation approach (PRNS/VLES) and its distinct features are presented. A nonlinear dynamic subscale model and its advantages over the linear subscale eddy viscosity model are described. In addition, a guideline for conducting a PRNS/VLES simulation is provided. Results are presented for three turbulent internal flows. The first one is the turbulent pipe flow at low and high Reynolds numbers to illustrate the basic features of PRNS/VLES; the second one is the swirling turbulent flow in a LM6000 single injector to further demonstrate the differences in the calculated flow fields resulting from the nonlinear model versus the pure eddy viscosity model; the third one is a more complex turbulent flow generated in a single-element lean direct injection (LDI) combustor, the calculated result has demonstrated that the current PRNS/VLES approach is capable of capturing the dynamically important, unsteady turbulent structures while using a relatively coarse grid.

Influence of composition fluctuations on the linear viscoelastic properties of symmetric diblock copolymers near the order-disorder transition

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

Hickey, Robert J.; Gillard, Timothy M.; Lodge, Timothy P.

2015-08-28

Rheological evidence of composition fluctuations in disordered diblock copolymers near the order disorder transition (ODT) has been documented in the literature over the past three decades, characterized by a failure of time–temperature superposition (tTS) to reduce linear dynamic mechanical spectroscopy (DMS) data in the terminal viscoelastic regime to a temperature-independent form. However, for some materials, most notably poly(styrene-b-isoprene) (PS–PI), no signature of these rheological features has been found. We present small-angle X-ray scattering (SAXS) results on symmetric poly(cyclohexylethylene-b-ethylene) (PCHE–PE) diblock copolymers that confirm the presence of fluctuations in the disordered state and DMS measurements that also show no sign ofmore » the features ascribed to composition fluctuations. Assessment of DMS results published on five different diblock copolymer systems leads us to conclude that the effects of composition fluctuations can be masked by highly asymmetric block dynamics, thereby resolving a long-standing disagreement in the literature and reinforcing the importance of mechanical contrast in understanding the dynamics of ordered and disordered block polymers.« less

Short-term climate variability and atmospheric teleconnections from satellite-observed outgoing longwave radiation. I Simultaneous relationships. II - Lagged correlations

NASA Technical Reports Server (NTRS)

Lau, K.-M.; Chan, P. H.

1983-01-01

Attention is given to the low-frequency variability of outgoing longwave radiation (OLR) fluctuations, their possible correlations over different parts of the globe, and their relationships with teleconnections obtained from other meteorological parameters, for example, geopotential and temperature fields. Simultaneous relationships with respect to the Southern Oscillation (Namais, 1978; Barnett, 1981) signal and the reference OLR fluctuation over the equatorial central Pacific are investigated. Emphasis is placed on the relative importance of the Southern Oscillation (SO) signal over preferred regions. Using lag cross-correlation statistics, possible lagged relationships between the tropics and midlatitudes and their relationships with the SO are then investigated. Only features that are consistent with present knowledge of the dynamics of the system are emphasized. Certain features which may not meet rigorous statistical significance tests but yet are either expected a priori from independent observations or are predicted from dynamical theories are also explored.

Test Activities in the Langley Transonic Dynamics Tunnel and a Summary of Recent Facility Improvements

NASA Technical Reports Server (NTRS)

Cole, Stanley R.; Johnson, R. Keith; Piatak, David J.; Florance, Jennifer P.; Rivera, Jose A., Jr.

2003-01-01

The Langley Transonic Dynamics Tunnel (TDT) has provided a unique capability for aeroelastic testing for over forty years. The facility has a rich history of significant contributions to the design of many United States commercial transports, military aircraft, launch vehicles, and spacecraft. The facility has many features that contribute to its uniqueness for aeroelasticity testing, perhaps the most important feature being the use of a heavy gas test medium to achieve higher test densities compared to testing in air. Higher test medium densities substantially improve model-building requirements and therefore simplify the fabrication process for building aeroelastically scaled wind tunnel models. This paper describes TDT capabilities that make it particularly suited for aeroelasticity testing. The paper also discusses the nature of recent test activities in the TDT, including summaries of several specific tests. Finally, the paper documents recent facility improvement projects and the continuous statistical quality assessment effort for the TDT.

Multiple visions of Indonesia's mud volcano: understanding representations of disaster across discursive settings.

PubMed

Drake, Phillip

2016-04-01

The Lapindo mudflow is one of the most controversial disasters in Indonesian history. Despite its unique biophysical features, most consider the mudflow a social disaster as scientific conflicts about its main trigger have evolved into legal disputes over accountability and rights. This paper examines this 'trigger debate', the stakes of scientific contention and the broader social and natural dynamics that shape the terms of this debate. A Latourian impulse drives this analysis, which aims to improve both understandings of--and responses to--complex disasters. This paper also notes that the stakes of representation extend to constructions of its stakeholders, especially to victims. As socionatural disasters become an increasingly common feature of the contemporary world, from mud volcanoes to extreme weather events caused by global warming, it is more important than ever to understand the dynamics of representing disasters and stakeholders. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

Past, Present, and Future Capabilities of the Transonic Dynamics Tunnel from an Aeroelasticity Perspective

NASA Technical Reports Server (NTRS)

Cole, Stanley R.; Garcia, Jerry L.

2000-01-01

The NASA Langley Transonic Dynamics Tunnel (TDT) has provided a unique capability for aeroelastic testing for forty years. The facility has a rich history of significant contributions to the design of many United States commercial transports, military aircraft, launch vehicles, and spacecraft. The facility has many features that contribute to its uniqueness for aeroelasticity testing, perhaps the most important feature being the use of a heavy gas test medium to achieve higher test densities. Higher test medium densities substantially improve model-building requirements and therefore simplify the fabrication process for building aeroelastically scaled wind tunnel models. Aeroelastic scaling for the heavy gas results in lower model structural frequencies. Lower model frequencies tend to a make aeroelastic testing safer. This paper will describe major developments in the testing capabilities at the TDT throughout its history, the current status of the facility, and planned additions and improvements to its capabilities in the near future.

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

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

Pu, Hung-Yi; Asada, Keiichi; Akiyama, Kazunori

A radiatively inefficient accretion flow (RIAF), which is commonly characterized by its sub-Keplerian nature, is a favored accretion model for the supermassive black hole at the Galactic center, Sagittarius A*. To investigate the observable features of an RIAF, we compare the modeled shadow images, visibilities, and spectra of three flow models with dynamics characterized by (i) a Keplerian shell that is rigidly rotating outside the innermost stable circular orbit (ISCO) and infalling with a constant angular momentum inside ISCO, (ii) a sub-Keplerian motion, and (iii) a free-falling motion with zero angular momentum at infinity. At near-millimeter wavelengths, the emission ismore » dominated by the flow within several Schwarzschild radii. The energy shift due to these flow dynamics becomes important and distinguishable, suggesting that the flow dynamics are an important model parameter for interpreting the millimeter/sub-millimeter very long baseline interferometric observations with the forthcoming, fully assembled Event Horizon Telescope (EHT). As an example, we demonstrate that structural variations of Sagittarius A* on event horizon-scales detected in previous EHT observations can be explained by the non-stationary dynamics of an RIAF.« less

Dynamic trapping of a polarization rotation vector soliton in a fiber laser.

PubMed

Liu, Meng; Luo, Ai-Ping; Luo, Zhi-Chao; Xu, Wen-Cheng

2017-01-15

Ultrafast fiber laser, as a dissipative nonlinear optical system, plays an important role in investigating various nonlinear phenomena and soliton dynamics. Vector features of solitons, including polarization locked and polarization rotation vector solitons (PRVSs), are interesting nonlinear dynamics in ultrafast fiber lasers. Herein, we experimentally reveal the trapping characteristics of PRVSs for the first time, to the best of our best knowledge. We show that, for the conventional soliton trapping in the ultrafast fiber laser, the soliton central wavelengths of the two polarization components are constant at the laser output port. However, it is found that the dynamic trapping can be observed for the PRVS. That is, the peak frequencies along the two orthogonal polarization directions are dynamically alternating, depending on the relative intensities of the two polarization components. The obtained results would further unveil the physical mechanism of PRVSs.

Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

NASA Astrophysics Data System (ADS)

Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

2015-06-01

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

Multiple objects tracking in fluorescence microscopy.

PubMed

Kalaidzidis, Yannis

2009-01-01

Many processes in cell biology are connected to the movement of compact entities: intracellular vesicles and even single molecules. The tracking of individual objects is important for understanding cellular dynamics. Here we describe the tracking algorithms which have been developed in the non-biological fields and successfully applied to object detection and tracking in biological applications. The characteristics features of the different algorithms are compared.

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

PubMed

Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R

2006-02-01

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.

Dynamic compressive properties of bovine knee layered tissue

NASA Astrophysics Data System (ADS)

Nishida, Masahiro; Hino, Yuki; Todo, Mitsugu

2015-09-01

In Japan, the most common articular disease is knee osteoarthritis. Among many treatment methodologies, tissue engineering and regenerative medicine have recently received a lot of attention. In this field, cells and scaffolds are important, both ex vivo and in vivo. From the viewpoint of effective treatment, in addition to histological features, the compatibility of mechanical properties is also important. In this study, the dynamic and static compressive properties of bovine articular cartilage-cancellous bone layered tissue were measured using a universal testing machine and a split Hopkinson pressure bar method. The compressive behaviors of bovine articular cartilage-cancellous bone layered tissue were examined. The effects of strain rate on the maximum stress and the slope of stress-strain curves of the bovine articular cartilage-cancellous bone layered tissue were discussed.

Modeling and Optimization for Management of Intermittent Water Supply

NASA Astrophysics Data System (ADS)

Lieb, A. M.; Wilkening, J.; Rycroft, C.

2014-12-01

In many urban areas, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at controlling valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Gradient-based optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability at system endpoints.

Parametric study of laminated composite material shaft of high speed rotor-bearing system

NASA Astrophysics Data System (ADS)

Gonsalves, Thimothy Harold; Kumar, G. C. Mohan; Ramesh, M. R.

2018-04-01

In this paper some of the important parameters that influence the effectiveness of composite material shaft of high speed rotor-bearing system on rotor dynamics are analyzed. The type of composite material composition, the number of layers along with their stacking sequences are evaluated as they play an important role in deciding the best configuration suitable for the high-speed application. In this work the lateral modal frequencies for five types of composite materials shaft of a high-speed power turbine rotor-bearing system and stresses due to operating torque are evaluated. The results are useful for the selection of right combination of material, number of layers and their stacking sequences. The numerical analysis is carried out using the ANSYS Rotor dynamic analysis features.

Optical polarimetry and molecular line studies of L1157 dark molecular cloud

NASA Astrophysics Data System (ADS)

Sharma, Ekta; Soam, Archana; Gopinathan, Maheswar

2018-04-01

Filaments are omnipresent in molecular clouds which are believed to fragment into cores. The detailed process of the evolution from filaments to cores depends critically on the physical conditions in the star forming region. This study aims at characterising gas motions using velocity structure and finding the dynamical importance of magnetic fields in the filament morphology. The plane-of-the-sky component of the magnetic field has been measured using optical polarization of the background stars. The orientation is found to be almost perpendicular to the filament implying its dynamical importance in the evolution of the cloud. Optical polarimetric results match very well with the sub millimetre polarization angles obtained in the inner core regions. The magnetic fields are found to have an orientation of 130° east with respect to north. The angular offset between the outflow axis and the magnetic field direction is found to be 25°. Values for parameters like the excitation temperature, optical depth and column densities have been derived using molecular lines. Optically thick lines show non-gaussian features. The non-thermal widths tell about the presence of turbulent motions whereas the C180 lines follow Gaussian features almost at all the locations observed in the filament.

Adaptive measurements of urban runoff quality

NASA Astrophysics Data System (ADS)

Wong, Brandon P.; Kerkez, Branko

2016-11-01

An approach to adaptively measure runoff water quality dynamics is introduced, focusing specifically on characterizing the timing and magnitude of urban pollutographs. Rather than relying on a static schedule or flow-weighted sampling, which can miss important water quality dynamics if parameterized inadequately, novel Internet-enabled sensor nodes are used to autonomously adapt their measurement frequency to real-time weather forecasts and hydrologic conditions. This dynamic approach has the potential to significantly improve the use of constrained experimental resources, such as automated grab samplers, which continue to provide a strong alternative to sampling water quality dynamics when in situ sensors are not available. Compared to conventional flow-weighted or time-weighted sampling schemes, which rely on preset thresholds, a major benefit of the approach is the ability to dynamically adapt to features of an underlying hydrologic signal. A 28 km2 urban watershed was studied to characterize concentrations of total suspended solids (TSS) and total phosphorus. Water quality samples were autonomously triggered in response to features in the underlying hydrograph and real-time weather forecasts. The study watershed did not exhibit a strong first flush and intraevent concentration variability was driven by flow acceleration, wherein the largest loadings of TSS and total phosphorus corresponded with the steepest rising limbs of the storm hydrograph. The scalability of the proposed method is discussed in the context of larger sensor network deployments, as well the potential to improving control of urban water quality.

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

PubMed Central

Song, Le; Epps, Julien

2007-01-01

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

Composite quantum collision models

NASA Astrophysics Data System (ADS)

Lorenzo, Salvatore; Ciccarello, Francesco; Palma, G. Massimo

2017-09-01

A collision model (CM) is a framework to describe open quantum dynamics. In its memoryless version, it models the reservoir R as consisting of a large collection of elementary ancillas: the dynamics of the open system S results from successive collisions of S with the ancillas of R . Here, we present a general formulation of memoryless composite CMs, where S is partitioned into the very open system under study S coupled to one or more auxiliary systems {Si} . Their composite dynamics occurs through internal S -{Si} collisions interspersed with external ones involving {Si} and the reservoir R . We show that important known instances of quantum non-Markovian dynamics of S —such as the emission of an atom into a reservoir featuring a Lorentzian, or multi-Lorentzian, spectral density or a qubit subject to random telegraph noise—can be mapped on to such memoryless composite CMs.

No question about exciting questions in cell biology.

PubMed

Pollard, Thomas D

2013-12-01

Although we have a good grasp of many important processes in cell biology, including knowledge of many molecules involved and how they interact with each other, we still do not understand most of the dynamical features that are the essence of living systems. Fortunately, we now have the ability to dissect biological systems in enough detail to understand their dynamics, including the use of mathematical models to account for past observations and predict future experiments. This deep level of mechanistic understanding should be our goal—not simply to satisfy our scientific curiosity, but also to understand the causes of disease well enough to predict risks, make early diagnoses, and treat effectively. Many big questions remain to be answered before we reach this goal of understanding cellular dynamics.

Patient-specific CFD simulation of intraventricular haemodynamics based on 3D ultrasound imaging.

PubMed

Bavo, A M; Pouch, A M; Degroote, J; Vierendeels, J; Gorman, J H; Gorman, R C; Segers, P

2016-09-09

The goal of this paper is to present a computational fluid dynamic (CFD) model with moving boundaries to study the intraventricular flows in a patient-specific framework. Starting from the segmentation of real-time transesophageal echocardiographic images, a CFD model including the complete left ventricle and the moving 3D mitral valve was realized. Their motion, known as a function of time from the segmented ultrasound images, was imposed as a boundary condition in an Arbitrary Lagrangian-Eulerian framework. The model allowed for a realistic description of the displacement of the structures of interest and for an effective analysis of the intraventricular flows throughout the cardiac cycle. The model provides detailed intraventricular flow features, and highlights the importance of the 3D valve apparatus for the vortex dynamics and apical flow. The proposed method could describe the haemodynamics of the left ventricle during the cardiac cycle. The methodology might therefore be of particular importance in patient treatment planning to assess the impact of mitral valve treatment on intraventricular flow dynamics.

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations.

PubMed

Deng, Lu; Du, Jincheng

2018-01-14

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Q n distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3 B and 4 B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Deng, Lu; Du, Jincheng

2018-01-01

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Qn distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3B and 4B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Complex collective dynamics of active torque-driven colloids at interfaces

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

Snezhko, Alexey

Modern self-assembly techniques aiming to produce complex structural order or functional diversity often rely on non-equilibrium conditions in the system. Light, electric, or magnetic fields are predominantly used to modify interaction profiles of colloidal particles during self-assembly or induce complex out-of-equilibrium dynamic ordering. The energy injection rate, properties of the environment are important control parameters that influence the outcome of active (dynamic) self-assembly. The current review is focused on a case of collective dynamics and self-assembly of particles with externally driven torques coupled to a liquid or solid interface. The complexity of interactions in such systems is further enriched bymore » strong hydrodynamic coupling between particles. Unconventionally ordered dynamic self-assembled patterns, spontaneous symmetry breaking phenomena, self-propulsion, and collective transport have been reported in torque-driven colloids. Some of the features of the complex collective behavior and dynamic pattern formation in those active systems have been successfully captured in simulations.« less

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

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

PubMed

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

2016-04-01

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

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

Tom, N.; Lawson, M.; Yu, Y. H.

WEC-Sim is a midfidelity numerical tool for modeling wave energy conversion devices. The code uses the MATLAB SimMechanics package to solve multibody dynamics and models wave interactions using hydrodynamic coefficients derived from frequency-domain boundary-element methods. This paper presents the new modeling features introduced in the latest release of WEC-Sim. The first feature discussed conversion of the fluid memory kernel to a state-space form. This enhancement offers a substantial computational benefit after the hydrodynamic body-to-body coefficients are introduced and the number of interactions increases exponentially with each additional body. Additional features include the ability to calculate the wave-excitation forces based onmore » the instantaneous incident wave angle, allowing the device to weathervane, as well as import a user-defined wave elevation time series. A review of the hydrodynamic theory for each feature is provided and the successful implementation is verified using test cases.« less

A Human-Autonomy Teaming Approach for a Flight-Following Task

NASA Technical Reports Server (NTRS)

Brandt, Summer L.; Lachter, Joel; Russell, Ricky; Shively, R. Jay

2017-01-01

Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human autonomy teaming (HAT) in aviation, a study was conducted to evaluate proposed tenets of HAT. Participants performed a flight-following task at a ground station both with and without HAT features enabled. Overall, participants preferred the ground station with HAT features enabled over the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task, reduced the necessary workload and were efficient. Overall, there was general agreement that HAT features supported teaming with the automation. These results will be used to refine and expand our proposed framework for human-autonomy teaming.

A Framework for Speech Activity Detection Using Adaptive Auditory Receptive Fields.

PubMed

Carlin, Michael A; Elhilali, Mounya

2015-12-01

One of the hallmarks of sound processing in the brain is the ability of the nervous system to adapt to changing behavioral demands and surrounding soundscapes. It can dynamically shift sensory and cognitive resources to focus on relevant sounds. Neurophysiological studies indicate that this ability is supported by adaptively retuning the shapes of cortical spectro-temporal receptive fields (STRFs) to enhance features of target sounds while suppressing those of task-irrelevant distractors. Because an important component of human communication is the ability of a listener to dynamically track speech in noisy environments, the solution obtained by auditory neurophysiology implies a useful adaptation strategy for speech activity detection (SAD). SAD is an important first step in a number of automated speech processing systems, and performance is often reduced in highly noisy environments. In this paper, we describe how task-driven adaptation is induced in an ensemble of neurophysiological STRFs, and show how speech-adapted STRFs reorient themselves to enhance spectro-temporal modulations of speech while suppressing those associated with a variety of nonspeech sounds. We then show how an adapted ensemble of STRFs can better detect speech in unseen noisy environments compared to an unadapted ensemble and a noise-robust baseline. Finally, we use a stimulus reconstruction task to demonstrate how the adapted STRF ensemble better captures the spectrotemporal modulations of attended speech in clean and noisy conditions. Our results suggest that a biologically plausible adaptation framework can be applied to speech processing systems to dynamically adapt feature representations for improving noise robustness.

Residual perception of biological motion in cortical blindness.

PubMed

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

2016-12-01

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

Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro.

PubMed

Schroeter, Manuel S; Charlesworth, Paul; Kitzbichler, Manfred G; Paulsen, Ole; Bullmore, Edward T

2015-04-08

Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. Copyright © 2015 the authors 0270-6474/15/355459-12$15.00/0.

Social class variation in risk: a comparative analysis of the dynamics of economic vulnerability.

PubMed

Whelan, Christopher T; Maître, Bertrand

2008-12-01

A joint concern with multidimensionality and dynamics is a defining feature of the pervasive use of the terminology of social exclusion in the European Union. The notion of social exclusion focuses attention on economic vulnerability in the sense of exposure to risk and uncertainty. Sociological concern with these issues has been associated with the thesis that risk and uncertainty have become more pervasive and extend substantially beyond the working class. This paper combines features of recent approaches to statistical modelling of poverty dynamics and multidimensional deprivation in order to develop our understanding of the dynamics of economic vulnerability. An analysis involving nine countries and covering the first five waves of the European Community Household Panel shows that, across nations and time, it is possible to identify an economically vulnerable class. This class is characterized by heightened risk of falling below a critical resource level, exposure to material deprivation and experience of subjective economic stress. Cross-national differentials in persistence of vulnerability are wider than in the case of income poverty and less affected by measurement error. Economic vulnerability profiles vary across welfare regimes in a manner broadly consistent with our expectations. Variation in the impact of social class within and across countries provides no support for the argument that its role in structuring such risk has become much less important. Our findings suggest that it is possible to accept the importance of the emergence of new forms of social risk and acknowledge the significance of efforts to develop welfare states policies involving a shift of opportunities and decision making on to individuals without accepting the 'death of social class' thesis.

Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

PubMed

Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

2013-06-01

Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

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

Wang, Shaobu; Lu, Shuai; Zhou, Ning

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

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

PubMed Central

McElree, Brian; Carrasco, Marisa

2012-01-01

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

A Space Affine Matching Approach to fMRI Time Series Analysis.

PubMed

Chen, Liang; Zhang, Weishi; Liu, Hongbo; Feng, Shigang; Chen, C L Philip; Wang, Huili

2016-07-01

For fMRI time series analysis, an important challenge is to overcome the potential delay between hemodynamic response signal and cognitive stimuli signal, namely the same frequency but different phase (SFDP) problem. In this paper, a novel space affine matching feature is presented by introducing the time domain and frequency domain features. The time domain feature is used to discern different stimuli, while the frequency domain feature to eliminate the delay. And then we propose a space affine matching (SAM) algorithm to match fMRI time series by our affine feature, in which a normal vector is estimated using gradient descent to explore the time series matching optimally. The experimental results illustrate that the SAM algorithm is insensitive to the delay between the hemodynamic response signal and the cognitive stimuli signal. Our approach significantly outperforms GLM method while there exists the delay. The approach can help us solve the SFDP problem in fMRI time series matching and thus of great promise to reveal brain dynamics.

Dynamical scattering in coherent hard x-ray nanobeam Bragg diffraction

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

PubMed

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

2017-12-01

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

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

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

Diffraction of SH-waves by topographic features in a layered transversely isotropic half-space

NASA Astrophysics Data System (ADS)

Ba, Zhenning; Liang, Jianwen; Zhang, Yanju

2017-01-01

The scattering of plane SH-waves by topographic features in a layered transversely isotropic (TI) half-space is investigated by using an indirect boundary element method (IBEM). Firstly, the anti-plane dynamic stiffness matrix of the layered TI half-space is established and the free fields are solved by using the direct stiffness method. Then, Green's functions are derived for uniformly distributed loads acting on an inclined line in a layered TI half-space and the scattered fields are constructed with the deduced Green's functions. Finally, the free fields are added to the scattered ones to obtain the global dynamic responses. The method is verified by comparing results with the published isotropic ones. Both the steady-state and transient dynamic responses are evaluated and discussed. Numerical results in the frequency domain show that surface motions for the TI media can be significantly different from those for the isotropic case, which are strongly dependent on the anisotropy property, incident angle and incident frequency. Results in the time domain show that the material anisotropy has important effects on the maximum duration and maximum amplitudes of the time histories.

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

Coupling population dynamics with earth system models: the POPEM model.

PubMed

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

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

NASA Astrophysics Data System (ADS)

Kim, Minsu; Or, Dani

2017-12-01

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

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging.

PubMed

Feng, Wei; Zhang, Fumin; Wang, Weijing; Xing, Wei; Qu, Xinghua

2017-05-01

In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

Active site dynamics of ribonuclease.

PubMed Central

Brünger, A T; Brooks, C L; Karplus, M

1985-01-01

The stochastic boundary molecular dynamics method is used to study the structure, dynamics, and energetics of the solvated active site of bovine pancreatic ribonuclease A. Simulations of the native enzyme and of the enzyme complexed with the dinucleotide substrate CpA and the transition-state analog uridine vanadate are compared. Structural features and dynamical couplings for ribonuclease residues found in the simulation are consistent with experimental data. Water molecules, most of which are not observed in crystallographic studies, are shown to play an important role in the active site. Hydrogen bonding of residues with water molecules in the free enzyme is found to mimic the substrate-enzyme interactions of residues involved in binding. Networks of water stabilize the cluster of positively charged active site residues. Correlated fluctuations between the uridine vanadate complex and the distant lysine residues are mediated through water and may indicate a possible role for these residues in stabilizing the transition state. Images PMID:3866234

Detecting dynamical changes in time series by using the Jensen Shannon divergence

NASA Astrophysics Data System (ADS)

Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

2017-08-01

Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.

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

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

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

The significance of the amorphous potential energy landscape for dictating glassy dynamics and driving solid-state crystallisation.

PubMed

Ruggiero, Michael T; Krynski, Marcin; Kissi, Eric Ofosu; Sibik, Juraj; Markl, Daniel; Tan, Nicholas Y; Arslanov, Denis; van der Zande, Wim; Redlich, Britta; Korter, Timothy M; Grohganz, Holger; Löbmann, Korbinian; Rades, Thomas; Elliott, Stephen R; Zeitler, J Axel

2017-11-15

The fundamental origins surrounding the dynamics of disordered solids near their characteristic glass transitions continue to be fiercely debated, even though a vast number of materials can form amorphous solids, including small-molecule organic, inorganic, covalent, metallic, and even large biological systems. The glass-transition temperature, T g , can be readily detected by a diverse set of techniques, but given that these measurement modalities probe vastly different processes, there has been significant debate regarding the question of why T g can be detected across all of them. Here we show clear experimental and computational evidence in support of a theory that proposes that the shape and structure of the potential-energy surface (PES) is the fundamental factor underlying the glass-transition processes, regardless of the frequency that experimental methods probe. Whilst this has been proposed previously, we demonstrate, using ab initio molecular-dynamics (AIMD) simulations, that it is of critical importance to carefully consider the complete PES - both the intra-molecular and inter-molecular features - in order to fully understand the entire range of atomic-dynamical processes in disordered solids. Finally, we show that it is possible to utilise this dependence to directly manipulate and harness amorphous dynamics in order to control the behaviour of such solids by using high-powered terahertz pulses to induce crystallisation and preferential crystal-polymorph growth in glasses. Combined, these findings provide compelling evidence that the PES landscape, and the corresponding energy barriers, are the ultimate controlling feature behind the atomic and molecular dynamics of disordered solids, regardless of the frequency at which they occur.

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

PubMed Central

Baity-Jesi, Marco; Calore, Enrico; Cruz, Andres; Fernandez, Luis Antonio; Gil-Narvión, José Miguel; Gordillo-Guerrero, Antonio; Iñiguez, David; Maiorano, Andrea; Marinari, Enzo; Martin-Mayor, Victor; Monforte-Garcia, Jorge; Muñoz Sudupe, Antonio; Navarro, Denis; Parisi, Giorgio; Perez-Gaviro, Sergio; Ricci-Tersenghi, Federico; Ruiz-Lorenzo, Juan Jesus; Schifano, Sebastiano Fabio; Tarancón, Alfonso; Tripiccione, Raffaele; Yllanes, David

2017-01-01

We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the special-purpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes. PMID:28174274

Pancreatic cancer study based on full field OCT and dynamic full field OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Apelian, Clement; Camus, Marine; Prat, Frederic; Boccara, A. Claude

2017-02-01

Pancreatic cancer is one of the most feared cancer types due to high death rates and the difficulty to perform surgery. This cancer outcome could benefit from recent technological developments for diagnosis. We used a combination of standard Full Field OCT and Dynamic Full Field OCT to capture both morphological features and metabolic functions of rodents pancreas in normal and cancerous conditions with and without chemotherapy. Results were compared to histology to evaluate the performances and the specificities of the method. The comparison highlighted the importance of a number of endogenous markers like immune cells, fibrous development, architecture and more.

A dynamically adaptive multigrid algorithm for the incompressible Navier-Stokes equations: Validation and model problems

NASA Technical Reports Server (NTRS)

Thompson, C. P.; Leaf, G. K.; Vanrosendale, J.

1991-01-01

An algorithm is described for the solution of the laminar, incompressible Navier-Stokes equations. The basic algorithm is a multigrid based on a robust, box-based smoothing step. Its most important feature is the incorporation of automatic, dynamic mesh refinement. This algorithm supports generalized simple domains. The program is based on a standard staggered-grid formulation of the Navier-Stokes equations for robustness and efficiency. Special grid transfer operators were introduced at grid interfaces in the multigrid algorithm to ensure discrete mass conservation. Results are presented for three models: the driven-cavity, a backward-facing step, and a sudden expansion/contraction.

Supporting Scientific Analysis within Collaborative Problem Solving Environments

NASA Technical Reports Server (NTRS)

Watson, Velvin R.; Kwak, Dochan (Technical Monitor)

2000-01-01

Collaborative problem solving environments for scientists should contain the analysis tools the scientists require in addition to the remote collaboration tools used for general communication. Unfortunately, most scientific analysis tools have been designed for a "stand-alone mode" and cannot be easily modified to work well in a collaborative environment. This paper addresses the questions, "What features are desired in a scientific analysis tool contained within a collaborative environment?", "What are the tool design criteria needed to provide these features?", and "What support is required from the architecture to support these design criteria?." First, the features of scientific analysis tools that are important for effective analysis in collaborative environments are listed. Next, several design criteria for developing analysis tools that will provide these features are presented. Then requirements for the architecture to support these design criteria are listed. Sonic proposed architectures for collaborative problem solving environments are reviewed and their capabilities to support the specified design criteria are discussed. A deficiency in the most popular architecture for remote application sharing, the ITU T. 120 architecture, prevents it from supporting highly interactive, dynamic, high resolution graphics. To illustrate that the specified design criteria can provide a highly effective analysis tool within a collaborative problem solving environment, a scientific analysis tool that contains the specified design criteria has been integrated into a collaborative environment and tested for effectiveness. The tests were conducted in collaborations between remote sites in the US and between remote sites on different continents. The tests showed that the tool (a tool for the visual analysis of computer simulations of physics) was highly effective for both synchronous and asynchronous collaborative analyses. The important features provided by the tool (and made possible by the specified design criteria) are: 1. The tool provides highly interactive, dynamic, high resolution, 3D graphics. 2. All remote scientists can view the same dynamic, high resolution, 3D scenes of the analysis as the analysis is being conducted. 3. The responsiveness of the tool is nearly identical to the responsiveness of the tool in a stand-alone mode. 4. The scientists can transfer control of the analysis between themselves. 5. Any analysis session or segment of an analysis session, whether done individually or collaboratively, can be recorded and posted on the Web for other scientists or students to download and play in either a collaborative or individual mode. 6. The scientist or student who downloaded the session can, individually or collaboratively, modify or extend the session with his/her own "what if" analysis of the data and post his/her version of the analysis back onto the Web. 7. The peak network bandwidth used in the collaborative sessions is only 1K bit/second even though the scientists at all sites are viewing high resolution (1280 x 1024 pixels), dynamic, 3D scenes of the analysis. The links between the specified design criteria and these performance features are presented.

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

USGS Publications Warehouse

Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.

2011-01-01

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

A Molecular Dynamics Study of the Structure-Dynamics Relationships of Supercooled Liquids and Glasses

NASA Astrophysics Data System (ADS)

Soklaski, Ryan

Central to the field of condensed matter physics is a decades old outstanding problem in the study of glasses -- namely explaining the extreme slowing of dynamics in a liquid as it is supercooled towards the so-called glass transition. Efforts to universally describe the stretched relaxation processes and heterogeneous dynamics that characteristically develop in supercooled liquids remain divided in both their approaches and successes. Towards this end, a consensus on the role that atomic and molecular structures play in the liquid is even more tenuous. However, mounting material science research efforts have culminated to reveal that the vast diversity of metallic glass species and their properties are rooted in an equally-broad set of structural archetypes. Herein lies the motivation of this dissertation: the detailed information available regarding the structure-property relationships of metallic glasses provides a new context in which one can study the evolution of a supercooled liquid by utilizing a structural motif that is known to dominate the glass. Cu64Zr36 is a binary alloy whose good glass-forming ability and simple composition makes it a canonical material to both empirical and numerical studies. Here, we perform classical molecular dynamics simulations and conduct a comprehensive analysis of the dynamical regimes of liquid Cu64Zr36, while focusing on the roles played by atomic icosahedral ordering -- a structural motif which ultimately percolates the glass' structure. Large data analysis techniques are leveraged to obtain uniquely detailed structural and dynamical information in this context. In doing so, we develop the first account of the origin of icosahedral order in this alloy, revealing deep connections between this incipient structural ordering, frustration-limited domain theory, and recent important empirical findings that are relevant to the nature of metallic liquids at large. Furthermore, important dynamical landmarks such as the breakdown of the Stokes-Einstein relationship, the decoupling of particle diffusivities, and the development of general "glassy" relaxation features are found to coincide with successive manifestation of icosahedral ordering that arise as the liquid is supercooled. Remarkably, we detect critical-like features in the growth of the icosahedron network, with signatures that suggest that a liquid-liquid phase transition may occur in the deeply supercooled regime to precede glass formation. Such a transition is predicted to occur in many supercooled liquids, although explicit evidence of this phenomenon in realistic systems is scarce. Ultimately this work concludes that icosahedral order characterizes all dynamical regimes of Cu64Zr 36, demonstrating the importance and utility of studying supercooled liquids in the context of locally-preferred structure. More broadly, it serves to confirm and inform recent theoretical and empirical findings that are central to understanding the physics underlying the glass transition.

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; Hurtado, John E.

2011-01-01

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Dynamics and Context-Dependent Roles of DNA Methylation.

PubMed

Ambrosi, Christina; Manzo, Massimiliano; Baubec, Tuncay

2017-05-19

DNA methylation is one of the most extensively studied epigenetic marks. It is involved in transcriptional gene silencing and plays important roles during mammalian development. Its perturbation is often associated with human diseases. In mammalian genomes, DNA methylation is a prevalent modification that decorates the majority of cytosines. It is found at the promoters and enhancers of inactive genes, at repetitive elements, and within transcribed gene bodies. Its presence at promoters is dynamically linked to gene activity, suggesting that it could directly influence gene expression patterns and cellular identity. The genome-wide distribution and dynamic behaviour of this mark have been studied in great detail in a variety of tissues and cell lines, including early embryonic development and in embryonic stem cells. In combination with functional studies, these genome-wide maps of DNA methylation revealed interesting features of this mark and provided important insights into its dynamic nature and potential functional role in genome regulation. In this review, we discuss how these recent observations, in combination with insights obtained from biochemical and functional genetics studies, have expanded our current knowledge about the regulation and context-dependent roles of DNA methylation in mammalian genomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

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

2014-01-01

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

Insights into the dynamics of planetary interiors obtained through the study of global distribution of volcanoes I: Empirical calibration on Earth

NASA Astrophysics Data System (ADS)

Cañon-Tapia, Edgardo; Mendoza-Borunda, Ramón

2014-06-01

The distribution of volcanic features is ultimately controlled by processes taking place beneath the surface of a planet. For this reason, characterization of volcano distribution at a global scale can be used to obtain insights concerning dynamic aspects of planetary interiors. Until present, studies of this type have focused on volcanic features of a specific type, or have concentrated on relatively small regions. In this paper, (the first of a series of three papers) we describe the distribution of volcanic features observed over the entire surface of the Earth, combining an extensive database of submarine and subaerial volcanoes. The analysis is based on spatial density contours obtained with the Fisher kernel. Based on an empirical approach that makes no a priori assumptions concerning the number of modes that should characterize the density distribution of volcanism we identified the most significant modes. Using those modes as a base, the relevant distance for the formation of clusters of volcanoes is constrained to be on the order of 100 to 200 km. In addition, it is noted that the most significant modes lead to the identification of clusters that outline the most important tectonic margins on Earth without the need of making any ad hoc assumptions. Consequently, we suggest that this method has the potential of yielding insights about the probable occurrence of tectonic features within other planets.

Strongly coupled gauge theories: What can lattice calculations teach us?

NASA Astrophysics Data System (ADS)

Hasenfratz, A.; Brower, R. C.; Rebbi, C.; Weinberg, E.; Witzel, O.

2017-12-01

The dynamical origin of electroweak symmetry breaking is an open question with many possible theoretical explanations. Strongly coupled systems predicting the Higgs boson as a bound state of a new gauge-fermion interaction form one class of candidate models. Due to increased statistics, LHC run II will further constrain the phenomenologically viable models in the near future. In the meanwhile it is important to understand the general properties and specific features of the different competing models. In this work we discuss many-flavor gauge-fermion systems that contain both massless (light) and massive fermions. The former provide Goldstone bosons and trigger electroweak symmetry breaking, while the latter indirectly influence the infrared dynamics. Numerical results reveal that such systems can exhibit a light 0++ isosinglet scalar, well separated from the rest of the spectrum. Further, when we set the scale via the vev of electroweak symmetry breaking, we predict a 2 TeV vector resonance which could be a generic feature of SU(3) gauge theories.

Model-based Robotic Dynamic Motion Control for the Robonaut 2 Humanoid Robot

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Hulse, Aaron M.; Taylor, Ross C.; Curtis, Andrew W.; Gooding, Dustin R.; Thackston, Allison

2013-01-01

Robonaut 2 (R2), an upper-body dexterous humanoid robot, has been undergoing experimental trials on board the International Space Station (ISS) for more than a year. R2 will soon be upgraded with two climbing appendages, or legs, as well as a new integrated model-based control system. This control system satisfies two important requirements; first, that the robot can allow humans to enter its workspace during operation and second, that the robot can move its large inertia with enough precision to attach to handrails and seat track while climbing around the ISS. This is achieved by a novel control architecture that features an embedded impedance control law on the motor drivers called Multi-Loop control which is tightly interfaced with a kinematic and dynamic coordinated control system nicknamed RoboDyn that resides on centralized processors. This paper presents the integrated control algorithm as well as several test results that illustrate R2's safety features and performance.

Dynamical complexity in a mean-field model of human EEG

NASA Astrophysics Data System (ADS)

Frascoli, Federico; Dafilis, Mathew P.; van Veen, Lennaert; Bojak, Ingo; Liley, David T. J.

2008-12-01

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

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

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F.

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. While considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here in this paper, we examine the importance of substrate dynamics in the cleavage of Kunitz-BPTI protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4 Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals amore » dramatic conformational change in the substrate upon proteolysis. Using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning three orders of magnitude, we identify global and local dynamic features of substrates on the ns-μs timescale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substratelike and product-like states, linking substrate dynamics on the ns-μs timescale with large collective substrate motions on the much slower timescale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis.« less

Nursing professionalism: An evolutionary concept analysis

PubMed Central

Ghadirian, Fataneh; Salsali, Mahvash; Cheraghi, Mohammad Ali

2014-01-01

Background: Professionalism is an important feature of the professional jobs. Dynamic nature and the various interpretations of this term lead to multiple definitions of this concept. The aim of this paper is to identify the core attributes of the nursing professionalism. Materials and Methods: We followed Rodgers’ evolutionary method of concept analysis. Texts published in scientific databases about nursing professionalism between 1980 and 2011 were assessed. After applying the selection criteria, the final sample consisting of 4 books and 213 articles was selected, examined, and analyzed in depth. Two experts checked the process of analysis and monitored and reviewed them. Results: The analysis showed that nursing professionalism is determined by three attributes of cognitive, attitudinal, and psychomotor. In addition, the most important antecedents concepts were demographic, experiential, educational, environmental, and attitudinal factors. Conclusion: Nursing professionalism is an inevitable, complex, varied, and dynamic process. In this study, the importance, scope, and concept of professionalism in nursing, the concept of a beginning for further research and development, and expanding the nursing knowledge are explained and clarified. PMID:24554953

Microfluidic perfusion shows intersarcomere dynamics within single skeletal muscle myofibrils

PubMed Central

Minozzo, Fabio C.; Altman, David; Rassier, Dilson E.

2017-01-01

The sarcomere is the smallest functional unit of myofibrils in striated muscles. Sarcomeres are connected in series through a network of elastic and structural proteins. During myofibril activation, sarcomeres develop forces that are regulated through complex dynamics among their structures. The mechanisms that regulate intersarcomere dynamics are unclear, which limits our understanding of fundamental muscle features. Such dynamics are associated with the loss in forces caused by mechanical instability encountered in muscle diseases and cardiomyopathy and may underlie potential target treatments for such conditions. In this study, we developed a microfluidic perfusion system to control one sarcomere within a myofibril, while measuring the individual behavior of all sarcomeres. We found that the force from one sarcomere leads to adjustments of adjacent sarcomeres in a mechanism that is dependent on the sarcomere length and the myofibril stiffness. We concluded that the cooperative work of the contractile and the elastic elements within a myofibril rules the intersarcomere dynamics, with important consequences for muscle contraction. PMID:28765372

Branching dynamics of viral information spreading.

PubMed

Iribarren, José Luis; Moro, Esteban

2011-10-01

Despite its importance for rumors or innovations propagation, peer-to-peer collaboration, social networking, or marketing, the dynamics of information spreading is not well understood. Since the diffusion depends on the heterogeneous patterns of human behavior and is driven by the participants' decisions, its propagation dynamics shows surprising properties not explained by traditional epidemic or contagion models. Here we present a detailed analysis of our study of real viral marketing campaigns where tracking the propagation of a controlled message allowed us to analyze the structure and dynamics of a diffusion graph involving over 31,000 individuals. We found that information spreading displays a non-Markovian branching dynamics that can be modeled by a two-step Bellman-Harris branching process that generalizes the static models known in the literature and incorporates the high variability of human behavior. It explains accurately all the features of information propagation under the "tipping point" and can be used for prediction and management of viral information spreading processes.

Branching dynamics of viral information spreading

NASA Astrophysics Data System (ADS)

Iribarren, José Luis; Moro, Esteban

2011-10-01

Despite its importance for rumors or innovations propagation, peer-to-peer collaboration, social networking, or marketing, the dynamics of information spreading is not well understood. Since the diffusion depends on the heterogeneous patterns of human behavior and is driven by the participants’ decisions, its propagation dynamics shows surprising properties not explained by traditional epidemic or contagion models. Here we present a detailed analysis of our study of real viral marketing campaigns where tracking the propagation of a controlled message allowed us to analyze the structure and dynamics of a diffusion graph involving over 31 000 individuals. We found that information spreading displays a non-Markovian branching dynamics that can be modeled by a two-step Bellman-Harris branching process that generalizes the static models known in the literature and incorporates the high variability of human behavior. It explains accurately all the features of information propagation under the “tipping point” and can be used for prediction and management of viral information spreading processes.

Study of Comets Composition and Structure

NASA Astrophysics Data System (ADS)

Khalaf, S. Z.; Selman, A. A.; Ali, H. S.

2008-12-01

The present paper focuses on the nature of the different interactions between cometary nucleus and tail with solar wind. The dynamics of the comet will impose many features that provide unique behavior of the comet when entering the solar system. These features are reviewed in this paper and few investigations are made. The calculations made in this work represent the analysis and interpretation of the different features of the comet, such as perihelion and eccentricity dependence on the gas production rate, and the dependence of the latter on the composition of the comet nucleus. The dependences of the heliocentric, bow shock, contact surface, and stand-off distances with gas production rate for many types of comets that cover linear and non-linear types are studied in this work. Important results are obtained which indicated the different physical interactions between cometary ions and solar wind. Furthermore, the important relation between mean molecular weight and gas production rate are analyzed and studied in this work and a conclusion is made that, as the gas production rate increases, the mean molecular weight will decrease exponentially. A detailed discussion for this unique relation is given.

Analytical solutions of Landau (1+1)-dimensional hydrodynamics

DOE PAGES

Wong, Cheuk-Yin; Sen, Abhisek; Gerhard, Jochen; ...

2014-12-17

To help guide our intuition, summarize important features, and point out essential elements, we review the analytical solutions of Landau (1+1)-dimensional hydrodynamics and exhibit the full evolution of the dynamics from the very beginning to subsequent times. Special emphasis is placed on the matching and the interplay between the Khalatnikov solution and the Riemann simple wave solution at the earliest times and in the edge regions at later times.

Study of Varying Boundary Layer Height on Turret Flow Structures

DTIC Science & Technology

2011-06-01

fluid dynamics. The difficulties of the problem arise in modeling several complex flow features including separation, reattachment, three-dimensional...impossible. In this case, the approach is to create a model to calculate the properties of interest. The main issue with resolving turbulent flows...operation and their effect is modeled through subgrid scale models . As a result, the the most important turbulent scales are resolved and the

Generation of magnetic fields by chaotic fluid convection - The fast dynamo problem

NASA Technical Reports Server (NTRS)

Finn, John M.

1992-01-01

In the kinematic fast dynamo problem, the underlying nonlinear dynamics of the flow play a critical role in the behavior of a dynamo field. It is presently noted that the two important facets of the problem are the approximately lognormal distribution of vector lengths, and the presence of partial cancellation. It is suggested that these features may be reflected in the magnetic fields observed on the sun.

A dilation-driven vortex flow in sheared granular materials explains a rheometric anomaly.

PubMed

Krishnaraj, K P; Nott, Prabhu R

2016-02-11

Granular flows occur widely in nature and industry, yet a continuum description that captures their important features is yet not at hand. Recent experiments on granular materials sheared in a cylindrical Couette device revealed a puzzling anomaly, wherein all components of the stress rise nearly exponentially with depth. Here we show, using particle dynamics simulations and imaging experiments, that the stress anomaly arises from a remarkable vortex flow. For the entire range of fill heights explored, we observe a single toroidal vortex that spans the entire Couette cell and whose sense is opposite to the uppermost Taylor vortex in a fluid. We show that the vortex is driven by a combination of shear-induced dilation, a phenomenon that has no analogue in fluids, and gravity flow. Dilatancy is an important feature of granular mechanics, but not adequately incorporated in existing models.

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Expression profiling of mouse subplate reveals a dynamic gene network and disease association with autism and schizophrenia

PubMed Central

Hoerder-Suabedissen, Anna; Oeschger, Franziska M.; Krishnan, Michelle L.; Belgard, T. Grant; Wang, Wei Zhi; Lee, Sheena; Webber, Caleb; Petretto, Enrico; Edwards, A. David; Molnár, Zoltán

2013-01-01

The subplate zone is a highly dynamic transient sector of the developing cerebral cortex that contains some of the earliest generated neurons and the first functional synapses of the cerebral cortex. Subplate cells have important functions in early establishment and maturation of thalamocortical connections, as well as in the development of inhibitory cortical circuits in sensory areas. So far no role has been identified for cells in the subplate in the mature brain and disease association of the subplate-specific genes has not been analyzed systematically. Here we present gene expression evidence for distinct roles of the mouse subplate across development as well as unique molecular markers to extend the repertoire of subplate labels. Performing systematic comparisons between different ages (embryonic days 15 and 18, postnatal day 8, and adult), we reveal the dynamic and constant features of the markers labeling subplate cells during embryonic and early postnatal development and in the adult. This can be visualized using the online database of subplate gene expression at https://molnar.dpag.ox.ac.uk/subplate/. We also identify embryonic similarities in gene expression between the ventricular zones, intermediate zone, and subplate, and distinct postnatal similarities between subplate, layer 5, and layers 2/3. The genes expressed in a subplate-specific manner at some point during development show a statistically significant enrichment for association with autism spectrum disorders and schizophrenia. Our report emphasizes the importance of the study of transient features of the developing brain to better understand neurodevelopmental disorders. PMID:23401504

Dynamic modeling of the neck muscles during horizontal head movement. Part II: Model construction in Pro/Engineer.

PubMed

Haapala, Stephenie A; Enderle, John D

2003-01-01

This paper describes the next phase of research on a parametric model of the head-neck system for dynamic simulation of horizontal head rotation. A skull has been imported into Pro/Engineer software and has been assigned mass properties such as density, surface area and moments of inertia. The origin of a universal coordinate system has been located at the center of gravity of the T1 vertebrae. Identification of this origin allows insertion and attachment points of the sternocleidomastoid (SCOM) and splenius capitis to be located. An assembly has been created, marking the location of both muscle sets. This paper will also explore the obstacles encountered when working with an imported feature in Pro/E and attempts to resolve some of these issues. The goal of this work involves the creation of a 3D homeomorphic saccadic eye and head movement system.

The role of molecular hydrogen and methane oxidation in the water vapour budget of the stratosphere

NASA Technical Reports Server (NTRS)

Le Texier, H.; Solomon, S.; Garcia, R. R.

1988-01-01

The detailed photochemistry of methane oxidation has been studied in a coupled chemical/dynamical model of the middle atmosphere. The photochemistry of formaldehyde plays an important role in determining the production of water vapor from methane oxidation. At high latitudes, the production and transport of molecular hydrogen is particularly important in determining the water vapor distribution. It is shown that the ratio of the methane vertical gradient to the water vapor vertical gradient at any particular latitude should not be expected to be precisely 2, due both to photochemical and dynamical effects. Modeled H2O profiles are compared with measurements from the Limb Infrared Monitor of the Stratosphere (LIMS) experiment at various latitudes. Molecular hydrogen is shown to be responsible for the formation of a secondary maximum displayed by the model water vapor profiles in high latitude summer, a feature also found in the LIMS data.

Adopted children's emotion regulation: The role of parental attitudes and communication about adoption.

PubMed

Soares, Joana; Barbosa-Ducharne, Maria; Palacios, Jesús; Pacheco, Ana

2017-02-01

Acknowledgement/rejection of adoption related differences and communication about adoption are two of the most important features of  adoptive family dynamics. The present study focuses on the role played by these two variables on the adoptees’ emotion regulation. The adoptive parents of 70 school-aged children participated in the study. Data showed that participant parents perceived their adopted children’s emotion regulation as adequate. In relation to family dynamics, acknowledgment of the adoption specificities significantly predicted the emotional lability/negativity of the adoptees, simultaneously mediated by the emotional quality of and the parental satisfaction with the communication about adoption. Furthermore, there was an indirect effect of early adversity on the adopted child’s emotional lability. These findings provide new insight into adopted children’s emotional development, highlighting the importance of the family environment and pre-adoption experiences.

Nanomotor dynamics in a chemically oscillating medium

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

Robertson, Bryan, E-mail: bryan.robertson@mail.utoronto.ca; Kapral, Raymond, E-mail: rkapral@chem.utoronto.ca

2015-04-21

Synthetic nanomotors powered by chemical reactions have potential uses as cargo transport vehicles in both in vivo and in vitro applications. In many situations, motors will have to operate in out-of-equilibrium complex chemically reacting media, which supply fuel to the motors and remove the products they produce. Using molecular simulation and mean-field theory, this paper describes some of the new features that arise when a chemically powered nanomotor, operating through a diffusiophoretic mechanism, moves in an environment that supports an oscillatory chemical reaction network. It is shown how oscillations in the concentrations in chemical species in the environment give risemore » to oscillatory motor dynamics. More importantly, since the catalytic reactions on the motor that are responsible for its propulsion couple to the bulk phase reaction network, the motor can change its local environment. This process can give rise to distinctive spatiotemporal structures in reaction-diffusion media that occur as a result of active motor motion. Such locally induced nonequilibrium structure will play an important role in applications that involve motor dynamics in complex chemical media.« less

The fluid dynamics of deep-sea mining

NASA Astrophysics Data System (ADS)

Peacock, Thomas; Rzeznik, Andrew

2017-11-01

With vast mineral deposits on the ocean floor, deep-sea nodule mining operations are expected to commence in the next decade. Among several fundamental fluid dynamics problems, this could involve plans for dewatering plumes to be released into the water column by surface processing vessels. To study this scenario, we consider the effects of non-uniform, realistic stratifications on forced compressible plumes with finite initial size. The classical plume model is developed to take into account the influence of thermal conduction through the dewatering pipe and also compressibility effects, for which a dimensionless number is introduced to determine their importance compared to the background stratification. Among other things, our results show that small-scale features of a realistic stratification can have a large effect on plume dynamics compared to smoothed profiles and that for any given set of environmental parameters there is a discharge flow rate that minimizes the plume vertical extent. Our findings are put in the context of nodule mining plumes for which the rapid and efficient re-sedimentation of waste material has important environmental consequences.

Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

PubMed

Venkataraman, Vinay; Turaga, Pavan

2016-12-01

This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

[Diagnosis and therapy of gigantism].

PubMed

Sorgo, W; Teller, W M

1987-01-01

Some of the most important types of nonfamilial tall stature are discussed by stressing the clinical features, diagnostic aspects and therapeutic possibilities. The indications of treatment, the diagnostic procedures and steroid therapy of the familial type of tall stature, the predominant variant of tall stature, are presented in detail. The effects, side effects and contraindications of high dose steroid treatment are described. The important prerequisite for the evaluation of psychosomatic problems of tall stature is the understanding of the dynamics and variations of normal growth. This and the knowledge of methods concerning growth analyses continue to be the basis of an accurate diagnosis.

FLIPing heterokaryons to analyze nucleo-cytoplasmic shuttling of yeast proteins.

PubMed

Belaya, Katsiaryna; Tollervey, David; Kos, Martin

2006-05-01

Nucleo-cytoplasmic shuttling is an important feature of proteins involved in nuclear export/import of RNAs, proteins, and also large ribonucleoprotein complexes such as ribosomes. The vast amount of proteomic data available shows that many of these processes are highly dynamic. Therefore, methods are needed to reliably assess whether a protein shuttles between nucleus and cytoplasm, and the kinetics with which it exchanges. Here we describe a combination of the classical heterokaryon assay with fluorescence recovery after photobleaching (FRAP) and fluorescence loss in photobleaching (FLIP) techniques, which allows an assessment of the kinetics of protein shuttling in the yeast Saccharomyces cerevisiae.

Case Study of Airborne Pathogen Dispersion Patterns in Emergency Departments with Different Ventilation and Partition Conditions

PubMed Central

Cheong, Chang Heon; Lee, Seonhye

2018-01-01

The prevention of airborne infections in emergency departments is a very important issue. This study investigated the effects of architectural features on airborne pathogen dispersion in emergency departments by using a CFD (computational fluid dynamics) simulation tool. The study included three architectural features as the major variables: increased ventilation rate, inlet and outlet diffuser positions, and partitions between beds. The most effective method for preventing pathogen dispersion and reducing the pathogen concentration was found to be increasing the ventilation rate. Installing partitions between the beds and changing the ventilation system’s inlet and outlet diffuser positions contributed only minimally to reducing the concentration of airborne pathogens. PMID:29534043

Case Study of Airborne Pathogen Dispersion Patterns in Emergency Departments with Different Ventilation and Partition Conditions.

PubMed

Cheong, Chang Heon; Lee, Seonhye

2018-03-13

The prevention of airborne infections in emergency departments is a very important issue. This study investigated the effects of architectural features on airborne pathogen dispersion in emergency departments by using a CFD (computational fluid dynamics) simulation tool. The study included three architectural features as the major variables: increased ventilation rate, inlet and outlet diffuser positions, and partitions between beds. The most effective method for preventing pathogen dispersion and reducing the pathogen concentration was found to be increasing the ventilation rate. Installing partitions between the beds and changing the ventilation system's inlet and outlet diffuser positions contributed only minimally to reducing the concentration of airborne pathogens.

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection was suggested. On the basis of analyzing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from remote sensing data was discussed. Spectral signatures of different terrain features have been used to extract structural patterns aiming to separate surface units and to classify the general categories. The synergetic analysis and interpretation of the different satellite images (LANDSAT: TM, ETM; MODIS, IKONOS) acquired over a period of more than 20 years reveals significant aspects regarding impacts of climate and anthropogenic changes on urban/periurban environment. It was delimited residential zones of industrial zones which are very often a source of pollution. An important role has urban green cover assessment. Have been emphasized the particularities of the functional zones from different points of view: architectural, streets and urban surface traffic, some components of urban infrastructure as well as habitat quality. The growth of Bucharest urban area in Romania has been a result of a rapid process of industrialization, and also of the increase of urban population. Information on the spatial pattern and temporal dynamics of land cover and land use of urban areas is critical to address a wide range of practical problems relating to urban regeneration, urban sustainability and rational planning policy.

Structural dynamics of Casein Kinase I (CKI) from malarial parasite Plasmodium falciparum (Isolate 3D7): Insights from theoretical modelling and molecular simulations.

PubMed

Dehury, Budheswar; Behera, Santosh Kumar; Mahapatra, Namita

2017-01-01

The protein kinases (PKs), belonging to serine/threonine kinase (STKs), are important drug targets for a wide spectrum of diseases in human. Among protein kinases, the Casein Kinases (CKs) are vastly expanded in various organisms, where, the malarial parasite Plasmodium falciparum possesses a single member i.e., PfCKI, which can phosphorylate various proteins in parasite extracts in vitro condition. But, the structure-function relationship of PfCKI and dynamics of ATP binding is yet to be understood. Henceforth, an attempt was made to study the dynamics, stability, and ATP binding mechanisms of PfCKI through computational modelling, docking, molecular dynamics (MD) simulations, and MM/PBSA binding free energy estimation. Bi-lobed catalytic domain of PfCKI shares a high degree of secondary structure topology with CKI domains of rice, human, and mouse indicating co-evolution of these kinases. Molecular docking study revealed that ATP binds to the active site where the glycine-rich ATP-binding motif (G16-X-G18-X-X-G21) along with few conserved residues plays a crucial role maintaining stability of the complex. Structural superposition of PfCKI with close structural homologs depicted that the location and length of important loops are different, indicating the dynamic properties of these loops among CKIs, which is consistent with principal component analysis (PCA). PCA displayed that the overall global motion of ATP-bound form is comparatively higher than that of apo form. The present study provides insights into the structural features of PfCKI, which could contribute towards further understanding of related protein structures, dynamics of catalysis and phosphorylation mechanism in these important STKs from malarial parasite in near future. Copyright © 2016 Elsevier Inc. All rights reserved.

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis*

PubMed Central

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F.; Cohen, Itay; Henin, Rachel D.; Hockla, Alexandra; Soares, Alexei S.; Papo, Niv; Caulfield, Thomas R.; Radisky, Evette S.

2016-01-01

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. Although considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here, we examine the importance of substrate dynamics in the cleavage of Kunitz-bovine pancreatic trypsin inhibitor protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4-Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. By using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning 3 orders of magnitude, we identify global and local dynamic features of substrates on the nanosecond-microsecond time scale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substrate-like and product-like states, linking substrate dynamics on the nanosecond-microsecond time scale with large collective substrate motions on the much slower time scale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis. PMID:27810896

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis

DOE PAGES

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F.; ...

2016-11-03

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. While considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here in this paper, we examine the importance of substrate dynamics in the cleavage of Kunitz-BPTI protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4 Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals amore » dramatic conformational change in the substrate upon proteolysis. Using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning three orders of magnitude, we identify global and local dynamic features of substrates on the ns-μs timescale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substratelike and product-like states, linking substrate dynamics on the ns-μs timescale with large collective substrate motions on the much slower timescale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis.« less

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

Object impedance control for cooperative manipulation - Theory and experimental results

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Cannon, Robert H., Jr.

1992-01-01

This paper presents the dynamic control module of the Dynamic and Strategic Control of Cooperating Manipulators (DASCCOM) project at Stanford University's Aerospace Robotics Laboratory. First, the cooperative manipulation problem is analyzed from a systems perspective, and the desirable features of a control system for cooperative manipulation are discussed. Next, a control policy is developed that enforces a controlled impedance not of the individual arm endpoints, but of the manipulated object itself. A parallel implementation for a multiprocessor system is presented. The controller fully compensates for the system dynamics and directly controls the object internal forces. Most importantly, it presents a simple, powerful, intuitive interface to higher level strategic control modules. Experimental results from a dual two-link-arm robotic system are used to compare the object impedance controller with other strategies, both for free-motion slews and environmental contact.

Quantum critical point revisited by dynamical mean-field theory

NASA Astrophysics Data System (ADS)

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.

2017-03-01

Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. We use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. By comparing with the calculations based on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.

Quantum critical point revisited by dynamical mean-field theory

DOE PAGES

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.

2017-03-31

Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. We characterize the QCP by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. Here, we use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. Furthermore, by comparing with the calculations basedmore » on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.« less

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

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

The yeast Golgi apparatus: insights and mysteries

PubMed Central

Papanikou, Effrosyni; Glick, Benjamin S.

2009-01-01

The Golgi apparatus is known to modify and sort newly synthesized secretory proteins. However, fundamental mysteries remain about the structure, operation, and dynamics of this organelle. Important insights have emerged from studying the Golgi in yeasts. For example, yeasts have provided direct evidence for Golgi cisternal maturation, a mechanism that is likely to be broadly conserved. Here, we highlight features of the yeast Golgi as well as challenges that lie ahead. PMID:19879270

The Colossus of ubiquitylation –decrypting a cellular code

PubMed Central

Williamson, Adam; Werner, Achim; Rape, Michael

2013-01-01

Ubiquitylation is an essential posttranslational modification that can regulate the stability, activity, or localization of thousands of proteins. The reversible attachment of ubiquitin as well as interpretation of the ubiquitin signal depend on dynamic protein networks that are challenging to analyze. In this perspective, we discuss tools of the trade that have recently been developed to dissect mechanisms of ubiquitin-dependent signaling, thereby revealing the critical features of an important cellular code. PMID:23438855

When small changes matter: the role of cross-scale interactions between habitat and ecological connectivity in recovery.

PubMed

Thrush, Simon F; Hewitt, Judi E; Lohrer, Andrew M; Chiaroni, Luca D

2013-01-01

Interaction between the diversity of local communities and the degree of connectivity between them has the potential to influence local recovery rates and thus profoundly affect community dynamics in the face of the cumulative impacts that occur across regions. Although such complex interactions have been modeled, field experiments in natural ecosystems to investigate the importance of interactions between local and regional processes are rare, especially so in coastal marine seafloor habitats subjected to many types of disturbance. We conducted a defaunation experiment at eight subtidal sites, incorporating manipulation of habitat structure, to test the relative importance of local habitat features and colonist supply in influencing macrobenthic community recovery rate. Our sites varied in community composition, habitat characteristics, and hydrodynamic conditions, and we conducted the experiment in two phases, exposing defaunated plots to colonists during periods of either high or low larval colonist supply. In both phases of the experiment, five months after disturbance, we were able to develop models that explained a large proportion of variation in community recovery rate between sites. Our results emphasize that the connectivity to the regional species pool influences recovery rate, and although local habitat effects were important, the strength of these effects was affected by broader-scale site characteristics and connectivity. Empirical evidence that cross-scale interactions are important in disturbance-recovery dynamics emphasizes the complex dynamics underlying seafloor community responses to cumulative disturbance.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex.

PubMed

Bello, Martiniano; Correa-Basurto, José

2016-04-01

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

Inline Measurement of Particle Concentrations in Multicomponent Suspensions using Ultrasonic Sensor and Least Squares Support Vector Machines.

PubMed

Zhan, Xiaobin; Jiang, Shulan; Yang, Yili; Liang, Jian; Shi, Tielin; Li, Xiwen

2015-09-18

This paper proposes an ultrasonic measurement system based on least squares support vector machines (LS-SVM) for inline measurement of particle concentrations in multicomponent suspensions. Firstly, the ultrasonic signals are analyzed and processed, and the optimal feature subset that contributes to the best model performance is selected based on the importance of features. Secondly, the LS-SVM model is tuned, trained and tested with different feature subsets to obtain the optimal model. In addition, a comparison is made between the partial least square (PLS) model and the LS-SVM model. Finally, the optimal LS-SVM model with the optimal feature subset is applied to inline measurement of particle concentrations in the mixing process. The results show that the proposed method is reliable and accurate for inline measuring the particle concentrations in multicomponent suspensions and the measurement accuracy is sufficiently high for industrial application. Furthermore, the proposed method is applicable to the modeling of the nonlinear system dynamically and provides a feasible way to monitor industrial processes.

Dynamical features of an anisotropic cosmological model

NASA Astrophysics Data System (ADS)

Mishra, B.; Tarai, Sankarsan; Tripathy, S. K.

2018-04-01

The dynamical features of Bianchi type VI_h (BVI_h) universe are investigated in f(R, T) theory of gravity. The field equations and the physical properties of the model are derived considering a power law expansion of the universe. The effect of anisotropy on the dynamics of the universe as well as on the energy conditions are studied. The assumed anisotropy of the model is found to have substantial effects on the energy conditions and dynamical parameters.

Voltage noise of current-driven vortices in disordered Josephson junction arrays.

PubMed

He, G L; Zhao, Z G; Liu, S; Yang, Y H; Liu, M; Xing, D Y

2006-08-16

Dynamical phenomena of moving vortices and voltage noise spectra are studied in disordered Josephson junction arrays (JJAs). The plastic motion of vortices, smectic flow, and moving Bragg glass phases are separated by two dynamic melting transitions driven by current. From the voltage noise spectra of moving vortices, it is found that the driving current plays an important role in the melting of pinning vortices glass and ordering of moving vortices. The features of noise spectra obtained in the disordered JJA model have been observed recently in the high-temperature superconductor Bi(2)Sr(2)CaCu(2)O(y) near the first-order melting transition, indicating that both of them are related to each other.

Feature-based interference from unattended visual field during attentional tracking in younger and older adults.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2011-02-01

The ability to attend to multiple objects that move in the visual field is important for many aspects of daily functioning. The attentional capacity for such dynamic tracking, however, is highly limited and undergoes age-related decline. Several aspects of the tracking process can influence performance. Here, we investigated effects of feature-based interference from distractor objects that appear in unattended regions of the visual field with a hemifield-tracking task. Younger and older participants performed an attentional tracking task in one hemifield while distractor objects were concurrently presented in the unattended hemifield. Feature similarity between objects in the attended and unattended hemifields as well as motion speed and the number of to-be-tracked objects were parametrically manipulated. The results show that increasing feature overlap leads to greater interference from the unattended visual field. This effect of feature-based interference was only present in the slow speed condition, indicating that the interference is mainly modulated by perceptual demands. High-performing older adults showed a similar interference effect as younger adults, whereas low-performing adults showed poor tracking performance overall.

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

PubMed

Rodríguez-Arias, Miquel Angel; Rodó, Xavier

2004-03-01

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Effect of infrastructure design on commons dilemmas in social-ecological system dynamics.

PubMed

Yu, David J; Qubbaj, Murad R; Muneepeerakul, Rachata; Anderies, John M; Aggarwal, Rimjhim M

2015-10-27

The use of shared infrastructure to direct natural processes for the benefit of humans has been a central feature of human social organization for millennia. Today, more than ever, people interact with one another and the environment through shared human-made infrastructure (the Internet, transportation, the energy grid, etc.). However, there has been relatively little work on how the design characteristics of shared infrastructure affect the dynamics of social-ecological systems (SESs) and the capacity of groups to solve social dilemmas associated with its provision. Developing such understanding is especially important in the context of global change where design criteria must consider how specific aspects of infrastructure affect the capacity of SESs to maintain vital functions in the face of shocks. Using small-scale irrigated agriculture (the most ancient and ubiquitous example of public infrastructure systems) as a model system, we show that two design features related to scale and the structure of benefit flows can induce fundamental changes in qualitative behavior, i.e., regime shifts. By relating the required maintenance threshold (a design feature related to infrastructure scale) to the incentives facing users under different regimes, our work also provides some general guidance on determinants of robustness of SESs under globalization-related stresses.

Effect of infrastructure design on commons dilemmas in social−ecological system dynamics

PubMed Central

Yu, David J.; Qubbaj, Murad R.; Muneepeerakul, Rachata; Anderies, John M.; Aggarwal, Rimjhim M.

2015-01-01

The use of shared infrastructure to direct natural processes for the benefit of humans has been a central feature of human social organization for millennia. Today, more than ever, people interact with one another and the environment through shared human-made infrastructure (the Internet, transportation, the energy grid, etc.). However, there has been relatively little work on how the design characteristics of shared infrastructure affect the dynamics of social−ecological systems (SESs) and the capacity of groups to solve social dilemmas associated with its provision. Developing such understanding is especially important in the context of global change where design criteria must consider how specific aspects of infrastructure affect the capacity of SESs to maintain vital functions in the face of shocks. Using small-scale irrigated agriculture (the most ancient and ubiquitous example of public infrastructure systems) as a model system, we show that two design features related to scale and the structure of benefit flows can induce fundamental changes in qualitative behavior, i.e., regime shifts. By relating the required maintenance threshold (a design feature related to infrastructure scale) to the incentives facing users under different regimes, our work also provides some general guidance on determinants of robustness of SESs under globalization-related stresses. PMID:26460043

Facial expression identification using 3D geometric features from Microsoft Kinect device

NASA Astrophysics Data System (ADS)

Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

2016-05-01

Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

Feature integration across space, time, and orientation

PubMed Central

Otto, Thomas U.; Öğmen, Haluk; Herzog, Michael H.

2012-01-01

The perception of a visual target can be strongly influenced by flanking stimuli. In static displays, performance on the target improves when the distance to the flanking elements increases- proposedly because feature pooling and integration vanishes with distance. Here, we studied feature integration with dynamic stimuli. We show that features of single elements presented within a continuous motion stream are integrated largely independent of spatial distance (and orientation). Hence, space based models of feature integration cannot be extended to dynamic stimuli. We suggest that feature integration is guided by perceptual grouping operations that maintain the identity of perceptual objects over space and time. PMID:19968428

Selective host molecules obtained by dynamic adaptive chemistry.

PubMed

Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

2014-02-17

Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Relaxation and physical aging in network glasses: a review.

PubMed

Micoulaut, Matthieu

2016-06-01

Recent progress in the description of glassy relaxation and aging are reviewed for the wide class of network-forming materials such as GeO2, Ge x Se1-x , silicates (SiO2-Na2O) or borates (B2O3-Li2O), all of which have an important usefulness in domestic, geological or optoelectronic applications. A brief introduction of the glass transition phenomenology is given, together with the salient features that are revealed both from theory and experiments. Standard experimental methods used for the characterization of the slowing down of the dynamics are reviewed. We then discuss the important role played by aspects of network topology and rigidity for the understanding of the relaxation of the glass transition, while also permitting analytical predictions of glass properties from simple and insightful models based on the network structure. We also emphasize the great utility of computer simulations which probe the dynamics at the molecular level, and permit the calculation of various structure-related functions in connection with glassy relaxation and the physics of aging which reveal the non-equilibrium nature of glasses. We discuss the notion of spatial variations of structure which leads to the concept of 'dynamic heterogeneities', and recent results in relation to this important topic for network glasses are also reviewed.

Counter-intuitive features of the dynamic topography unveiled by tectonically realistic 3D numerical models of mantle-lithosphere interactions

NASA Astrophysics Data System (ADS)

Burov, Evgueni; Gerya, Taras

2013-04-01

It has been long assumed that the dynamic topography associated with mantle-lithosphere interactions should be characterized by long-wavelength features (> 1000 km) correlating with morphology of mantle flow and expanding beyond the scale of tectonic processes. For example, debates on the existence of mantle plumes largely originate from interpretations of expected signatures of plume-induced topography that are compared to the predictions of analytical and numerical models of plume- or mantle-lithosphere interactions (MLI). Yet, most of the large-scale models treat the lithosphere as a homogeneous stagnant layer. We show that in continents, the dynamic topography is strongly affected by rheological properties and layered structure of the lithosphere. For that we reconcile mantle- and tectonic-scale models by introducing a tectonically realistic continental plate model in 3D large-scale plume-mantle-lithosphere interaction context. This model accounts for stratified structure of continental lithosphere, ductile and frictional (Mohr-Coulomb) plastic properties and thermodynamically consistent density variations. The experiments reveal a number of important differences from the predictions of the conventional models. In particular, plate bending, mechanical decoupling of crustal and mantle layers and intra-plate tension-compression instabilities result in transient topographic signatures such as alternating small-scale surface features that could be misinterpreted in terms of regional tectonics. Actually thick ductile lower crustal layer absorbs most of the "direct" dynamic topography and the features produced at surface are mostly controlled by the mechanical instabilities in the upper and intermediate crustal layers produced by MLI-induced shear and bending at Moho and LAB. Moreover, the 3D models predict anisotropic response of the lithosphere even in case of isotropic solicitations by axisymmetric mantle upwellings such as plumes. In particular, in presence of small (i.e. insufficient to produce solely any significant deformation) uniaxial extensional tectonic stress field, the plume-produced surface and LAB features have anisotropic linear shapes perpendicular to the far-field tectonic forces, typical for continental rifts. Compressional field results in singular sub-linear folds above the plume head, perpendicular to the direction of compression. Small bi-axial tectonic stress fields (compression in one direction and extension in the orthogonal direction) result in oblique, almost linear segmented normal or inverse faults with strike-slip components (or visa verse , strike-slip faults with normal or inverse components)

Time-Variable Transit Time Distributions in the Hyporheic Zone of a Headwater Mountain Stream

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.

2018-03-01

Exchange of water between streams and their hyporheic zones is known to be dynamic in response to hydrologic forcing, variable in space, and to exist in a framework with nested flow cells. The expected result of heterogeneous geomorphic setting, hydrologic forcing, and between-feature interaction is hyporheic transit times that are highly variable in both space and time. Transit time distributions (TTDs) are important as they reflect the potential for hyporheic processes to impact biogeochemical transformations and ecosystems. In this study we simulate time-variable transit time distributions based on dynamic vertical exchange in a headwater mountain stream with observed, heterogeneous step-pool morphology. Our simulations include hyporheic exchange over a 600 m river corridor reach driven by continuously observed, time-variable hydrologic conditions for more than 1 year. We found that spatial variability at an instance in time is typically larger than temporal variation for the reach. Furthermore, we found reach-scale TTDs were marginally variable under all but the most extreme hydrologic conditions, indicating that TTDs are highly transferable in time. Finally, we found that aggregation of annual variation in space and time into a "master TTD" reasonably represents most of the hydrologic dynamics simulated, suggesting that this aggregation approach may provide a relevant basis for scaling from features or short reaches to entire networks.

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

NASA Astrophysics Data System (ADS)

Chen, Lipeng; Zhao, Yang

2017-12-01

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

Geometric reduction of dynamical nonlocality in nanoscale quantum circuits.

PubMed

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

2016-01-06

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

Insights into structural and dynamical features of water at halloysite interfaces probed by DFT and classical molecular dynamics simulations.

PubMed

Presti, Davide; Pedone, Alfonso; Mancini, Giordano; Duce, Celia; Tiné, Maria Rosaria; Barone, Vincenzo

2016-01-21

Density functional theory calculations and classical molecular dynamics simulations have been used to investigate the structure and dynamics of water molecules on kaolinite surfaces and confined in the interlayer of a halloysite model of nanometric dimension. The first technique allowed us to accurately describe the structure of the tetrahedral-octahedral slab of kaolinite in vacuum and in interaction with water molecules and to assess the performance of two widely employed empirical force fields to model water/clay interfaces. Classical molecular dynamics simulations were used to study the hydrogen bond network structure and dynamics of water adsorbed on kaolinite surfaces and confined in the halloysite interlayer. The results are in nice agreement with the few experimental data available in the literature, showing a pronounced ordering and reduced mobility of water molecules at the hydrophilic octahedral surfaces of kaolinite and confined in the halloysite interlayer, with respect to water interacting with the hydrophobic tetrahedral surfaces and in the bulk. Finally, this investigation provides new atomistic insights into the structural and dynamical properties of water-clay interfaces, which are of fundamental importance for both natural processes and industrial applications.

A Self-Adaptive Dynamic Recognition Model for Fatigue Driving Based on Multi-Source Information and Two Levels of Fusion

PubMed Central

Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai

2015-01-01

To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615

Modeling the dynamic crush of impact mitigating materials

NASA Astrophysics Data System (ADS)

Logan, R. W.; McMichael, L. D.

1995-05-01

Crushable materials are commonly utilized in the design of structural components to absorb energy and mitigate shock during the dynamic impact of a complex structure, such as an automobile chassis or drum-type shipping container. The development and application of several finite-element material models which have been developed at various times at LLNL for DYNA3D are discussed. Between the models, they are able to account for several of the predominant mechanisms which typically influence the dynamic mechanical behavior of crushable materials. One issue we addressed was that no single existing model would account for the entire gambit of constitutive features which are important for crushable materials. Thus, we describe the implementation and use of an additional material model which attempts to provide a more comprehensive model of the mechanics of crushable material behavior. This model combines features of the pre-existing DYNA models and incorporates some new features as well in an invariant large-strain formulation. In addition to examining the behavior of a unit cell in uniaxial compression, two cases were chosen to evaluate the capabilities and accuracy of the various material models in DYNA. In the first case, a model for foam filled box beams was developed and compared to test data from a four-point bend test. The model was subsequently used to study its effectiveness in energy absorption in an aluminum extrusion, spaceframe, vehicle chassis. The second case examined the response of the AT-400A shipping container and the performance of the overpack material during accident environments selected from 10CFR71 and IAEA regulations.

Automated Fluid Feature Extraction from Transient Simulations

NASA Technical Reports Server (NTRS)

Haimes, Robert; Lovely, David

1999-01-01

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

The reflectivity, wettability and scratch durability of microsurface features molded in the injection molding process using a dynamic tool tempering system

NASA Astrophysics Data System (ADS)

Kuhn, Sascha; Burr, August; Kübler, Michael; Deckert, Matthias; Bleesen, Christoph

2011-02-01

In this paper the replication qualities of periodically and randomly arranged micro-features molded in the injection molding process and their effects on surface properties are studied. The features are molded in PC, PMMA and PP at different mold wall temperatures in order to point out the necessity and profitability of a variotherm mold wall temperature control system. A one-dimensional heat conduction model is proposed to predict the cycle times of the variotherm injection molding processes. With regard to these processes, the molding results are compared to the molded surface feature heights using an atomic force microscope. In addition, the effects of the molded surface features on macroscopic surfaces are characterized in terms of light reflection using a spectrometer and in terms of water wettability by measuring the static contact angle. Furthermore, due to the sensitivity of the surface features on the molded parts, their durability is compared in a scratch test with a diamond tip. This leads to successful implementation in applications in which the optical appearance, in terms of gloss and reflection, and the water repellence, in terms of drag flow and adhesion, are of importance.

Improving the long-lead predictability of El Niño using a novel forecasting scheme based on a dynamic components model

NASA Astrophysics Data System (ADS)

Petrova, Desislava; Koopman, Siem Jan; Ballester, Joan; Rodó, Xavier

2017-02-01

El Niño (EN) is a dominant feature of climate variability on inter-annual time scales driving changes in the climate throughout the globe, and having wide-spread natural and socio-economic consequences. In this sense, its forecast is an important task, and predictions are issued on a regular basis by a wide array of prediction schemes and climate centres around the world. This study explores a novel method for EN forecasting. In the state-of-the-art the advantageous statistical technique of unobserved components time series modeling, also known as structural time series modeling, has not been applied. Therefore, we have developed such a model where the statistical analysis, including parameter estimation and forecasting, is based on state space methods, and includes the celebrated Kalman filter. The distinguishing feature of this dynamic model is the decomposition of a time series into a range of stochastically time-varying components such as level (or trend), seasonal, cycles of different frequencies, irregular, and regression effects incorporated as explanatory covariates. These components are modeled separately and ultimately combined in a single forecasting scheme. Customary statistical models for EN prediction essentially use SST and wind stress in the equatorial Pacific. In addition to these, we introduce a new domain of regression variables accounting for the state of the subsurface ocean temperature in the western and central equatorial Pacific, motivated by our analysis, as well as by recent and classical research, showing that subsurface processes and heat accumulation there are fundamental for the genesis of EN. An important feature of the scheme is that different regression predictors are used at different lead months, thus capturing the dynamical evolution of the system and rendering more efficient forecasts. The new model has been tested with the prediction of all warm events that occurred in the period 1996-2015. Retrospective forecasts of these events were made for long lead times of at least two and a half years. Hence, the present study demonstrates that the theoretical limit of ENSO prediction should be sought much longer than the commonly accepted "Spring Barrier". The high correspondence between the forecasts and observations indicates that the proposed model outperforms all current operational statistical models, and behaves comparably to the best dynamical models used for EN prediction. Thus, the novel way in which the modeling scheme has been structured could also be used for improving other statistical and dynamical modeling systems.

Extremely selective attention: eye-tracking studies of the dynamic allocation of attention to stimulus features in categorization.

PubMed

Blair, Mark R; Watson, Marcus R; Walshe, R Calen; Maj, Fillip

2009-09-01

Humans have an extremely flexible ability to categorize regularities in their environment, in part because of attentional systems that allow them to focus on important perceptual information. In formal theories of categorization, attention is typically modeled with weights that selectively bias the processing of stimulus features. These theories make differing predictions about the degree of flexibility with which attention can be deployed in response to stimulus properties. Results from 2 eye-tracking studies show that humans can rapidly learn to differently allocate attention to members of different categories. These results provide the first unequivocal demonstration of stimulus-responsive attention in a categorization task. Furthermore, the authors found clear temporal patterns in the shifting of attention within trials that follow from the informativeness of particular stimulus features. These data provide new insights into the attention processes involved in categorization. (c) 2009 APA, all rights reserved.

Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex

PubMed Central

2010-01-01

Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project. PMID:18568015

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

PubMed Central

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

2016-01-01

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

Linguistic labels, dynamic visual features, and attention in infant category learning.

PubMed

Deng, Wei Sophia; Sloutsky, Vladimir M

2015-06-01

How do words affect categorization? According to some accounts, even early in development words are category markers and are different from other features. According to other accounts, early in development words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12-month-old infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye-tracking results indicated that infants exhibited better category learning in the motion-defined condition than in the label-defined condition, and their attention was more distributed among different features when there was a dynamic visual feature compared with the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Linguistic Labels, Dynamic Visual Features, and Attention in Infant Category Learning

PubMed Central

Deng, Wei (Sophia); Sloutsky, Vladimir M.

2015-01-01

How do words affect categorization? According to some accounts, even early in development, words are category markers and are different from other features. According to other accounts, early in development, words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12- month infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye tracking results indicated that infants exhibited better category learning in the motion-defined than in the label-defined condition and their attention was more distributed among different features when there was a dynamic visual feature compared to the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. PMID:25819100

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

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

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C.

2014-03-15

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strengthmore » the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.« less

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system.

PubMed

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B C

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

NASA Astrophysics Data System (ADS)

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B. C.

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Dynamics of Variable Mass Systems

NASA Technical Reports Server (NTRS)

Eke, Fidelis O.

1998-01-01

This report presents the results of an investigation of the effects of mass loss on the attitude behavior of spinning bodies in flight. The principal goal is to determine whether there are circumstances under which the motion of variable mass systems can become unstable in the sense that their transverse angular velocities become unbounded. Obviously, results from a study of this kind would find immediate application in the aerospace field. The first part of this study features a complete and mathematically rigorous derivation of a set of equations that govern both the translational and rotational motions of general variable mass systems. The remainder of the study is then devoted to the application of the equations obtained to a systematic investigation of the effect of various mass loss scenarios on the dynamics of increasingly complex models of variable mass systems. It is found that mass loss can have a major impact on the dynamics of mechanical systems, including a possible change in the systems stability picture. Factors such as nozzle geometry, combustion chamber geometry, propellant's initial shape, size and relative mass, and propellant location can all have important influences on the system's dynamic behavior. The relative importance of these parameters on-system motion are quantified in a way that is useful for design purposes.

A Structural Perspective on the Dynamics of Kinesin Motors

PubMed Central

Hyeon, Changbong; Onuchic, José N.

2011-01-01

Despite significant fluctuation under thermal noise, biological machines in cells perform their tasks with exquisite precision. Using molecular simulation of a coarse-grained model and theoretical arguments, we envisaged how kinesin, a prototype of biological machines, generates force and regulates its dynamics to sustain persistent motor action. A structure-based model, which can be versatile in adapting its structure to external stresses while maintaining its native fold, was employed to account for several features of kinesin dynamics along the biochemical cycle. This analysis complements our current understandings of kinesin dynamics and connections to experiments. We propose a thermodynamic cycle for kinesin that emphasizes the mechanical and regulatory role of the neck linker and clarify issues related to the motor directionality, and the difference between the external stalling force and the internal tension responsible for the head-head coordination. The comparison between the thermodynamic cycle of kinesin and macroscopic heat engines highlights the importance of structural change as the source of work production in biomolecular machines. PMID:22261064

Emotion unfolded by motion: a role for parietal lobe in decoding dynamic facial expressions.

PubMed

Sarkheil, Pegah; Goebel, Rainer; Schneider, Frank; Mathiak, Klaus

2013-12-01

Facial expressions convey important emotional and social information and are frequently applied in investigations of human affective processing. Dynamic faces may provide higher ecological validity to examine perceptual and cognitive processing of facial expressions. Higher order processing of emotional faces was addressed by varying the task and virtual face models systematically. Blood oxygenation level-dependent activation was assessed using functional magnetic resonance imaging in 20 healthy volunteers while viewing and evaluating either emotion or gender intensity of dynamic face stimuli. A general linear model analysis revealed that high valence activated a network of motion-responsive areas, indicating that visual motion areas support perceptual coding for the motion-based intensity of facial expressions. The comparison of emotion with gender discrimination task revealed increased activation of inferior parietal lobule, which highlights the involvement of parietal areas in processing of high level features of faces. Dynamic emotional stimuli may help to emphasize functions of the hypothesized 'extended' over the 'core' system for face processing.

Vehicle-pedestrian collisions - Aspects regarding pedestrian kinematics, dynamics and biomechanics

NASA Astrophysics Data System (ADS)

Petrescu, L.; Petrescu, Al

2017-10-01

Vehicle-pedestrian collisions result in a substantial number of pedestrian fatalities and injuries worldwide. Concern continues to limit and reduce the tragic consequences suffered by pedestrians involved in road accidents, caused the vehicle-pedestrian accident reconstruction become an important area and distinctly outlined in the reconstruction of road incidents involving vehicle. This paper analyzes the dynamics of vehicle-pedestrian impact influence over pedestrian biomechanics, which is directly connected with the severity of injury after contact with the vehicle profile and with the place where the pedestrian is projected. The main goal of this paper is to highlight some features of reconstruction of road accidents involving pedestrian, looking at the kinematics and dynamics of pedestrian impact for a better understanding of the phenomena that occur. The study on the dynamics and biomechanics of the pedestrian hit by the vehicle is useful in order to understand how the injuries, including the lethal ones, are generated in the collision, what is essential in road accidents reconstruction.

sedFlow - an efficient tool for simulating bedload transport, bed roughness, and longitudinal profile evolution in mountain streams

NASA Astrophysics Data System (ADS)

Heimann, F. U. M.; Rickenmann, D.; Turowski, J. M.; Kirchner, J. W.

2014-07-01

Especially in mountainuous environments, the prediction of sediment dynamics is important for managing natural hazards, assessing in-stream habitats, and understanding geomorphic evolution. We present the new modelling tool sedFlow for simulating fractional bedload transport dynamics in mountain streams. The model can deal with the effects of adverse slopes and uses state of the art approaches for quantifying macro-roughness effects in steep channels. Local grain size distributions are dynamically adjusted according to the transport dynamics of each grain size fraction. The tool sedFlow features fast calculations and straightforward pre- and postprocessing of simulation data. The model is provided together with its complete source code free of charge under the terms of the GNU General Public License (www.wsl.ch/sedFlow). Examples of the application of sedFlow are given in a companion article by Heimann et al. (2014).

Understanding dynamic friction through spontaneously evolving laboratory earthquakes

PubMed Central

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

2017-01-01

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

Super-resolution microscopy reveals cell wall dynamics and peptidoglycan architecture in ovococcal bacteria.

PubMed

Wheeler, Richard; Mesnage, Stéphane; Boneca, Ivo G; Hobbs, Jamie K; Foster, Simon J

2011-12-01

Cell morphology and viability in Eubacteria is dictated by the architecture of peptidoglycan, the major and essential structural component of the cell wall. Although the biochemical composition of peptidoglycan is well understood, how the peptidoglycan architecture can accommodate the dynamics of growth and division while maintaining cell shape remains largely unknown. Here, we elucidate the peptidoglycan architecture and dynamics of bacteria with ovoid cell shape (ovococci), which includes a number of important pathogens, by combining biochemical analyses with atomic force and super-resolution microscopies. Atomic force microscopy analysis showed preferential orientation of the peptidoglycan network parallel to the short axis of the cell, with distinct architectural features associated with septal and peripheral wall synthesis. Super-resolution three-dimensional structured illumination fluorescence microscopy was applied for the first time in bacteria to unravel the dynamics of peptidoglycan assembly in ovococci. The ovococci have a unique peptidoglycan architecture and growth mode not observed in other model organisms. © 2011 Blackwell Publishing Ltd.

Modeling and complexity of stochastic interacting Lévy type financial price dynamics

NASA Astrophysics Data System (ADS)

Wang, Yiduan; Zheng, Shenzhou; Zhang, Wei; Wang, Jun; Wang, Guochao

2018-06-01

In attempt to reproduce and investigate nonlinear dynamics of security markets, a novel nonlinear random interacting price dynamics, which is considered as a Lévy type process, is developed and investigated by the combination of lattice oriented percolation and Potts dynamics, which concerns with the instinctive random fluctuation and the fluctuation caused by the spread of the investors' trading attitudes, respectively. To better understand the fluctuation complexity properties of the proposed model, the complexity analyses of random logarithmic price return and corresponding volatility series are preformed, including power-law distribution, Lempel-Ziv complexity and fractional sample entropy. In order to verify the rationality of the proposed model, the corresponding studies of actual security market datasets are also implemented for comparison. The empirical results reveal that this financial price model can reproduce some important complexity features of actual security markets to some extent. The complexity of returns decreases with the increase of parameters γ1 and β respectively, furthermore, the volatility series exhibit lower complexity than the return series

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

The IRM fluxgate magnetometer

NASA Technical Reports Server (NTRS)

Luehr, H.; Kloecker, N.; Oelschlaegel, W.; Haeusler, B.; Acuna, M.

1985-01-01

This report describes the three-axis fluxgate magnetometer instrument on board the AMPTE IRM spacecraft. Important features of the instrument are its wide dynamic range (0.1-60,000 nT), a high resolution (16-bit analog to digital conversion) and the capability to operate automatically or via telecommand in two gain states. In addition, the wave activity is monitored in all three components up to 50 Hz. Inflight checkout proved the nominal functioning of the instrument in all modes.

Potential Vorticity Streamers as Precursors to Tropical Cyclone Genesis in the Western Pacific

DTIC Science & Technology

2012-03-01

study a developing system with an extratropical precursor (TCS-037) developing into Tropical Storm 16W (TS 16W)” (Schönenberger 2010). This subsection...tropopause maps), the TC genesis event is termed a tropical transition (TT) case. If no such extratropical feature 38 is present, the storm in... extratropical origin is deemed to play an important role in the dynamical evolution leading to tropical cyclogenesis. In contrast, non-TT storms

An investigation of the astronomical theory of the ice ages using a simple climate-ice sheet model

NASA Technical Reports Server (NTRS)

Pollard, D.

1978-01-01

The astronomical theory of the Quaternary ice ages is incorporated into a simple climate model for global weather; important features of the model include the albedo feedback, topography and dynamics of the ice sheets. For various parameterizations of the orbital elements, the model yields realistic assessments of the northern ice sheet. Lack of a land-sea heat capacity contrast represents one of the chief difficulties of the model.

The prediction of palmitoylation site locations using a multiple feature extraction method.

PubMed

Shi, Shao-Ping; Sun, Xing-Yu; Qiu, Jian-Ding; Suo, Sheng-Bao; Chen, Xiang; Huang, Shu-Yun; Liang, Ru-Ping

2013-03-01

As an extremely important and ubiquitous post-translational lipid modification, palmitoylation plays a significant role in a variety of biological and physiological processes. Unlike other lipid modifications, protein palmitoylation and depalmitoylation are highly dynamic and can regulate both protein function and localization. The dynamic nature of palmitoylation is poorly understood because of the limitations in current assay methods. The in vivo or in vitro experimental identification of palmitoylation sites is both time consuming and expensive. Due to the large volume of protein sequences generated in the post-genomic era, it is extraordinarily important in both basic research and drug discovery to rapidly identify the attributes of a new protein's palmitoylation sites. In this work, a new computational method, WAP-Palm, combining multiple feature extraction, has been developed to predict the palmitoylation sites of proteins. The performance of the WAP-Palm model is measured herein and was found to have a sensitivity of 81.53%, a specificity of 90.45%, an accuracy of 85.99% and a Matthews correlation coefficient of 72.26% in 10-fold cross-validation test. The results obtained from both the cross-validation and independent tests suggest that the WAP-Palm model might facilitate the identification and annotation of protein palmitoylation locations. The online service is available at http://bioinfo.ncu.edu.cn/WAP-Palm.aspx. Copyright © 2013 Elsevier Inc. All rights reserved.

Solvation Dynamics in Different Phases of the Lyotropic Liquid Crystalline System.

PubMed

Roy, Bibhisan; Satpathi, Sagar; Gavvala, Krishna; Koninti, Raj Kumar; Hazra, Partha

2015-09-03

Reverse hexagonal (HII) liquid crystalline material based on glycerol monooleate (GMO) is considered as a potential carrier for drugs and other important biomolecules due to its thermotropic phase change and excellent morphology. In this work, the dynamics of encapsulated water, which plays important role in stabilization and formation of reverse hexagonal mesophase, has been investigated by time dependent Stokes shift method using Coumarin-343 as a solvation probe. The formation of the reverse hexagonal mesophase (HII) and transformation to the L2 phase have been monitored using small-angle X-ray scattering and polarized light microscopy experiments. REES studies suggest the existence of different polar regions in both HII and L2 systems. The solvation dynamics study inside the reverse hexagonal (HII) phase reveals the existence of two different types of water molecules exhibiting dynamics on a 120-900 ps time scale. The estimated diffusion coefficients of both types of water molecules obtained from the observed dynamics are in good agreement with the measured diffusion coefficient collected from the NMR study. The calculated activation energy is found to be 2.05 kcal/mol, which is associated with coupled rotational-translational water relaxation dynamics upon the transition from "bound" to "quasi-free" state. The observed ∼2 ns faster dynamics of the L2 phase compared to the HII phase may be associated with both the phase transformation as well as thermotropic effect on the relaxation process. Microviscosities calculated from time-resolved anisotropy studies infer that the interface is almost ∼22 times higher viscous than the central part of the cylinder. Overall, our results reveal the unique dynamical features of water inside the cylinder of reverse hexagonal and inverse micellar phases.

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

PubMed

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

2018-06-07

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

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

PubMed

Mereghetti, Paolo; Wade, Rebecca C

2012-07-26

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

Multi-frame X-ray Phase Contrast Imaging (MPCI) for Dynamic Experiments

NASA Astrophysics Data System (ADS)

Iverson, Adam; Carlson, Carl; Sanchez, Nathaniel; Jensen, Brian

2017-06-01

Recent advances in coupling synchrotron X-ray diagnostics to dynamic experiments are providing new information about the response of materials at extremes. For example, propagation based X-ray Phase Contrast Imaging (PCI) which is sensitive to differences in density has been successfully used to study a wide range of phenomena, e.g. jet-formation, compression of additive manufactured (AM) materials, and detonator dynamics. In this talk, we describe the current multi-frame X-ray phase contrast imaging (MPCI) system which allows up to eight frames per experiment, remote optimization, and an improved optical design that increases optical efficiency and accommodates dual-magnification during a dynamic event. Data will be presented that used the dual-magnification feature to obtain multiple images of an exploding foil initiator. In addition, results from static testing will be presented that used a multiple scintillator configuration required to extend the density retrieval to multi-constituent, or heterogeneous systems. The continued development of this diagnostic is fundamentally important to capabilities at the APS including IMPULSE and the Dynamic Compression Sector (DCS), and will benefit future facilities such as MaRIE at Los Alamos National Laboratory.

Multiplex visibility graphs to investigate recurrent neural network dynamics

NASA Astrophysics Data System (ADS)

Bianchi, Filippo Maria; Livi, Lorenzo; Alippi, Cesare; Jenssen, Robert

2017-03-01

A recurrent neural network (RNN) is a universal approximator of dynamical systems, whose performance often depends on sensitive hyperparameters. Tuning them properly may be difficult and, typically, based on a trial-and-error approach. In this work, we adopt a graph-based framework to interpret and characterize internal dynamics of a class of RNNs called echo state networks (ESNs). We design principled unsupervised methods to derive hyperparameters configurations yielding maximal ESN performance, expressed in terms of prediction error and memory capacity. In particular, we propose to model time series generated by each neuron activations with a horizontal visibility graph, whose topological properties have been shown to be related to the underlying system dynamics. Successively, horizontal visibility graphs associated with all neurons become layers of a larger structure called a multiplex. We show that topological properties of such a multiplex reflect important features of ESN dynamics that can be used to guide the tuning of its hyperparamers. Results obtained on several benchmarks and a real-world dataset of telephone call data records show the effectiveness of the proposed methods.

Multiplex visibility graphs to investigate recurrent neural network dynamics

PubMed Central

Bianchi, Filippo Maria; Livi, Lorenzo; Alippi, Cesare; Jenssen, Robert

2017-01-01

A recurrent neural network (RNN) is a universal approximator of dynamical systems, whose performance often depends on sensitive hyperparameters. Tuning them properly may be difficult and, typically, based on a trial-and-error approach. In this work, we adopt a graph-based framework to interpret and characterize internal dynamics of a class of RNNs called echo state networks (ESNs). We design principled unsupervised methods to derive hyperparameters configurations yielding maximal ESN performance, expressed in terms of prediction error and memory capacity. In particular, we propose to model time series generated by each neuron activations with a horizontal visibility graph, whose topological properties have been shown to be related to the underlying system dynamics. Successively, horizontal visibility graphs associated with all neurons become layers of a larger structure called a multiplex. We show that topological properties of such a multiplex reflect important features of ESN dynamics that can be used to guide the tuning of its hyperparamers. Results obtained on several benchmarks and a real-world dataset of telephone call data records show the effectiveness of the proposed methods. PMID:28281563

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

PubMed Central

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

2017-01-01

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

Gut Microbial Succession Follows Acute Secretory Diarrhea in Humans

PubMed Central

David, Lawrence A.; Weil, Ana; Ryan, Edward T.; Calderwood, Stephen B.; Harris, Jason B.; Chowdhury, Fahima; Begum, Yasmin; Qadri, Firdausi

2015-01-01

ABSTRACT Disability after childhood diarrhea is an important burden on global productivity. Recent studies suggest that gut bacterial communities influence how humans recover from infectious diarrhea, but we still lack extensive data and mechanistic hypotheses for how these bacterial communities respond to diarrheal disease and its treatment. Here, we report that after Vibrio cholerae infection, the human gut microbiota undergoes an orderly and reproducible succession that features transient reversals in relative levels of enteric Bacteroides and Prevotella. Elements of this succession may be a common feature in microbiota recovery from acute secretory diarrhea, as we observed similar successional dynamics after enterotoxigenic Escherichia coli (ETEC) infection. Our metagenomic analyses suggest that multiple mechanisms drive microbial succession after cholera, including bacterial dispersal properties, changing enteric oxygen and carbohydrate levels, and phage dynamics. Thus, gut microbiota recovery after cholera may be predictable at the level of community structure but is driven by a complex set of temporally varying ecological processes. Our findings suggest opportunities for diagnostics and therapies targeting the gut microbiota in humans recovering from infectious diarrhea. PMID:25991682

Dimension reduction and multiscaling law through source extraction

NASA Astrophysics Data System (ADS)

Capobianco, Enrico

2003-04-01

Through the empirical analysis of financial return generating processes one may find features that are common to other research fields, such as internet data from network traffic, physiological studies about human heart beat, speech and sleep recorded time series, geophysics signals, just to mention well-known cases of study. In particular, long range dependence, intermittency, heteroscedasticity are clearly appearing, and consequently power laws and multi-scaling behavior result typical signatures of either the spectral or the time correlation diagnostics. We study these features and the dynamics underlying financial volatility, which can respectively be detected and inferred from high frequency realizations of stock index returns, and show that they vary according to the resolution levels used for both the analysis and the synthesis of the available information. Discovering whether the volatility dynamics are subject to changes in scaling regimes requires the consideration of a model embedding scale-dependent information packets, thus accounting for possible heterogeneous activity occurring in financial markets. Independent component analysis result to be an important tool for reducing the dimension of the problem and calibrating greedy approximation techniques aimed to learn the structure of the underlying volatility.

Comparing Dynamic Treatment Regimes Using Repeated-Measures Outcomes: Modeling Considerations in SMART Studies

PubMed Central

Lu, Xi; Nahum-Shani, Inbal; Kasari, Connie; Lynch, Kevin G.; Oslin, David W.; Pelham, William E.; Fabiano, Gregory; Almirall, Daniel

2016-01-01

A dynamic treatment regime (DTR) is a sequence of decision rules, each of which recommends a treatment based on a patient’s past and current health status. Sequential, multiple assignment, randomized trials (SMARTs) are multi-stage trial designs that yield data specifically for building effective DTRs. Modeling the marginal mean trajectories of a repeated-measures outcome arising from a SMART presents challenges, because traditional longitudinal models used for randomized clinical trials do not take into account the unique design features of SMART. We discuss modeling considerations for various forms of SMART designs, emphasizing the importance of considering the timing of repeated measures in relation to the treatment stages in a SMART. For illustration, we use data from three SMART case studies with increasing level of complexity, in autism, child attention deficit hyperactivity disorder (ADHD), and adult alcoholism. In all three SMARTs we illustrate how to accommodate the design features along with the timing of the repeated measures when comparing DTRs based on mean trajectories of the repeated-measures outcome. PMID:26638988

Urban sprawl and fragmentation in Latin America: a dynamic quantification and characterization of spatial patterns.

PubMed

Inostroza, Luis; Baur, Rolf; Csaplovics, Elmar

2013-01-30

South America is one of the most urbanized continents in the world, where almost 84% of the total population lives in cities, more urbanized than North America (82%) and Europe (73%). Spatial dynamics, their structure, main features, land consumption rates, spatial arrangement, fragmentation degrees and comparability, remain mostly unknown for most Latin American cities. Using satellite imagery the main parameters of sprawl are quantified for 10 Latin American cities over a period of 20 years by monitoring growth patterns and identifying spatial metrics to characterize urban development and sprawling features measured with GIS tools. This quantification contributes to a better understanding of urban form in Latin America. A pervasive spatial expansion has been observed, where most of the studied cities are expanding at fast rates with falling densities trend. Although important differences in the rates of land consumption and densities exist, there is an underlying fragmentation trend towards increasing sprawl. These trends of spatial discontinuity may eventually be intensified by further economic development. Urban Sprawl/Latin America/GIS metrics/spatial development. Copyright © 2012 Elsevier Ltd. All rights reserved.

A rare gas optics-free absolute photon flux and energy analyzer to provide absolute photoionization rates of inflowing interstellar neutrals

NASA Technical Reports Server (NTRS)

Judge, Darrell L.

1994-01-01

A prototype spectrometer has been developed for space applications requiring long term absolute EUV photon flux measurements. The energy spectrum of the incoming photons is transformed directly into an electron energy spectrum by taking advantage of the photoelectric effect in one of several rare gases at low pressures. Using an electron energy spectrometer, followed by an electron multiplier detector, pulses due to individual electrons are counted. The overall efficiency of this process can be made essentially independent of gain drifts in the signal path, and the secular degradation of optical components which is often a problem in other techniques is avoided. A very important feature of this approach is its freedom from the problem of overlapping spectral orders that plagues grating EUV spectrometers. An instrument with these features has not been flown before, but is essential to further advances in our understanding of solar EUV flux dynamics, and the coupled dynamics of terrestrial and planetary atmospheres. The detailed characteristics of this optics-free spectrometer are presented in the publications section.

A rare gas optics-free absolute photon flux and energy analyzer for solar and planetary observations

NASA Technical Reports Server (NTRS)

Judge, Darrell L.

1994-01-01

We have developed a prototype spectrometer for space applications requiring long term absolute EUV photon flux measurements. In this recently developed spectrometer, the energy spectrum of the incoming photons is transformed directly into an electron energy spectrum by taking advantage of the photoelectric effect in one of several rare gases at low pressures. Using an electron energy spectrometer, followed by an electron multiplier detector, pulses due to individual electrons are counted. The overall efficiency of this process can be made essentially independent of gain drifts in the signal path, and the secular degradation of optical components which is often a problem in other techniques is avoided. A very important feature of this approach is its freedom from the problem of overlapping spectral orders that plagues grating EUV spectrometers. An instrument with these features has not been flown before, but is essential to further advances in our understanding of solar EUV flux dynamics, and the coupled dynamics of terrestrial and planetary atmospheres. The detailed characteristics of this optics-free spectrometer are presented in the publications section.

Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies.

PubMed

Lu, Xi; Nahum-Shani, Inbal; Kasari, Connie; Lynch, Kevin G; Oslin, David W; Pelham, William E; Fabiano, Gregory; Almirall, Daniel

2016-05-10

A dynamic treatment regime (DTR) is a sequence of decision rules, each of which recommends a treatment based on a patient's past and current health status. Sequential, multiple assignment, randomized trials (SMARTs) are multi-stage trial designs that yield data specifically for building effective DTRs. Modeling the marginal mean trajectories of a repeated-measures outcome arising from a SMART presents challenges, because traditional longitudinal models used for randomized clinical trials do not take into account the unique design features of SMART. We discuss modeling considerations for various forms of SMART designs, emphasizing the importance of considering the timing of repeated measures in relation to the treatment stages in a SMART. For illustration, we use data from three SMART case studies with increasing level of complexity, in autism, child attention deficit hyperactivity disorder, and adult alcoholism. In all three SMARTs, we illustrate how to accommodate the design features along with the timing of the repeated measures when comparing DTRs based on mean trajectories of the repeated-measures outcome. Copyright © 2015 John Wiley & Sons, Ltd.

Radiotherapy volume delineation using dynamic [18F]-FDG PET/CT imaging in patients with oropharyngeal cancer: a pilot study.

PubMed

Silvoniemi, Antti; Din, Mueez U; Suilamo, Sami; Shepherd, Tony; Minn, Heikki

2016-11-01

Delineation of gross tumour volume in 3D is a critical step in the radiotherapy (RT) treatment planning for oropharyngeal cancer (OPC). Static [ 18 F]-FDG PET/CT imaging has been suggested as a method to improve the reproducibility of tumour delineation, but it suffers from low specificity. We undertook this pilot study in which dynamic features in time-activity curves (TACs) of [ 18 F]-FDG PET/CT images were applied to help the discrimination of tumour from inflammation and adjacent normal tissue. Five patients with OPC underwent dynamic [ 18 F]-FDG PET/CT imaging in treatment position. Voxel-by-voxel analysis was performed to evaluate seven dynamic features developed with the knowledge of differences in glucose metabolism in different tissue types and visual inspection of TACs. The Gaussian mixture model and K-means algorithms were used to evaluate the performance of the dynamic features in discriminating tumour voxels compared to the performance of standardized uptake values obtained from static imaging. Some dynamic features showed a trend towards discrimination of different metabolic areas but lack of consistency means that clinical application is not recommended based on these results alone. Impact of inflammatory tissue remains a problem for volume delineation in RT of OPC, but a simple dynamic imaging protocol proved practicable and enabled simple data analysis techniques that show promise for complementing the information in static uptake values.

Many Specialists for Suppressing Cortical Excitation

PubMed Central

Burkhalter, Andreas

2008-01-01

Cortical computations are critically dependent on GABA-releasing neurons for dynamically balancing excitation with inhibition that is proportional to the overall level of activity. Although it is widely accepted that there are multiple types of interneurons, defining their identities based on qualitative descriptions of morphological, molecular and physiological features has failed to produce a universally accepted ‘parts list’, which is needed to understand the roles that interneurons play in cortical processing. A list of features has been published by the Petilla Interneurons Nomenclature Group, which represents an important step toward an unbiased classification of interneurons. To this end some essential features have recently been studied quantitatively and their association was examined using multidimensional cluster analyses. These studies revealed at least 3 distinct electrophysiological, 6 morphological and 15 molecular phenotypes. This is a conservative estimate of the number of interneuron types, which almost certainly will be revised as more quantitative studies will be performed and similarities will be defined objectively. It is clear that interneurons are organized with physiological attributes representing the most general, molecular characteristics the most detailed and morphological features occupying the middle ground. By themselves, none of these features are sufficient to define classes of interneurons. The challenge will be to determine which features belong together and how cell type-specific feature combinations are genetically specified. PMID:19225588

Using LabView for real-time monitoring and tracking of multiple biological objects

NASA Astrophysics Data System (ADS)

Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

2017-04-01

Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

Topological edge states and impurities: Manifestation in the local static and dynamical characteristics of dimerized quantum chains

NASA Astrophysics Data System (ADS)

Zvyagin, A. A.

2018-04-01

Based on the results of exact analytic calculations, we show that topological edge states and impurities in quantum dimerized chains manifest themselves in various local static and dynamical characteristics, which can be measured in experiments. In particular, topological edge states can be observed in the magnetic field behavior of the local magnetization or magnetic susceptibility of dimerized spin chains as jumps (for the magnetization) and features (for the static susceptibility) at zero field. In contrast, impurities reveal themselves in similar jumps and features, however, at nonzero values of the critical field. We also show that dynamical characteristics of dimerized quantum chains also manifest the features, related to the topological edge states and impurities. Those features, as a rule, can be seen more sharply than the manifestation of bulk extended states in, e.g., the dynamical local susceptibility. Such peculiarities can be observed in one-dimensional dimerized spin chains, e.g., in NMR experiments, or in various realizations of quantum dimerized chains in optical experiments.

Dynamics of epidemic diseases on a growing adaptive network

PubMed Central

Demirel, Güven; Barter, Edmund; Gross, Thilo

2017-01-01

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists. PMID:28186146

Dynamics of epidemic diseases on a growing adaptive network.

PubMed

Demirel, Güven; Barter, Edmund; Gross, Thilo

2017-02-10

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

Dynamics of epidemic diseases on a growing adaptive network

NASA Astrophysics Data System (ADS)

Demirel, Güven; Barter, Edmund; Gross, Thilo

2017-02-01

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

Universal evaporation dynamics of a confined sessile droplet

NASA Astrophysics Data System (ADS)

Bansal, Lalit; Hatte, Sandeep; Basu, Saptarshi; Chakraborty, Suman

2017-09-01

Droplet evaporation under confinement is ubiquitous to multitude of applications such as microfluidics, surface patterning, and ink-jet printing. However, the rich physics governing the universality in the underlying dynamics remains grossly elusive. Here, we bring out hitherto unexplored universal features of the evaporation dynamics of a sessile droplet entrapped in a 3D confined fluidic environment. We show, through extensive set of experiments and theoretical formulations, that the evaporation timescale for such a droplet can be represented by a unique function of the initial conditions. Moreover, using same theoretical considerations, we are able to trace and universally merge the volume evolution history of the droplets along with evaporation lifetimes, irrespective of the extent of confinement. We also showcase the internal flow transitions caused by spatio-temporal variation of evaporation flux due to confinement. These findings may be of profound importance in designing functionalized droplet evaporation devices for emerging engineering and biomedical applications.

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

Yurk, Brian P; Cobbold, Christina A

2018-12-01

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

Quantum Critical Point revisited by the Dynamical Mean Field Theory

NASA Astrophysics Data System (ADS)

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei

Dynamical mean field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low energy kink and the high energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high energy antiferromagnetic paramagnons. We use the frequency dependent four-point correlation function of spin operators to calculate the momentum dependent correction to the electron self energy. Our results reveal a substantial difference with the calculations based on the Spin-Fermion model which indicates that the frequency dependence of the the quasiparitcle-paramagnon vertices is an important factor. The authors are supported by Center for Computational Design of Functional Strongly Correlated Materials and Theoretical Spectroscopy under DOE Grant DE-FOA-0001276.

Patterns of gender development.

PubMed

Martin, Carol Lynn; Ruble, Diane N

2010-01-01

A comprehensive theory of gender development must describe and explain long-term developmental patterning and changes and how gender is experienced in the short term. This review considers multiple views on gender patterning, illustrated with contemporary research. First, because developmental research involves understanding normative patterns of change with age, several theoretically important topics illustrate gender development: how children come to recognize gender distinctions and understand stereotypes, and the emergence of prejudice and sexism. Second, developmental researchers study the stability of individual differences over time, which elucidates developmental processes. We review stability in two domains-sex segregation and activities/interests. Finally, a new approach advances understanding of developmental patterns, based on dynamic systems theory. Dynamic systems theory is a metatheoretical framework for studying stability and change, which developed from the study of complex and nonlinear systems in physics and mathematics. Some major features and examples show how dynamic approaches have been and could be applied in studying gender development.

From electromyographic activity to frequency modulation in zebra finch song.

PubMed

Döppler, Juan F; Bush, Alan; Goller, Franz; Mindlin, Gabriel B

2018-02-01

Behavior emerges from the interaction between the nervous system and peripheral devices. In the case of birdsong production, a delicate and fast control of several muscles is required to control the configuration of the syrinx (the avian vocal organ) and the respiratory system. In particular, the syringealis ventralis muscle is involved in the control of the tension of the vibrating labia and thus affects the frequency modulation of the sound. Nevertheless, the translation of the instructions (which are electrical in nature) into acoustical features is complex and involves nonlinear, dynamical processes. In this work, we present a model of the dynamics of the syringealis ventralis muscle and the labia, which allows calculating the frequency of the generated sound, using as input the electrical activity recorded in the muscle. In addition, the model provides a framework to interpret inter-syllabic activity and hints at the importance of the biomechanical dynamics in determining behavior.

Patterns of Gender Development

PubMed Central

Martin, Carol Lynn; Ruble, Diane N.

2013-01-01

A comprehensive theory of gender development must describe and explain long-term developmental patterning and changes and how gender is experienced in the short term. This review considers multiple views on gender patterning, illustrated with contemporary research. First, because developmental research involves understanding normative patterns of change with age, several theoretically important topics illustrate gender development: how children come to recognize gender distinctions and understand stereotypes, and the emergence of prejudice and sexism. Second, developmental researchers study the stability of individual differences over time, which elucidates developmental processes. We review stability in two domains—sex segregation and activities/interests. Finally, a new approach advances understanding of developmental patterns, based on dynamic systems theory. Dynamic systems theory is a metatheoretical framework for studying stability and change, which developed from the study of complex and nonlinear systems in physics and mathematics. Some major features and examples show how dynamic approaches have been and could be applied in studying gender development. PMID:19575615

From supramolecular chemistry towards constitutional dynamic chemistry and adaptive chemistry.

PubMed

Lehn, Jean-Marie

2007-02-01

Supramolecular chemistry has developed over the last forty years as chemistry beyond the molecule. Starting with the investigation of the basis of molecular recognition, it has explored the implementation of molecular information in the programming of chemical systems towards self-organisation processes, that may occur either on the basis of design or with selection of their components. Supramolecular entities are by nature constitutionally dynamic by virtue of the lability of non-covalent interactions. Importing such features into molecular chemistry, through the introduction of reversible bonds into molecules, leads to the emergence of a constitutional dynamic chemistry, covering both the molecular and supramolecular levels. It considers chemical objects and systems capable of responding to external solicitations by modification of their constitution through component exchange or reorganisation. It thus opens the way towards an adaptive and evolutive chemistry, a further step towards the chemistry of complex matter.

Intermediate disturbance in experimental landscapes improves persistence of beetle metapopulations.

PubMed

Govindan, Byju N; Feng, Zhilan; DeWoody, Yssa D; Swihart, Robert K

2015-03-01

Human-dominated landscapes often feature patches that fluctuate in suitability through space and time, but there is little experimental evidence relating the consequences of dynamic patches for species persistence. We used a spatially and temporally dynamic metapopulation model to assess and compare metapopulation capacity and persistence for red flour beetles (Tribolium castaneum) in experimental landscapes differentiated by resource structure, patch dynamics (destruction and restoration), and connectivity. High connectivity increased the colonization rate of beetles, but this effect was less pronounced in heterogeneous relative to homogeneous landscapes. Higher connectivity and faster patch dynamics increased extinction rates in landscapes. Lower connectivity promoted density-dependent emigration. Heterogeneous landscapes containing patches of different carrying capacity enhanced landscape-level occupancy probability. The highest metapopulation capacity and persistence was observed in landscapes with heterogeneous patches, low connectivity, and slow patch dynamics. Control landscapes with no patch dynamics exhibited rapid declines in abundance and approached extinction due to increased adult mortality in the matrix, higher pupal cannibalism by adults, and extremely low rates of exchange between remaining habitable patches. Our results highlight the role of intermediate patch dynamics, intermediate connectivity, and the nature of density dependence of emigration for persistence of species in heterogeneous landscapes. Our results also demonstrate the importance of incorporating local dynamics into the estimation of metapopulation capacity for conservation planning.

Organizational contextual features that influence the implementation of evidence-based practices across healthcare settings: a systematic integrative review.

PubMed

Li, Shelly-Anne; Jeffs, Lianne; Barwick, Melanie; Stevens, Bonnie

2018-05-05

Organizational contextual features have been recognized as important determinants for implementing evidence-based practices across healthcare settings for over a decade. However, implementation scientists have not reached consensus on which features are most important for implementing evidence-based practices. The aims of this review were to identify the most commonly reported organizational contextual features that influence the implementation of evidence-based practices across healthcare settings, and to describe how these features affect implementation. An integrative review was undertaken following literature searches in CINAHL, MEDLINE, PsycINFO, EMBASE, Web of Science, and Cochrane databases from January 2005 to June 2017. English language, peer-reviewed empirical studies exploring organizational context in at least one implementation initiative within a healthcare setting were included. Quality appraisal of the included studies was performed using the Mixed Methods Appraisal Tool. Inductive content analysis informed data extraction and reduction. The search generated 5152 citations. After removing duplicates and applying eligibility criteria, 36 journal articles were included. The majority (n = 20) of the study designs were qualitative, 11 were quantitative, and 5 used a mixed methods approach. Six main organizational contextual features (organizational culture; leadership; networks and communication; resources; evaluation, monitoring and feedback; and champions) were most commonly reported to influence implementation outcomes in the selected studies across a wide range of healthcare settings. We identified six organizational contextual features that appear to be interrelated and work synergistically to influence the implementation of evidence-based practices within an organization. Organizational contextual features did not influence implementation efforts independently from other features. Rather, features were interrelated and often influenced each other in complex, dynamic ways to effect change. These features corresponded to the constructs in the Consolidated Framework for Implementation Research (CFIR), which supports the use of CFIR as a guiding framework for studies that explore the relationship between organizational context and implementation. Organizational culture was most commonly reported to affect implementation. Leadership exerted influence on the five other features, indicating it may be a moderator or mediator that enhances or impedes the implementation of evidence-based practices. Future research should focus on how organizational features interact to influence implementation effectiveness.

Effects of inverting contour and features on processing for static and dynamic face perception: an MEG study.

PubMed

Miki, Kensaku; Takeshima, Yasuyuki; Watanabe, Shoko; Honda, Yukiko; Kakigi, Ryusuke

2011-04-06

We investigated the effects of inverting facial contour (hair and chin) and features (eyes, nose and mouth) on processing for static and dynamic face perception using magnetoencephalography (MEG). We used apparent motion, in which the first stimulus (S1) was replaced by a second stimulus (S2) with no interstimulus interval and subjects perceived visual motion, and presented three conditions as follows: (1) U&U: Upright contour and Upright features, (2) U&I: Upright contour and Inverted features, and (3) I&I: Inverted contour and Inverted features. In static face perception (S1 onset), the peak latency of the fusiform area's activity, which was related to static face perception, was significantly longer for U&I and I&I than for U&U in the right hemisphere and for U&I than for U&U and I&I in the left. In dynamic face perception (S2 onset), the strength (moment) of the occipitotemporal area's activity, which was related to dynamic face perception, was significantly larger for I&I than for U&U and U&I in the right hemisphere, but not the left. These results can be summarized as follows: (1) in static face perception, the activity of the right fusiform area was more affected by the inversion of features while that of the left fusiform area was more affected by the disruption of the spatial relation between the contour and features, and (2) in dynamic face perception, the activity of the right occipitotemporal area was affected by the inversion of the facial contour. Copyright © 2011 Elsevier B.V. All rights reserved.

Ambient response of a unique performance-based design building with dynamic response modification features

USGS Publications Warehouse

Çelebi, Mehmet; Huang, Moh; Shakal, Antony; Hooper, John; Klemencic, Ron

2012-01-01

A 64-story, performance-based design building with reinforced concrete core shear-walls and unique dynamic response modification features (tuned liquid sloshing dampers and buckling-restrained braces) has been instrumented with a monitoring array of 72 channels of accelerometers. Ambient vibration data recorded are analyzed to identify modes and associated frequencies and damping. The low-amplitude dynamic characteristics are considerably different than those computed from design analyses, but serve as a baseline against which to compare with future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the added features to the building and help improve designs in the future.

Using dynamic geometry software for teaching conditional probability with area-proportional Venn diagrams

NASA Astrophysics Data System (ADS)

Radakovic, Nenad; McDougall, Douglas

2012-10-01

This classroom note illustrates how dynamic visualization can be used to teach conditional probability and Bayes' theorem. There are two features of the visualization that make it an ideal pedagogical tool in probability instruction. The first feature is the use of area-proportional Venn diagrams that, along with showing qualitative relationships, describe the quantitative relationship between two sets. The second feature is the slider and animation component of dynamic geometry software enabling students to observe how the change in the base rate of an event influences conditional probability. A hypothetical instructional sequence using a well-known breast cancer example is described.

Predictive Ensemble Decoding of Acoustical Features Explains Context-Dependent Receptive Fields.

PubMed

Yildiz, Izzet B; Mesgarani, Nima; Deneve, Sophie

2016-12-07

A primary goal of auditory neuroscience is to identify the sound features extracted and represented by auditory neurons. Linear encoding models, which describe neural responses as a function of the stimulus, have been primarily used for this purpose. Here, we provide theoretical arguments and experimental evidence in support of an alternative approach, based on decoding the stimulus from the neural response. We used a Bayesian normative approach to predict the responses of neurons detecting relevant auditory features, despite ambiguities and noise. We compared the model predictions to recordings from the primary auditory cortex of ferrets and found that: (1) the decoding filters of auditory neurons resemble the filters learned from the statistics of speech sounds; (2) the decoding model captures the dynamics of responses better than a linear encoding model of similar complexity; and (3) the decoding model accounts for the accuracy with which the stimulus is represented in neural activity, whereas linear encoding model performs very poorly. Most importantly, our model predicts that neuronal responses are fundamentally shaped by "explaining away," a divisive competition between alternative interpretations of the auditory scene. Neural responses in the auditory cortex are dynamic, nonlinear, and hard to predict. Traditionally, encoding models have been used to describe neural responses as a function of the stimulus. However, in addition to external stimulation, neural activity is strongly modulated by the responses of other neurons in the network. We hypothesized that auditory neurons aim to collectively decode their stimulus. In particular, a stimulus feature that is decoded (or explained away) by one neuron is not explained by another. We demonstrated that this novel Bayesian decoding model is better at capturing the dynamic responses of cortical neurons in ferrets. Whereas the linear encoding model poorly reflects selectivity of neurons, the decoding model can account for the strong nonlinearities observed in neural data. Copyright © 2016 Yildiz et al.

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis.

PubMed

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F; Cohen, Itay; Henin, Rachel D; Hockla, Alexandra; Soares, Alexei S; Papo, Niv; Caulfield, Thomas R; Radisky, Evette S

2016-12-16

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. Although considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here, we examine the importance of substrate dynamics in the cleavage of Kunitz-bovine pancreatic trypsin inhibitor protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4-Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. By using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning 3 orders of magnitude, we identify global and local dynamic features of substrates on the nanosecond-microsecond time scale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substrate-like and product-like states, linking substrate dynamics on the nanosecond-microsecond time scale with large collective substrate motions on the much slower time scale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model Descriptor Consistent Between Processes

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

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-05-10

A major problem with cavitation in pumps and other hydraulic devices is that there is no effective method for detecting or predicting its inception. The traditional approach is to declare the pump in cavitation when the total head pressure drops by some arbitrary value (typically 3o/0) in response to a reduction in pump inlet pressure. However, the pump is already cavitating at this point. A method is needed in which cavitation events are captured as they occur and characterized by their process dynamics. The object of this research was to identify specific features of cavitation that could be used asmore » a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor was based on the physics of the phenomena, capturing the salient features of the process dynamics. An important element of this concept is the development and formulation of the extended process feature vector @) or model vector. Thk model-based descriptor encodes the specific information that describes the phenomena and its dynamics and is formulated as a data structure consisting of several elements. The first is a descriptive model abstracting the phenomena. The second is the parameter list associated with the functional model. The third is a figure of merit, a single number between [0,1] representing a confidence factor that the functional model and parameter list actually describes the observed data. Using this as a basis and applying it to the cavitation problem, any given location in a flow loop will have this data structure, differing in value but not content. The extended process feature vector is formulated as follows: E`> [ , {parameter Iist}, confidence factor]. (1) For this study, the model that characterized cavitation was a chirped-exponentially decaying sinusoid. Using the parameters defined by this model, the parameter list included frequency, decay, and chirp rate. Based on this, the process feature vector has the form: @=> [, {01 = a, ~= b, ~ = c}, cf = 0.80]. (2) In this experiment a reversible catastrophe was examined. The reason for this is that the same catastrophe could be repeated to ensure the statistical significance of the data.« less

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Theoretical features of MHD equilibria with flow

NASA Astrophysics Data System (ADS)

Beklemishev, Alexei; Tessarotto, Massimo

2002-11-01

The effect produced on plasma dynamics by plasma flows, especially those produced by strong E× B-drifts represent an important theoretical issue in magnetic confinement. These include in particular Stellarator equilibria in the presence of weak flows, with velocity much smaller in magnitude than the ion thermal velocity [1]. Strong flows, however, more generally can be produced locally in a variety of physical situations (for example due to strong radial electric fields, neutral beams, RF heating, etc.). These flows can be important in establishing advanced operational regimes, such as the recently discovered HDH mode in the W7-AS Stellarator [2]. Goal of this work is to investigate theoretical features of the MHD equilibria in the presence of strong flows, with particular reference to conditions of existence of kinetic equilibria, particle adiabatic and/or bounce-averaged invariants. References 1 - M. Tessarotto, J.L. Johnson, R.B. White and L.J. Zheng, Phys. Plasmas 3, 2653 (1996); 2 - K. McCormick et al., Phys. Rev. Lett. 89, 15001 (2002).

Hierarchy of forward-backward stochastic Schrödinger equation

NASA Astrophysics Data System (ADS)

Ke, Yaling; Zhao, Yi

2016-07-01

Driven by the impetus to simulate quantum dynamics in photosynthetic complexes or even larger molecular aggregates, we have established a hierarchy of forward-backward stochastic Schrödinger equation in the light of stochastic unravelling of the symmetric part of the influence functional in the path-integral formalism of reduced density operator. The method is numerically exact and is suited for Debye-Drude spectral density, Ohmic spectral density with an algebraic or exponential cutoff, as well as discrete vibrational modes. The power of this method is verified by performing the calculations of time-dependent population differences in the valuable spin-boson model from zero to high temperatures. By simulating excitation energy transfer dynamics of the realistic full FMO trimer, some important features are revealed.

Dynamics and yielding of binary self-suspended nanoparticle fluids

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

Agrawal, Akanksha; Yu, Hsiu-Yu; Srivastava, Samanvaya

Yielding and flow transitions in bi-disperse suspensions of particles are studied using a model system comprised of self-suspended spherical nanoparticles. An important feature of the materials is that the nanoparticles are uniformly dispersed in the absence of a solvent. Addition of larger particles to a suspension of smaller ones is found to soften the suspensions, and in the limit of large size disparities, completely fluidizes the material. We show that these behaviors coincide with a speeding-up of de-correlation dynamics of all particles in the suspensions and are accompanied by a reduction in the energy dissipated at the yielding transition. Wemore » discuss our findings in terms of ligand-mediated jamming and un-jamming of hairy particle suspensions.« less

Dynamics of Conflicts in Wikipedia

PubMed Central

Yasseri, Taha; Sumi, Robert; Rung, András; Kornai, András; Kertész, János

2012-01-01

In this work we study the dynamical features of editorial wars in Wikipedia (WP). Based on our previously established algorithm, we build up samples of controversial and peaceful articles and analyze the temporal characteristics of the activity in these samples. On short time scales, we show that there is a clear correspondence between conflict and burstiness of activity patterns, and that memory effects play an important role in controversies. On long time scales, we identify three distinct developmental patterns for the overall behavior of the articles. We are able to distinguish cases eventually leading to consensus from those cases where a compromise is far from achievable. Finally, we analyze discussion networks and conclude that edit wars are mainly fought by few editors only. PMID:22745683

Perceived image quality for autostereoscopic holograms in healthcare training

NASA Astrophysics Data System (ADS)

Goldiez, Brian; Abich, Julian; Carter, Austin; Hackett, Matthew

2017-03-01

The current state of dynamic light field holography requires further empirical investigation to ultimately advance this developing technology. This paper describes a user-centered design approach for gaining insight into the features most important to clinical personnel using emerging dynamic holographic displays. The approach describes the generation of a high quality holographic model of a simulated traumatic amputation above the knee using 3D scanning. Using that model, a set of static holographic prints will be created varying in color or monochrome, contrast ratio, and polygon density. Leveraging methods from image quality research, the goal for this paper is to describe an experimental approach wherein participants are asked to provide feedback regarding the elements previously mentioned in order to guide the ongoing evolution of holographic displays.

Electrical manipulation of dynamic magnetic impurity and spin texture of helical Dirac fermions

NASA Astrophysics Data System (ADS)

Wang, Rui-Qiang; Zhong, Min; Zheng, Shi-Han; Yang, Mou; Wang, Guang-Hui

2016-05-01

We have theoretically investigated the spin inelastic scattering of helical electrons off a high-spin nanomagnet absorbed on a topological surface. The nanomagnet is treated as a dynamic quantum spin and driven by the spin transfer torque effect. We proposed a mechanism to electrically manipulate the spin texture of helical Dirac fermions rather than by an external magnetic field. By tuning the bias voltage and the direction of impurity magnetization, we present rich patterns of spin texture, from which important fingerprints exclusively associated with the spin helical feature are obtained. Furthermore, it is found that the nonmagnetic potential can create the resonance state in the spin density with different physics as the previously reported resonance of charge density.

The atmospheres of Saturn and Titan in the near-infrared: First results of Cassini/Vims

USGS Publications Warehouse

Baines, K.H.; Momary, T.W.; Buratti, B.J.; Matson, D.L.; Nelson, R.M.; Drossart, P.; Sicardy, B.; Formisano, V.; Bellucci, G.; Coradini, A.; Griffith, C.; Brown, R.H.; Bibring, J.-P.; Langevin, Y.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Combes, M.; Cruikshank, D.P.; Jaumann, R.; McCordt, T.B.; Mennella, V.; Nicholson, P.D.; Sotin, Christophe

2006-01-01

The wide spectral coverage and extensive spatial, temporal, and phase-angle mapping capabilities of the Visual Infrared Mapping Spectrometer (VIMS) onboard the Cassini-Huygens Orbiter are producing fundamental new insights into the nature of the atmospheres of Saturn and Titan. For both bodies, VIMS maps over time and solar phase angles provide information for a multitude of atmospheric constituents and aerosol layers, providing new insights into atmospheric structure and dynamical and chemical processes. For Saturn, salient early results include evidence for phosphine depletion in relatively dark and less cloudy belts at temperate and mid-latitudes compared to the relatively bright and cloudier Equatorial Region, consistent with traditional theories of belts being regions of relative downwelling. Additional Saturn results include (1) the mapping of enhanced trace gas absorptions at the south pole, and (2) the first high phase-angle, high-spatial-resolution imagery of CH4 fluorescence. An additional fundamental new result is the first nighttime near-infrared mapping of Saturn, clearly showing discrete meteorological features relatively deep in the atmosphere beneath the planet's sunlit haze and cloud layers, thus revealing a new dynamical regime at depth where vertical dynamics is relatively more important than zonal dynamics in determining cloud morphology. Zonal wind measurements at deeper levels than previously available are achieved by tracking these features over multiple days, thereby providing measurements of zonal wind shears within Saturn's troposphere when compared to cloudtop movements measured in reflected sunlight. For Titan, initial results include (1) the first detection and mapping of thermal emission spectra of CO, CO2, and CH3D on Titan's nightside limb, (2) the mapping of CH4 fluorescence over the dayside bright limb, extending to ??? 750 km altitude, (3) wind measurements of ???0.5 ms-1, favoring prograde, from the movement of a persistent (multiple months) south polar cloud near 88??S latitude, and (4) the imaging of two transient mid-southern-latitude cloud features. ?? Springer Science+Business Media, Inc. 2006.

MicroRNA targeting microtubule cross-linked protein (MACF1) would suppress the invasion and metastasis of malignant tumor.

PubMed

Zhao, Wenpeng; Qian, Huiming; Zhang, Ruisan; Gao, Xingchun; Gou, Xingchun

2017-07-01

Cancer is one of the most serious diseases that endanger human health in the world today, and the incidence and mortality of cancer increases year by year. Invasion and metastasis is the most prominent feature of malignant tumors, but also becomes the primary factor of threatening patient's health. Tumor cell invasion and metastasis which closely related to the dynamic changes of the cytoskeleton is an important factor influencing the survival of patients. Therefore, inhibition of tumor cell invasion and metastasis is a key strategy for the treatment of cancer. MACF1 is a microtubule microfilament cross-linking factor that plays an important role in cell polarization, cell migration, and maintenance of tissue integrity. A lot of studies have shown that microRNAs play an important role in tumorigenesis, invasion and metastasis. Therefore, we propose the following scientific assumptions: MACF1, an important molecule in adjusting the invasion and metastasis of tumor cells, regulates microfilaments, microtubules participating in cytoskeleton dynamics to promote malignant tumor cell migration and invasion; MicroRNA targeting MACF1 can decrease the expression of MACF1 and thus disrupt the dynamic balance of microtubule or microfilaments as an effective way to inhibit the invasion and metastasis of tumor cells. So we can use it as a new target for clinical early diagnosis and treatment of malignant tumor invasion and metastasis. Copyright © 2017 Elsevier Ltd. All rights reserved.

NeuroRhythmics: software for analyzing time-series measurements of saltatory movements in neuronal processes.

PubMed

Kerlin, Aaron M; Lindsley, Tara A

2008-08-15

Time-lapse imaging of living neurons both in vivo and in vitro has revealed that the growth of axons and dendrites is highly dynamic and characterized by alternating periods of extension and retraction. These growth dynamics are associated with important features of neuronal development and are differentially affected by experimental treatments, but the underlying cellular mechanisms are poorly understood. NeuroRhythmics was developed to semi-automate specific quantitative tasks involved in analysis of two-dimensional time-series images of processes that exhibit saltatory elongation. This software provides detailed information on periods of growth and nongrowth that it identifies by transitions in elongation (i.e. initiation time, average rate, duration) and information regarding the overall pattern of saltatory growth (i.e. time of pattern onset, frequency of transitions, relative time spent in a state of growth vs. nongrowth). Plots and numeric output are readily imported into other applications. The user has the option to specify criteria for identifying transitions in growth behavior, which extends the potential application of the software to neurons of different types or developmental stage and to other time-series phenomena that exhibit saltatory dynamics. NeuroRhythmics will facilitate mechanistic studies of periodic axonal and dendritic growth in neurons.

Collective Dynamics for Heterogeneous Networks of Theta Neurons

NASA Astrophysics Data System (ADS)

Luke, Tanushree

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

Neural dynamics and information representation in microcircuits of motor cortex.

PubMed

Tsubo, Yasuhiro; Isomura, Yoshikazu; Fukai, Tomoki

2013-01-01

The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

Rivers as Political Boundaries: Peru and its Dynamic Borders

NASA Astrophysics Data System (ADS)

Abad, J. D.; Escobar, C.; Garcia, A. M. P.; Ortals, C.; Frias, C. E.; Vizcarra, J.

2014-12-01

Rivers, although inherently dynamic, have been chosen as political boundaries since the beginning of colonization for several reasons. Such divisions were chosen namely for their defensive capabilities and military benefits, and because they were often the first features mapped out by explorers. Furthermore, rivers were indisputable boundaries that did not require boundary pillars or people to guard them. However, it is important to understand the complexities of a river as a boundary. All rivers inevitably change over time through processes such as accretion, deposition, cut-off, or avulsion, rendering a political boundary subject to dispute. Depending upon the flow, size, and surrounding land, a river will migrate differently than others. As these natural features migrate one country loses land while another gains land leading to tension between legal rigidity and fluid dynamism. This in turn can manifest in social disruption due to cultural differences, political upheaval, or conflict risk as a result of scarce water resources. The purpose of this research is to assess the temporal and spatial variability of the political boundaries of Peru that follow rivers. Peru shares borders with Colombia, Brazil, Bolivia, Chile, and Ecuador. A large part of its northern border with Colombia follows the Putumayo River and later the Amazon River. Part of its eastern border with Brazil follows the Yavari River and later the Yaquirana River. These rivers are natural features used as political boundaries yet they differ in how each migrates. By means of a spatial and temporal analysis of satellite images it was possible to obtain erosion and deposition areas for the Putumayo River, the portion of the Amazon River that is part of the Peruvian boundary, the Yavari River, and the Yaquirana River. The erosion and deposition areas were related to land distribution among Peru, Colombia, and Brazil. By examining the Digital Elevation Model one can see how the altitude of the surrounding land affects the watersheds and thus better understand the dynamic of rivers. Ultimately, this research combines data regarding the morphodynamics of these rivers with historical insight on border treaties in order to gain a comprehensive understanding of political implications and social repercussions of dynamic boundaries.

Structural features that predict real-value fluctuations of globular proteins

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-01-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real-value of residue fluctuations using the support vector regression. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson’s correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models is that the former predicts the real-value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. PMID:22328193

Visual scan-path analysis with feature space transient fixation moments

NASA Astrophysics Data System (ADS)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

A computer simulation of Skylab dynamics and attitude control for performance verification and operational support

NASA Technical Reports Server (NTRS)

Buchanan, H.; Nixon, D.; Joyce, R.

1974-01-01

A simulation of the Skylab attitude and pointing control system (APCS) is outlined and discussed. Implementation is via a large hybrid computer and includes those factors affecting system momentum management, propellant consumption, and overall vehicle performance. The important features of the flight system are discussed; the mathematical models necessary for this treatment are outlined; and the decisions involved in implementation are discussed. A brief summary of the goals and capabilities of this tool is also included.

Transonic propulsion system integration analysis at McDonnell Aircraft Company

NASA Technical Reports Server (NTRS)

Cosner, Raymond R.

1989-01-01

The technology of Computational Fluid Dynamics (CFD) is becoming an important tool in the development of aircraft propulsion systems. Two of the most valuable features of CFD are: (1) quick acquisition of flow field data; and (2) complete description of flow fields, allowing detailed investigation of interactions. Current analysis methods complement wind tunnel testing in several ways. Herein, the discussion is focused on CFD methods. However, aircraft design studies need data from both CFD and wind tunnel testing. Each approach complements the other.

[Body language group: depersonalization and repersonalization using make-up].

PubMed

Quidu, M; Tabary, C

1981-04-01

Make up was used as a support by a corporal expression group which met two hours a week during three months. This method call particularly for tact and sight, the importance of these factors being well known to attain the elaboration and the integration of body scheme. In a recreative, therefore reassuring context, reinforced by the group phenomenon, the dynamism of gesture and relationship extends far beyond the features. The trends of make-up during the sessions and themes based on mimesis allowed to measure progress.

Neuronal network model of interictal and recurrent ictal activity

NASA Astrophysics Data System (ADS)

Lopes, M. A.; Lee, K.-E.; Goltsev, A. V.

2017-12-01

We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.

A generative spike train model with time-structured higher order correlations.

PubMed

Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

2013-01-01

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.

Molecular Dynamics Simulations of Acylpeptide Hydrolase Bound to Chlorpyrifosmethyl Oxon and Dichlorvos

PubMed Central

Jin, Hanyong; Zhou, Zhenhuan; Wang, Dongmei; Guan, Shanshan; Han, Weiwei

2015-01-01

Acylpeptide hydrolases (APHs) catalyze the removal of N-acylated amino acids from blocked peptides. Like other prolyloligopeptidase (POP) family members, APHs are believed to be important targets for drug design. To date, the binding pose of organophosphorus (OP) compounds of APH, as well as the different OP compounds binding and inducing conformational changes in two domains, namely, α/β hydrolase and β-propeller, remain poorly understood. We report a computational study of APH bound to chlorpyrifosmethyl oxon and dichlorvos. In our docking study, Val471 and Gly368 are important residues for chlorpyrifosmethyl oxon and dichlorvos binding. Molecular dynamics simulations were also performed to explore the conformational changes between the chlorpyrifosmethyl oxon and dichlorvos bound to APH, which indicated that the structural feature of chlorpyrifosmethyl oxon binding in APH permitted partial opening of the β-propeller fold and allowed the chlorpyrifosmethyl oxon to easily enter the catalytic site. These results may facilitate the design of APH-targeting drugs with improved efficacy. PMID:25794283

Stochastic volatility of the futures prices of emission allowances: A Bayesian approach

NASA Astrophysics Data System (ADS)

Kim, Jungmu; Park, Yuen Jung; Ryu, Doojin

2017-01-01

Understanding the stochastic nature of the spot volatility of emission allowances is crucial for risk management in emissions markets. In this study, by adopting a stochastic volatility model with or without jumps to represent the dynamics of European Union Allowances (EUA) futures prices, we estimate the daily volatilities and model parameters by using the Markov Chain Monte Carlo method for stochastic volatility (SV), stochastic volatility with return jumps (SVJ) and stochastic volatility with correlated jumps (SVCJ) models. Our empirical results reveal three important features of emissions markets. First, the data presented herein suggest that EUA futures prices exhibit significant stochastic volatility. Second, the leverage effect is noticeable regardless of whether or not jumps are included. Third, the inclusion of jumps has a significant impact on the estimation of the volatility dynamics. Finally, the market becomes very volatile and large jumps occur at the beginning of a new phase. These findings are important for policy makers and regulators.

Role of word-of-mouth for programs of voluntary vaccination: A game-theoretic approach.

PubMed

Bhattacharyya, Samit; Bauch, Chris T; Breban, Romulus

2015-11-01

We propose a model describing the synergetic feedback between word-of-mouth (WoM) and epidemic dynamics controlled by voluntary vaccination. The key feature consists in combining a game-theoretic model for the spread of WoM and a compartmental model describing VSIR disease dynamics in the presence of a program of voluntary vaccination. We evaluate and compare two scenarios for determinants of behavior, depending on what WoM disseminates: (1) vaccine advertising, which may occur whether or not an epidemic is ongoing and (2) epidemic status, notably disease prevalence. Understanding the synergy between the two strategies could be particularly important for designing voluntary vaccination campaigns. We find that, in the initial phase of an epidemic, vaccination uptake is determined more by vaccine advertising than the epidemic status. As the epidemic progresses, epidemic status becomes increasingly important for vaccination uptake, considerably accelerating vaccination uptake toward a stable vaccination coverage. Copyright © 2015 Elsevier Inc. All rights reserved.

Layer-Dependent Ultrafast Carrier and Coherent Phonon Dynamics in Black Phosphorus.

PubMed

Miao, Xianchong; Zhang, Guowei; Wang, Fanjie; Yan, Hugen; Ji, Minbiao

2018-05-09

Black phosphorus is a layered semiconducting material, demonstrating strong layer-dependent optical and electronic properties. Probing the photophysical properties on ultrafast time scales is of central importance in understanding many-body interactions and nonequilibrium quasiparticle dynamics. Here, we applied temporally, spectrally, and spatially resolved pump-probe microscopy to study the transient optical responses of mechanically exfoliated few-layer black phosphorus, with layer numbers ranging from 2 to 9. We have observed layer-dependent resonant transient absorption spectra with both photobleaching and red-shifted photoinduced absorption features, which could be attributed to band gap renormalization of higher subband transitions. Surprisingly, coherent phonon oscillations with unprecedented intensities were observed when the probe photons were in resonance with the optical transitions, which correspond to the low-frequency layer-breathing mode. Our results reveal strong Coulomb interactions and electron-phonon couplings in photoexcited black phosphorus, providing important insights into the ultrafast optical, nanomechanical, and optoelectronic properties of this novel two-dimensional material.

Environment and initial state engineered dynamics of quantum and classical correlations

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

Wang, Cheng-Zhi, E-mail: czczwang@outlook.com; Li, Chun-Xian; Guo, Yu

Based on an open exactly solvable system coupled to an environment with nontrivial spectral density, we connect the features of quantum and classical correlations with some features of the environment, initial states of the system, and the presence of initial system–environment correlations. Some interesting features not revealed before are observed by changing the structure of environment, the initial states of system, and the presence of initial system–environment correlations. The main results are as follows. (1) Quantum correlations exhibit temporary freezing and permanent freezing even at high temperature of the environment, for which the necessary and sufficient conditions are given bymore » three propositions. (2) Quantum correlations display a transition from temporary freezing to permanent freezing by changing the structure of environment. (3) Quantum correlations can be enhanced all the time, for which the condition is put forward. (4) The one-to-one dependency relationship between all kinds of dynamic behaviors of quantum correlations and the initial states of the system as well as environment structure is established. (5) In the presence of initial system–environment correlations, quantum correlations under local environment exhibit temporary multi-freezing phenomenon. While under global environment they oscillate, revive, and damp, an explanation for which is given. - Highlights: • Various interesting behaviors of quantum and classical correlations are observed in an open exactly solvable model. • The important effects of the bath structure on quantum and classical correlations are revealed. • The one-to-one correspondence between the type of dynamical behavior of quantum discord and the initial state is given. • Quantum correlations are given in the presence of initial qubits–bath correlations.« less

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Solar Flare Prediction Model with Three Machine-learning Algorithms using Ultraviolet Brightening and Vector Magnetograms

NASA Astrophysics Data System (ADS)

Nishizuka, N.; Sugiura, K.; Kubo, Y.; Den, M.; Watari, S.; Ishii, M.

2017-02-01

We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 hr. Machine learning is used to devise algorithms that can learn from and make decisions on a huge amount of data. We used solar observation data during the period 2010-2015, such as vector magnetograms, ultraviolet (UV) emission, and soft X-ray emission taken by the Solar Dynamics Observatory and the Geostationary Operational Environmental Satellite. We detected active regions (ARs) from the full-disk magnetogram, from which ˜60 features were extracted with their time differentials, including magnetic neutral lines, the current helicity, the UV brightening, and the flare history. After standardizing the feature database, we fully shuffled and randomly separated it into two for training and testing. To investigate which algorithm is best for flare prediction, we compared three machine-learning algorithms: the support vector machine, k-nearest neighbors (k-NN), and extremely randomized trees. The prediction score, the true skill statistic, was higher than 0.9 with a fully shuffled data set, which is higher than that for human forecasts. It was found that k-NN has the highest performance among the three algorithms. The ranking of the feature importance showed that previous flare activity is most effective, followed by the length of magnetic neutral lines, the unsigned magnetic flux, the area of UV brightening, and the time differentials of features over 24 hr, all of which are strongly correlated with the flux emergence dynamics in an AR.

Solar Flare Prediction Model with Three Machine-learning Algorithms using Ultraviolet Brightening and Vector Magnetograms

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

Nishizuka, N.; Kubo, Y.; Den, M.

We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 hr. Machine learning is used to devise algorithms that can learn from and make decisions on a huge amount of data. We used solar observation data during the period 2010–2015, such as vector magnetograms, ultraviolet (UV) emission, and soft X-ray emission taken by the Solar Dynamics Observatory and the Geostationary Operational Environmental Satellite . We detected active regions (ARs) from the full-disk magnetogram, from which ∼60 features were extracted with their time differentials, including magnetic neutralmore » lines, the current helicity, the UV brightening, and the flare history. After standardizing the feature database, we fully shuffled and randomly separated it into two for training and testing. To investigate which algorithm is best for flare prediction, we compared three machine-learning algorithms: the support vector machine, k-nearest neighbors (k-NN), and extremely randomized trees. The prediction score, the true skill statistic, was higher than 0.9 with a fully shuffled data set, which is higher than that for human forecasts. It was found that k-NN has the highest performance among the three algorithms. The ranking of the feature importance showed that previous flare activity is most effective, followed by the length of magnetic neutral lines, the unsigned magnetic flux, the area of UV brightening, and the time differentials of features over 24 hr, all of which are strongly correlated with the flux emergence dynamics in an AR.« less

Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

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

PubMed

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

2016-08-15

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

Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

RNA-Seq reveals the dynamic and diverse features of digestive enzymes during early development of Pacific white shrimp Litopenaeus vannamei.

PubMed

Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Li, Fuhua; Xiang, Jianhai

2014-09-01

The Pacific white shrimp (Litopenaeus vannamei), with high commercial value, has a typical metamorphosis pattern by going through embryo, nauplius, zoea, mysis and postlarvae during early development. Its diets change continually in this period, and a high mortality of larvae also occurs in this period. Since there is a close relationship between diets and digestive enzymes, a comprehensive investigation about the types and expression patterns of all digestive enzyme genes during early development of L. vannamei is of considerable significance for shrimp diets and larvae culture. Using RNA-Seq data, the types and expression characteristics of the digestive enzyme genes were analyzed during five different development stages (embryo, nauplius, zoea, mysis and postlarvae) in L. vannamei. Among the obtained 66,815 unigenes, 296 were annotated as 16 different digestive enzymes including five types of carbohydrase, seven types of peptidase and four types of lipase. Such a diverse suite of enzymes illustrated the capacity of L. vannamei to exploit varied diets to fit their nutritional requirements. The analysis of their dynamic expression patterns during development also indicated the importance of transcriptional regulation to adapt to the diet transition. Our study revealed the diverse and dynamic features of digestive enzymes during early development of L. vannamei. These results would provide support to better understand the physiological changes during diet transition. Copyright © 2014 Elsevier Inc. All rights reserved.

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

PubMed

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

2012-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

An evolution-based DNA-binding residue predictor using a dynamic query-driven learning scheme.

PubMed

Chai, H; Zhang, J; Yang, G; Ma, Z

2016-11-15

DNA-binding proteins play a pivotal role in various biological activities. Identification of DNA-binding residues (DBRs) is of great importance for understanding the mechanism of gene regulations and chromatin remodeling. Most traditional computational methods usually construct their predictors on static non-redundant datasets. They excluded many homologous DNA-binding proteins so as to guarantee the generalization capability of their models. However, those ignored samples may potentially provide useful clues when studying protein-DNA interactions, which have not obtained enough attention. In view of this, we propose a novel method, namely DQPred-DBR, to fill the gap of DBR predictions. First, a large-scale extensible sample pool was compiled. Second, evolution-based features in the form of a relative position specific score matrix and covariant evolutionary conservation descriptors were used to encode the feature space. Third, a dynamic query-driven learning scheme was designed to make more use of proteins with known structure and functions. In comparison with a traditional static model, the introduction of dynamic models could obviously improve the prediction performance. Experimental results from the benchmark and independent datasets proved that our DQPred-DBR had promising generalization capability. It was capable of producing decent predictions and outperforms many state-of-the-art methods. For the convenience of academic use, our proposed method was also implemented as a web server at .

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System

PubMed Central

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L.; Wennekers, Thomas; Chicca, Elisabetta

2011-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems. PMID:22347163

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

PubMed

Schniepp, Roman; Möhwald, Ken; Wuehr, Max

2017-10-01

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

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Scalable Online Network Modeling and Simulation

DTIC Science & Technology

2005-08-01

ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski , Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...performance for a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature ...a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature interactions

Universal ultrafast signatures of photoexcitations in conjugated polymers: excitons and charge-transfer polarons

NASA Astrophysics Data System (ADS)

McBranch, Duncan W.; Kraabel, Brett; Xu, Su; Wang, Hsing-Lin; Klimov, Victor I.

1999-12-01

Using subpicosecond transient absorption spectroscopy, we have investigated the primary photoexcitations in thin films and solution of several phenylene-based conjugated polymers and an oligomer. We identify two features in the transient absorption spectra and dynamics that are common to all of the materials which we have studied from this family. The first spectral feature is a photoinduced absorption (PA) band peaking near 1 eV which has intensity-dependent dynamics which match the stimulated emission dynamics exactly over two orders of magnitude in excitation density. This band is associated with singlet intrachain excitons. The second spectral feature (observed only in thin films and aggregated solutions) is a PA band peaking near 1.8 eV, which is longer-lived than the 1 eV exciton PA band, and which has dynamics that are independent (or weakly-dependent) on excitation density. This feature is attributed to charge separated (interchain) excitations. These excitations are generated through a bimolecular process. By comparing to samples in which charged excitations are created deliberately by doping with C6O, we assign these secondary species as bound polarons.

Empirical analysis of vegetation dynamics and the possibility of a catastrophic desertification transition

PubMed Central

Kent, Rafi; Michael, Yaron; Shnerb, Nadav M.

2017-01-01

The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states. Some support to this idea comes from the analysis of static patterns, where peaks of the vegetation density histogram were associated with these alternative states. Here we present a large-scale empirical study of vegetation dynamics, aimed at identifying and quantifying directly the effects of positive feedback. To do that, we have analyzed vegetation density across 2.5 × 106 km2 of the African Sahel region, with spatial resolution of 30 × 30 meters, using three consecutive snapshots. The results are mixed. The local vegetation density (measured at a single pixel) moves towards the average of the corresponding rainfall line, indicating a purely negative feedback. On the other hand, the chance of spatial clusters (of many “green” pixels) to expand in the next census is growing with their size, suggesting some positive feedback. We show that these apparently contradicting results emerge naturally in a model with positive feedback and strong demographic stochasticity, a model that allows for a catastrophic shift only in a certain range of parameters. Static patterns, like the double peak in the histogram of vegetation density, are shown to vary between censuses, with no apparent correlation with the actual dynamical features. Our work emphasizes the importance of dynamic response patterns as indicators of the state of the system, while the usefulness of static modality features appears to be quite limited. PMID:29261678

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

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

Empirical analysis of vegetation dynamics and the possibility of a catastrophic desertification transition.

PubMed

Weissmann, Haim; Kent, Rafi; Michael, Yaron; Shnerb, Nadav M

2017-01-01

The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states. Some support to this idea comes from the analysis of static patterns, where peaks of the vegetation density histogram were associated with these alternative states. Here we present a large-scale empirical study of vegetation dynamics, aimed at identifying and quantifying directly the effects of positive feedback. To do that, we have analyzed vegetation density across 2.5 × 106 km2 of the African Sahel region, with spatial resolution of 30 × 30 meters, using three consecutive snapshots. The results are mixed. The local vegetation density (measured at a single pixel) moves towards the average of the corresponding rainfall line, indicating a purely negative feedback. On the other hand, the chance of spatial clusters (of many "green" pixels) to expand in the next census is growing with their size, suggesting some positive feedback. We show that these apparently contradicting results emerge naturally in a model with positive feedback and strong demographic stochasticity, a model that allows for a catastrophic shift only in a certain range of parameters. Static patterns, like the double peak in the histogram of vegetation density, are shown to vary between censuses, with no apparent correlation with the actual dynamical features. Our work emphasizes the importance of dynamic response patterns as indicators of the state of the system, while the usefulness of static modality features appears to be quite limited.

Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

PubMed

Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

2016-04-23

This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features derived from the properties of two highest peaks as important predictors of personal shot effectiveness. Activation sequence profiles helped in analyzing muscle orchestration during golf shot, exposing a specific avalanche pattern, but data from more players are needed for stronger conclusions. Results demonstrate that information arising from an EMG signal stream is useful for predicting golf shot success, in terms of club head speed and ball carry distance, with acceptable accuracy. Surface EMG data, collected with a goal to automatically evaluate golf player's performance, enables wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance drive.

Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

PubMed Central

Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M. Charlotte

2016-01-01

This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features derived from the properties of two highest peaks as important predictors of personal shot effectiveness. Activation sequence profiles helped in analyzing muscle orchestration during golf shot, exposing a specific avalanche pattern, but data from more players are needed for stronger conclusions. Results demonstrate that information arising from an EMG signal stream is useful for predicting golf shot success, in terms of club head speed and ball carry distance, with acceptable accuracy. Surface EMG data, collected with a goal to automatically evaluate golf player’s performance, enables wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance drive. PMID:27120604

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory

PubMed Central

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding. PMID:24917833

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory.

PubMed

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

Trajectories of charged dust grains in the cometary environment

NASA Astrophysics Data System (ADS)

Horanyi, M.; Mendis, D. A.

1985-07-01

Using a simple model of the particles and fields environment of a comet, the trajectories of the smallest (micron- and submicron-sized) dust grains that are expected to be released from a cometary nucleus are calculated. It is shown that electromagnetic forces play a crucial role in the dynamics of these particles. The present calculations indicate not only the asymmetry of the sunward dust envelopes that have been suggested earlier by other authors, but they also indicate the possible existence of wavy dust features far down the tail, reminiscent of the peculiar wavy dust feature observed in the dust tail of Comet Ikeya-Seki 1965f. The importance of these findings in studying the lower end of the cometary dust mass spectrum during the forthcoming fly-by missions to Comet Halley is underscored.

Turbulent Output-Based Anisotropic Adaptation

NASA Technical Reports Server (NTRS)

Park, Michael A.; Carlson, Jan-Renee

2010-01-01

Controlling discretization error is a remaining challenge for computational fluid dynamics simulation. Grid adaptation is applied to reduce estimated discretization error in drag or pressure integral output functions. To enable application to high O(10(exp 7)) Reynolds number turbulent flows, a hybrid approach is utilized that freezes the near-wall boundary layer grids and adapts the grid away from the no slip boundaries. The hybrid approach is not applicable to problems with under resolved initial boundary layer grids, but is a powerful technique for problems with important off-body anisotropic features. Supersonic nozzle plume, turbulent flat plate, and shock-boundary layer interaction examples are presented with comparisons to experimental measurements of pressure and velocity. Adapted grids are produced that resolve off-body features in locations that are not known a priori.

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

Li, Mi; Pu, Yunqiao; Yoo, Chang Geun

The native recalcitrance of plants hinders the biomass conversion process using current biorefinery techniques. Down-regulation of the caffeic acid O-methyltransferase (COMT) gene in the lignin biosynthesis pathway of switchgrass reduced the thermochemical and biochemical conversion recalcitrance of biomass. Due to potential environmental influences on lignin biosynthesis and deposition, studying the consequences of physicochemical changes in field-grown plants without pretreatment is essential to evaluate the performance of lignin-altered plants. In this study, we determined the chemical composition, cellulose crystallinity and the degree of its polymerization, molecular weight of hemicellulose, and cellulose accessibility of cell walls in order to better understand themore » fundamental features of why biomass is recalcitrant to conversion without pretreatment. The most important is to investigate whether traits and features are stable in the dynamics of field environmental effects over multiple years.« less

Weighted Distance Functions Improve Analysis of High-Dimensional Data: Application to Molecular Dynamics Simulations.

PubMed

Blöchliger, Nicolas; Caflisch, Amedeo; Vitalis, Andreas

2015-11-10

Data mining techniques depend strongly on how the data are represented and how distance between samples is measured. High-dimensional data often contain a large number of irrelevant dimensions (features) for a given query. These features act as noise and obfuscate relevant information. Unsupervised approaches to mine such data require distance measures that can account for feature relevance. Molecular dynamics simulations produce high-dimensional data sets describing molecules observed in time. Here, we propose to globally or locally weight simulation features based on effective rates. This emphasizes, in a data-driven manner, slow degrees of freedom that often report on the metastable states sampled by the molecular system. We couple this idea to several unsupervised learning protocols. Our approach unmasks slow side chain dynamics within the native state of a miniprotein and reveals additional metastable conformations of a protein. The approach can be combined with most algorithms for clustering or dimensionality reduction.

Local-feature analysis for automated coarse-graining of bulk-polymer molecular dynamics simulations.

PubMed

Xue, Y; Ludovice, P J; Grover, M A

2012-12-01

A method for automated coarse-graining of bulk polymers is presented, using the data-mining tool of local feature analysis. Most existing methods for polymer coarse-graining define superatoms based on their covalent bonding topology along the polymer backbone, but here superatoms are defined based only on their correlated motions, as observed in molecular dynamics simulations. Correlated atomic motions are identified in the simulation data using local feature analysis, between atoms in the same or in different polymer chains. Groups of highly correlated atoms constitute the superatoms in the coarse-graining scheme, and the positions of their seed coordinates are then projected forward in time. Based on only the seed positions, local feature analysis enables the full reconstruction of all atomic positions. This reconstruction suggests an iterative scheme to reduce the computation of the simulations to initialize another short molecular dynamic simulation, identify new superatoms, and again project forward in time.

Supramolecular assembly/reassembly processes: molecular motors and dynamers operating at surfaces.

PubMed

Ciesielski, Artur; Samorì, Paolo

2011-04-01

Among the many significant advances within the field of supramolecular chemistry over the past decades, the development of the so-called "dynamers" features a direct relevance to materials science. Defined as "combinatorial dynamic polymers", dynamers are constitutional dynamic systems and materials resulting from the application of the principles of supramolecular chemistry to polymer science. Like supramolecular materials in general, dynamers are reversible dynamic multifunctional architectures, capable of modifying their constitution by exchanging, recombining, incorporating components. They may exhibit a variety of novel properties and behave as adaptive materials. In this review we focus on the design of responsive switchable monolayers, i.e. monolayers capable to undergo significant changes in their physical or chemical properties as a result of external stimuli. Scanning tunneling microscopy studies provide direct evidence with a sub-nanometre resolution, on the formation and dynamic response of these self-assembled systems featuring controlled geometries and properties.

Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

PubMed

Zhang, Jianhua; Yin, Zhong; Wang, Rubin

2017-01-01

This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

A design for a dynamic biomimetic sonarhead inspired by horseshoe bats.

PubMed

Caspers, Philip; Mueller, Rolf

2018-05-24

The noseleaf and pinnae of horseshoe bats (Rhinolophus ferrumequinum) have both been shown to actively deform during biosonar operation. Since these baffle structures directly affect the properties of the animal's biosonar system, this work mimics horseshoe bat sonar system with the goal of developing a platform to study the dynamic sensing principles horseshoe bats employ. Consequently, two robotic devices were developed to mimic the dynamic emission and reception characteristics of horseshoe bats. The noseleaf and pinnae shapes were modeled as smooth blanks matched to digital representations of a horseshoe bat specimen's noseleaf and pinnae. Local shape features mimicking structures on the pinnae and noseleaf were added digitally. Flexible baffles with local shape feature combinations were manufactured and paired with actuation mechanisms to mimic pinnae and noseleaf deformations in-vivo. Two noseleaves with and without local shape features were considered. Each noseleaf baffle was mounted to a platform called the dynamic emission head to actuate three surface elements of the baffle. Similarly, 12 pinna realizations composed of combinations of three local shape features were mounted to a platform called the dynamic reception head to deform the left and right pinnae independently. Motion of the noseleaf and pinnae were synchronized to the incoming and outgoing sonar waveform, and the joint time-frequency properties of the noseleaf and pinnae local feature combinations and combinations of the pinnae and noseleaf thereof were characterized across spatial direction. Amplitude modulations to the outgoing and incoming sonar pulse information across spatial direction were observed for all pinnae and noseleaf local shape feature combinations. Peak modulation variance generated by motion of the pinnae and combinations of the noseleaf and pinnae approached a white Gaussian noise variance bound. However, it was found the dynamic emitter generated less modulation than either the combined or reception scenarios. © 2018 IOP Publishing Ltd.

Quasistationary areas of NDVI trend dynamics is a powerful research tool for studying spatial patterns of land vegetation

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Larko, Aleksandr

The most important task for humankind is to study and understand global processes on Earth. Large factual material on the dynamics of the optical spectral characteristics of the land surface has been accumulated in recent decades. This has been only made possible due to the use of satellite information. The development of satellite measurement technologies and new methods for pre-processing and interpretation of satellite data allowed the research adequate to the scale of the Earth. This adequacy includes the compliance of scale terrestrial objects to the scale of satellite measurements. Research is not limited by any latitude or longitude of the objects studied. The second most important quality is the adequacy of the technologies used to velocities of processes on Earth. This is enabled by long-term continuous satellite measurements at almost all latitudes. Effectiveness of this approach to the study of natural systems has been shown by the authors in ASR publications (AP Shevyrnogov, GS Vysotskaya, JI Gitelson, Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996), which reported a method for determining the ocean surface quasistationary zones. This approach allowed us to identify different types of phytopigment dynamics and the hydrological structure of the ocean. We proposed a similar approach for the study of land vegetation. In some aspects, it is similar to the previously published approach, despite the different nature of terrestrial and aquatic ecosystems. The results are based on the processing of satellite data from 1981 to 2006. Dynamics is the most interesting and important parameter of ecosystems, especially their trends. Therefore, it has been chosen for the analysis of spatial patterns of plant biota. The first results showed great heterogeneity of variances in nonlinear trends of the study areas of the Earth's surface. They corresponded to different natural systems. Various scales of temporal and spatial windows highlight different features of land vegetation. Methods for normalization of the initial information are also effective for highlighting the features of the spatial structure of vegetation. Thus, we have a powerful tool to analyze the spatial distribution and dynamics of terrestrial vegetation based on satellite data. This approach provides a great opportunity to get fundamental knowledge on the functioning of the biosphere. This is global warming, shifts in permafrost boundaries, global gas exchange, etc. It can be used for practical applications in various fields of human activity: forestry, environmental protection, agriculture, etc. We show the illustration of this method: the global maps of land surface dynamics of trends with different parameters of data processing.

Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans.

PubMed

Lohmann, Philipp; Stoffels, Gabriele; Ceccon, Garry; Rapp, Marion; Sabel, Michael; Filss, Christian P; Kamp, Marcel A; Stegmayr, Carina; Neumaier, Bernd; Shah, Nadim J; Langen, Karl-Josef; Galldiks, Norbert

2017-07-01

We investigated the potential of textural feature analysis of O-(2-[ 18 F]fluoroethyl)-L-tyrosine ( 18 F-FET) PET to differentiate radiation injury from brain metastasis recurrence. Forty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic 18 F-FET PET. Tumour-to-brain ratios (TBRs) of 18 F-FET uptake and 62 textural parameters were determined on summed images 20-40 min post-injection. Tracer uptake kinetics, i.e., time-to-peak (TTP) and patterns of time-activity curves (TAC) were evaluated on dynamic PET data from 0-50 min post-injection. Diagnostic accuracy of investigated parameters and combinations thereof to discriminate between brain metastasis recurrence and radiation injury was compared. Diagnostic accuracy increased from 81 % for TBR mean alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR max alone was 83 % and increased to 85 % after combination with the textural parameters Coarseness, Short-zone emphasis, or Correlation. Analysis of TACs resulted in an accuracy of 70 % for kinetic pattern alone and increased to 83 % when combined with TBR max . Textural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic 18 F-FET PET scans. • Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.

A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

NASA Astrophysics Data System (ADS)

Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

2017-07-01

Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

Conserved patterns of incomplete reporting in pre-vaccine era childhood diseases

PubMed Central

Gunning, Christian E.; Erhardt, Erik; Wearing, Helen J.

2014-01-01

Incomplete observation is an important yet often neglected feature of observational ecological timeseries. In particular, observational case report timeseries of childhood diseases have played an important role in the formulation of mechanistic dynamical models of populations and metapopulations. Yet to our knowledge, no comprehensive study of childhood disease reporting probabilities (commonly referred to as reporting rates) has been conducted to date. Here, we provide a detailed analysis of measles and whooping cough reporting probabilities in pre-vaccine United States cities and states, as well as measles in cities of England and Wales. Overall, we find the variability between locations and diseases greatly exceeds that between methods or time periods. We demonstrate a strong relationship within location between diseases and within disease between geographical areas. In addition, we find that demographic covariates such as ethnic composition and school attendance explain a non-trivial proportion of reporting probability variation. Overall, our findings show that disease reporting is both variable and non-random and that completeness of reporting is influenced by disease identity, geography and socioeconomic factors. We suggest that variations in incomplete observation can be accounted for and that doing so can reveal ecologically important features that are otherwise obscured. PMID:25232131

TRX-LOGOS - a graphical tool to demonstrate DNA information content dependent upon backbone dynamics in addition to base sequence.

PubMed

Fortin, Connor H; Schulze, Katharina V; Babbitt, Gregory A

2015-01-01

It is now widely-accepted that DNA sequences defining DNA-protein interactions functionally depend upon local biophysical features of DNA backbone that are important in defining sites of binding interaction in the genome (e.g. DNA shape, charge and intrinsic dynamics). However, these physical features of DNA polymer are not directly apparent when analyzing and viewing Shannon information content calculated at single nucleobases in a traditional sequence logo plot. Thus, sequence logos plots are severely limited in that they convey no explicit information regarding the structural dynamics of DNA backbone, a feature often critical to binding specificity. We present TRX-LOGOS, an R software package and Perl wrapper code that interfaces the JASPAR database for computational regulatory genomics. TRX-LOGOS extends the traditional sequence logo plot to include Shannon information content calculated with regard to the dinucleotide-based BI-BII conformation shifts in phosphate linkages on the DNA backbone, thereby adding a visual measure of intrinsic DNA flexibility that can be critical for many DNA-protein interactions. TRX-LOGOS is available as an R graphics module offered at both SourceForge and as a download supplement at this journal. To demonstrate the general utility of TRX logo plots, we first calculated the information content for 416 Saccharomyces cerevisiae transcription factor binding sites functionally confirmed in the Yeastract database and matched to previously published yeast genomic alignments. We discovered that flanking regions contain significantly elevated information content at phosphate linkages than can be observed at nucleobases. We also examined broader transcription factor classifications defined by the JASPAR database, and discovered that many general signatures of transcription factor binding are locally more information rich at the level of DNA backbone dynamics than nucleobase sequence. We used TRX-logos in combination with MEGA 6.0 software for molecular evolutionary genetics analysis to visually compare the human Forkhead box/FOX protein evolution to its binding site evolution. We also compared the DNA binding signatures of human TP53 tumor suppressor determined by two different laboratory methods (SELEX and ChIP-seq). Further analysis of the entire yeast genome, center aligned at the start codon, also revealed a distinct sequence-independent 3 bp periodic pattern in information content, present only in coding region, and perhaps indicative of the non-random organization of the genetic code. TRX-LOGOS is useful in any situation in which important information content in DNA can be better visualized at the positions of phosphate linkages (i.e. dinucleotides) where the dynamic properties of the DNA backbone functions to facilitate DNA-protein interaction.

"Not just a dog": an attachment perspective on relationships with assistance dogs.

PubMed

Kwong, Marilyn J; Bartholomew, Kim

2011-09-01

We explored individuals' relationships with an assistance dog from an attachment-theory perspective. We used both inductive and deductive thematic methods to analyze semi-structured interviews with 25 participants who had lost an assistance dog to retirement or death. Analyses revealed attachment processes of safe haven, secure base, and separation anxiety. Although attachment dynamics were an important feature of these relationships, caregiving was equally important. When confronted with the loss of their dog, almost all participants experienced intense grief. Most grief responses were consistent with the loss of a caregiving relationship. Findings suggest that grief is a natural response to the loss of a beloved companion who fulfilled fundamental needs for attachment and caregiving.

The Emergence of Life as a First-Order Phase Transition

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

Mathis, Cole; Bhattacharya, Tanmoy; Walker, Sara Imari

It is well known that life on Earth alters its environment over evolutionary and geological timescales. An important open question is whether this is a result of evolutionary optimization or a universal feature of life. In the latter case, the origin of life would be coincident with a shift in environmental conditions. Here in this paper we present a model for the emergence of life in which replicators are explicitly coupled to their environment through the recycling of a finite supply of resources. The model exhibits a dynamic, first-order phase transition from nonlife to life, where the life phase ismore » distinguished by selection on replicators. We show that environmental coupling plays an important role in the dynamics of the transition. The transition corresponds to a redistribution of matter in replicators and their environment, driven by selection on replicators, exhibiting an explosive growth in diversity as replicators are selected. The transition is accurately tracked by the mutual information shared between replicators and their environment. In the absence of successfully repartitioning system resources, the transition fails to complete, leading to the possibility of many frustrated trials before life first emerges. Often, the replicators that initiate the transition are not those that are ultimately selected. The results are consistent with the view that life's propensity to shape its environment is indeed a universal feature of replicators, characteristic of the transition from nonlife to life. We discuss the implications of these results for understanding life's emergence and evolutionary transitions more broadly.« less

The Emergence of Life as a First-Order Phase Transition

DOE PAGES

Mathis, Cole; Bhattacharya, Tanmoy; Walker, Sara Imari

2017-03-01

It is well known that life on Earth alters its environment over evolutionary and geological timescales. An important open question is whether this is a result of evolutionary optimization or a universal feature of life. In the latter case, the origin of life would be coincident with a shift in environmental conditions. Here in this paper we present a model for the emergence of life in which replicators are explicitly coupled to their environment through the recycling of a finite supply of resources. The model exhibits a dynamic, first-order phase transition from nonlife to life, where the life phase ismore » distinguished by selection on replicators. We show that environmental coupling plays an important role in the dynamics of the transition. The transition corresponds to a redistribution of matter in replicators and their environment, driven by selection on replicators, exhibiting an explosive growth in diversity as replicators are selected. The transition is accurately tracked by the mutual information shared between replicators and their environment. In the absence of successfully repartitioning system resources, the transition fails to complete, leading to the possibility of many frustrated trials before life first emerges. Often, the replicators that initiate the transition are not those that are ultimately selected. The results are consistent with the view that life's propensity to shape its environment is indeed a universal feature of replicators, characteristic of the transition from nonlife to life. We discuss the implications of these results for understanding life's emergence and evolutionary transitions more broadly.« less

The Emergence of Life as a First-Order Phase Transition

NASA Astrophysics Data System (ADS)

Mathis, Cole; Bhattacharya, Tanmoy; Imari Walker, Sara

2017-03-01

It is well known that life on Earth alters its environment over evolutionary and geological timescales. An important open question is whether this is a result of evolutionary optimization or a universal feature of life. In the latter case, the origin of life would be coincident with a shift in environmental conditions. Here we present a model for the emergence of life in which replicators are explicitly coupled to their environment through the recycling of a finite supply of resources. The model exhibits a dynamic, first-order phase transition from nonlife to life, where the life phase is distinguished by selection on replicators. We show that environmental coupling plays an important role in the dynamics of the transition. The transition corresponds to a redistribution of matter in replicators and their environment, driven by selection on replicators, exhibiting an explosive growth in diversity as replicators are selected. The transition is accurately tracked by the mutual information shared between replicators and their environment. In the absence of successfully repartitioning system resources, the transition fails to complete, leading to the possibility of many frustrated trials before life first emerges. Often, the replicators that initiate the transition are not those that are ultimately selected. The results are consistent with the view that life's propensity to shape its environment is indeed a universal feature of replicators, characteristic of the transition from nonlife to life. We discuss the implications of these results for understanding life's emergence and evolutionary transitions more broadly.

True Triaxial Experimental Study of Rockbursts Induced By Ramp and Cyclic Dynamic Disturbances

NASA Astrophysics Data System (ADS)

Su, Guoshao; Hu, Lihua; Feng, Xiating; Yan, Liubin; Zhang, Gangliang; Yan, Sizhou; Zhao, Bin; Yan, Zhaofu

2018-04-01

A modified rockburst testing system was utilized to reproduce rockbursts induced by ramp and cyclic dynamic disturbances with a low-intermediate strain rate of 2 × 10-3-5 × 10-3 s-1 in the laboratory. The experimental results show that both the ramp and cyclic dynamic disturbances play a significant role in inducing rockbursts. In the tests of rockbursts induced by a ramp dynamic disturbance, as the static stress before the dynamic disturbance increases, both the strength of specimens and the kinetic energy of the ejected fragments first increase and then decrease. In the tests of rockbursts induced by a cyclic dynamic disturbance, there exists a rockburst threshold of the static stress and the dynamic disturbance amplitude, and the kinetic energy of the ejected fragments first increases and then decreases as the cyclic dynamic disturbance frequency increases. The main differences between rockbursts induced by ramp dynamic disturbances and those induced by cyclic dynamic disturbances are as follows: the rockburst development process of the former is characterized by an impact failure feature, while that of the latter is characterized by a fatigue failure feature; the damage evolution curve of the specimen of the former has a leap-developing form with a significant catastrophic feature, while that of the latter has an inverted S-shape with a remarkable fatigue damage characteristic; the energy mechanism of the former involves the ramp dynamic disturbance giving extra elastic strain energy to rocks, while that of the latter involves the cyclic dynamic disturbance decreasing the ultimate energy storage capacity of rocks.

Indirect dynamics in SN2@N: insight into the influence of central atoms.

PubMed

Liu, Xu; Zhao, Chenyang; Yang, Li; Zhang, Jiaxu; Sun, Rui

2017-08-30

Central atoms have a significant influence on the reaction kinetics and dynamics of nucleophilic substitution (S N 2). Herein, atomistic dynamics of a prototype S N 2@N reaction F - + NH 2 Cl is uncovered employing direct dynamics simulations that show strikingly distinct features from those determined for a S N 2@C congener F - + CH 3 Cl. Indirect scattering is found to prevail, which proceeds predominantly through a hydrogen-bonded F - -HNHCl complex in the reactant entrance channel. This unexpected finding of a pronounced contribution of indirect reaction dynamics, even at a high collision energy, is in strong contrast to a general evolution from indirect to direct dynamics with enhanced energy that characterizes S N 2@C. This result suggests that the relative importance of different atomic-level mechanisms may depend essentially on the interaction potential of reactive encounters and the coupling between inter- and intramolecular modes of the pre-reaction complex. For F - + NH 2 Cl the proton transfer pathway is less competitive than S N 2. A remarkable finding is that the more favorable energetics for NH 2 Cl proton transfer, as compared to that for CH 3 Cl, does not manifest itself in the reaction dynamics. The present work sheds light on the underlying reaction dynamics of S N 2@N, which remain largely unclear compared to well-studied S N 2@C.

A comparison of East Asian summer monsoon simulations from CAM3.1 with three dynamic cores

NASA Astrophysics Data System (ADS)

Wei, Ting; Wang, Lanning; Dong, Wenjie; Dong, Min; Zhang, Jingyong

2011-12-01

This paper examines the sensitivity of CAM3.1 simulations of East Asian summer monsoon (EASM) to the choice of dynamic cores using three long-term simulations, one with each of the following cores: the Eulerian spectral transform method (EUL), semi-Lagrangian scheme (SLD) and finite volume approach (FV). Our results indicate that the dynamic cores significantly influence the simulated fields not only through dynamics, such as wind, but also through physical processes, such as precipitation. Generally speaking, SLD is superior to EUL and FV in simulating the climatological features of EASM and its interannual variability. The SLD version of the CAM model partially reduces its known deficiency in simulating the climatological features of East Asian summer precipitation. The strength and position of simulated western Pacific subtropical high (WPSH) and its ridge line compare more favourably with observations in SLD and FV than in EUL. They contribute to the intensification of the south-easterly along the south of WPSH and the vertical motion through the troposphere around 30° N, where the subtropical rain belt exists. Additionally, SLD simulates the scope of the westerly jet core over East Asia more realistically than the other two dynamic cores do. Considerable systematic errors of the seasonal migration of monsoon rain belt and water vapour flux exist in all of the three versions of CAM3.1 model, although it captures the broad northward shift of convection, and the simulated results share similarities. The interannual variation of EASM is found to be more accurate in SLD simulation, which reasonably reproduces the leading combined patterns of precipitation and 850-hPa winds in East Asia, as well as the 2.5- and 10-year periods of Li-Zeng EASM index. These results emphasise the importance of dynamic cores for the EASM simulation as distinct from the simulation's sensitivity to the physical parameterisations.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming.

PubMed

Chiu, Stephanie J; Toth, Cynthia A; Bowes Rickman, Catherine; Izatt, Joseph A; Farsiu, Sina

2012-05-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

PubMed Central

Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina

2012-01-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602

Mental simulation of routes during navigation involves adaptive temporal compression

PubMed Central

Arnold, Aiden E.G.F.; Iaria, Giuseppe; Ekstrom, Arne D.

2016-01-01

Mental simulation is a hallmark feature of human cognition, allowing features from memories to be flexibly used during prospection. While past studies demonstrate the preservation of real-world features such as size and distance during mental simulation, their temporal dynamics remains unknown. Here, we compare mental simulations to navigation of routes in a large-scale spatial environment to test the hypothesis that such simulations are temporally compressed in an adaptive manner. Our results show that simulations occurred at 2.39x the speed it took to navigate a route, increasing in compression (3.57x) for slower movement speeds. Participant self-reports of vividness and spatial coherence of simulations also correlated strongly with simulation duration, providing an important link between subjective experiences of simulated events and how spatial representations are combined during prospection. These findings suggest that simulation of spatial events involve adaptive temporal mechanisms, mediated partly by the fidelity of memories used to generate the simulation. PMID:27568586

Sex-chromosome turnovers: the hot-potato model.

PubMed

Blaser, Olivier; Neuenschwander, Samuel; Perrin, Nicolas

2014-01-01

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

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of cellular diversity for genetic and phenotypic features

PubMed Central

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G.; Helland, Åslaug; Rye, Inga H.; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L.; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-01-01

SUMMARY Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype-specific and it did not change during treatment in tumors with partial or no response. However, lower pre-treatment genetic diversity was significantly associated with complete pathologic response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. PMID:24462293

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Hold your horses: A comparison of human laryngomalacia with analogous equine airway pathology.

PubMed

Lawrence, Rachael J; Butterell, Matthew J; Constable, James D; Daniel, Matija

2018-02-01

Laryngomalacia is the most common cause of stridor in infants. Dynamic airway collapse is also a well-recognised entity in horses and an important cause of surgical veterinary intervention. We compare the aetiology, clinical features and management of human laryngomalacia with equine dynamic airway collapse. A structured review of the PubMed, the Ovid Medline and the Cochrane Collaboration databases (Cochrane Central Register of Controlled Trials, Cochrane Database of Systemic Reviews). There are numerous equine conditions that cause dynamic airway collapse defined specifically by the anatomical structures involved. Axial Deviation of the Aryepiglottic Folds (ADAF) is the condition most clinically analogous to laryngomalacia in humans, and is likewise most prevalent in the immature equine airway. Both conditions are managed either conservatively, or if symptoms require it, with surgical intervention. The operative procedures performed for ADAF and laryngomalacia are technically comparable. Dynamic collapse of the equine larynx, especially ADAF, is clinically similar to human laryngomalacia, and both are treated in a similar fashion. Copyright © 2017 Elsevier B.V. All rights reserved.

The Effects of Aging and Dual Tasking on Human Gait Complexity During Treadmill Walking: A Comparative Study Using Quantized Dynamical Entropy and Sample Entropy.

PubMed

Ahmadi, Samira; Wu, Christine; Sepehri, Nariman; Kantikar, Anuprita; Nankar, Mayur; Szturm, Tony

2018-01-01

Quantized dynamical entropy (QDE) has recently been proposed as a new measure to quantify the complexity of dynamical systems with the purpose of offering a better computational efficiency. This paper further investigates the viability of this method using five different human gait signals. These signals are recorded while normal walking and while performing secondary tasks among two age groups (young and older age groups). The results are compared with the outcomes of previously established sample entropy (SampEn) measure for the same signals. We also study how analyzing segmented and spatially and temporally normalized signal differs from analyzing whole data. Our findings show that human gait signals become more complex as people age and while they are cognitively loaded. Center of pressure (COP) displacement in mediolateral direction is the best signal for showing the gait changes. Moreover, the results suggest that by segmenting data, more information about intrastride dynamical features are obtained. Most importantly, QDE is shown to be a reliable measure for human gait complexity analysis.

Data collapse and critical dynamics in neuronal avalanche data

NASA Astrophysics Data System (ADS)

Butler, Thomas; Friedman, Nir; Dahmen, Karin; Beggs, John; Deville, Lee; Ito, Shinya

2012-02-01

The tasks of information processing, computation, and response to stimuli require neural computation to be remarkably flexible and diverse. To optimally satisfy the demands of neural computation, neuronal networks have been hypothesized to operate near a non-equilibrium critical point. In spite of their importance for neural dynamics, experimental evidence for critical dynamics has been primarily limited to power law statistics that can also emerge from non-critical mechanisms. By tracking the firing of large numbers of synaptically connected cortical neurons and comparing the resulting data to the predictions of critical phenomena, we show that cortical tissues in vitro can function near criticality. Among the most striking predictions of critical dynamics is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function (data collapse). We show for the first time that this prediction is confirmed in neuronal networks. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

Comparison of satellite-derived dynamical quantities for the stratosphere of the Southern Hemisphere

NASA Technical Reports Server (NTRS)

Miles, Thomas (Editor); Oneill, Alan (Editor)

1989-01-01

As part of the international Middle Atmosphere Program (MAP), a project was instituted to study the dynamics of the Middle Atmosphere in the Southern Hemisphere (MASH). A pre-MASH workshop was held with two aims: comparison of Southern Hemisphere dynamical quantities derived from various archives of satellite data; and assessing the impact of different base-level height information on such derived quantities. The dynamical quantities examined included geopotential height, zonal wind, potential vorticity, eddy heat and momentum fluxes, and Eliassen-Palm fluxes. It was found that while there was usually qualitative agreement between the different sets of fields, substantial quantitative differences were evident, particularly in high latitudes. The fidelity of the base-level analysis was found to be of prime importance in calculating derived quantities - especially the Eliassen-Palm flux divergence and potential vorticity. Improvements in base-level analyses are recommended. In particular, quality controls should be introduced to remove spurious localized features from analyses, and information from all Antarctic radiosondes should be utilized where possible. Caution in drawing quantitative inferences from satellite data for the middle atmosphere of the Southern Hemisphere is advised.

Dynamic Effects in the Photoionization of the 6s Subshell of Radon and Nobelium

NASA Astrophysics Data System (ADS)

Keating, David; Manson, Steven; Deshmukh, Pranawa

2017-04-01

Relativistic interactions are very important contributors to atomic properties. Of interest is the alterations made to the wave functions, i.e., the dynamics. These dynamical changes can greatly affect the photoionization cross section of heavy (high Z) atoms. To explore the extent of these dynamic effects a theoretical study of the 6s photoionization cross section of both radon (Z = 86) and nobelium (Z = 102) have been performed using the relativistic random phase approximation (RRPA) methodology. These two cases have been selected because they offer the clearest picture of the effects in question. In order to determine which features in the photoionization cross section are due to relativity, calculations using the (nonrelativistic) random phase approximation with exchange method (RPAE) are performed for comparison. Interchannel coupling can obscure the dynamic effects by ``pulling'' minima out of the discrete spectrum and into the continuum or by inducing minima. Therefore it is necessary to perform calculations without coupling included. This is possible thanks to the RRPA and RPAE codes being able to calculate cross sections with particular channels omitted. Comparisons are presented between calculations with and without interchannel coupling. Work supported by DOE and NSF.

The Mathematics of Psychotherapy: A Nonlinear Model of Change Dynamics.

PubMed

Schiepek, Gunter; Aas, Benjamin; Viol, Kathrin

2016-07-01

Psychotherapy is a dynamic process produced by a complex system of interacting variables. Even though there are qualitative models of such systems the link between structure and function, between network and network dynamics is still missing. The aim of this study is to realize these links. The proposed model is composed of five state variables (P: problem severity, S: success and therapeutic progress, M: motivation to change, E: emotions, I: insight and new perspectives) interconnected by 16 functions. The shape of each function is modified by four parameters (a: capability to form a trustful working alliance, c: mentalization and emotion regulation, r: behavioral resources and skills, m: self-efficacy and reward expectation). Psychologically, the parameters play the role of competencies or traits, which translate into the concept of control parameters in synergetics. The qualitative model was transferred into five coupled, deterministic, nonlinear difference equations generating the dynamics of each variable as a function of other variables. The mathematical model is able to reproduce important features of psychotherapy processes. Examples of parameter-dependent bifurcation diagrams are given. Beyond the illustrated similarities between simulated and empirical dynamics, the model has to be further developed, systematically tested by simulated experiments, and compared to empirical data.

A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy

NASA Astrophysics Data System (ADS)

Karsten, Sven; Bokarev, Sergey I.; Aziz, Saadullah G.; Ivanov, Sergei D.; Kühn, Oliver

2017-06-01

Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.

A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy.

PubMed

Karsten, Sven; Bokarev, Sergey I; Aziz, Saadullah G; Ivanov, Sergei D; Kühn, Oliver

2017-06-14

Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.

Efficacy of guided spiral drawing in the classification of Parkinson's Disease.

PubMed

Zham, Poonam; Arjunan, Sridhar; Raghav, Sanjay; Kumar, Dinesh Kant

2017-10-11

Change of handwriting can be an early marker for severity of Parkinson's disease but suffers from poor sensitivity and specificity due to inter-subject variations. This study has investigated the group-difference in the dynamic features during sketching of spiral between PD and control subjects with the aim of developing an accurate method for diagnosing PD patients. Dynamic handwriting features were computed for 206 specimens collected from 62 Subjects (31 Parkinson's and 31 Controls). These were analyzed based on the severity of the disease to determine group-difference. Spearman rank correlation coefficient was computed to evaluate the strength of association for the different features. Maximum area under ROC curve (AUC) using the dynamic features during different writing and spiral sketching tasks were in the range of 67 to 79 %. However, when angular features ( and ) and count of direction inversion during sketching of the spiral were used, AUC improved to 93.3%. Spearman correlation coefficient was highest for and . The angular features and count of direction inversion which can be obtained in real-time while sketching the Archimedean guided spiral on a digital tablet can be used for differentiating between Parkinson's and healthy cohort.

Covalency in transition-metal oxides within all-electron dynamical mean-field theory

NASA Astrophysics Data System (ADS)

Haule, Kristjan; Birol, Turan; Kotliar, Gabriel

2014-08-01

A combination of dynamical mean field theory and density functional theory, as implemented by Haule et al. [Phys. Rev. B 81, 195107 (2010), 10.1103/PhysRevB.81.195107], is applied to both the early and late transition metal oxides. For a fixed value of the local Coulomb repulsion, without fine tuning, we obtain the main features of these series, such as the metallic character of SrVO3 and the insulating gaps of LaVO3,LaTiO3, and La2CO4, which are in good agreement with experiment. This study highlights the importance of local physics and high energy hybridization in the screening of the Hubbard interaction and how different low energy behaviors can emerge from the unified treatment of the transition metal series.

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

PubMed

Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

Dynamically assisted Schwinger effect beyond the spatially-uniform-field approximation

NASA Astrophysics Data System (ADS)

Aleksandrov, I. A.; Plunien, G.; Shabaev, V. M.

2018-06-01

We investigate the phenomenon of electron-positron pair production from vacuum in the presence of a strong electric field superimposed by a weak but fast varying pulse which substantially increases the total particle yield. We employ a nonperturbative numerical technique and perform the calculations beyond the spatially-uniform-field approximation, i.e., dipole approximation, taking into account the coordinate dependence of the fast component. The analysis of the main characteristics of the pair-production process (momentum spectra of particles and total amount of pairs) reveals a number of important features which are absent within the previously used approximation. In particular, the structure of the momentum distribution is modified both qualitatively and quantitatively, and the total number of pairs created as well as the enhancement factor due to dynamical assistance become significantly smaller.

The interplay of biomolecules and water at the origin of the active behavior of living organisms

NASA Astrophysics Data System (ADS)

Del Giudice, E.; Stefanini, P.; Tedeschi, A.; Vitiello, G.

2011-12-01

It is shown that the main component of living matter, namely liquid water, is not an ensemble of independent molecules but an ensemble of phase correlated molecules kept in tune by an electromagnetic (e.m) field trapped in the ensemble. This field and the correlated potential govern the interaction among biomolecules suspended in water and are in turn affected by the chemical interactions of molecules. In particular, the phase of the coherent fields appears to play an important role in this dynamics. Recent experiments reported by the Montagnier group seem to corroborate this theory. Some features of the dynamics of human organisms, as reported by psychotherapy, holistic medicine and Eastern traditions, are analyzed in this frame and could find a rationale in this context.

Chemical Reaction Rate Coefficients from Ring Polymer Molecular Dynamics: Theory and Practical Applications

DOE PAGES

Suleimanov, Yury V.; Aoiz, F. Javier; Guo, Hua

2016-09-14

This Feature Article presents an overview of the current status of ring polymer molecular dynamics (RPMD) rate theory. We first analyze the RPMD approach and its connection to quantum transition-state theory. We then focus on its practical applications to prototypical chemical reactions in the gas phase, which demonstrate how accurate and reliable RPMD is for calculating thermal chemical reaction rate coefficients in multifarious cases. This review serves as an important checkpoint in RPMD rate theory development, which shows that RPMD is shifting from being just one of recent novel ideas to a well-established and validated alternative to conventional techniques formore » calculating thermal chemical rate coefficients. We also hope it will motivate further applications of RPMD to various chemical reactions.« less

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

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.

Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. We characterize the QCP by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. Here, we use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. Furthermore, by comparing with the calculations basedmore » on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.« less

Using Dynamic Geometry Software for Teaching Conditional Probability with Area-Proportional Venn Diagrams

ERIC Educational Resources Information Center

Radakovic, Nenad; McDougall, Douglas

2012-01-01

This classroom note illustrates how dynamic visualization can be used to teach conditional probability and Bayes' theorem. There are two features of the visualization that make it an ideal pedagogical tool in probability instruction. The first feature is the use of area-proportional Venn diagrams that, along with showing qualitative relationships,…

Dynamic Compression of the Signal in a Charge Sensitive Amplifier: From Concept to Design

NASA Astrophysics Data System (ADS)

Manghisoni, Massimo; Comotti, Daniele; Gaioni, Luigi; Ratti, Lodovico; Re, Valerio

2015-10-01

This work is concerned with the design of a low-noise Charge Sensitive Amplifier featuring a dynamic signal compression based on the non-linear features of an inversion-mode MOS capacitor. These features make the device suitable for applications where a non-linear characteristic of the front-end is required, such as in imaging instrumentation for free electron laser experiments. The aim of the paper is to discuss a methodology for the proper design of the feedback network enabling the dynamic signal compression. Starting from this compression solution, the design of a low-noise Charge Sensitive Amplifier is also discussed. The study has been carried out by referring to a 65 nm CMOS technology.

Automated dynamic feature tracking of RSLs on the Martian surface through HiRISE super-resolution restoration and 3D reconstruction techniques

NASA Astrophysics Data System (ADS)

Tao, Y.; Muller, J.-P.

2017-09-01

In this paper, we demonstrate novel Super-resolution restoration and 3D reconstruction tools developed within the EU FP7 projects and their applications to advanced dynamic feature tracking through HiRISE repeat stereo. We show an example with one of the RSL sites in the Palikir Crater took 8 repeat-pass 25cm HiRISE images from which a 5cm RSL-free SRR image is generated using GPT-SRR. Together with repeat 3D modelling of the same area, it allows us to overlay tracked dynamic features onto the reconstructed "original" surface, providing a much more comprehensive interpretation of the surface formation processes in 3D.

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

PubMed

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

2006-01-01

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

Ambiguity, logic, simplicity, and dynamics: Wittgensteinian evaluative criteria in peer review of quantitative research on categorization.

PubMed

Shimp, Charles P

2004-06-30

Research on categorization has changed over time, and some of these changes resemble how Wittgenstein's views changed from his Tractatus Logico-Philosophicus to his Philosophical Investigations. Wittgenstein initially focused on unambiguous, abstract, parsimonious, logical propositions and rules, and on independent, static, "atomic facts." This approach subsequently influenced the development of logical positivism and thereby may have indirectly influenced method and theory in research on categorization: much animal research on categorization has focused on learning simple, static, logical rules unambiguously interrelating small numbers of independent features. He later rejected logical simplicity and rigor and focused instead on Gestalt ideas about figure-ground reversals and context, the ambiguity of family resemblance, and the function of details of everyday language. Contemporary contextualism has been influenced by this latter position, some features of which appear in contemporary empirical research on categorization. These developmental changes are illustrated by research on avian local and global levels of visual perceptual analysis, categorization of rectangles and moving objects, and artificial grammar learning. Implications are described for peer review of quantitative theory in which ambiguity, logical rigor, simplicity, or dynamics are designed to play important roles.

Structural disorder in plant proteins: where plasticity meets sessility.

PubMed

Covarrubias, Alejandra A; Cuevas-Velazquez, Cesar L; Romero-Pérez, Paulette S; Rendón-Luna, David F; Chater, Caspar C C

2017-09-01

Plants are sessile organisms. This intriguing nature provokes the question of how they survive despite the continual perturbations caused by their constantly changing environment. The large amount of knowledge accumulated to date demonstrates the fascinating dynamic and plastic mechanisms, which underpin the diverse strategies selected in plants in response to the fluctuating environment. This phenotypic plasticity requires an efficient integration of external cues to their growth and developmental programs that can only be achieved through the dynamic and interactive coordination of various signaling networks. Given the versatility of intrinsic structural disorder within proteins, this feature appears as one of the leading characters of such complex functional circuits, critical for plant adaptation and survival in their wild habitats. In this review, we present information of those intrinsically disordered proteins (IDPs) from plants for which their high level of predicted structural disorder has been correlated with a particular function, or where there is experimental evidence linking this structural feature with its protein function. Using examples of plant IDPs involved in the control of cell cycle, metabolism, hormonal signaling and regulation of gene expression, development and responses to stress, we demonstrate the critical importance of IDPs throughout the life of the plant.

[Landscape pattern gradient dynamics and desakota features in rapid urbanization area: a case study in Panyu of Guangzhou].

PubMed

Yu, Long-Sheng; Fu, Yi-Fu; Yu, Huai-Yi; Li, Zhi-Qin

2011-01-01

In order to understand the landscape pattern gradient dynamics and desakota features in rapid urbanization area, this paper took the rapidly urbanizing Panyu District of Guangzhou City as a case, and analyzed its land use and land cover data, based on four Landsat TM images from 1990 to 2008. With the combination of gradient analysis and landscape pattern analysis, and by using the landscape indices in both class and landscape scales, the spatial dynamics and desakota feature of this rapidly urbanizing district were quantified. In the study district, there was a significant change in the landscape pattern, and a typical desakota feature presented along buffer gradient zones. Urban landscape increased and expanded annually, accompanied with serious fragmentation of agricultural landscape. The indices patch density, contagion, and landscape diversity, etc., changed regularly in the urbanization gradient, and the peak of landscape indices appeared in the gradient zone of 4-6 km away from the urban center. The landscape patterns at time series also reflected the differences among the dynamics in different gradient zones. The landscape pattern in desakota region was characterized by complex patch shape, high landscape diversity and fragmentation, and remarkable landscape dynamics. The peaks of landscape indices spread from the urban center to border areas, and desakota region was expanding gradually. The general trend of spatiotemporal dynamics in desakota region and its driving forces were discussed, which could be benefit to the regional land use policy-making and sustainable development planning.

Hydrogen bond dynamics in bulk alcohols.

PubMed

Shinokita, Keisuke; Cunha, Ana V; Jansen, Thomas L C; Pshenichnikov, Maxim S

2015-06-07

Hydrogen-bonded liquids play a significant role in numerous chemical and biological phenomena. In the past decade, impressive developments in multidimensional vibrational spectroscopy and combined molecular dynamics-quantum mechanical simulation have established many intriguing features of hydrogen bond dynamics in one of the fundamental solvents in nature, water. The next class of a hydrogen-bonded liquid--alcohols--has attracted much less attention. This is surprising given such important differences between water and alcohols as the imbalance between the number of hydrogen bonds, each molecule can accept (two) and donate (one) and the very presence of the hydrophobic group in alcohols. Here, we use polarization-resolved pump-probe and 2D infrared spectroscopy supported by extensive theoretical modeling to investigate hydrogen bond dynamics in methanol, ethanol, and isopropanol employing the OH stretching mode as a reporter. The sub-ps dynamics in alcohols are similar to those in water as they are determined by similar librational and hydrogen-bond stretch motions. However, lower density of hydrogen bond acceptors and donors in alcohols leads to the appearance of slow diffusion-controlled hydrogen bond exchange dynamics, which are essentially absent in water. We anticipate that the findings herein would have a potential impact on fundamental chemistry and biology as many processes in nature involve the interplay of hydrophobic and hydrophilic groups.

Dynamic Target Match Signals in Perirhinal Cortex Can Be Explained by Instantaneous Computations That Act on Dynamic Input from Inferotemporal Cortex

PubMed Central

Pagan, Marino

2014-01-01

Finding sought objects requires the brain to combine visual and target signals to determine when a target is in view. To investigate how the brain implements these computations, we recorded neural responses in inferotemporal cortex (IT) and perirhinal cortex (PRH) as macaque monkeys performed a delayed-match-to-sample target search task. Our data suggest that visual and target signals were combined within or before IT in the ventral visual pathway and then passed onto PRH, where they were reformatted into a more explicit target match signal over ∼10–15 ms. Accounting for these dynamics in PRH did not require proposing dynamic computations within PRH itself but, rather, could be attributed to instantaneous PRH computations performed upon an input representation from IT that changed with time. We found that the dynamics of the IT representation arose from two commonly observed features: individual IT neurons whose response preferences were not simply rescaled with time and variable response latencies across the population. Our results demonstrate that these types of time-varying responses have important consequences for downstream computation and suggest that dynamic representations can arise within a feedforward framework as a consequence of instantaneous computations performed upon time-varying inputs. PMID:25122904

Neural dynamics underlying attentional orienting to auditory representations in short-term memory.

PubMed

Backer, Kristina C; Binns, Malcolm A; Alain, Claude

2015-01-21

Sounds are ephemeral. Thus, coherent auditory perception depends on "hearing" back in time: retrospectively attending that which was lost externally but preserved in short-term memory (STM). Current theories of auditory attention assume that sound features are integrated into a perceptual object, that multiple objects can coexist in STM, and that attention can be deployed to an object in STM. Recording electroencephalography from humans, we tested these assumptions, elucidating feature-general and feature-specific neural correlates of auditory attention to STM. Alpha/beta oscillations and frontal and posterior event-related potentials indexed feature-general top-down attentional control to one of several coexisting auditory representations in STM. Particularly, task performance during attentional orienting was correlated with alpha/low-beta desynchronization (i.e., power suppression). However, attention to one feature could occur without simultaneous processing of the second feature of the representation. Therefore, auditory attention to memory relies on both feature-specific and feature-general neural dynamics. Copyright © 2015 the authors 0270-6474/15/351307-12$15.00/0.

Tools for assessing mitochondrial dynamics in mouse tissues and neurodegenerative models

NASA Astrophysics Data System (ADS)

Pham, Anh H.

Mitochondria are dynamic organelles that undergo membrane fusion and fission and transport. The dynamic properties of mitochondria are important for regulating mitochondrial function. Defects in mitochondrial dynamics are linked neurodegenerative diseases and affect the development of many tissues. To investigate the role of mitochondrial dynamics in diseases, versatile tools are needed to explore the physiology of these dynamic organelles in multiple tissues. Current tools for monitoring mitochondrial dynamics have been limited to studies in cell culture, which may be inadequate model systems for exploring the network of tissues. Here, we have generated mouse models for monitoring mitochondrial dynamics in a broad spectrum of tissues and cell types. The Photo-Activatable Mitochondrial (PhAM floxed) line enables Cre-inducible expression of a mitochondrial targeted photoconvertible protein, Dendra2 (mito-Dendra2). In the PhAMexcised line, mito-Dendra2 is ubiquitously expressed to facilitate broad analysis of mitochondria at various developmental processes. We have utilized these models to study mitochondrial dynamics in the nigrostriatal circuit of Parkinson's disease (PD) and in the development of skeletal muscles. Increasing evidences implicate aberrant regulation of mitochondrial fusion and fission in models of PD. To assess the function of mitochondrial dynamics in the nigrostriatal circuit, we utilized transgenic techniques to abrogate mitochondrial fusion. We show that deletion of the Mfn2 leads to the degeneration of dopaminergic neurons and Parkinson's-like features in mice. To elucidate the dynamic properties of mitochondria during muscle development, we established a platform for examining mitochondrial compartmentalization in skeletal muscles. This model system may yield clues to the role of mitochondrial dynamics in mitochondrial myopathies.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The balance of dynamic vorticity for the Presidents' Day storm

NASA Astrophysics Data System (ADS)

Zapotocny, Tom Harmon

1990-06-01

The maintenance of isentropic dynamic vorticity, defined as the vertical component of the curl of momentum, is examined for the life cycle of the Presidents'Day storm. Dynamic vorticity and its tendency are also compared to the more commonly used kinematic vorticity and its tendency. Diagnostics are first performed on an inviscid numerical simulation of an amplifying baroclinic disturbance by a hybrid isentropic-sigma coordinate channel model. The main purpose for studying a simulation with the channel model is to examine the first-order balance of dynamic vorticity during development under simplified conditions. A more in-depth evaluation of dynamic vorticity is presented for an excellent numerical simulation of the Presidents' Day storm of 18 to 20 February 1979. Dynamic vorticity diagnostics for the Presidents' Day storm reveal the importance of mass asymmetries within an isentropic layer and also document the effect of weak static stability. Prior to cyclogenesis, a strong cyclonic circulation tendency exists from both the vertical advection of vorticity and tilting terms. Another important feature is the merging of two synoptic scale short waves; one propagating southeast from the Great Lakes states, the other moving northeast from the Gulf of Mexico. Cyclogenesis is initiated by the latter of these two short waves, while rapid development occurs when the Great Lakes short waves reaches the Middle Atlantic states. During rapid development, an assessment of the ageostrophic component on spin-up is obtained from a balance of the divergence term and pressure stresses. Spin-up from the ageostrophic component is largest ahead of the lower tropospheric warm front. The impact of an 80 m/s subtropical jet streak, which enhances upper tropospheric processes during development, is also examined.

Cross-modal integration of lexical-semantic features during word processing: evidence from oscillatory dynamics during EEG.

PubMed

van Ackeren, Markus J; Rueschemeyer, Shirley-Ann

2014-01-01

In recent years, numerous studies have provided converging evidence that word meaning is partially stored in modality-specific cortical networks. However, little is known about the mechanisms supporting the integration of this distributed semantic content into coherent conceptual representations. In the current study we aimed to address this issue by using EEG to look at the spatial and temporal dynamics of feature integration during word comprehension. Specifically, participants were presented with two modality-specific features (i.e., visual or auditory features such as silver and loud) and asked to verify whether these two features were compatible with a subsequently presented target word (e.g., WHISTLE). Each pair of features described properties from either the same modality (e.g., silver, tiny  =  visual features) or different modalities (e.g., silver, loud  =  visual, auditory). Behavioral and EEG data were collected. The results show that verifying features that are putatively represented in the same modality-specific network is faster than verifying features across modalities. At the neural level, integrating features across modalities induces sustained oscillatory activity around the theta range (4-6 Hz) in left anterior temporal lobe (ATL), a putative hub for integrating distributed semantic content. In addition, enhanced long-range network interactions in the theta range were seen between left ATL and a widespread cortical network. These results suggest that oscillatory dynamics in the theta range could be involved in integrating multimodal semantic content by creating transient functional networks linking distributed modality-specific networks and multimodal semantic hubs such as left ATL.

Neural dynamics of speech act comprehension: an MEG study of naming and requesting.

PubMed

Egorova, Natalia; Pulvermüller, Friedemann; Shtyrov, Yury

2014-05-01

The neurobiological basis and temporal dynamics of communicative language processing pose important yet unresolved questions. It has previously been suggested that comprehension of the communicative function of an utterance, i.e. the so-called speech act, is supported by an ensemble of neural networks, comprising lexico-semantic, action and mirror neuron as well as theory of mind circuits, all activated in concert. It has also been demonstrated that recognition of the speech act type occurs extremely rapidly. These findings however, were obtained in experiments with insufficient spatio-temporal resolution, thus possibly concealing important facets of the neural dynamics of the speech act comprehension process. Here, we used magnetoencephalography to investigate the comprehension of Naming and Request actions performed with utterances controlled for physical features, psycholinguistic properties and the probability of occurrence in variable contexts. The results show that different communicative actions are underpinned by a dynamic neural network, which differentiates between speech act types very early after the speech act onset. Within 50-90 ms, Requests engaged mirror-neuron action-comprehension systems in sensorimotor cortex, possibly for processing action knowledge and intentions. Still, within the first 200 ms of stimulus onset (100-150 ms), Naming activated brain areas involved in referential semantic retrieval. Subsequently (200-300 ms), theory of mind and mentalising circuits were activated in medial prefrontal and temporo-parietal areas, possibly indexing processing of intentions and assumptions of both communication partners. This cascade of stages of processing information about actions and intentions, referential semantics, and theory of mind may underlie dynamic and interactive speech act comprehension.

Numerical results on noise-induced dynamics in the subthreshold regime for thermoacoustic systems

NASA Astrophysics Data System (ADS)

Gupta, Vikrant; Saurabh, Aditya; Paschereit, Christian Oliver; Kabiraj, Lipika

2017-03-01

Thermoacoustic instability is a serious issue in practical combustion systems. Such systems are inherently noisy, and hence the influence of noise on the dynamics of thermoacoustic instability is an aspect of practical importance. The present work is motivated by a recent report on the experimental observation of coherence resonance, or noise-induced coherence with a resonance-like dependence on the noise intensity as the system approaches the stability margin, for a prototypical premixed laminar flame combustor (Kabiraj et al., Phys. Rev. E, 4 (2015)). We numerically investigate representative thermoacoustic models for such noise-induced dynamics. Similar to the experiments, we study variation in system dynamics in response to variations in the noise intensity and in a critical control parameter as the systems approach their stability margins. The qualitative match identified between experimental results and observations in the representative models investigated here confirms that coherence resonance is a feature of thermoacoustic systems. We also extend the experimental results, which were limited to the case of subcritical Hopf bifurcation, to the case of supercritical Hopf bifurcation. We identify that the phenomenon has qualitative differences for the systems undergoing transition via subcritical and supercritical Hopf bifurcations. Two important practical implications are associated with the findings. Firstly, the increase in noise-induced coherence as the system approaches the onset of thermoacoustic instability can be considered as a precursor to the instability. Secondly, the dependence of noise-induced dynamics on the bifurcation type can be utilised to distinguish between subcritical and supercritical bifurcation prior to the onset of the instability.

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Dynamic data distributions in Vienna Fortran

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Mehrotra, Piyush; Moritsch, Hans; Zima, Hans

1993-01-01

Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data (SPMD) paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. Those features of Vienna Fortran that allow the data distributions of arrays to change dynamically, depending on runtime conditions are discussed. The relevant language features are discussed, their implementation is outlined, and how they may be used in applications is described.

Dynamic Imaging of Mouse Embryos and Cardiodynamics in Static Culture.

PubMed

Lopez, Andrew L; Larina, Irina V

2018-01-01

The heart is a dynamic organ that quickly undergoes morphological and mechanical changes through early embryonic development. Characterizing these early moments is important for our understanding of proper embryonic development and the treatment of heart disease. Traditionally, tomographic imaging modalities and fluorescence-based microscopy are excellent approaches to visualize structural features and gene expression patterns, respectively, and connect aberrant gene programs to pathological phenotypes. However, these approaches usually require static samples or fluorescent markers, which can limit how much information we can derive from the dynamic and mechanical changes that regulate heart development. Optical coherence tomography (OCT) is unique in this circumstance because it allows for the acquisition of three-dimensional structural and four-dimensional (3D + time) functional images of living mouse embryos without fixation or contrast reagents. In this chapter, we focus on how OCT can visualize heart morphology at different stages of development and provide cardiodynamic information to reveal mechanical properties of the developing heart.

Solid-state NMR characterization of cross-linking in EPDM/PP blends from 1H-13C polarization transfer dynamics.

PubMed

Aluas, Mihaela; Filip, Claudiu

2005-05-01

A novel approach for solid-state NMR characterization of cross-linking in polymer blends from the analysis of (1)H-(13)C polarization transfer dynamics is introduced. It extends the model of residual dipolar couplings under permanent cross-linking, typically used to describe (1)H transverse relaxation techniques, by considering a more realistic distribution of the order parameter along a polymer chain in rubbers. Based on a systematic numerical analysis, the extended model was shown to accurately reproduce all the characteristic features of the cross-polarization curves measured on such materials. This is particularly important for investigating blends of great technological potential, like thermoplastic elastomers, where (13)C high-resolution techniques, such as CP-MAS, are indispensable to selectively investigate structural and dynamical properties of the desired component. The validity of the new approach was demonstrated using the example of the CP build-up curves measured on a well resolved EPDM resonance line in a series of EPDM/PP blends.

Universal Hitting Time Statistics for Integrable Flows

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

CLASP2 interacts with p120-catenin and governs microtubule dynamics at adherens junctions

PubMed Central

Shahbazi, Marta N.; Megias, Diego; Epifano, Carolina; Akhmanova, Anna; Gundersen, Gregg G.; Fuchs, Elaine

2013-01-01

Classical cadherins and their connections with microtubules (MTs) are emerging as important determinants of cell adhesion. However, the functional relevance of such interactions and the molecular players that contribute to tissue architecture are still emerging. In this paper, we report that the MT plus end–binding protein CLASP2 localizes to adherens junctions (AJs) via direct interaction with p120-catenin (p120) in primary basal mouse keratinocytes. Reductions in the levels of p120 or CLASP2 decreased the localization of the other protein to cell–cell contacts and altered AJ dynamics and stability. These features were accompanied by decreased MT density and altered MT dynamics at intercellular junction sites. Interestingly, CLASP2 was enriched at the cortex of basal progenitor keratinocytes, in close localization to p120. Our findings suggest the existence of a new mechanism of MT targeting to AJs with potential functional implications in the maintenance of proper cell–cell adhesion in epidermal stem cells. PMID:24368809

Evidence from molecular dynamics simulations of conformational preorganization in the ribonuclease H active site

PubMed Central

Stafford, Kate A.; Palmer III, Arthur G.

2014-01-01

Ribonuclease H1 (RNase H) enzymes are well-conserved endonucleases that are present in all domains of life and are particularly important in the life cycle of retroviruses as domains within reverse transcriptase. Despite extensive study, especially of the E. coli homolog, the interaction of the highly negatively charged active site with catalytically required magnesium ions remains poorly understood. In this work, we describe molecular dynamics simulations of the E. coli homolog in complex with magnesium ions, as well as simulations of other homologs in their apo states. Collectively, these results suggest that the active site is highly rigid in the apo state of all homologs studied and is conformationally preorganized to favor the binding of a magnesium ion. Notably, representatives of bacterial, eukaryotic, and retroviral RNases H all exhibit similar active-site rigidity, suggesting that this dynamic feature is only subtly modulated by amino acid sequence and is primarily imposed by the distinctive RNase H protein fold. PMID:25075292

How input fluctuations reshape the dynamics of a biological switching system

NASA Astrophysics Data System (ADS)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

NASA Astrophysics Data System (ADS)

Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

2017-12-01

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

A molecular dynamics study of loop fluctuation in human papillomavirus type 16 virus-like particles: a possible indicator of immunogenicity.

PubMed

Joshi, Harshad; Cheluvaraja, Srinath; Somogyi, Endre; Brown, Darron R; Ortoleva, Peter

2011-11-28

Immunogenicity varies between the human papillomavirus (HPV) L1 monomer assemblies of various sizes (e.g., monomers, pentamers or whole capsids). The hypothesis that this can be attributed to the intensity of fluctuations of important loops containing neutralizing epitopes for the various assemblies is proposed for HPV L1 assemblies. Molecular dynamics simulations were utilized to begin testing this hypothesis. Fluctuations of loops that contain critical neutralizing epitopes (especially FG loop) were quantified via root-mean-square fluctuation and features in the frequency spectrum of dynamic changes in loop conformation. If this fluctuation-immunogenicity hypothesis is a universal aspect of immunogenicity (i.e., immune system recognition of an epitope within a loop is more reliable when it is presented via a more stable delivery structure), then fluctuation measures can serve as one predictor of immunogenicity as part of a computer-aided vaccine design strategy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Impact analysis of two kinds of failure strategies in Beijing road transportation network

NASA Astrophysics Data System (ADS)

Zhang, Zundong; Xu, Xiaoyang; Zhang, Zhaoran; Zhou, Huijuan

The Beijing road transportation network (BRTN), as a large-scale technological network, exhibits very complex and complicate features during daily periods. And it has been widely highlighted that how statistical characteristics (i.e. average path length and global network efficiency) change while the network evolves. In this paper, by using different modeling concepts, three kinds of network models of BRTN namely the abstract network model, the static network model with road mileage as weights and the dynamic network model with travel time as weights — are constructed, respectively, according to the topological data and the real detected flow data. The degree distribution of the three kinds of network models are analyzed, which proves that the urban road infrastructure network and the dynamic network behavior like scale-free networks. By analyzing and comparing the important statistical characteristics of three models under random attacks and intentional attacks, it shows that the urban road infrastructure network and the dynamic network of BRTN are both robust and vulnerable.

Non-linear corrections to the time-covariance function derived from a multi-state chemical master equation.

PubMed

Scott, M

2012-08-01

The time-covariance function captures the dynamics of biochemical fluctuations and contains important information about the underlying kinetic rate parameters. Intrinsic fluctuations in biochemical reaction networks are typically modelled using a master equation formalism. In general, the equation cannot be solved exactly and approximation methods are required. For small fluctuations close to equilibrium, a linearisation of the dynamics provides a very good description of the relaxation of the time-covariance function. As the number of molecules in the system decrease, deviations from the linear theory appear. Carrying out a systematic perturbation expansion of the master equation to capture these effects results in formidable algebra; however, symbolic mathematics packages considerably expedite the computation. The authors demonstrate that non-linear effects can reveal features of the underlying dynamics, such as reaction stoichiometry, not available in linearised theory. Furthermore, in models that exhibit noise-induced oscillations, non-linear corrections result in a shift in the base frequency along with the appearance of a secondary harmonic.

Handling and safety enhancement of race cars using active aerodynamic systems

NASA Astrophysics Data System (ADS)

Diba, Fereydoon; Barari, Ahmad; Esmailzadeh, Ebrahim

2014-09-01

A methodology is presented in this work that employs the active inverted wings to enhance the road holding by increasing the downward force on the tyres. In the proposed active system, the angles of attack of the vehicle's wings are adjusted by using a real-time controller to increase the road holding and hence improve the vehicle handling. The handling of the race car and safety of the driver are two important concerns in the design of race cars. The handling of a vehicle depends on the dynamic capabilities of the vehicle and also the pneumatic tyres' limitations. The vehicle side-slip angle, as a measure of the vehicle dynamic safety, should be narrowed into an acceptable range. This paper demonstrates that active inverted wings can provide noteworthy dynamic capabilities and enhance the safety features of race cars. Detailed analytical study and formulations of the race car nonlinear model with the airfoils are presented. Computer simulations are carried out to evaluate the performance of the proposed active aerodynamic system.

Building cosmological frozen stars

NASA Astrophysics Data System (ADS)

Kastor, David; Traschen, Jennie

2017-02-01

Janis-Newman-Winicour (JNW) solutions generalize Schwarzschild to include a massless scalar field. While they share the familiar infinite redshift feature of Schwarzschild, they suffer from the presence of naked singularities. Cosmological versions of JNW spacetimes were discovered some years ago, in the most general case, by Fonarev. Fonarev solutions are also plagued by naked singularities, but have the virtue, unlike e.g. Schwarzschild-deSitter, of being dynamical. Given that exact dynamical cosmological black hole solutions are scarce, Fonarev solutions merit further study. We show how Fonarev solutions can be obtained via generalized dimensional reduction from simpler static vacuum solutions. These results may lead towards constructions of actual dynamical cosmological black holes. In particular, we note that cosmological versions of extremal charged dilaton black holes are known. JNW spacetimes represent a different limiting case of the family of charged dilaton black holes, which have been important in the context of string theory, and better understanding their cosmological versions of JNW spacetimes thus provides a second data point towards finding cosmological versions of the entire family.

Genetic algorithms for the application of Activated Sludge Model No. 1.

PubMed

Kim, S; Lee, H; Kim, J; Kim, C; Ko, J; Woo, H; Kim, S

2002-01-01

The genetic algorithm (GA) has been integrated into the IWA ASM No. 1 to calibrate important stoichiometric and kinetic parameters. The evolutionary feature of GA was used to configure the multiple local optima as well as the global optimum. The objective function of optimization was designed to minimize the difference between estimated and measured effluent concentrations at the activated sludge system. Both steady state and dynamic data of the simulation benchmark were used for calibration using denitrification layout. Depending upon the confidence intervals and objective functions, the proposed method provided distributions of parameter space. Field data have been collected and applied to validate calibration capacity of GA. Dynamic calibration was suggested to capture periodic variations of inflow concentrations. Also, in order to verify this proposed method in real wastewater treatment plant, measured data sets for substrate concentrations were obtained from Haeundae wastewater treatment plant and used to estimate parameters in the dynamic system. The simulation results with calibrated parameters matched well with the observed concentrations of effluent COD.

Two-color single-photon emission from InAs quantum dots: toward logic information management using quantum light.

PubMed

Rivas, David; Muñoz-Matutano, Guillermo; Canet-Ferrer, Josep; García-Calzada, Raúl; Trevisi, Giovanna; Seravalli, Luca; Frigeri, Paola; Martínez-Pastor, Juan P

2014-02-12

In this work, we propose the use of the Hanbury-Brown and Twiss interferometric technique and a switchable two-color excitation method for evaluating the exciton and noncorrelated electron-hole dynamics associated with single photon emission from indium arsenide (InAs) self-assembled quantum dots (QDs). Using a microstate master equation model we demonstrate that our single QDs are described by nonlinear exciton dynamics. The simultaneous detection of two-color, single photon emission from InAs QDs using these nonlinear dynamics was used to design a NOT AND logic transference function. This computational functionality combines the advantages of working with light/photons as input/output device parameters (all-optical system) and that of a nanodevice (QD size of ∼ 20 nm) while also providing high optical sensitivity (ultralow optical power operational requirements). These system features represent an important and interesting step toward the development of new prototypes for the incoming quantum information technologies.

Chunking dynamics: heteroclinics in mind

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S.

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics. PMID:24672469

Chunking dynamics: heteroclinics in mind.

PubMed

Rabinovich, Mikhail I; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components-brain modes-participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles-metastable states-connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

Money-center structures in dynamic banking systems

NASA Astrophysics Data System (ADS)

Li, Shouwei; Zhang, Minghui

2016-10-01

In this paper, we propose a dynamic model for banking systems based on the description of balance sheets. It generates some features identified through empirical analysis. Through simulation analysis of the model, we find that banking systems have the feature of money-center structures, that bank asset distributions are power-law distributions, and that contract size distributions are log-normal distributions.

Statistical physics and physiology: monofractal and multifractal approaches

NASA Technical Reports Server (NTRS)

Stanley, H. E.; Amaral, L. A.; Goldberger, A. L.; Havlin, S.; Peng, C. K.

1999-01-01

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

A Single Nucleotide Polymorphism Uncovers a Novel Function for the Transcription Factor Ace2 during Candida albicans Hyphal Development

PubMed Central

Orellana-Muñoz, Sara; Gutiérrez-Escribano, Pilar; Arnáiz-Pita, Yolanda; Dueñas-Santero, Encarnación; Suárez, M. Belén; Bougnoux, Marie-Elisabeth; del Rey, Francisco; Sherlock, Gavin; d’Enfert, Christophe; Correa-Bordes, Jaime; de Aldana, Carlos R. Vázquez

2015-01-01

Candida albicans is a major invasive fungal pathogen in humans. An important virulence factor is its ability to switch between the yeast and hyphal forms, and these filamentous forms are important in tissue penetration and invasion. A common feature for filamentous growth is the ability to inhibit cell separation after cytokinesis, although it is poorly understood how this process is regulated developmentally. In C. albicans, the formation of filaments during hyphal growth requires changes in septin ring dynamics. In this work, we studied the functional relationship between septins and the transcription factor Ace2, which controls the expression of enzymes that catalyze septum degradation. We found that alternative translation initiation produces two Ace2 isoforms. While full-length Ace2, Ace2L, influences septin dynamics in a transcription-independent manner in hyphal cells but not in yeast cells, the use of methionine-55 as the initiation codon gives rise to Ace2S, which functions as the nuclear transcription factor required for the expression of cell separation genes. Genetic evidence indicates that Ace2L influences the incorporation of the Sep7 septin to hyphal septin rings in order to avoid inappropriate activation of cell separation during filamentous growth. Interestingly, a natural single nucleotide polymorphism (SNP) present in the C. albicans WO-1 background and other C. albicans commensal and clinical isolates generates a stop codon in the ninth codon of Ace2L that mimics the phenotype of cells lacking Ace2L. Finally, we report that Ace2L and Ace2S interact with the NDR kinase Cbk1 and that impairing activity of this kinase results in a defect in septin dynamics similar to that of hyphal cells lacking Ace2L. Together, our findings identify Ace2L and the NDR kinase Cbk1 as new elements of the signaling system that modify septin ring dynamics in hyphae to allow cell-chain formation, a feature that appears to have evolved in specific C. albicans lineages. PMID:25875512

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

PubMed

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

2012-08-01

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

Prediction of paroxysmal atrial fibrillation using recurrence plot-based features of the RR-interval signal.

PubMed

Mohebbi, Maryam; Ghassemian, Hassan

2011-08-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia and increases the risk of stroke. Predicting the onset of paroxysmal AF (PAF), based on noninvasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize risks for the patients. In this paper, we propose an effective PAF predictor which is based on the analysis of the RR-interval signal. This method consists of three steps: preprocessing, feature extraction and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the RR-interval signal is extracted. In the next step, the recurrence plot (RP) of the RR-interval signal is obtained and five statistically significant features are extracted to characterize the basic patterns of the RP. These features consist of the recurrence rate, length of longest diagonal segments (L(max )), average length of the diagonal lines (L(mean)), entropy, and trapping time. Recurrence quantification analysis can reveal subtle aspects of dynamics not easily appreciated by other methods and exhibits characteristic patterns which are caused by the typical dynamical behavior. In the final step, a support vector machine (SVM)-based classifier is used for PAF prediction. The performance of the proposed method in prediction of PAF episodes was evaluated using the Atrial Fibrillation Prediction Database (AFPDB) which consists of both 30 min ECG recordings that end just prior to the onset of PAF and segments at least 45 min distant from any PAF events. The obtained sensitivity, specificity, positive predictivity and negative predictivity were 97%, 100%, 100%, and 96%, respectively. The proposed methodology presents better results than other existing approaches.

Substructured multibody molecular dynamics.

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

Grest, Gary Stephen; Stevens, Mark Jackson; Plimpton, Steven James

2006-11-01

We have enhanced our parallel molecular dynamics (MD) simulation software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator, lammps.sandia.gov) to include many new features for accelerated simulation including articulated rigid body dynamics via coupling to the Rensselaer Polytechnic Institute code POEMS (Parallelizable Open-source Efficient Multibody Software). We use new features of the LAMMPS software package to investigate rhodopsin photoisomerization, and water model surface tension and capillary waves at the vapor-liquid interface. Finally, we motivate the recipes of MD for practitioners and researchers in numerical analysis and computational mechanics.

From ab Initio Potential Energy Surfaces to State-Resolved Reactivities: X + H 2O ↔ HX + OH [X = F, Cl, and O( 3P)] Reactions

DOE PAGES

Li, Jun; Jiang, Bin; Song, Hongwei; ...

2015-04-17

Here, we survey the recent advances in theoretical understanding of quantum state resolved dynamics, using the title reactions as examples. It is shown that the progress was made possible by major developments in two areas. First, an accurate analytical representation of many high-level ab initio points over a large configuration space can now be made with high fidelity and the necessary permutation symmetry. The resulting full-dimensional global potential energy surfaces enable dynamical calculations using either quasi-classical trajectory or more importantly quantum mechanical methods. The second advance is the development of accurate and efficient quantum dynamical methods, which are necessary formore » providing a reliable treatment of quantum effects in reaction dynamics such as tunneling, resonances, and zero-point energy. The powerful combination of the two advances has allowed us to achieve a quantitatively accurate characterization of the reaction dynamics, which unveiled rich dynamical features such as steric steering, strong mode specificity, and bond selectivity. The dependence of reactivity on reactant modes can be rationalized by the recently proposed sudden vector projection model, which attributes the mode specificity and bond selectivity to the coupling of reactant modes with the reaction coordinate at the relevant transition state. The deeper insights provided by these theoretical studies have advanced our understanding of reaction dynamics to a new level.« less

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection.

PubMed

Bogaarts, J G; Hilkman, D M W; Gommer, E D; van Kranen-Mastenbroek, V H J M; Reulen, J P H

2016-12-01

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

A Semiquantitative Framework for Gene Regulatory Networks: Increasing the Time and Quantitative Resolution of Boolean Networks

PubMed Central

Kerkhofs, Johan; Geris, Liesbet

2015-01-01

Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour. PMID:26067297

Application of recurrence quantification analysis for the automated identification of epileptic EEG signals.

PubMed

Acharya, U Rajendra; Sree, S Vinitha; Chattopadhyay, Subhagata; Yu, Wenwei; Ang, Peng Chuan Alvin

2011-06-01

Epilepsy is a common neurological disorder that is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals are widely used to diagnose seizures. Because of the non-linear and dynamic nature of the EEG signals, it is difficult to effectively decipher the subtle changes in these signals by visual inspection and by using linear techniques. Therefore, non-linear methods are being researched to analyze the EEG signals. In this work, we use the recorded EEG signals in Recurrence Plots (RP), and extract Recurrence Quantification Analysis (RQA) parameters from the RP in order to classify the EEG signals into normal, ictal, and interictal classes. Recurrence Plot (RP) is a graph that shows all the times at which a state of the dynamical system recurs. Studies have reported significantly different RQA parameters for the three classes. However, more studies are needed to develop classifiers that use these promising features and present good classification accuracy in differentiating the three types of EEG segments. Therefore, in this work, we have used ten RQA parameters to quantify the important features in the EEG signals.These features were fed to seven different classifiers: Support vector machine (SVM), Gaussian Mixture Model (GMM), Fuzzy Sugeno Classifier, K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tree (DT), and Radial Basis Probabilistic Neural Network (RBPNN). Our results show that the SVM classifier was able to identify the EEG class with an average efficiency of 95.6%, sensitivity and specificity of 98.9% and 97.8%, respectively.

Tissue-specific features of the X chromosome and nucleolus spatial dynamics in a malaria mosquito, Anopheles atroparvus

PubMed Central

Bondarenko, Semen M.; Artemov, Gleb N.; Stegniy, Vladimir N.

2017-01-01

Spatial organization of chromosome territories is important for maintenance of genomic stability and regulation of gene expression. Recent studies have shown tissue-specific features of chromosome attachments to the nuclear envelope in various organisms including malaria mosquitoes. However, other spatial characteristics of nucleus organization, like volume and shape of chromosome territories, have not been studied in Anopheles. We conducted a thorough analysis of tissue-specific features of the X chromosome and nucleolus volume and shape in follicular epithelium and nurse cells of the Anopheles atroparvus ovaries using a modern open-source software. DNA of the polytene X chromosome from ovarian nurse cells was obtained by microdissection and was used as a template for amplification with degenerate oligo primers. A fluorescently labeled X chromosome painting probe was hybridized with formaldehyde-fixed ovaries of mosquitoes using a 3D-FISH method. The nucleolus was stained by immunostaining with an anti-fibrillarin antibody. The analysis was conducted with TANGO—a software for a chromosome spatial organization analysis. We show that the volume and position of the X chromosome have tissue-specific characteristics. Unlike nurse cell nuclei, the growth of follicular epithelium nuclei is not accompanied with the proportional growth of the X chromosome. However, the shape of the X chromosome does not differ between the tissues. The dynamics of the X chromosome attachment regions location is tissue-specific and it is correlated with the process of nucleus growth in follicular epithelium and nurse cells. PMID:28158219

Tissue-specific features of the X chromosome and nucleolus spatial dynamics in a malaria mosquito, Anopheles atroparvus.

PubMed

Bondarenko, Semen M; Artemov, Gleb N; Sharakhov, Igor V; Stegniy, Vladimir N

2017-01-01

Spatial organization of chromosome territories is important for maintenance of genomic stability and regulation of gene expression. Recent studies have shown tissue-specific features of chromosome attachments to the nuclear envelope in various organisms including malaria mosquitoes. However, other spatial characteristics of nucleus organization, like volume and shape of chromosome territories, have not been studied in Anopheles. We conducted a thorough analysis of tissue-specific features of the X chromosome and nucleolus volume and shape in follicular epithelium and nurse cells of the Anopheles atroparvus ovaries using a modern open-source software. DNA of the polytene X chromosome from ovarian nurse cells was obtained by microdissection and was used as a template for amplification with degenerate oligo primers. A fluorescently labeled X chromosome painting probe was hybridized with formaldehyde-fixed ovaries of mosquitoes using a 3D-FISH method. The nucleolus was stained by immunostaining with an anti-fibrillarin antibody. The analysis was conducted with TANGO-a software for a chromosome spatial organization analysis. We show that the volume and position of the X chromosome have tissue-specific characteristics. Unlike nurse cell nuclei, the growth of follicular epithelium nuclei is not accompanied with the proportional growth of the X chromosome. However, the shape of the X chromosome does not differ between the tissues. The dynamics of the X chromosome attachment regions location is tissue-specific and it is correlated with the process of nucleus growth in follicular epithelium and nurse cells.

F-BAR family proteins, emerging regulators for cell membrane dynamic changes-from structure to human diseases.

PubMed

Liu, Suxuan; Xiong, Xinyu; Zhao, Xianxian; Yang, Xiaofeng; Wang, Hong

2015-05-09

Eukaryotic cell membrane dynamics change in curvature during physiological and pathological processes. In the past ten years, a novel protein family, Fes/CIP4 homology-Bin/Amphiphysin/Rvs (F-BAR) domain proteins, has been identified to be the most important coordinators in membrane curvature regulation. The F-BAR domain family is a member of the Bin/Amphiphysin/Rvs (BAR) domain superfamily that is associated with dynamic changes in cell membrane. However, the molecular basis in membrane structure regulation and the biological functions of F-BAR protein are unclear. The pathophysiological role of F-BAR protein is unknown. This review summarizes the current understanding of structure and function in the BAR domain superfamily, classifies F-BAR family proteins into nine subfamilies based on domain structure, and characterizes F-BAR protein structure, domain interaction, and functional relevance. In general, F-BAR protein binds to cell membrane via F-BAR domain association with membrane phospholipids and initiates membrane curvature and scission via Src homology-3 (SH3) domain interaction with its partner proteins. This process causes membrane dynamic changes and leads to seven important cellular biological functions, which include endocytosis, phagocytosis, filopodium, lamellipodium, cytokinesis, adhesion, and podosome formation, via distinct signaling pathways determined by specific domain-binding partners. These cellular functions play important roles in many physiological and pathophysiological processes. We further summarize F-BAR protein expression and mutation changes observed in various diseases and developmental disorders. Considering the structure feature and functional implication of F-BAR proteins, we anticipate that F-BAR proteins modulate physiological and pathophysiological processes via transferring extracellular materials, regulating cell trafficking and mobility, presenting antigens, mediating extracellular matrix degradation, and transmitting signaling for cell proliferation.

Dynamic binding of visual features by neuronal/stimulus synchrony.

PubMed

Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application

PubMed Central

Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-01-01

Background The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. Objective The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Methods Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. Results The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. Conclusions This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. PMID:28903894

Cultured bovine granulosa cells rapidly lose important features of their identity and functionality but partially recover under long-term culture conditions.

PubMed

Yenuganti, Vengala Rao; Vanselow, Jens

2017-05-01

Cell culture models are essential for the detailed study of molecular processes. We analyze the dynamics of changes in a culture model of bovine granulosa cells. The cells were cultured for up to 8 days and analyzed for steroid production and gene expression. According to the expression of the marker genes CDH1, CDH2 and VIM, the cells maintained their mesenchymal character throughout the time of culture. In contrast, the levels of functionally important transcripts and of estradiol and progesterone production were rapidly down-regulated but showed a substantial up-regulation from day 4. FOXL2, a marker for granulosa cell identity, was also rapidly down-regulated after plating but completely recovered towards the end of culture. In contrast, expression of the Sertoli cell marker SOX9 and the lesion/inflammation marker PTGS2 increased during the first 2 days after plating but gradually decreased later on. We conclude that only long-term culture conditions (>4 days) allow the cells to recover from plating stress and to re-acquire characteristic granulosa cell features.

Feature Integration across Space, Time, and Orientation

ERIC Educational Resources Information Center

Otto, Thomas U.; Ogmen, Haluk; Herzog, Michael H.

2009-01-01

The perception of a visual target can be strongly influenced by flanking stimuli. In static displays, performance on the target improves when the distance to the flanking elements increases--presumably because feature pooling and integration vanishes with distance. Here, we studied feature integration with dynamic stimuli. We show that features of…

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Spatially resolved dielectric constant of confined water and its connection to the non-local nature of bulk water

NASA Astrophysics Data System (ADS)

Schaaf, Christian; Gekle, Stephan

2016-08-01

We use molecular dynamics simulations to compute the spatially resolved static dielectric constant of water in cylindrical and spherical nanopores as occurring, e.g., in protein water pockets or carbon nanotubes. For this, we derive a linear-response formalism which correctly takes into account the dielectric boundary conditions in the considered geometries. We find that in cylindrical confinement, the axial component behaves similar as the local density akin to what is known near planar interfaces. The radial dielectric constant shows some oscillatory features when approaching the surface if their radius is larger than about 2 nm. Most importantly, however, the radial component exhibits pronounced oscillations at the center of the cavity. These surprising features are traced back quantitatively to the non-local dielectric nature of bulk water.

Work/control stations in Space Station weightlessness

NASA Technical Reports Server (NTRS)

Willits, Charles

1990-01-01

An ergonomic integration of controls, displays, and associated interfaces with an operator, whose body geometry and dynamics may be altered by the state of weightlessness, is noted to rank in importance with the optimal positioning of controls relative to the layout and architecture of 'body-ported' work/control stations applicable to the NASA Space Station Freedom. A long-term solution to this complex design problem is envisioned to encompass the following features: multiple imaging, virtual optics, screen displays controlled by a keyboard ergonomically designed for weightlessness, cursor control, a CCTV camera, and a hand-controller featuring 'no-grip' vernier/tactile positioning. This controller frees all fingers for multiple-switch actuations, while retaining index/register determination with the hand controller. A single architectural point attachment/restraint may be used which requires no residual muscle tension in either brief or prolonged operation.

Hdr Imaging for Feature Detection on Detailed Architectural Scenes

NASA Astrophysics Data System (ADS)

Kontogianni, G.; Stathopoulou, E. K.; Georgopoulos, A.; Doulamis, A.

2015-02-01

3D reconstruction relies on accurate detection, extraction, description and matching of image features. This is even truer for complex architectural scenes that pose needs for 3D models of high quality, without any loss of detail in geometry or color. Illumination conditions influence the radiometric quality of images, as standard sensors cannot depict properly a wide range of intensities in the same scene. Indeed, overexposed or underexposed pixels cause irreplaceable information loss and degrade digital representation. Images taken under extreme lighting environments may be thus prohibitive for feature detection/extraction and consequently for matching and 3D reconstruction. High Dynamic Range (HDR) images could be helpful for these operators because they broaden the limits of illumination range that Standard or Low Dynamic Range (SDR/LDR) images can capture and increase in this way the amount of details contained in the image. Experimental results of this study prove this assumption as they examine state of the art feature detectors applied both on standard dynamic range and HDR images.

Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data

NASA Astrophysics Data System (ADS)

Zhu, Zhe; Harowicz, Michael; Zhang, Jun; Saha, Ashirbani; Grimm, Lars J.; Hwang, Shelley; Mazurowski, Maciej A.

2018-02-01

Approximately 25% of patients with ductal carcinoma in situ (DCIS) diagnosed from core needle biopsy are subsequently upstaged to invasive cancer at surgical excision. Identifying patients with occult invasive disease is important as it changes treatment and precludes enrollment in active surveillance for DCIS. In this study, we investigated upstaging of DCIS to invasive disease using deep features. While deep neural networks require large amounts of training data, the available data to predict DCIS upstaging is sparse and thus directly training a neural network is unlikely to be successful. In this work, a pre-trained neural network is used as a feature extractor and a support vector machine (SVM) is trained on the extracted features. We used the dynamic contrast-enhanced (DCE) MRIs of patients at our institution from January 1, 2000, through March 23, 2014 who underwent MRI following a diagnosis of DCIS. Among the 131 DCIS patients, there were 35 patients who were upstaged to invasive cancer. Area under the ROC curve within the 10-fold cross-validation scheme was used for validation of our predictive model. The use of deep features was able to achieve an AUC of 0.68 (95% CI: 0.56-0.78) to predict occult invasive disease. This preliminary work demonstrates the promise of deep features to predict surgical upstaging following a diagnosis of DCIS.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Constructing the reduced dynamical models of interannual climate variability from spatial-distributed time series

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

We suggest a method for empirical forecast of climate dynamics basing on the reconstruction of reduced dynamical models in a form of random dynamical systems [1,2] derived from observational time series. The construction of proper embedding - the set of variables determining the phase space the model works in - is no doubt the most important step in such a modeling, but this task is non-trivial due to huge dimension of time series of typical climatic fields. Actually, an appropriate expansion of observational time series is needed yielding the number of principal components considered as phase variables, which are to be efficient for the construction of low-dimensional evolution operator. We emphasize two main features the reduced models should have for capturing the main dynamical properties of the system: (i) taking into account time-lagged teleconnections in the atmosphere-ocean system and (ii) reflecting the nonlinear nature of these teleconnections. In accordance to these principles, in this report we present the methodology which includes the combination of a new way for the construction of an embedding by the spatio-temporal data expansion and nonlinear model construction on the basis of artificial neural networks. The methodology is aplied to NCEP/NCAR reanalysis data including fields of sea level pressure, geopotential height, and wind speed, covering Northern Hemisphere. Its efficiency for the interannual forecast of various climate phenomena including ENSO, PDO, NAO and strong blocking event condition over the mid latitudes, is demonstrated. Also, we investigate the ability of the models to reproduce and predict the evolution of qualitative features of the dynamics, such as spectral peaks, critical transitions and statistics of extremes. This research was supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS) [1] Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, "Random dynamical models from time series," Phys. Rev. E, vol. 85, no. 3, p. 036216, 2012. [2] D. Mukhin, D. Kondrashov, E. Loskutov, A. Gavrilov, A. Feigin, and M. Ghil, "Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models," J. Clim., vol. 28, no. 5, pp. 1962-1976, 2015.

Spatial Heterogeneity as a Genetic Mixing Mechanism in Highly Philopatric Colonial Seabirds

PubMed Central

Cristofari, Robin; Trucchi, Emiliano; Whittington, Jason D.; Vigetta, Stéphanie; Gachot-Neveu, Hélène; Stenseth, Nils Christian; Le Maho, Yvon; Le Bohec, Céline

2015-01-01

How genetic diversity is maintained in philopatric colonial systems remains unclear, and understanding the dynamic balance of philopatry and dispersal at all spatial scales is essential to the study of the evolution of coloniality. In the King penguin, Aptenodytes patagonicus, return rates of post-fledging chicks to their natal sub-colony are remarkably high. Empirical studies have shown that adults return year after year to their previous breeding territories within a radius of a few meters. Yet, little reliable data are available on intra- and inter-colonial dispersal in this species. Here, we present the first fine-scale study of the genetic structure in a king penguin colony in the Crozet Archipelago. Samples were collected from individual chicks and analysed at 8 microsatellite loci. Precise geolocation data of hatching sites and selective pressures associated with habitat features were recorded for all sampling locations. We found that despite strong natal and breeding site fidelity, king penguins retain a high degree of panmixia and genetic diversity. Yet, genetic structure appears markedly heterogeneous across the colony, with higher-than-expected inbreeding levels, and local inbreeding and relatedness hotspots that overlap predicted higher-quality nesting locations. This points towards heterogeneous population structure at the sub-colony level, in which fine-scale environmental features drive local philopatric behaviour, while lower-quality patches may act as genetic mixing mechanisms at the colony level. These findings show how a lack of global genetic structuring can emerge from small-scale heterogeneity in ecological parameters, as opposed to the classical model of homogeneous dispersal. Our results also emphasize the importance of sampling design for estimation of population parameters in colonial seabirds, as at high spatial resolution, basic genetic features are shown to be location-dependent. Finally, this study stresses the importance of understanding intra-colonial dispersal and genetic mixing mechanisms in order to better estimate species-wide gene flows and population dynamics. PMID:25680103

Spatial heterogeneity as a genetic mixing mechanism in highly philopatric colonial seabirds.

PubMed

Cristofari, Robin; Trucchi, Emiliano; Whittington, Jason D; Vigetta, Stéphanie; Gachot-Neveu, Hélène; Stenseth, Nils Christian; Le Maho, Yvon; Le Bohec, Céline

2015-01-01

How genetic diversity is maintained in philopatric colonial systems remains unclear, and understanding the dynamic balance of philopatry and dispersal at all spatial scales is essential to the study of the evolution of coloniality. In the King penguin, Aptenodytes patagonicus, return rates of post-fledging chicks to their natal sub-colony are remarkably high. Empirical studies have shown that adults return year after year to their previous breeding territories within a radius of a few meters. Yet, little reliable data are available on intra- and inter-colonial dispersal in this species. Here, we present the first fine-scale study of the genetic structure in a king penguin colony in the Crozet Archipelago. Samples were collected from individual chicks and analysed at 8 microsatellite loci. Precise geolocation data of hatching sites and selective pressures associated with habitat features were recorded for all sampling locations. We found that despite strong natal and breeding site fidelity, king penguins retain a high degree of panmixia and genetic diversity. Yet, genetic structure appears markedly heterogeneous across the colony, with higher-than-expected inbreeding levels, and local inbreeding and relatedness hotspots that overlap predicted higher-quality nesting locations. This points towards heterogeneous population structure at the sub-colony level, in which fine-scale environmental features drive local philopatric behaviour, while lower-quality patches may act as genetic mixing mechanisms at the colony level. These findings show how a lack of global genetic structuring can emerge from small-scale heterogeneity in ecological parameters, as opposed to the classical model of homogeneous dispersal. Our results also emphasize the importance of sampling design for estimation of population parameters in colonial seabirds, as at high spatial resolution, basic genetic features are shown to be location-dependent. Finally, this study stresses the importance of understanding intra-colonial dispersal and genetic mixing mechanisms in order to better estimate species-wide gene flows and population dynamics.

Transition metal redox switches for reversible "on/off" and "slow/fast" single-molecule magnet behaviour in dysprosium and erbium bis-diamidoferrocene complexes.

PubMed

Dickie, Courtney M; Laughlin, Alexander L; Wofford, Joshua D; Bhuvanesh, Nattamai S; Nippe, Michael

2017-12-01

Single-molecule magnets (SMMs) are considered viable candidates for next-generation data storage and quantum computing. Systems featuring switchability of their magnetization dynamics are particularly interesting with respect to accessing more complex logic gates and device architectures. Here we show that transition metal based redox events can be exploited to enable reversible switchability of slow magnetic relaxation of magnetically anisotropic lanthanide ions. Specifically, we report anionic homoleptic bis-diamidoferrocene complexes of Dy 3+ (oblate) and Er 3+ (prolate) which can be reversibly oxidized by one electron to yield their respective charge neutral redox partners (Dy: [1] - , 1 ; Er: [2] - , 2 ). Importantly, compounds 1 and 2 are thermally stable which allowed for detailed studies of their magnetization dynamics. We show that the Dy 3+ [1] - / 1 system can function as an "on"/"off" or a "slow"/"fast" redox switchable SMM system in the absence or presence of applied dc fields, respectively. The Er 3+ based [2] - / 2 system features "on"/"off" switchability of SMM properties in the presence of applied fields. Results from electrochemical investigations, UV-vis-NIR spectroscopy, and 57 Fe Mössbauer spectroscopy indicate the presence of significant electronic communication between the mixed-valent Fe ions in 1 and 2 in both solution and solid state. This comparative evaluation of redox-switchable magnetization dynamics in low coordinate lanthanide complexes may be used as a potential blueprint toward the development of future switchable magnetic materials.

Branching, Chain Scission, and Solution Stability of Worm-Like Micelles

NASA Astrophysics Data System (ADS)

Beaucage, Greg; Vogtt, Karsten; Jiang, Hanqui

As salt is added to a simple micelle solution such as SDS or SLES, the zero shear rate specific viscosity rises rapidly followed by a maximum and decay. The rapid rise in viscosity is associated with formation of elliptical and extended chain worm-like micelles, WLMs. Entanglement of these long chain micelles leads to the viscoelastic behavior we associate with shampoo and body wash. The plateau and drop in viscosity at high salt concentrations is caused by a special type of topological branching where the branch points have no energy penalty to motion along the chain according to Cates theory. These have some similarity to catenane crosslinks. Predictive dynamic theories for WLMs rely on structural details; the diameter, persistence length, contour length, branch length, segment length between branch points, and mesh size. Further, since the contour length and other large scale features are in kinetic equilibrium, with frequent chain breakage and formation, the thermodynamics of these long chain structures are of interest both in terms of chain scission as well as in terms of the stability of the colloidal solution as a whole. Recent structural studies of WLMs using static neutron scattering based on new scattering models will be presented demonstrating that these input parameters for dynamic models of complex topological systems are quantitatively and directly available. In this context it is important to consider a comparison between dynamic features, for instance entanglement, and their static analogs, chain overlap.

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

PubMed

Ly, Cheng

2015-12-01

Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

Dynamic features of apo and bound HIV-Nef protein reveal the anti-HIV dimerization inhibition mechanism.

PubMed

Moonsamy, Suri; Bhakat, Soumendranath; Soliman, Mahmoud E S

2015-01-01

The first account on the dynamic features of Nef or negative factor, a small myristoylated protein located in the cytoplasm believes to increase HIV-1 viral titer level, is reported herein. Due to its major role in HIV-1 pathogenicity, Nef protein is considered an emerging target in anti-HIV drug design and discovery process. In this study, comparative long-range all-atom molecular dynamics simulations were employed for apo and bound protein to unveil molecular mechanism of HIV-Nef dimerization and inhibition. Results clearly revealed that B9, a newly discovered Nef inhibitor, binds at the dimeric interface of Nef protein and caused significant separation between orthogonally opposed residues, namely Asp108, Leu112 and Gln104. Large differences in magnitudes were observed in the radius of gyration (∼1.5 Å), per-residue fluctuation (∼2 Å), C-alpha deviations (∼2 Å) which confirm a comparatively more flexible nature of apo conformation due to rapid dimeric association. Compared to the bound conformer, a more globally correlated motion in case of apo structure of HIV-Nef confirms the process of dimeric association. This clearly highlights the process of inhibition as a result of ligand binding. The difference in principal component analysis (PCA) scatter plot and per-residue mobility plot across first two normal modes further justifies the same findings. The in-depth dynamic analyses of Nef protein presented in this report would serve crucial in understanding its function and inhibition mechanisms. Information on inhibitor binding mode would also assist in designing of potential inhibitors against this important HIV target.

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

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

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Characterizing and modeling the dynamics of online popularity.

PubMed

Ratkiewicz, Jacob; Fortunato, Santo; Flammini, Alessandro; Menczer, Filippo; Vespignani, Alessandro

2010-10-08

Online popularity has an enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.

Exploration of the canyon-incised continental margin of the northeastern United States reveals dynamic habitats and diverse communities

USGS Publications Warehouse

Quattrini, Andrea; Nizinski, Martha S.; Chaytor, Jason; Demopoulos, Amanda W.J.; Roark, E. Brendan; France, Scott; Moore, Jon A.; Heyl, Taylor P.; Auster, Peter J.; Ruppel, Carolyn D.; Elliott, Kelley P.; Kennedy, Brian R.C.; Lobecker, Elizabeth A.; Skarke, Adam; Shank, Timothy M.

2015-01-01

The continental margin off the northeastern United States (NEUS) contains numerous, topographically complex features that increase habitat heterogeneity across the region. However, the majority of these rugged features have never been surveyed, particularly using direct observations. During summer 2013, 31 Remotely-Operated Vehicle (ROV) dives were conducted from 494 to 3271 m depth across a variety of seafloor features to document communities and to infer geological processes that produced such features. The ROV surveyed six broad-scale habitat features, consisting of shelf-breaching canyons, slope-sourced canyons, inter-canyon areas, open-slope/landslide-scar areas, hydrocarbon seeps, and Mytilus Seamount. Four previously unknown chemosynthetic communities dominated by Bathymodiolus mussels were documented. Seafloor methane hydrate was observed at two seep sites. Multivariate analyses indicated that depth and broad-scale habitat significantly influenced megafaunal coral (58 taxa), demersal fish (69 taxa), and decapod crustacean (34 taxa) assemblages. Species richness of fishes and crustaceans significantly declined with depth, while there was no relationship between coral richness and depth. Turnover in assemblage structure occurred on the middle to lower slope at the approximate boundaries of water masses found previously in the region. Coral species richness was also an important variable explaining variation in fish and crustacean assemblages. Coral diversity may serve as an indicator of habitat suitability and variation in available niche diversity for these taxonomic groups. Our surveys added 24 putative coral species and three fishes to the known regional fauna, including the black coral Telopathes magna, the octocoral Metallogorgia melanotrichosand the fishes Gaidropsarus argentatus, Guttigadus latifrons, and Lepidion guentheri. Marine litter was observed on 81% of the dives, with at least 12 coral colonies entangled in debris. While initial exploration revealed the NEUS region to be both geologically dynamic and biologically diverse, further research into the abiotic conditions and the biotic interactions that influence species abundance and distribution is needed.

Exploration of the Canyon-Incised Continental Margin of the Northeastern United States Reveals Dynamic Habitats and Diverse Communities.

PubMed

Quattrini, Andrea M; Nizinski, Martha S; Chaytor, Jason D; Demopoulos, Amanda W J; Roark, E Brendan; France, Scott C; Moore, Jon A; Heyl, Taylor; Auster, Peter J; Kinlan, Brian; Ruppel, Carolyn; Elliott, Kelley P; Kennedy, Brian R C; Lobecker, Elizabeth; Skarke, Adam; Shank, Timothy M

2015-01-01

The continental margin off the northeastern United States (NEUS) contains numerous, topographically complex features that increase habitat heterogeneity across the region. However, the majority of these rugged features have never been surveyed, particularly using direct observations. During summer 2013, 31 Remotely-Operated Vehicle (ROV) dives were conducted from 494 to 3271 m depth across a variety of seafloor features to document communities and to infer geological processes that produced such features. The ROV surveyed six broad-scale habitat features, consisting of shelf-breaching canyons, slope-sourced canyons, inter-canyon areas, open-slope/landslide-scar areas, hydrocarbon seeps, and Mytilus Seamount. Four previously unknown chemosynthetic communities dominated by Bathymodiolus mussels were documented. Seafloor methane hydrate was observed at two seep sites. Multivariate analyses indicated that depth and broad-scale habitat significantly influenced megafaunal coral (58 taxa), demersal fish (69 taxa), and decapod crustacean (34 taxa) assemblages. Species richness of fishes and crustaceans significantly declined with depth, while there was no relationship between coral richness and depth. Turnover in assemblage structure occurred on the middle to lower slope at the approximate boundaries of water masses found previously in the region. Coral species richness was also an important variable explaining variation in fish and crustacean assemblages. Coral diversity may serve as an indicator of habitat suitability and variation in available niche diversity for these taxonomic groups. Our surveys added 24 putative coral species and three fishes to the known regional fauna, including the black coral Telopathes magna, the octocoral Metallogorgia melanotrichos and the fishes Gaidropsarus argentatus, Guttigadus latifrons, and Lepidion guentheri. Marine litter was observed on 81% of the dives, with at least 12 coral colonies entangled in debris. While initial exploration revealed the NEUS region to be both geologically dynamic and biologically diverse, further research into the abiotic conditions and the biotic interactions that influence species abundance and distribution is needed.

Exploration of the Canyon-Incised Continental Margin of the Northeastern United States Reveals Dynamic Habitats and Diverse Communities

PubMed Central

Quattrini, Andrea M.; Nizinski, Martha S.; Chaytor, Jason D.; Demopoulos, Amanda W. J.; Roark, E. Brendan; France, Scott C.; Moore, Jon A.; Heyl, Taylor; Auster, Peter J.; Kinlan, Brian; Ruppel, Carolyn; Elliott, Kelley P.; Kennedy, Brian R.C.; Lobecker, Elizabeth; Skarke, Adam; Shank, Timothy M.

2015-01-01

The continental margin off the northeastern United States (NEUS) contains numerous, topographically complex features that increase habitat heterogeneity across the region. However, the majority of these rugged features have never been surveyed, particularly using direct observations. During summer 2013, 31 Remotely-Operated Vehicle (ROV) dives were conducted from 494 to 3271 m depth across a variety of seafloor features to document communities and to infer geological processes that produced such features. The ROV surveyed six broad-scale habitat features, consisting of shelf-breaching canyons, slope-sourced canyons, inter-canyon areas, open-slope/landslide-scar areas, hydrocarbon seeps, and Mytilus Seamount. Four previously unknown chemosynthetic communities dominated by Bathymodiolus mussels were documented. Seafloor methane hydrate was observed at two seep sites. Multivariate analyses indicated that depth and broad-scale habitat significantly influenced megafaunal coral (58 taxa), demersal fish (69 taxa), and decapod crustacean (34 taxa) assemblages. Species richness of fishes and crustaceans significantly declined with depth, while there was no relationship between coral richness and depth. Turnover in assemblage structure occurred on the middle to lower slope at the approximate boundaries of water masses found previously in the region. Coral species richness was also an important variable explaining variation in fish and crustacean assemblages. Coral diversity may serve as an indicator of habitat suitability and variation in available niche diversity for these taxonomic groups. Our surveys added 24 putative coral species and three fishes to the known regional fauna, including the black coral Telopathes magna, the octocoral Metallogorgia melanotrichos and the fishes Gaidropsarus argentatus, Guttigadus latifrons, and Lepidion guentheri. Marine litter was observed on 81% of the dives, with at least 12 coral colonies entangled in debris. While initial exploration revealed the NEUS region to be both geologically dynamic and biologically diverse, further research into the abiotic conditions and the biotic interactions that influence species abundance and distribution is needed. PMID:26509818

A numerical study of local variations in tidal regime of Tagus estuary, Portugal.

PubMed

Dias, João Miguel; Valentim, Juliana Marques; Sousa, Magda Catarina

2013-01-01

Tidal dynamics of shallow estuaries and lagoons is a complex matter that has attracted the attention of a large number of researchers over the last few decades. The main purpose of the present work is to study the intricate tidal dynamics of the Tagus estuary, which states as the largest estuary of the Iberian Peninsula and one of the most important wetlands in Portugal and Europe. Tagus has large areas of low depth and a remarkable geomorphology, both determining the complex propagation of tidal waves along the estuary of unknown manner. A non-linear two-dimensional vertically integrated hydrodynamic model was considered to be adequate to simulate its hydrodynamics and an application developed from the SIMSYS2D model was applied to study the tidal propagation along the estuary. The implementation and calibration of this model revealed its accuracy to predict tidal properties along the entire system. Several model runs enabled the analysis of the local variations in tidal dynamics, through the interpretation of amplitude and phase patterns of the main tidal constituents, tidal asymmetry, tidal ellipses, form factor and tidal dissipation. Results show that Tagus estuary tidal dynamics is extremely dependent on an estuarine resonance mode for the semi-diurnal constituents that induce important tidal characteristics. Besides, the estuarine coastline features and topography determines the changes in tidal propagation along the estuary, which therefore result essentially from a balance between convergence/divergence and friction and advection effects, besides the resonance effects.

A Numerical Study of Local Variations in Tidal Regime of Tagus Estuary, Portugal

PubMed Central

Dias, João Miguel; Valentim, Juliana Marques; Sousa, Magda Catarina

2013-01-01

Tidal dynamics of shallow estuaries and lagoons is a complex matter that has attracted the attention of a large number of researchers over the last few decades. The main purpose of the present work is to study the intricate tidal dynamics of the Tagus estuary, which states as the largest estuary of the Iberian Peninsula and one of the most important wetlands in Portugal and Europe. Tagus has large areas of low depth and a remarkable geomorphology, both determining the complex propagation of tidal waves along the estuary of unknown manner. A non-linear two-dimensional vertically integrated hydrodynamic model was considered to be adequate to simulate its hydrodynamics and an application developed from the SIMSYS2D model was applied to study the tidal propagation along the estuary. The implementation and calibration of this model revealed its accuracy to predict tidal properties along the entire system. Several model runs enabled the analysis of the local variations in tidal dynamics, through the interpretation of amplitude and phase patterns of the main tidal constituents, tidal asymmetry, tidal ellipses, form factor and tidal dissipation. Results show that Tagus estuary tidal dynamics is extremely dependent on an estuarine resonance mode for the semi-diurnal constituents that induce important tidal characteristics. Besides, the estuarine coastline features and topography determines the changes in tidal propagation along the estuary, which therefore result essentially from a balance between convergence/divergence and friction and advection effects, besides the resonance effects. PMID:24312474

Fluid dynamics of the 1997 Boxing Day volcanic blast on Montserrat, West Indies

NASA Astrophysics Data System (ADS)

Esposti Ongaro, T.; Clarke, A. B.; Neri, A.; Voight, B.; Widiwijayanti, C.

2008-03-01

Directed volcanic blasts are powerful explosions with a significant laterally directed component, which can generate devastating, high-energy pyroclastic density currents (PDCs). Such blasts are an important class of eruptive phenomena, but quantified understanding of their dynamics and effects is still incomplete. Here we use 2-D and 3-D multiparticle thermofluid dynamic flow codes to examine a powerful volcanic blast that occurred on Montserrat in December 1997. On the basis of the simulations, we divide the blast into three phases: an initial burst phase that lasts roughly 5 s and involves rapid expansion of the gas-pyroclast mixture, a gravitational collapse phase that occurs when the erupted material fails to mix with sufficient air to form a buoyant column and thus collapses asymmetrically, and a PDC phase that is dominated by motion parallel to the ground surface and is influenced by topography. We vary key input parameters such as total gas energy and total solid mass to understand their influence on simulations, and we compare the simulations with independent field observations of damage and deposits, demonstrating that the models generally capture important large-scale features of the natural phenomenon. We also examine the 2-D and 3-D model results to estimate the flow Mach number and conclude that the range of damage sustained at villages on Montserrat can be reasonably explained by the spatial and temporal distribution of the dynamic pressure associated with subsonic PDCs.

Spermatozoa scattering by a microchannel feature: an elastohydrodynamic model

PubMed Central

Montenegro-Johnson, T. D.; Gadêlha, H.; Smith, D. J.

2015-01-01

Sperm traverse their microenvironment through viscous fluid by propagating flagellar waves; the waveform emerges as a consequence of elastic structure, internal active moments and low Reynolds number fluid dynamics. Engineered microchannels have recently been proposed as a method of sorting and manipulating motile cells; the interaction of cells with these artificial environments therefore warrants investigation. A numerical method is presented for large-amplitude elastohydrodynamic interaction of active swimmers with domain features. This method is employed to examine hydrodynamic scattering by a model microchannel backstep feature. Scattering is shown to depend on backstep height and the relative strength of viscous and elastic forces in the flagellum. In a ‘high viscosity’ parameter regime corresponding to human sperm in cervical mucus analogue, this hydrodynamic contribution to scattering is comparable in magnitude to recent data on contact effects, being of the order of 5°–10°. Scattering can be positive or negative depending on the relative strength of viscous and elastic effects, emphasizing the importance of viscosity on the interaction of sperm with their microenvironment. The modulation of scattering angle by viscosity is associated with variations in flagellar asymmetry induced by the elastohydrodynamic interaction with the boundary feature. PMID:26064617

Dynamic biophotonics: female squid exhibit sexually dimorphic tunable leucophores and iridocytes.

PubMed

DeMartini, Daniel G; Ghoshal, Amitabh; Pandolfi, Erica; Weaver, Aaron T; Baum, Mary; Morse, Daniel E

2013-10-01

Loliginid squid use tunable multilayer reflectors to modulate the optical properties of their skin for camouflage and communication. Contained inside specialized cells called iridocytes, these photonic structures have been a model for investigations into bio-inspired adaptive optics. Here, we describe two distinct sexually dimorphic tunable biophotonic features in the commercially important species Doryteuthis opalescens: bright stripes of rainbow iridescence on the mantle just beneath each fin attachment and a bright white stripe centered on the dorsal surface of the mantle between the fins. Both of these cellular features are unique to the female; positioned in the same location as the conspicuously bright white testis in the male, they are completely switchable, transitioning between transparency and high reflectivity. The sexual dimorphism, location and tunability of these features suggest that they may function in mating or reproduction. These features provide advantageous new models for investigation of adaptive biophotonics. The intensely reflective cells of the iridescent stripes provide a greater signal-to-noise ratio than the adaptive iridocytes studied thus far, while the cells constituting the white stripe are adaptive leucophores--unique biological tunable broadband scatterers containing Mie-scattering organelles activated by acetylcholine, and a unique complement of reflectin proteins.

Interpreting expressive performance through listener judgments of musical tension

PubMed Central

Farbood, Morwaread M.; Upham, Finn

2013-01-01

This study examines listener judgments of musical tension for a recording of a Schubert song and its harmonic reduction. Continuous tension ratings collected in an experiment and quantitative descriptions of the piece's musical features, include dynamics, pitch height, harmony, onset frequency, and tempo, were analyzed from two different angles. In the first part of the analysis, the different processing timescales for disparate features contributing to tension were explored through the optimization of a predictive tension model. The results revealed the optimal time windows for harmony were considerably longer (~22 s) than for any other feature (~1–4 s). In the second part of the analysis, tension ratings for the individual verses of the song and its harmonic reduction were examined and compared. The results showed that although the average tension ratings between verses were very similar, differences in how and when participants reported tension changes highlighted performance decisions made in the interpretation of the score, ambiguity in tension implications of the music, and the potential importance of contrast between verses and phrases. Analysis of the tension ratings for the harmonic reduction also provided a new perspective for better understanding how complex musical features inform listener tension judgments. PMID:24416024

A Human-Autonomy Teaming Approach for a Flight-Following Task

NASA Technical Reports Server (NTRS)

Brandt, Summer L.; Russell, Ricky; Lachter, Joel; Shively, Robert

2017-01-01

Managing aircraft is becoming more complex with increasingly sophisticated automation responsible for more flight tasks. With this increased complexity, it is becoming more difficult for operators to understand what the automation is doing and why. Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human-autonomy teaming (HAT) in aviation, a part-task study was conducted to demonstrate, evaluate and refine proposed critical aspects of HAT. These features were built into an automated recommender system on a ground station available from previous studies. Participants performed a flight-following task once with the original ground station (i.e., No HAT condition) and once with the HAT features enabled (i.e., HAT condition). Behavioral and subjective measures were collected; subjective measures are presented here. Overall, participants preferred the ground station with HAT features enabled compared to the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task and reduced workload relative to the No HAT baseline.

The role of the reef-dune system in coastal protection in Puerto Morelos (Mexico)

NASA Astrophysics Data System (ADS)

Franklin, Gemma L.; Torres-Freyermuth, Alec; Medellin, Gabriela; Allende-Arandia, María Eugenia; Appendini, Christian M.

2018-04-01

Reefs and sand dunes are critical morphological features providing natural coastal protection. Reefs dissipate around 90 % of the incident wave energy through wave breaking, whereas sand dunes provide the final natural barrier against coastal flooding. The storm impact on coastal areas with these features depends on the relative elevation of the extreme water levels with respect to the sand dune morphology. However, despite the importance of barrier reefs and dunes in coastal protection, poor management practices have degraded these ecosystems, increasing their vulnerability to coastal flooding. The present study aims to theoretically investigate the role of the reef-dune system in coastal protection under current climatic conditions at Puerto Morelos, located in the Mexican Caribbean Sea, using a widely validated nonlinear non-hydrostatic numerical model (SWASH). Wave hindcast information, tidal level, and a measured beach profile of the reef-dune system in Puerto Morelos are employed to estimate extreme runup and the storm impact scale for current and theoretical scenarios. The numerical results show the importance of including the storm surge when predicting extreme water levels and also show that ecosystem degradation has important implications for coastal protection against storms with return periods of less than 10 years. The latter highlights the importance of conservation of the system as a mitigation measure to decrease coastal vulnerability and infrastructure losses in coastal areas in the short to medium term. Furthermore, the results are used to evaluate the applicability of runup parameterisations for beaches to reef environments. Numerical analysis of runup dynamics suggests that runup parameterisations for reef environments can be improved by including the fore reef slope. Therefore, future research to develop runup parameterisations incorporating reef geometry features (e.g. reef crest elevation, reef lagoon width, fore reef slope) is warranted.

[Psychological features of the motivation component in the training of doctors in the system of postgraduate education].

PubMed

Koshova, Svitlana; Horachuk, Viktoriia; Pishchykov, Valerii

2018-01-01

Introduction: Тhe problem of motivating adult learning in postgraduate education has so far been the subject of study primarily in methodological and pedagogical studies. They focus on the analysis of the content side of the motivation of adult learning activities. As for the problem of the dynamics of motivation for adult learning activities, including for doctors in the system of postgraduate medical education with continuous professional development, it has not been sufficiently studied so far. The aim: This work is to analyze information and psychological features of the motivational sphere of doctors, which contribute to their successful training during continuous professional development in the system of postgraduate medical education. Materials and methods: In the work is used a range of methods: content analysis, bibliosemantic, systematic approach, analysis of products of activity. Review: At the present stage of social and economic transformations in Ukraine, the development of the general abilities of a person, his professional self-awareness, motivation for postgraduate education and obtaining a new specialization (E.О. Klimov, N.S. Glukhanyuk, I.V. Dubrovin, D.N. Zabrodin, T.V. Kudryavtsev, V.D. Shadrikov, etc.) The existing system of professional retraining does not pay enough attention to the study of conscious motives in adult learning activity. The practical relevance of this problem is determined, on the one hand, by the dynamic processes in the system of vocational training and retraining, the requirements for high efficiency of the results of the work of trained specialists. On the other hand, there is need to create conditions in the system of continuing education, the result of which is the effectiveness of adult learning activities. Conclusions: The study of the dynamics of motivation of adult learning activities is, in our opinion, relevant and has great theoretical as well as practical interest. It will allow to expand the idea of dynamics as the most important characteristic of motivation of educational activity. In addition, the knowledge of the features of the dynamics of the motivation of the learning activity of the adult factors that determine it will become in the hands of the practical teachers the lever through which it will be possible to control the motivation of adults during the educational activity with continuous postgraduate education.

High-fidelity gravity modeling applied to spacecraft trajectories and lunar interior analysis

NASA Astrophysics Data System (ADS)

Chappaz, Loic P. R.

As the complexity and boldness of emerging mission proposals increase, and with the rapid evolution of the available computational capabilities, high-accuracy and high-resolution gravity models and the tools to exploit such models are increasingly attractive within the context of spaceflight mechanics, mission design and analysis, and planetary science in general. First, in trajectory design applications, a gravity representation for the bodies of interest is, in general, assumed and exploited to determine the motion of a spacecraft in any given system. The focus is the exploration of trajectories in the vicinity of a system comprised of two small irregular bodies. Within this context, the primary bodies are initially modeled as massive ellipsoids and tools to construct third-body trajectories are developed. However, these dynamical models are idealized representations of the actual dynamical regime and do not account for any perturbing effects. Thus, a robust strategy to maintain a spacecraft near reference third-body trajectories is constructed. Further, it is important to assess the perturbing effect that dominates the dynamics of the spacecraft in such a region as a function of the baseline orbit. Alternatively, the motion of the spacecraft around a given body may be known to extreme precision enabling the derivation of a very high-accuracy gravity field for that body. Such knowledge can subsequently be exploited to gain insight into specific properties of the body. The success of the NASA's GRAIL mission ensures that the highest resolution and most accurate gravity data for the Moon is now available. In the GRAIL investigation, the focus is on the specific task of detecting the presence and extent of subsurface features, such as empty lava tubes beneath the mare surface. In addition to their importance for understanding the emplacement of the mare flood basalts, open lava tubes are of interest as possible habitation sites safe from cosmic radiation and micrometeorite impacts. Tools are developed to best exploit the rich gravity data toward the numerical detection of such small features.

The many impacts of building mountain belts on plate tectonics and mantle flow

NASA Astrophysics Data System (ADS)

Yamato, Philippe; Husson, Laurent

2015-04-01

During the Cenozoic, the number of orogens on Earth increased. This observation readily indicates that in the same time, compression in the lithosphere became gradually more and more important. Such an increase of stresses in the lithosphere can impact on plate tectonics and mantle dynamics. We show that mountain belts at plate boundaries increasingly obstruct plate tectonics, slowing down and reorienting their motions. In turn, this changes the dynamic and kinematic surface conditions of the underlying flowing mantle. Ultimately, this modifies the pattern of mantle flow. This forcing could explain many first order features of Cenozoic plate tectonics and mantle flow. Among these, one can cite the compression of passive margins, the important variations in the rates of spreading at oceanic ridges, or the initiation of subduction, the onset of obduction, for the lithosphere. In the mantle, such change in boundary condition redesigns the pattern of mantle flow and, consequently, the oceanic lithosphere cooling. In order to test this hypothesis we first present thermo-mechanical numerical models of mantle convection above which a lithosphere rests. Our results show that when collision occurs, the mantle flow is highly modified, which leads to (i) increasing shear stresses below the lithosphere and (ii) to a modification of the convection style. In turn, the transition between a 'free' convection (mobile lid) and an 'upset' convection (stagnant -or sluggish- lid) highly impacts the dynamics of the lithosphere at the surface of the Earth. Thereby, on the basis of these models and a variety of real examples, we show that on the other side of a collision zone, passive margins become squeezed and can undergo compression, which may ultimately evolve into subduction or obduction. We also show that much further, due to the blocking of the lithosphere, spreading rates decrease at the ridge, a fact that may explain a variety of features such as the low magmatism of ultraslow spreading ridges or the departure of slow spreading ridges from the half-space cooling model.

Wall shear stress fixed points in blood flow

NASA Astrophysics Data System (ADS)

Arzani, Amirhossein; Shadden, Shawn

2017-11-01

Patient-specific computational fluid dynamics produces large datasets, and wall shear stress (WSS) is one of the most important parameters due to its close connection with the biological processes at the wall. While some studies have investigated WSS vectorial features, the WSS fixed points have not received much attention. In this talk, we will discuss the importance of WSS fixed points from three viewpoints. First, we will review how WSS fixed points relate to the flow physics away from the wall. Second, we will discuss how certain types of WSS fixed points lead to high biochemical surface concentration in cardiovascular mass transport problems. Finally, we will introduce a new measure to track the exposure of endothelial cells to WSS fixed points.

Liquid Biopsy and its Potential for Management of Hepatocellular Carcinoma.

PubMed

Zhou, Jian; Huang, Ao; Yang, Xin-Rong

2016-06-01

We summarized the recent findings of liquid biopsy in cancer field and discussed its potential utility in hepatocellular carcinoma. Literature published in MEDLINE, EMBASE, and Science Direct electronic databases was searched and reviewed. Liquid biopsy specially referred to the detection of nucleic acids (circulating cell-free DNA, cfDNA) and circulating tumor cells (CTCs) in the blood of cancer patients. Compared to conventional single-site sampling or biopsy method, liquid biopsy had the advantages such as non-invasiveness, dynamic monitoring, and the most important of all, overcoming the limit of spatial and temporal heterogeneity. The genomic information of cancer could be profiled by genotyping cfDNA/CTC and subsequently applied to make molecular classification, targeted therapy guidance, and unveil drug resistance mechanisms. The serial sampling feature of liquid biopsy made it possible to monitor treatment response in a real-time manner and predict tumor metastasis/recurrence in advance. Liquid biopsy is a non-invasive, dynamic, and informative sampling method with important clinical translational significance in cancer research and practice. Much work needs to be done before it is used in the management of HCC.

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

PubMed Central

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

2012-01-01

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

Young People’s Sexual Partnerships in KwaZulu/Natal, South Africa: Patterns, Contextual Influences, and HIV Risk

PubMed Central

Harrison, Abigail; Cleland, John; Frohlich, Janet

2013-01-01

Certain sexual partnering practices, such as multiple, concurrent or age-discrepant partnerships, are known to increase HIV risk. Yet the underlying dynamics of young people’s relationships are less understood. Using household survey and qualitative data, this study examines the partnership context of HIV risk, including partner types, their characteristics, and key aspects of partnership dynamics, including partner numbers and age differences, duration, concurrency, and frequency of contact among youth aged 15–24 in rural KwaZulu/Natal, South Africa. One-third of men reported multiple and/or concurrent partnering, while one-quarter of women had partners > 5 years older. Non-participation in civic organizations or schooling was correlated with higher risk partnerships for women, but not men. On average, relationships lasted >1 year for women and men, and were frequently characterized as ‘serious’. However, qualitative findings pointed to the sequential and overlapping nature of relationships, with distance and mobility as important influences. These fluid partnership patterns are an important feature of young people’s sexual risk in the context of South Africa’s severe HIV epidemic. PMID:19248716

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

PubMed

Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

2018-02-01

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

PubMed

Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively, compared to AUC values of previous approach of 0.8562 and 0.8311, respectively. The proposed approach based on 2D textural features quantifying spatiotemporal changes of the contrast-agent uptake significantly outperforms the previous approach based on 3D morphology and dynamic analysis in differentiating the malignant and benign breast lesions, showing its potential to aid clinical decision making. © 2017 American Association of Physicists in Medicine.

Non-linear dynamics and alternating 'flip' solutions in ferrofluidic Taylor-Couette flow

NASA Astrophysics Data System (ADS)

Altmeyer, Sebastian

2018-04-01

This study treats with the influence of a symmetry-breaking transversal magnetic field on the nonlinear dynamics of ferrofluidic Taylor-Couette flow - flow confined between two concentric independently rotating cylinders. We detected alternating 'flip' solutions which are flow states featuring typical characteristics of slow-fast-dynamics in dynamical systems. The flip corresponds to a temporal change in the axial wavenumber and we find them to appear either as pure 2-fold axisymmetric (due to the symmetry-breaking nature of the applied transversal magnetic field) or involving non-axisymmetric, helical modes in its interim solution. The latter ones show features of typical ribbon solutions. In any case the flip solutions have a preferential first axial wavenumber which corresponds to the more stable state (slow dynamics) and second axial wavenumber, corresponding to the short appearing more unstable state (fast dynamics). However, in both cases the flip time grows exponential with increasing the magnetic field strength before the flip solutions, living on 2-tori invariant manifolds, cease to exist, with lifetime going to infinity. Further we show that ferrofluidic flow turbulence differ from the classical, ordinary (usually at high Reynolds number) turbulence. The applied magnetic field hinders the free motion of ferrofluid partials and therefore smoothen typical turbulent quantities and features so that speaking of mildly chaotic dynamics seems to be a more appropriate expression for the observed motion.

Heat Transfer and Fluid Mechanics Institute, Meeting, 25th, University of California, Davis, Calif., June 21-23, 1976, Proceedings

NASA Technical Reports Server (NTRS)

Mckillop, A. A.; Baughn, J. W.; Dwyer, H. A.

1976-01-01

Major research advances in heat transfer and fluid dynamics are outlined, with particular reference to relevant energy problems. Of significant importance are such topics as synthetic fuels in combustion, turbulence models, combustion modeling, numerical methods for interacting boundary layers, and light-scattering diagnostics for gases. The discussion covers thermal convection, two-phase flow and boiling heat transfer, turbulent flows, combustion, and aerospace heat transfer problems. Other areas discussed include compressible flows, fluid mechanics and drag, and heat exchangers. Featured topics comprise heat and salt transfer in double-diffusive systems, limits of boiling heat transfer in a liquid-filled enclosure, investigation of buoyancy-induced flow stratification in a cylindrical plenum, and digital algorithms for dynamic analysis of a heat exchanger. Individual items are announced in this issue.

Carrier lifetime in exfoliated few-layer graphene determined from intersubband optical transitions.

PubMed

Limmer, Thomas; Feldmann, Jochen; Da Como, Enrico

2013-05-24

We report a femtosecond transient spectroscopy study in the near to middle infrared range, 0.8-0.35 eV photon energy, on graphene and few layer graphene single flakes. The spectra show an evolving structure of photoinduced absorption bands superimposed on the bleaching caused by Pauli blocking of the interband optically coupled states. Supported by tight-binding model calculations, we assign the photoinduced absorption features to intersubband transitions as the number of layers is increased. Interestingly, the intersubband photoinduced resonances show a longer dynamics than the interband bleaching, because of their independence from the absolute energy of the carriers with respect to the Dirac point. The dynamic of these intersubband transitions reflects the lifetime of the hot carriers and provides an elegant method to access it in this important class of semimetals.

Carrier Lifetime in Exfoliated Few-Layer Graphene Determined from Intersubband Optical Transitions

NASA Astrophysics Data System (ADS)

Limmer, Thomas; Feldmann, Jochen; Da Como, Enrico

2013-05-01

We report a femtosecond transient spectroscopy study in the near to middle infrared range, 0.8-0.35 eV photon energy, on graphene and few layer graphene single flakes. The spectra show an evolving structure of photoinduced absorption bands superimposed on the bleaching caused by Pauli blocking of the interband optically coupled states. Supported by tight-binding model calculations, we assign the photoinduced absorption features to intersubband transitions as the number of layers is increased. Interestingly, the intersubband photoinduced resonances show a longer dynamics than the interband bleaching, because of their independence from the absolute energy of the carriers with respect to the Dirac point. The dynamic of these intersubband transitions reflects the lifetime of the hot carriers and provides an elegant method to access it in this important class of semimetals.

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Quantitative Description of Crystal Nucleation and Growth from in Situ Liquid Scanning Transmission Electron Microscopy.

PubMed

Ievlev, Anton V; Jesse, Stephen; Cochell, Thomas J; Unocic, Raymond R; Protopopescu, Vladimir A; Kalinin, Sergei V

2015-12-22

Recent advances in liquid cell (scanning) transmission electron microscopy (S)TEM has enabled in situ nanoscale investigations of controlled nanocrystal growth mechanisms. Here, we experimentally and quantitatively investigated the nucleation and growth mechanisms of Pt nanostructures from an aqueous solution of K2PtCl6. Averaged statistical, network, and local approaches have been used for the data analysis and the description of both collective particles dynamics and local growth features. In particular, interaction between neighboring particles has been revealed and attributed to reduction of the platinum concentration in the vicinity of the particle boundary. The local approach for solving the inverse problem showed that particles dynamics can be simulated by a stationary diffusional model. The obtained results are important for understanding nanocrystal formation and growth processes and for optimization of synthesis conditions.

Characterization of dynamic physiology of the bladder by optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Zhijia; Keng, Kerri; Pan, Rubin; Ren, Hugang; Du, Congwu; Kim, Jason; Pan, Yingtian

2012-03-01

Because of its high spatial resolution and noninvasive imaging capabilities, optical coherence tomography has been used to characterize the morphological details of various biological tissues including urinary bladder and to diagnose their alternations (e.g., cancers). In addition to static morphology, the dynamic features of tissue morphology can provide important information that can be used to diagnose the physiological and functional characteristics of biological tissues. Here, we present the imaging studies based on optical coherence tomography to characterize motion related physiology and functions of rat bladder detrusor muscles and compared the results with traditional biomechanical measurements. Our results suggest that optical coherence tomography is capable of providing quantitative evaluation of contractile functions of intact bladder (without removing bladder epithelium and connective tissue), which is potentially of more clinical relevance for future clinical diagnosis - if incorporated with cystoscopic optical coherence tomography.

Towards Dynamic Contrast Specific Ultrasound Tomography

NASA Astrophysics Data System (ADS)

Demi, Libertario; van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-10-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography.

PubMed

Demi, Libertario; Van Sloun, Ruud J G; Wijkstra, Hessel; Mischi, Massimo

2016-10-05

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography

PubMed Central

Demi, Libertario; Van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-01-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast. PMID:27703251

Control of entanglement dynamics in a system of three coupled quantum oscillators.

PubMed

Gonzalez-Henao, J C; Pugliese, E; Euzzor, S; Meucci, R; Roversi, J A; Arecchi, F T

2017-08-30

Dynamical control of entanglement and its connection with the classical concept of instability is an intriguing matter which deserves accurate investigation for its important role in information processing, cryptography and quantum computing. Here we consider a tripartite quantum system made of three coupled quantum parametric oscillators in equilibrium with a common heat bath. The introduced parametrization consists of a pulse train with adjustable amplitude and duty cycle representing a more general case for the perturbation. From the experimental observation of the instability in the classical system we are able to predict the parameter values for which the entangled states exist. A different amount of entanglement and different onset times emerge when comparing two and three quantum oscillators. The system and the parametrization considered here open new perspectives for manipulating quantum features at high temperatures.

Genetic training of network using chaos concept: application to QSAR studies of vibration modes of tetrahedral halides.

PubMed

Lu, Qingzhang; Shen, Guoli; Yu, Ruqin

2002-11-15

The chaotic dynamical system is introduced in genetic algorithm to train ANN to formulate the CGANN algorithm. Logistic mapping as one of the most important chaotic dynamic mappings provides each new generation a high chance to hold GA's population diversity. This enhances the ability to overcome overfitting in training an ANN. The proposed CGANN has been used for QSAR studies to predict the tetrahedral modes (nu(1)(A1) and nu(2)(E)) of halides [MX(4)](epsilon). The frequencies predicted by QSAR were compared with those calculated by quantum chemistry methods including PM3, AM1, and MNDO/d. The possibility of improving the predictive ability of QSAR by including quantum chemistry parameters as feature variables has been investigated using tetrahedral tetrahalide examples. Copyright 2002 Wiley Periodicals, Inc.

Theory of networked minority games based on strategy pattern dynamics.

PubMed

Lo, T S; Chan, H Y; Hui, P M; Johnson, N F

2004-11-01

We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. An important feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the minority game with connected populations. Expressions for the mean success rate among the agents and for the mean success rate for agents with k neighbors are derived. We also use the theory to estimate the value of connectivity p above which the binary-agent-resource system with high resource levels makes the transition into the high-connectivity state.

The quest for stall-free dynamic lift

NASA Technical Reports Server (NTRS)

Tung, C.; Mcalister, K. W.; Carr, Lawrence W.; Duque, E.; Zinner, R.

1992-01-01

During the past decade, numerous major effects have addressed the question of how to control or alleviate dynamic stall effects on helicopter rotors, but little concrete evidence of any significant reduction of the adverse characteristics of the dynamic stall phenomenon has been demonstrated. Nevertheless, it is important to remember that the control of dynamic stall is an achievable goal. Experiments performed at the US Army Aeroflight-dynamics Directorate more than a decade ago demonstrated that dynamic stall is not an unavoidable penalty of high amplitude motion, and that airfoils can indeed operate dynamically at angles far above the static-stall angle without necessarily forming a stall vortex. These experiments, one of them featuring a slat that was designed from static airfoil considerations, showed that unsteadiness can be a very beneficial factor in the development of high-lift devices for helicopter rotors. The experience drawn from these early experiments is now being focused on a program for the alleviation of dynamic-stall effects on helicopter rotors. The purpose of this effort is to demonstrate that rotor stall can be controlled through an improved understanding of the unsteady effects on airfoil stall and to document the role of specific means that lead to stall alleviation in the three dimensional unsteady environment of helicopter rotors in forward flight. The first concept to be addressed in this program will be a slatted airfoil. A two dimensional unsteady Navier-Stokes code has been modified to compute the flow around a two-element airfoil.

Accounting for system dynamics in reserve design.

PubMed

Leroux, Shawn J; Schmiegelow, Fiona K A; Cumming, Steve G; Lessard, Robert B; Nagy, John

2007-10-01

Systematic conservation plans have only recently considered the dynamic nature of ecosystems. Methods have been developed to incorporate climate change, population dynamics, and uncertainty in reserve design, but few studies have examined how to account for natural disturbance. Considering natural disturbance in reserve design may be especially important for the world's remaining intact areas, which still experience active natural disturbance regimes. We developed a spatially explicit, dynamic simulation model, CONSERV, which simulates patch dynamics and fire, and used it to evaluate the efficacy of hypothetical reserve networks in northern Canada. We designed six networks based on conventional reserve design methods, with different conservation targets for woodland caribou habitat, high-quality wetlands, vegetation, water bodies, and relative connectedness. We input the six reserve networks into CONSERV and tracked the ability of each to maintain initial conservation targets through time under an active natural disturbance regime. None of the reserve networks maintained all initial targets, and some over-represented certain features, suggesting that both effectiveness and efficiency of reserve design could be improved through use of spatially explicit dynamic simulation during the planning process. Spatial simulation models of landscape dynamics are commonly used in natural resource management, but we provide the first illustration of their potential use for reserve design. Spatial simulation models could be used iteratively to evaluate competing reserve designs and select targets that have a higher likelihood of being maintained through time. Such models could be combined with dynamic planning techniques to develop a general theory for reserve design in an uncertain world.

Processing Dynamic Image Sequences from a Moving Sensor.

DTIC Science & Technology

1984-02-01

65 Roadsign Image Sequence ..... ................ ... 70 Roadsign Sequence with Redundant Features .. ........ . 79 Roadsign Subimage...Selected Feature Error Values .. ........ 66 2c. Industrial Image Selected Feature Local Search Values. .. .... 67 3ab. Roadsign Image Error Values...72 3c. Roadsign Image Local Search Values ............. 73 4ab. Roadsign Redundant Feature Error Values. ............ 8 4c. Roadsign

Some Surprising Implications of NMR-directed Simulations of Substrate Recognition and Binding by Cytochrome P450cam (CYP101A1).

PubMed

Asciutto, Eliana K; Pochapsky, Thomas C

2018-04-27

Cytochrome P450 cam (CYP101A1) catalyzes the stereospecific 5-exo hydroxylation of d-camphor by molecular oxygen. Previously, residual dipolar couplings measured for backbone amide 1 H- 15 N correlations in both substrate-free and bound forms of CYP101A1 were used as restraints in soft annealing molecular dynamic simulations in order to identify average conformations of the enzyme with and without substrate bound. Multiple substrate-dependent conformational changes remote from the enzyme active site were identified, and site-directed mutagenesis and activity assays confirmed the importance of these changes in substrate recognition. The current work makes use of perturbation response scanning (PRS) and umbrella sampling molecular dynamic of the residual dipolar coupling-derived CYP101A1 structures to probe the roles of remote structural features in enforcing the regio- and stereospecific nature of the hydroxylation reaction catalyzed by CYP101A1. An improper dihedral angle Ψ was defined and used to maintain substrate orientation in the CYP101A1 active site, and it was observed that different values of Ψ result in different PRS response maps. Umbrella sampling methods show that the free energy of the system is sensitive to Ψ, and bound substrate forms an important mechanical link in the transmission of mechanical coupling through the enzyme structure. Finally, a qualitative approach to interpreting PRS maps in terms of the roles of secondary structural features is proposed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characterizing chaotic melodies in automatic music composition

NASA Astrophysics Data System (ADS)

Coca, Andrés E.; Tost, Gerard O.; Zhao, Liang

2010-09-01

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

Mixing Silicate Melts with High Viscosity Contrast by Chaotic Dynamics: Results from a New Experimental Device

NASA Astrophysics Data System (ADS)

de Campos, Cristina; Perugini, Diego; Ertel-Ingrisch, Werner; Dingwell, Donald B.; Poli, Giampiero

2010-05-01

A new experimental device has been developed to perform chaotic mixing between high viscosity melts under controlled fluid-dynamic conditions. The apparatus is based on the Journal Bearing System (JBS). It consists of an outer cylinder hosting the melts of interest and an inner cylinder, which is eccentrically located. Both cylinders can be independently moved to generate chaotic streamlines in the mixing system. Two experiments were performed using as end-members different proportions of a peralkaline haplogranite and a mafic melt, corresponding to the 1 atm eutectic composition in the An-Di binary system. The two melts were stirred together in the JBS for ca. two hours, at 1,400° C and under laminar fluid dynamic condition (Re of the order of 10-7). The viscosity ratio between the two melts, at the beginning of the experiment, was of the order of 103. Optical analyses of experimental samples revealed, at short length scale (of the order of μm), a complex pattern of mixed structures. These consisted of an intimate distribution of filaments; a complex inter-fingering of the two melts. Such features are typically observed in rocks thought to be produced by magma mixing processes. Stretching and folding dynamics between the melts induced chaotic flow fields and generated wide compositional interfaces. In this way, chemical diffusion processes become more efficient, producing melts with highly heterogeneous compositions. A remarkable modulation of compositional fields has been obtained by performing short time-scale experiments and using melts with a high viscosity ratio. This indicates that chaotic mixing of magmas can be a very efficient process in modulating compositional variability in igneous systems, especially under high viscosity ratios and laminar fluid-dynamic regimes. Our experimental device may replicate magma mixing features, observed in natural rocks, and therefore open new frontiers in the study of this important petrologic and volcanological process.

Dynamic security contingency screening and ranking using neural networks.

PubMed

Mansour, Y; Vaahedi, E; El-Sharkawi, M A

1997-01-01

This paper summarizes BC Hydro's experience in applying neural networks to dynamic security contingency screening and ranking. The idea is to use the information on the prevailing operating condition and directly provide contingency screening and ranking using a trained neural network. To train the two neural networks for the large scale systems of BC Hydro and Hydro Quebec, in total 1691 detailed transient stability simulation were conducted, 1158 for BC Hydro system and 533 for the Hydro Quebec system. The simulation program was equipped with the energy margin calculation module (second kick) to measure the energy margin in each run. The first set of results showed poor performance for the neural networks in assessing the dynamic security. However a number of corrective measures improved the results significantly. These corrective measures included: 1) the effectiveness of output; 2) the number of outputs; 3) the type of features (static versus dynamic); 4) the number of features; 5) system partitioning; and 6) the ratio of training samples to features. The final results obtained using the large scale systems of BC Hydro and Hydro Quebec demonstrates a good potential for neural network in dynamic security assessment contingency screening and ranking.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the role of boundary forcing and the potential predictability of the monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both SST and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. For regional monsoons, however, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the potential predictability of the broad-scale and regional monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both Sea Surface Temperatures (SST) and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. However, for regional monsoons, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

DOE PAGES

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil; ...

2017-01-24

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

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

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less