Preference as a Function of Active Interresponse Times: A Test of the Active Time Model
ERIC Educational Resources Information Center
Misak, Paul; Cleaveland, J. Mark
2011-01-01
In this article, we describe a test of the active time model for concurrent variable interval (VI) choice. The active time model (ATM) suggests that the time since the most recent response is one of the variables controlling choice in concurrent VI VI schedules of reinforcement. In our experiment, pigeons were trained in a multiple concurrent…
Patterns of Activity Revealed by a Time Lag Analysis of a Model Active Region
NASA Astrophysics Data System (ADS)
Bradshaw, Stephen; Viall, Nicholeen
2016-05-01
We investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of average frequencies. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine an extrapolated magnetic skeleton with hydrodynamic and forward modeling codes to create a model active region, and apply the time lag method to synthetic observations. Our aim is to recover some typical properties and patterns of activity observed in active regions. Our key findings are: 1. Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. 2. Shorter coronal loops in the core cool more quickly than longer loops at the periphery. 3. All channel pairs show zero time lag when the line-of-sight passes through coronal loop foot-points. 4. There is strong evidence that plasma must be re-energized on a time scale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies operates across active regions. 5. Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.
ERIC Educational Resources Information Center
Fazio, C.; Guastella, I.; Tarantino, G.
2007-01-01
In this paper, we describe a pedagogical approach to elastic body movement based on measurements of the contact times between a metallic rod and small bodies colliding with it and on modelling of the experimental results by using a microcomputer-based laboratory and simulation tools. The experiments and modelling activities have been built in the…
Characterization and modeling time-dependent behavior in PZT fibers and active fiber composites
NASA Astrophysics Data System (ADS)
Dridi, Mohamed A.; Atitallah, Hassene B.; Ounaies, Zoubeida; Muliana, Anastasia
2015-04-01
Active fiber composites (AFC) are comprised of lead zirconate titanate (PZT) fibers embedded in a polymer. This paper presents an experimental characterization of the PZT fibers and a constitutive model focused on their time-dependent, nonlinear response. The experiments herein focus on characterizing time dependence of various properties by conducting creep, relaxation, mechanical and electric field-cyclic loading at different frequencies. The constitutive model is a time-dependent polarization model that predicts nonlinear polarization and electro-mechanical strain responses of the fibers. The model of PZT fibers is used in the FEM simulation of AFCs and results of the model are compared to experiments for validation.
AST: Activity-Security-Trust driven modeling of time varying networks.
Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen
2016-02-18
Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.
AST: Activity-Security-Trust driven modeling of time varying networks
Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen
2016-01-01
Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents’ interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes. PMID:26888717
AST: Activity-Security-Trust driven modeling of time varying networks.
Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen
2016-01-01
Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes. PMID:26888717
An application of the active time model to multiple concurrent variable-interval schedules.
Brown, Emily Kathryn; Cleaveland, J Mark
2009-06-01
The current experiment investigates whether an active time model can account for anomalous results that have emerged from multiple schedule, concurrent variable-interval (VI) VI experiments. The model assumes that (1) during concurrent VI VI training pigeons learn a function that relates time since the most immediate response, i.e., active time, to changeover probabilities and (2) that molar preference is the result of an interaction between inter-response time frequencies and the learned active time changeover functions. Pigeons were trained under a concurrent VI 30-s VI 30-s schedule and a concurrent VI 60-s VI 60-s schedule. Probes were conducted in which VI 30-s and VI 60-s stimuli were paired. During these probes, birds allocated choices equally to the stimuli. The active time model accurately fit individual subject data. In contrast data were not fit by a variant of scalar expectancy theory proposed by Gibbon [Gibbon, J., 1995. Dynamics of time matching: arousal makes better seem worse. Psychon. Bull. Rev. 2, 208-215].
Robinson, Brian S; Song, Dong; Berger, Theodore W
2014-01-01
This paper presents a methodology to estimate a learning rule that governs activity-dependent plasticity from behaviorally recorded spiking events. To demonstrate this framework, we simulate a probabilistic spiking neuron with spike-timing-dependent plasticity (STDP) and estimate all model parameters from the simulated spiking data. In the neuron model, output spiking activity is generated by the combination of noise, feedback from the output, and an input-feedforward component whose magnitude is modulated by synaptic weight. The synaptic weight is calculated with STDP with the following features: (1) weight change based on the relative timing of input-output spike pairs, (2) prolonged plasticity induction, and (3) considerations for system stability. Estimation of all model parameters is achieved iteratively by formulating the model as a generalized linear model with Volterra kernels and basis function expansion. Successful estimation of all model parameters in this study demonstrates the feasibility of this approach for in-vivo experimental studies. Furthermore, the consideration of system stability and prolonged plasticity induction enhances the ability to capture how STDP affects a neural population's signal transformation properties over a realistic time course. Plasticity characterization with this estimation method could yield insights into functional implications of STDP and be incorporated into a cortical prosthesis.
Active open boundary forcing using dual relaxation time-scales in downscaled ocean models
NASA Astrophysics Data System (ADS)
Herzfeld, M.; Gillibrand, P. A.
2015-05-01
Regional models actively forced with data from larger scale models at their open boundaries often contain motion at different time-scales (e.g. tidal and low frequency). These motions are not always individually well specified in the forcing data, and one may require a more active boundary forcing while the other exert less influence on the model interior. If a single relaxation time-scale is used to relax toward these data in the boundary equation, then this may be difficult. The method of fractional steps is used to introduce dual relaxation time-scales in an open boundary local flux adjustment scheme. This allows tidal and low frequency oscillations to be relaxed independently, resulting in a better overall solution than if a single relaxation parameter is optimized for tidal (short relaxation) or low frequency (long relaxation) boundary forcing. The dual method is compared to the single relaxation method for an idealized test case where a tidal signal is superimposed on a steady state low frequency solution, and a real application where the low frequency boundary forcing component is derived from a global circulation model for a region extending over the whole Great Barrier Reef, and a tidal signal subsequently superimposed.
Modelling the Effects of Ageing Time of Starch on the Enzymatic Activity of Three Amylolytic Enzymes
Guerra, Nelson P.; Pastrana Castro, Lorenzo
2012-01-01
The effect of increasing ageing time (t) of starch on the activity of three amylolytic enzymes (Termamyl, San Super, and BAN) was investigated. Although all the enzymatic reactions follow michaelian kinetics, vmax decreased significantly (P < 0.05) and KM increased (although not always significantly) with the increase in t. The conformational changes produced in the starch chains as a consequence of the ageing seemed to affect negatively the diffusivity of the starch to the active site of the enzymes and the release of the reaction products to the medium. A similar effect was observed when the enzymatic reactions were carried out with unaged starches supplemented with different concentrations of gelatine [G]. The inhibition in the amylolytic activities was best mathematically described by using three modified forms of the Michaelis-Menten model, which included a term to consider, respectively, the linear, exponential, and hyperbolic inhibitory effects of t and [G]. PMID:22666116
Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J
2015-06-01
This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. PMID:25843359
NASA Astrophysics Data System (ADS)
Welsch, Brian T.; Cheung, Mark CM; Fisher, George H.; Kazachenko, Maria D.; Sun, Xudong
2015-04-01
The Coronal Global Evolutionary Model (CGEM) is a model for the evolution of the magnetic field in the solar corona, driven using photospheric vector magnetic field and Doppler measurements by the HMI instrument on NASA's Solar Dynamics Observatory. Over days-long time scales, the coronal magnetic field configuration is determined quasi-statically using magnetofrictional relaxation. For a configuration that becomes unstable and erupts or undergoes rapid evolution, we can use the magnetofrictional configuration as the initial state for MHD simulations. The model will be run in both global configurations, covering the entire Sun, and local configurations, designed to model the evolution of the corona above active regions. The model uses spherical coordinates to realistically treat the large-scale coronal geometry. The CGEM project also includes the dissemination of other information derivable from HMI magnetogram data, such as (i) vertical and horizontal Lorentz forces computed over active region domains, to facilitate easier comparisons of flare/CME behavior and observed changes of the photospheric magnetic field, and (ii) estimates of the photospheric electric field and Poynting flux. We describe progress that we have made in development of both the coronal model and its input data, and discuss magnetic evolution in (i) the well-studied NOAA AR 11158 around the time of the 2011 February 15 X2.2 flare, and (ii) AR 11944 around the time of the 2014 January 7 X1.2 flare.
Albert, P S; McFarland, H F; Smith, M E; Frank, J A
Many chronic diseases are relapsing-remitting diseases, in which subjects alternate between periods with increasing and decreasing disease activity; relapsing-remitting multiple sclerosis is an example. This paper proposes two classes of models for sequences of counts observed from a relapsing-remitting disease. In the first, the relapsing-remitting nature of the data is modelled by a Poisson time series with a periodic trend in the mean. In this approach, the mean is expressed as a function of a sinusoidal trend and past observations of the time series. An algorithm that uses GLIM is developed, and it results in maximum-likelihood estimation for the amplitude, frequency and autoregressive effects. In the second class of models, the relapsing-remitting behaviour is described by a Poisson time series in which changes in the mean follow a latent Markov chain. An EM algorithm is developed for maximum-likelihood estimation for this model. The two models are illustrated and compared with data from a study evaluating the use of serial magnetic resonance imaging as a measure of disease activity in relapsing-remitting multiple sclerosis. PMID:8023028
Pitanga, Francisco José Gondim; Matos, Sheila Maria Alvim; Almeida, Maria da Conceição; Molina, Maria Del Carmen Bisi; Aquino, Estela M L
2016-09-01
The main objective of the study was identify the prevalence and factors associated with leisure time physical activity (LTPA) in adult participants of the Longitudinal Study of Adult Health (ELSA-Brasil). The LTPA was measured using the International Physical Activity Questionnaire (IPAQ), long version. A hierarchical ecological model was built with the possible factors associated with LTPA distributed across blocks. We estimated crude and adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) using logistic regression. In men, being more educated, having a high family income, living in environments with conditions and opportunities for PA, being retired and being overweight were positively associated, while current smoking, obesity and abdominal obesity were associated negatively with the LTPA. Among women, being over 60years old, being more educated, having a high family income, living in an environment with conditions and opportunities for PA practice and being retired were positively associated, while being overweight, obese and having abdominal obesity were associated negatively with the LTPA. The proposed ecological model explains the LTPA through the social, physical and personal environment and highlights gender differences in physical activity.
Forecasting geomagnetic activity at monthly and annual horizons: Time series models
NASA Astrophysics Data System (ADS)
Reikard, Gordon
2015-10-01
Most of the existing work on forecasting geomagnetic activity has been over short intervals, on the order of hours or days. However, it is also of interest to predict over longer horizons, ranging from months to years. Forecasting tests are run for the Aa index, which begins in 1868 and provides the longest continuous records of geomagnetic activity. This series is challenging to forecast. While it exhibits cycles at 11-22 years, the amplitude and period of the cycles varies over time. There is also evidence of discontinuous trending: the slope and direction of the trend change repeatedly. Further, at the monthly resolution, the data exhibits nonlinear variability, with intermittent large outliers. Several types of models are tested: regressions, neural networks, a frequency domain algorithm, and combined models. Forecasting tests are run at horizons of 1-11 years using the annual data, and 1-12 months using the monthly data. At the 1-year horizon, the mean errors are in the range of 13-17 percent while the median errors are in the range of 10-14 percent. The accuracy of the models deteriorates at longer horizons. At 5 years, the mean errors lie in the range of 21-23 percent, and at 11 years, 23-25 percent. At the 1 year horizon, the most accurate forecast is achieved by a combined model, but over longer horizons (2-11 years), the neural net dominates. At the monthly resolution, the mean errors are in the range of 17-19 percent at 1 month, while the median errors lie in a range of 14-17 percent. The mean error increases to 23-24 percent at 5 months, and 25 percent at 12 months. A model combining frequency and time domain methods is marginally better than regressions and neural networks alone, up to 11 months. The main conclusion is that geomagnetic activity can only be predicted to within a limited threshold of accuracy, over a given range of horizons. This is consistent with the finding of irregular trends and cycles in the annual data and nonlinear variability in
Statistical Properties of Longitudinal Time-Activity Data for Use in Human Exposure Modeling
Understanding the longitudinal properties of the time spent in different locations and activities is important in characterizing human exposure to pollutants. The results of a four-season longitudinal time-activity diary study in eight working adults are presented, with the goal ...
Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.
2003-10-29
Quantitative analysis of uptake and washout of cardiac single photon emission computed tomography (SPECT) radiopharmaceuticals has the potential to provide better contrast between healthy and diseased tissue, compared to conventional reconstruction of static images. Previously, we used B-splines to model time-activity curves (TACs) for segmented volumes of interest and developed fast least-squares algorithms to estimate spline TAC coefficients and their statistical uncertainties directly from dynamic SPECT projection data. This previous work incorporated physical effects of attenuation and depth-dependent collimator response. In the present work, we incorporate scatter and use a computer simulation to study how scatter modeling affects directly estimated TACs and subsequent estimates of compartmental model parameters. An idealized single-slice emission phantom was used to simulate a 15 min dynamic {sup 99m}Tc-teboroxime cardiac patient study in which 500,000 events containing scatter were detected from the slice. When scatter was modeled, unweighted least-squares estimates of TACs had root mean square (RMS) error that was less than 0.6% for normal left ventricular myocardium, blood pool, liver, and background tissue volumes and averaged 3% for two small myocardial defects. When scatter was not modeled, RMS error increased to average values of 16% for the four larger volumes and 35% for the small defects. Noise-to-signal ratios (NSRs) for TACs ranged between 1-18% for the larger volumes and averaged 110% for the small defects when scatter was modeled. When scatter was not modeled, NSR improved by average factors of 1.04 for the larger volumes and 1.25 for the small defects, as a result of the better-posed (though more biased) inverse problem. Weighted least-squares estimates of TACs had slightly better NSR and worse RMS error, compared to unweighted least-squares estimates. Compartmental model uptake and washout parameter estimates obtained from the TACs were less
Time on Your Hands: Modeling Time
ERIC Educational Resources Information Center
Finson, Kevin; Beaver, John
2007-01-01
Building physical models relative to a concept can be an important activity to help students develop and manipulate abstract ideas and mental models that often prove difficult to grasp. One such concept is "time". A method for helping students understand the cyclical nature of time involves the construction of a Time Zone Calculator through a…
A further application of the active time model to multiple concurrent variable-interval schedules.
McKenzie, Andrew T; Cleaveland, J Mark
2010-05-01
In this experiment we show that the active time model (ATM) accurately predicts probe data from multiple concurrent VI VI schedules. Subjects were trained under a concurrent VI 30-s VI 60-s and a concurrent VI 60-s VI 120-s schedule. Two types of unreinforced probes were then conducted. The first paired the two VI 60-s stimuli. These stimuli, while equivalent in their associated absolute rates of reinforcement, differed in their relative rates of reinforcement. The second probe paired the VI 30-s stimulus with the relatively rich VI 60-s stimulus. In contrast with the first probe, these stimuli differed in their absolute rates of reinforcement, while being similar in their relative rates. During the first set of probes, birds preferred the VI 60-s stimulus trained with the VI 120-s schedule. During the second set of probes, birds were indifferent to the two stimuli. These results are less extreme than others reported in the literature. Nonetheless, we found that ATM accurately fit individual subject data in both sets of probes. In contrast a variant of scalar expectancy theory did not fit the data at either the individual or group level.
A new costing model in hospital management: time-driven activity-based costing system.
Öker, Figen; Özyapıcı, Hasan
2013-01-01
Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas. PMID:23364414
A new costing model in hospital management: time-driven activity-based costing system.
Öker, Figen; Özyapıcı, Hasan
2013-01-01
Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas.
NASA Astrophysics Data System (ADS)
Das, Anusheela; Chaudhury, Srabanti
2015-11-01
Metal nanoparticles are heterogeneous catalysts and have a multitude of non-equivalent, catalytic sites on the nanoparticle surface. The product dissociation step in such reaction schemes can follow multiple pathways. Proposed here for the first time is a completely analytical theoretical framework, based on the first passage time distribution, that incorporates the effect of heterogeneity in nanoparticle catalysis explicitly by considering multiple, non-equivalent catalytic sites on the nanoparticle surface. Our results show that in nanoparticle catalysis, the effect of dynamic disorder is manifested even at limiting substrate concentrations in contrast to an enzyme that has only one well-defined active site.
Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M
2015-11-01
To develop and test time series single site and multi-site placement models, we used wrist, hip and ankle processed accelerometer data to estimate energy cost and type of physical activity in adults. Ninety-nine subjects in three age groups (18-39, 40-64, 65 + years) performed 11 activities while wearing three triaxial accelereometers: one each on the non-dominant wrist, hip, and ankle. During each activity net oxygen cost (METs) was assessed. The time series of accelerometer signals were represented in terms of uniformly discretized values called bins. Support Vector Machine was used for activity classification with bins and every pair of bins used as features. Bagged decision tree regression was used for net metabolic cost prediction. To evaluate model performance we employed the jackknife leave-one-out cross validation method. Single accelerometer and multi-accelerometer site model estimates across and within age group revealed similar accuracy, with a bias range of -0.03 to 0.01 METs, bias percent of -0.8 to 0.3%, and a rMSE range of 0.81-1.04 METs. Multi-site accelerometer location models improved activity type classification over single site location models from a low of 69.3% to a maximum of 92.8% accuracy. For each accelerometer site location model, or combined site location model, percent accuracy classification decreased as a function of age group, or when young age groups models were generalized to older age groups. Specific age group models on average performed better than when all age groups were combined. A time series computation show promising results for predicting energy cost and activity type. Differences in prediction across age group, a lack of generalizability across age groups, and that age group specific models perform better than when all ages are combined needs to be considered as analytic calibration procedures to detect energy cost and type are further developed. PMID:26449155
Quantitative structure-activity relationship models that stand the test of time.
Davis, Andrew M; Wood, David J
2013-04-01
The pharmaceutical industry is in a period of intense change. While this has many drivers, attrition through the development process continues to be an important pressure. The emerging definitions of "compound quality" that are based on retrospective analyses of developmental attrition have highlighted a new direction for medicinal chemistry and the paradigm of "quality at the point of design". The time has come for retrospective analyses to catalyze prospective action. Quality at the point of design places pressure on the quality of our predictive models. Empirical QSAR models when built with care provide true predictive control, but their accuracy and precision can be improved. Here we describe AstraZeneca's experience of automation in QSAR model building and validation, and how an informatics system can provide a step-change in predictive power to project design teams, if they choose to use it.
NASA Astrophysics Data System (ADS)
Mirmomeni, M.; Kamaliha, E.; Shafiee, M.; Lucas, C.
2009-09-01
Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and magnitude of such catastrophic events still remain. There are, however, descriptor systems that describe a wider class of systems, including physical models and non-dynamic constraints. It is well known that the descriptor system is much tighter than the state-space expression for representing real independent parametric perturbations. In addition, the fuzzy descriptor models as a generalization of the locally linear neurofuzzy models are general forms that can be trained by constructive intuitive learning algorithms. Here, we propose a combined model based on fuzzy descriptor models and singular spectrum analysis (SSA) (FD/SSA) to forecast a number of geomagnetic activity indices in a manner that optimizes a fuzzy descriptor model for each of the principal components obtained from singular spectrum analysis and recombines the predicted values so as to transform the geomagnetic activity time series into natural chaotic phenomena. The method has been applied to predict two solar and geomagnetic activity indices: geomagnetic aa and solar wind speed (SWS) of the solar wind index. The results demonstrate the higher power of the proposed method-- compared to other methods -- for predicting solar activity.
NASA Astrophysics Data System (ADS)
Gondoin, P.; Gandolfi, D.; Fridlund, M.; Frasca, A.; Guenther, E. W.; Hatzes, A.; Deeg, H. J.; Parviainen, H.; Eigmüller, P.; Deleuil, M.
2012-12-01
Aims: The present study reports measurements of the rotation period of a young solar analogue, estimates of its surface coverage by photospheric starspots and of its chromospheric activity level, and derivations of its evolutionary status. Detailed observations of many young solar-type stars, such as the one reported in the present paper, provide insight into rotation and magnetic properties that may have prevailed on the Sun in its early evolution. Methods: Using a model based on the rotational modulation of the visibility of active regions, we analysed the high-accuracy CoRoT lightcurve of the active star CoRoT 102899501. Spectroscopic follow-up observations were used to derive its fundamental parameters. We compared the chromospheric activity level of Corot 102899501 with the R'HK index distribution vs age established on a large sample of solar-type dwarfs in open clusters. We also compared the chromospheric activity level of this young star with a model of chromospheric activity evolution established by combining relationships between the R'HK index and the Rossby number with a recent model of stellar rotation evolution on the main sequence. Results: We measure the spot coverage of the stellar surface as a function of time and find evidence for a tentative increase from 5 - 14% at the beginning of the observing run to 13-29% 35 days later. A high level of magnetic activity on Corot 102899501 is corroborated by a strong emission in the Balmer and Ca ii H and K lines (R'HK ~ -4). The starspots used as tracers of the star rotation constrain the rotation period to 1.625 ± 0.002 days and do not show evidence for differential rotation. The effective temperature (Teff = 5180 ± 80 K), surface gravity (log g = 4.35 ± 0.1), and metallicity ([M/H] = 0.05 ± 0.07 dex) indicate that the object is located near the evolutionary track of a 1.09 ± 0.12 M⊙ pre-main sequence star at an age of 23 ± 10 Myr. This value is consistent with the "gyro-age" of about 8-25 Myr
Kostylev, Maxim; Wilson, David
2014-01-01
Lignocellulosic biomass is a potential source of renewable, low-carbon-footprint liquid fuels. Biomass recalcitrance and enzyme cost are key challenges associated with the large-scale production of cellulosic fuel. Kinetic modeling of enzymatic cellulose digestion has been complicated by the heterogeneous nature of the substrate and by the fact that a true steady state cannot be attained. We present a two-parameter kinetic model based on the Michaelis-Menten scheme (Michaelis L and Menten ML. (1913) Biochem Z 49:333–369), but with a time-dependent activity coefficient analogous to fractal-like kinetics formulated by Kopelman (Kopelman R. (1988) Science 241:1620–1626). We provide a mathematical derivation and experimental support to show that one of the parameters is a total activity coefficient and the other is an intrinsic constant that reflects the ability of the cellulases to overcome substrate recalcitrance. The model is applicable to individual cellulases and their mixtures at low-to-medium enzyme loads. Using biomass degrading enzymes from a cellulolytic bacterium Thermobifida fusca we show that the model can be used for mechanistic studies of enzymatic cellulose digestion. We also demonstrate that it applies to the crude supernatant of the widely studied cellulolytic fungus Trichoderma reesei and can thus be used to compare cellulases from different organisms. The two parameters may serve a similar role to Vmax, KM, and kcat in classical kinetics. A similar approach may be applicable to other enzymes with heterogeneous substrates and where a steady state is not achievable. PMID:23837567
Batista, Mariana R.B.; Martínez, Leandro
2013-01-01
Nuclear hormone receptors (NRs) are major targets for pharmaceutical development. Many experiments demonstrate that their C-terminal Helix (H12) is more flexible in the ligand-binding domains (LBDs) without ligand, this increased mobility being correlated with transcription repression and human diseases. Crystal structures have been obtained in which the H12 is extended, suggesting the possibility of large amplitude H12 motions in solution. However, these structures were interpreted as possible crystallographic artifacts, and thus the microscopic nature of H12 movements is not well known. To bridge the gap between experiments and molecular models and provide a definitive picture of H12 motions in solution, extensive molecular dynamics simulations of the peroxisome proliferator-activated receptor-γ LBD, in which the H12 was bound to a fluorescent probe, were performed. A direct comparison of the modeled anisotropy decays to time-resolved fluorescence anisotropy experiments was obtained. It is shown that the decay rates are dependent on the interactions of the probe with the surface of the protein, and display little correlation with the flexibility of the H12. Nevertheless, for the probe to interact with the surface of the LBD, the H12 must be folded over the body of the LBD. Therefore, the molecular mobility of the H12 should preserve the globularity of the LBD, so that ligand binding and dissociation occur by diffusion through the surface of a compact receptor. These results advance the comprehension of both ligand-bound and ligand-free receptor structures in solution, and also guide the interpretation of time-resolved anisotropy decays from a molecular perspective, particularly by the use of simulations. PMID:24094408
McCreddin, A; Alam, M S; McNabola, A
2015-01-01
An experimental assessment of personal exposure to PM10 in 59 office workers was carried out in Dublin, Ireland. 255 samples of 24-h personal exposure were collected in real time over a 28 month period. A series of modelling techniques were subsequently assessed for their ability to predict 24-h personal exposure to PM10. Artificial neural network modelling, Monte Carlo simulation and time-activity based models were developed and compared. The results of the investigation showed that using the Monte Carlo technique to randomly select concentrations from statistical distributions of exposure concentrations in typical microenvironments encountered by office workers produced the most accurate results, based on 3 statistical measures of model performance. The Monte Carlo simulation technique was also shown to have the greatest potential utility over the other techniques, in terms of predicting personal exposure without the need for further monitoring data. Over the 28 month period only a very weak correlation was found between background air quality and personal exposure measurements, highlighting the need for accurate models of personal exposure in epidemiological studies.
Gonzalez-Castillo, Javier; Saad, Ziad S.; Handwerker, Daniel A.; Inati, Souheil J.; Brenowitz, Noah; Bandettini, Peter A.
2012-01-01
The brain is the body's largest energy consumer, even in the absence of demanding tasks. Electrophysiologists report on-going neuronal firing during stimulation or task in regions beyond those of primary relationship to the perturbation. Although the biological origin of consciousness remains elusive, it is argued that it emerges from complex, continuous whole-brain neuronal collaboration. Despite converging evidence suggesting the whole brain is continuously working and adapting to anticipate and actuate in response to the environment, over the last 20 y, task-based functional MRI (fMRI) have emphasized a localizationist view of brain function, with fMRI showing only a handful of activated regions in response to task/stimulation. Here, we challenge that view with evidence that under optimal noise conditions, fMRI activations extend well beyond areas of primary relationship to the task; and blood-oxygen level-dependent signal changes correlated with task-timing appear in over 95% of the brain for a simple visual stimulation plus attention control task. Moreover, we show that response shape varies substantially across regions, and that whole-brain parcellations based on those differences produce distributed clusters that are anatomically and functionally meaningful, symmetrical across hemispheres, and reproducible across subjects. These findings highlight the exquisite detail lying in fMRI signals beyond what is normally examined, and emphasize both the pervasiveness of false negatives, and how the sparseness of fMRI maps is not a result of localized brain function, but a consequence of high noise and overly strict predictive response models. PMID:22431587
NASA Technical Reports Server (NTRS)
Thomas, Claudine
1995-01-01
The generation and dissemination of International Atomic Time, TAI, and of Coordinated Universal Time, UTC, are explicitly mentioned in the list of the principal tasks of the BIPM, recalled in the Comptes Rendus of the 18th Conference Generale des Poids et Mesures, in 1987. These tasks are fulfilled by the BIPM Time Section, thanks to international cooperation with national timing centers, which maintain, under metrological conditions, the clocks used to generate TAI. Besides the current work of data collection and processing, research activities are carried out in order to adapt the computation of TAI to the most recent improvements occurring in the time and frequency domains. Studies concerning the application of general relativity and pulsar timing to time metrology are also actively pursued. This paper summarizes the work done in all these fields and outlines future projects.
ERIC Educational Resources Information Center
Beville, Jill M.; Umstattd Meyer, M. Renée; Usdan, Stuart L.; Turner, Lori W.; Jackson, John C.; Lian, Brad E.
2014-01-01
Objective: National data consistently report that males participate in leisure time physical activity (LTPA) at higher rates than females. This study expanded previous research to examine gender differences in LTPA of college students using the theory of planned behavior (TPB) by including 2 additional constructs, descriptive norm and…
ERIC Educational Resources Information Center
Mata, Andrea D.; van Dulmen, Manfred H. M.
2012-01-01
This study investigated trajectories of time spent in structured activities from middle childhood to early adolescence by using data from the National Institute of Child Health & Human Development (NICHD) Study of Early Child Care. We used latent class growth analyses and identified five trajectories (stable low, increasing high, decreasing low,…
Sequential digital elevation models of active lava flows from ground-based stereo time-lapse imagery
NASA Astrophysics Data System (ADS)
James, M. R.; Robson, S.
2014-11-01
We describe a framework for deriving sequences of digital elevation models (DEMs) for the analysis of active lava flows using oblique stereo-pair time-lapse imagery. A photo-based technique was favoured over laser-based alternatives due to low equipment cost, high portability and capability for network expansion, with images of advancing flows captured by digital SLR cameras over durations of up to several hours. However, under typical field scale scenarios, relative camera orientations cannot be rigidly maintained (e.g. through the use of a stereo bar), preventing the use of standard stereo time-lapse processing software. Thus, we trial semi-automated DEM-sequence workflows capable of handling the small camera motions, variable image quality and restricted photogrammetric control that result from the practicalities of data collection at remote and hazardous sites. The image processing workflows implemented either link separate close-range photogrammetry and traditional stereo-matching software, or are integrated in a single software package based on structure-from-motion (SfM). We apply these techniques in contrasting case studies from Kilauea volcano, Hawaii and Mount Etna, Sicily, which differ in scale, duration and image texture. On Kilauea, the advance direction of thin fluid lava lobes was difficult to forecast, preventing good distribution of control. Consequently, volume changes calculated through the different workflows differed by ∼10% for DEMs (over ∼30 m2) that were captured once a minute for 37 min. On Mt. Etna, more predictable advance (∼3 m h-1 for ∼3 h) of a thicker, more viscous lava allowed robust control to be deployed and volumetric change results were generally within 5% (over ∼500 m2). Overall, the integrated SfM software was more straightforward to use and, under favourable conditions, produced results comparable to those from the close-range photogrammetry pipeline. However, under conditions with limited options for photogrammetric
Hagger, Martin; Chatzisarantis, Nikos L D; Hein, Vello; Soós, István; Karsai, István; Lintunen, Taru; Leemans, Sofie
2009-07-01
An extended trans-contextual model of motivation for health-related physical activity was tested in samples from four nations. The model proposes a motivational sequence in which perceived autonomy support from teachers in a physical education (PE) context and from peers and parents in a leisure-time physical activity context predict autonomous motivation, intentions and physical activity behaviour in a leisure-time context. A three-wave prospective correlational design was employed. High-school pupils from Britain, Estonia, Finland and Hungary completed measures of perceived autonomy support from PE teachers, autonomous motivation in both contexts, perceived autonomy support from peers and parents, attitudes, subjective norms, perceived behavioural control and intentions from the Theory of Planned Behaviour (TPB), and measures of behaviour and past behaviour in a leisure-time context. Path-analyses controlling for past behaviour supported trans-contextual model hypotheses across all samples. Effects of perceived autonomy support from peers and parents on leisure-time autonomous motivation were small and inconsistent, while effects on TPB variables were stronger. There was a unique effect of perceived autonomy support from PE teachers on leisure-time autonomous motivation. Findings support the model, which provides an explanation of the processes by which perceived autonomy support from different sources affects health-related physical activity motivation across these contexts.
Kössl, Manfred; Hechavarria, Julio; Voss, Cornelia; Schaefer, Markus; Vater, Marianne
2015-03-01
Audition in bats serves passive orientation, alerting functions and communication as it does in other vertebrates. In addition, bats have evolved echolocation for orientation and prey detection and capture. This put a selective pressure on the auditory system in regard to echolocation-relevant temporal computation and frequency analysis. The present review attempts to evaluate in which respect the processing modules of bat auditory cortex (AC) are a model for typical mammalian AC function or are designed for echolocation-unique purposes. We conclude that, while cortical area arrangement and cortical frequency processing does not deviate greatly from that of other mammals, the echo delay time-sensitive dorsal cortex regions contain special designs for very powerful time perception. Different bat species have either a unique chronotopic cortex topography or a distributed salt-and-pepper representation of echo delay. The two designs seem to enable similar behavioural performance. PMID:25728173
NASA Astrophysics Data System (ADS)
Kaiser, Andreas; Neugirg, Fabian; Hass, Erik; Jose, Steffen; Haas, Florian; Schmidt, Jürgen
2016-04-01
In erosional research a variety of processes are well understood and have been mimicked under laboratory conditions. In complex natural systems such as Alpine environments a multitude of influencing factors tend to superimpose single processes in a mixed signal which impedes a reliable interpretation. These mixed signals can already be captured by geoscientific research approaches such as sediment collectors, erosion pins or remote sensing surveys. Nevertheless, they fail to distinguish between single processes and their individual impact on slope morphology. Throughout the last two years a highly active slope of unsorted glacial deposits in the northern Alps has been monitored by repeated terrestrial laser scans roughly every three months. Resulting high resolution digital elevation models of difference were produced to identify possible seasonal patterns. By reproducing the TLS results with a physically based erosion model (EROSION 3D) ran with in situ input data from rainfall simulations and a climate station a better understanding of individual mechanism could be achieved. However, the already elaborate combination of soil science and close range remote sensing could not answer all questions concerning the slopes behaviour, especially not for freeze and thaw cycles and the winter period. Therefore, an array of three fully automatic synchronised cameras was setup to generate continuous 3D surface models. Among the main challenges faced for the system were the energy supply and durability, perspectives of the cameras to avoid shadowing and to guarantee sufficient overlap, a certain robustness to withstand rough alpine weather conditions, the scaling of each 3D model by tracked ground control points and the automatic data handling. First results show individual processes sculpting the slope's morphology but further work is required to improve automatic point cloud creation and change monitoring.
Time-driven activity-based costing.
Kaplan, Robert S; Anderson, Steven R
2004-11-01
In the classroom, activity-based costing (ABC) looks like a great way to manage a company's limited resources. But executives who have tried to implement ABC in their organizations on any significant scale have often abandoned the attempt in the face of rising costs and employee irritation. They should try again, because a new approach sidesteps the difficulties associated with large-scale ABC implementation. In the revised model, managers estimate the resource demands imposed by each transaction, product, or customer, rather than relying on time-consuming and costly employee surveys. This method is simpler since it requires, for each group of resources, estimates of only two parameters: how much it costs per time unit to supply resources to the business's activities (the total overhead expenditure of a department divided by the total number of minutes of employee time available) and how much time it takes to carry out one unit of each kind of activity (as estimated or observed by the manager). This approach also overcomes a serious technical problem associated with employee surveys: the fact that, when asked to estimate time spent on activities, employees invariably report percentages that add up to 100. Under the new system, managers take into account time that is idle or unused. Armed with the data, managers then construct time equations, a new feature that enables the model to reflect the complexity of real-world operations by showing how specific order, customer, and activity characteristics cause processing times to vary. This Tool Kit uses concrete examples to demonstrate how managers can obtain meaningful cost and profitability information, quickly and inexpensively. Rather than endlessly updating and maintaining ABC data,they can now spend their time addressing the deficiencies the model reveals: inefficient processes, unprofitable products and customers, and excess capacity.
Time-driven activity-based costing.
Kaplan, Robert S; Anderson, Steven R
2004-11-01
In the classroom, activity-based costing (ABC) looks like a great way to manage a company's limited resources. But executives who have tried to implement ABC in their organizations on any significant scale have often abandoned the attempt in the face of rising costs and employee irritation. They should try again, because a new approach sidesteps the difficulties associated with large-scale ABC implementation. In the revised model, managers estimate the resource demands imposed by each transaction, product, or customer, rather than relying on time-consuming and costly employee surveys. This method is simpler since it requires, for each group of resources, estimates of only two parameters: how much it costs per time unit to supply resources to the business's activities (the total overhead expenditure of a department divided by the total number of minutes of employee time available) and how much time it takes to carry out one unit of each kind of activity (as estimated or observed by the manager). This approach also overcomes a serious technical problem associated with employee surveys: the fact that, when asked to estimate time spent on activities, employees invariably report percentages that add up to 100. Under the new system, managers take into account time that is idle or unused. Armed with the data, managers then construct time equations, a new feature that enables the model to reflect the complexity of real-world operations by showing how specific order, customer, and activity characteristics cause processing times to vary. This Tool Kit uses concrete examples to demonstrate how managers can obtain meaningful cost and profitability information, quickly and inexpensively. Rather than endlessly updating and maintaining ABC data,they can now spend their time addressing the deficiencies the model reveals: inefficient processes, unprofitable products and customers, and excess capacity. PMID:15559451
NASA Astrophysics Data System (ADS)
Sato, Takeshi; Ishikawa, Kenichi L.
2015-02-01
The time-dependent multiconfiguration self-consistent-field method based on the occupation-restricted multiple-active-space model is proposed (TD-ORMAS) for multielectron dynamics in intense laser fields. Extending the previously proposed time-dependent complete-active-space self-consistent-field method [TD-CASSCF; Phys. Rev. A 88, 023402 (2013), 10.1103/PhysRevA.88.023402], which divides the occupied orbitals into core and active orbitals, the TD-ORMAS method further subdivides the active orbitals into an arbitrary number of subgroups and poses the occupation restriction by giving the minimum and maximum number of electrons distributed in each subgroup. This enables highly flexible construction of the configuration-interaction (CI) space, allowing a large-active-space simulation of dynamics, e.g., the core excitation or ionization. The equations of motion for both CI coefficients and spatial orbitals are derived based on the time-dependent variational principle, and an efficient algorithm is proposed to solve for the orbital time derivatives. In-depth descriptions of the computational implementation are given in a readily programmable manner. The numerical application to the one-dimensional lithium hydride cluster models demonstrates that the high flexibility of the TD-ORMAS framework allows for the cost-effective simulations of multielectron dynamics by exploiting systematic series of approximations to the TD-CASSCF method.
Deffner, Veronika; Küchenhoff, Helmut; Maier, Verena; Pitz, Mike; Cyrys, Josef; Breitner, Susanne; Schneider, Alexandra; Gu, Jianwei; Geruschkat, Uta; Peters, Annette
2016-01-01
Personal exposure to air pollution is associated with time- and location-specific factors including indoor and outdoor air pollution, meteorology and time activities. Our investigation aims at the description and identification of factors determining personal exposure to particle number concentration (PNC) in everyday situations. Ten volunteers recorded their personal exposure to PNC and kept an activity diary in three different seasons besides stationary measurements of ambient air pollution and meteorology. Background exposure to PNC was modelled using the most predictive variables. In a second step, the effects of the activities were calculated adjusted for the background exposure. The average personal PNC level was highest in winter and was three times higher than the mean stationary PNC level while staying indoors and two times higher while staying outdoors. Personal indoor PNC levels were significantly increased during the use of candles, cooking and the occurrence of smell of food. High stationary outdoor PNC levels and low dew point temperatures were associated with increased personal outdoor PNC levels. Times spent in public transport were associated with lower personal PNC levels than other times spent in transportation. Personal PNC levels in everyday situations exhibited a large variability because of seasonal, microenvironment-specific and activity-specific influences.
Hill, Yolanda R.; Child, Nick; Hanson, Ben; Wallman, Mikael; Coronel, Ruben; Plank, Gernot; Rinaldi, Christopher A.; Gill, Jaswinder; Smith, Nicolas P.; Taggart, Peter; Bishop, Martin J.
2016-01-01
Exit sites associated with scar-related reentrant arrhythmias represent important targets for catheter ablation therapy. However, their accurate location in a safe and robust manner remains a significant clinical challenge. We recently proposed a novel quantitative metric (termed the Reentry Vulnerability Index, RVI) to determine the difference between activation and repolarisation intervals measured from pairs of spatial locations during premature stimulation to accurately locate the critical site of reentry formation. In the clinic, the method showed potential to identify regions of low RVI corresponding to areas vulnerable to reentry, subsequently identified as ventricular tachycardia (VT) circuit exit sites. Here, we perform an in silico investigation of the RVI metric in order to aid the acquisition and interpretation of RVI maps and optimise its future usage within the clinic. Within idealised 2D sheet models we show that the RVI produces lower values under correspondingly more arrhythmogenic conditions, with even low resolution (8 mm electrode separation) recordings still able to locate vulnerable regions. When applied to models of infarct scars, the surface RVI maps successfully identified exit sites of the reentrant circuit, even in scenarios where the scar was wholly intramural. Within highly complex infarct scar anatomies with multiple reentrant pathways, the identified exit sites were dependent upon the specific pacing location used to compute the endocardial RVI maps. However, simulated ablation of these sites successfully prevented the reentry re-initiation. We conclude that endocardial surface RVI maps are able to successfully locate regions vulnerable to reentry corresponding to critical exit sites during sustained scar-related VT. The method is robust against highly complex and intramural scar anatomies and low resolution clinical data acquisition. Optimal location of all relevant sites requires RVI maps to be computed from multiple pacing
Hill, Yolanda R; Child, Nick; Hanson, Ben; Wallman, Mikael; Coronel, Ruben; Plank, Gernot; Rinaldi, Christopher A; Gill, Jaswinder; Smith, Nicolas P; Taggart, Peter; Bishop, Martin J
2016-01-01
Exit sites associated with scar-related reentrant arrhythmias represent important targets for catheter ablation therapy. However, their accurate location in a safe and robust manner remains a significant clinical challenge. We recently proposed a novel quantitative metric (termed the Reentry Vulnerability Index, RVI) to determine the difference between activation and repolarisation intervals measured from pairs of spatial locations during premature stimulation to accurately locate the critical site of reentry formation. In the clinic, the method showed potential to identify regions of low RVI corresponding to areas vulnerable to reentry, subsequently identified as ventricular tachycardia (VT) circuit exit sites. Here, we perform an in silico investigation of the RVI metric in order to aid the acquisition and interpretation of RVI maps and optimise its future usage within the clinic. Within idealised 2D sheet models we show that the RVI produces lower values under correspondingly more arrhythmogenic conditions, with even low resolution (8 mm electrode separation) recordings still able to locate vulnerable regions. When applied to models of infarct scars, the surface RVI maps successfully identified exit sites of the reentrant circuit, even in scenarios where the scar was wholly intramural. Within highly complex infarct scar anatomies with multiple reentrant pathways, the identified exit sites were dependent upon the specific pacing location used to compute the endocardial RVI maps. However, simulated ablation of these sites successfully prevented the reentry re-initiation. We conclude that endocardial surface RVI maps are able to successfully locate regions vulnerable to reentry corresponding to critical exit sites during sustained scar-related VT. The method is robust against highly complex and intramural scar anatomies and low resolution clinical data acquisition. Optimal location of all relevant sites requires RVI maps to be computed from multiple pacing
Student Modeling Based on Problem Solving Times
ERIC Educational Resources Information Center
Pelánek, Radek; Jarušek, Petr
2015-01-01
Student modeling in intelligent tutoring systems is mostly concerned with modeling correctness of students' answers. As interactive problem solving activities become increasingly common in educational systems, it is useful to focus also on timing information associated with problem solving. We argue that the focus on timing is natural for certain…
NASA Astrophysics Data System (ADS)
Semmar, Nadjib; Darif, Mohamed; Millon, Eric; Petit, Agnès; Etienne, Hasnaa; Delaporte, Philippe
2012-07-01
This work concerns the ALDIP (Laser Activation of Doping agents Implanted by Plasma immersion) project that was a successful collaboration with Ion Beam Services (IBS) corporation, the "Lasers, Plasmas and Photonic Processes" (LP3) laboratory and the GREMI laboratory. The aim of this work is to control the melted thickness (i.e. junction thickness in the range 10-100 nm) by the Real Time Reflectivity (TRR) monitoring during the Laser Thermal Processing (LTP). The LTP is achieved by using a KrF laser beam (248 nm, 27 ns) with a homogeneous 'Top-Hat' space distribution to induce a selective melting and the resolidification of the doped Si:B samples on few nanometers. This recrystallization is conducted here after the pre-amorphisation process resulting from the ionic implantation of Si (PIII IBS implanter). Thus, all the studied samples are partially amorphized and boron doped. TRR method allows the accurate evaluation of the melting threshold, the duration of the melting phase, and the maximum melted thickness. Obtained results versus laser fluence are shown in the new case of under vacuum treatment. In order to calibrate the TRR method (to determine the intensity and the profile of the TRR signal versus the melting depth), we have used the secondary ion mass spectrometry (TOF-SIMS) analysis. This technique gives the doping agents profile versus the depth before and after LTP and confirms also the melting kinetics from TRR results.
The Variance Reaction Time Model
ERIC Educational Resources Information Center
Sikstrom, Sverker
2004-01-01
The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…
Sunspot Time Series: Passive and Active Intervals
NASA Astrophysics Data System (ADS)
Zięba, S.; Nieckarz, Z.
2014-07-01
Solar activity slowly and irregularly decreases from the first spotless day (FSD) in the declining phase of the old sunspot cycle and systematically, but also in an irregular way, increases to the new cycle maximum after the last spotless day (LSD). The time interval between the first and the last spotless day can be called the passive interval (PI), while the time interval from the last spotless day to the first one after the new cycle maximum is the related active interval (AI). Minima of solar cycles are inside PIs, while maxima are inside AIs. In this article, we study the properties of passive and active intervals to determine the relation between them. We have found that some properties of PIs, and related AIs, differ significantly between two group of solar cycles; this has allowed us to classify Cycles 8 - 15 as passive cycles, and Cycles 17 - 23 as active ones. We conclude that the solar activity in the PI declining phase (a descending phase of the previous cycle) determines the strength of the approaching maximum in the case of active cycles, while the activity of the PI rising phase (a phase of the ongoing cycle early growth) determines the strength of passive cycles. This can have implications for solar dynamo models. Our approach indicates the important role of solar activity during the declining and the rising phases of the solar-cycle minimum.
Volcano Deformation and Modeling on Active Volcanoes in the Philippines from ALOS InSAR Time Series
NASA Astrophysics Data System (ADS)
Morales Rivera, Anieri M.; Amelung, Falk; Eco, Rodrigo
2015-05-01
Bulusan, Kanlaon, and Mayon volcanoes have erupted over the last decade, and Taal caldera showed signs of volcanic unrest within the same time range. Eruptions at these volcanoes are a threat to human life and infrastructure, having over 1,000,000 people living within 10 km from just these 4 volcanic centers. For this reason, volcano monitoring in the Philippines is of extreme importance. We use the ALOS-1 satellite from the Japanese Aerospace Exploration Agency (JAXA) to make an InSAR time series analysis over Bulusan, Kanlaon, Mayon, and Taal volcanoes for the 2007-2011 period. Time-dependent deformation was detected at all of the volcanoes. Deformation related to changes in pressurization of the volcanic systems was found on Taal caldera and Bulusan volcanoes, with best fitting Mogi sources located at half-space depths of 3.07 km and 0.5 km respectively.
Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen
2016-01-01
Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors. PMID:26943641
Yao, Min; Lu, Xin; Lei, Yingfeng; Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen
2016-01-01
Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors. PMID:26943641
Yao, Min; Lu, Xin; Lei, Yingfeng; Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen
2016-01-01
Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors.
Recognition of Short Time-Paired Activities
NASA Astrophysics Data System (ADS)
Chaminda, Hapugahage Thilak; Klyuev, Vitaly; Naruse, Keitaro; Osano, Minetada
We undertake numerous activities in our daily life and for some of those we forget to complete the action as originally intended. Significant aspects while performing most of these actions might be: “pairing of both hands simultaneously” and “short time consumption”. In this work an attempt has been made to recognize those kinds of Paired Activities (PAs), which are easy to forget, and to provide a method to remind about uncompleted PAs. To represent PAs, a study was done on opening and closing of various bottles. A model to define PAs, which simulated the paired behavior of both hands, is proposed, called “Paired Activity Model” (PAM). To recognize PAs using PAM, Paired Activity Recognition Algorithm (PARA) was implemented. Paired motion capturing was done by accelerometers, which were worn by subjects on the wrist areas of both hands. Individual and correlative behavior of both hands was used to recognize exact PA among other activities. Artificial Neural Network (ANN) algorithm was used for data categorization in PARA. ANN significantly outperformed the support vector machine algorithm in real time evaluations. In the user-independent case, PARA achieved recognition rates of 96% for only target PAs and 91% for target PAs undertaken amidst unrelated activities.
NASA Astrophysics Data System (ADS)
Jiang, C.; Feng, X.; Wu, S.; Hu, Q.
2012-12-01
Non-potentiality of the solar coronal magnetic field accounts for the solar explosion like flares and CMEs. We apply a data-driven CESE-MHD model to investigate the three-dimensional (3D) coronal magnetic field of NOAA active region (AR) 11117 around the time of a C-class confined flare occurred on 2010 October 25. The CESE-MHD model, based on the spacetime conservation-element and solution-element scheme, is designed to focus on the magnetic-field evolution and to consider a simplified solar atomsphere with finite plasma β. Magnetic vector-field data derived from the observations at the photoshpere is inputted directly to constrain the model. Assuming that the dynamic evolution of the coronal magnetic field can be approximated by successive equilibria, we solve a time sequence of MHD equilibria basing on a set of vector magnetograms for AR 11117 taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamic Observatory (SDO) around the time of flare. The model qualitatively reproduces the basic structures of the 3D magnetic field, as supported by the visual similarity between the field lines and the coronal loops observed by the Atmospheric Imaging Assembly (AIA), which shows that the coronal field can indeed be well characterized by the MHD equilibrium in most time. The magnetic configuration changes very limited during the studied time interval of two hours. A topological analysis reveals that the small flare is correlated with a bald patch (BP, where the magnetic field is tangent to the photoshpere), suggesting that the energy release of the flare can be understood by magnetic reconnection associated with the BP separatrices. The total magnetic flux and energy keep increasing slightly in spite of the flare, while the magnetic free energy drops during the flare with an amount of 1.7 × 1030 erg, which can be interpreted as the energy budget released by the minor C-class flare.
The Leisure-Time Activity of Citizens
ERIC Educational Resources Information Center
Sedova, N. N.
2011-01-01
Survey data show that Russians relegate free time and leisure activity to secondary status compared to work, and free time faces the threat of becoming devalued and losing its importance as a life value. At the same time, in the structure of Russians' leisure activities there is an ongoing tendency for leisure to become simpler, for active types…
Time Directed Avalanches in Invasion Models
Maslov, S. Department of Physics, SUNY at Stony Brook, Stony Brook, New York 11794 )
1995-01-23
We define forward and backward time-directed avalanches for a broad class of self-organized critical models including invasion percolation, interface depinning, and a simple model of evolution. Although the geometrical properties of the avalanches do not change under time reversal, their stationary state statistical distribution does. The overall distribution of forward avalanches [ital P]([ital s])[similar to][ital s][sup [minus]2] is superuniversal in this class of models. The power-law exponent [pi] for the distribution of distances between subsequent active sites is derived from the properties of backward avalanches.
Probabilistic Survivability Versus Time Modeling
NASA Technical Reports Server (NTRS)
Joyner, James J., Sr.
2015-01-01
This technical paper documents Kennedy Space Centers Independent Assessment team work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer (CSO) and GSDO management during key programmatic reviews. The assessments provided the GSDO Program with an analysis of how egress time affects the likelihood of astronaut and worker survival during an emergency. For each assessment, the team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedys Vehicle Assembly Building (VAB).Based on the composite survivability versus time graphs from the first two assessments, there was a soft knee in the Figure of Merit graphs at eight minutes (ten minutes after egress ordered). Thus, the graphs illustrated to the decision makers that the final emergency egress design selected should have the capability of transporting the flight crew from the top of LC 39B to a safe location in eight minutes or less. Results for the third assessment were dominated by hazards that were classified as instantaneous in nature (e.g. stacking mishaps) and therefore had no effect on survivability vs time to egress the VAB. VAB emergency scenarios that degraded over time (e.g. fire) produced survivability vs time graphs that were line with aerospace industry norms.
Trost, A; Motloch, K; Bruckner, D; Schroedl, F; Bogner, B; Kaser-Eichberger, A; Runge, C; Strohmaier, C; Klein, B; Aigner, L; Reitsamer, H A
2015-07-01
Glaucoma is a group of neurodegenerative diseases characterized by the progressive loss of retinal ganglion cells (RGCs) and their axons, and is the second leading cause of blindness worldwide. Elevated intraocular pressure is a well known risk factor for the development of glaucomatous optic neuropathy and pharmacological or surgical lowering of intraocular pressure represents a standard procedure in glaucoma treatment. However, the treatment options are limited and although lowering of intraocular pressure impedes disease progression, glaucoma cannot be cured by the currently available therapy concepts. In an acute short-term ocular hypertension model in rat, we characterize RGC loss, but also microglial cell activation and vascular alterations of the retina at certain time points. The combination of these three parameters might facilitate a better evaluation of the disease progression, and could further serve as a new model to test novel treatment strategies at certain time points. Acute ocular hypertension (OHT) was induced by the injection of magnetic microbeads into the rat anterior chamber angle (n = 22) with magnetic position control, leading to constant elevation of IOP. At certain time points post injection (4d, 7d, 10d, 14d and 21d), RGC loss, microglial activation, and microvascular pericyte (PC) coverage was analyzed using immunohistochemistry with corresponding specific markers (Brn3a, Iba1, NG2). Additionally, the tightness of the retinal vasculature was determined via injections of Texas Red labeled dextran (10 kDa) and subsequently analyzed for vascular leakage. For documentation, confocal laser-scanning microscopy was used, followed by cell counts, capillary length measurements and morphological and statistical analysis. The injection of magnetic microbeads led to a progressive loss of RGCs at the five time points investigated (20.07%, 29.52%, 41.80%, 61.40% and 76.57%). Microglial cells increased in number and displayed an activated morphology
Riesen, T K; Gottofrey, J; Heiz, H J; Schenker-Wicki, A
1996-12-01
The radioecological model ECOSYS-87 was used to evaluate the effect of countermeasures for reducing the ingestion dose by eating cattle meat after an accidental release of radioactive material. Calculations were performed using a database adapted to Swiss conditions for the case that (1) contaminated grass or hay is replaced by clean fodder; (2) the last 100 days before slaughter, taking place one year after an accident, only uncontaminated fodder is given; and (3) alternative feeding regimes are chosen. Seasonal effects were considered by doing all calculations for a deposition at each month of the year. Feeding uncontaminated forage 100 d before slaughter (case 2) proved to be the most effective countermeasure and reduced the integrated activity in meat by 90% to 99%. The effect of replacing contaminated grass (case 1) was less uniform and depended strongly on the time a deposition occurred. In this case the reduction was between 50% and 100% one year after deposition. The substitution of contaminated hay (case 1) was less effective compared to the substitution of grass. The choice of alternative feeding regimes (case 3) led to a reduction of the integrated activity of up to 40% one year after deposition. The present model calculations clearly reveal the importance of the seasonality and demonstrate the usefulness of such calculations as a basis for generating countermeasures in decision support systems. PMID:8919069
Riesen, T.K.; Gottofrey, J.; Heiz, H.J.; Schenker-Wicki, A.
1996-12-01
The radioecological model ECOSYS087 was used to evaluate the effect of countermeasures for reducing the ingestion dose by eating cattle meat after an accidental release of radioactive material. Calculations were performed using a database adapted to Swiss conditions for the case that (1) contaminated grass or hay is replaced by clean fodder; (2) the last 100 days before slaughter, taking place one year after an accident, only uncontaminated fodder is given; and (3) alternative feeding regimes are chosen. Seasonal effects were considered by doing all calculations for a deposition at each month of the year. Feeding uncontaminated forage 100 d before slaughter (case 2) proved to be the most effective countermeasure and reduced the integrated activity in meat by 90% to 99%. The effect of replacing contaminated grass (case 1) was less uniform and depended strongly on the time a deposition occurred. In this case the reduction was between 50% and 100% one year after deposition. The substitution of contaminated hay (case 1) was less effective compared to the substitution of grass. The choice of alternative feeding regimes (case 1) was less effective compared to the substitution of grass. The choice of alternative feeding regimes (case 3) led to a reduction of the integrated activity of up to 40% one year after deposition. The present model calculations clearly reveal the importance of the seasonality and demonstrate the usefulness of such calculations as a basis for generating countermeasures in decision support systems. 8 refs., 1 fig., 5 tabs.
NASA Astrophysics Data System (ADS)
Veltri, Alessandro; Chipouline, Arkadi; Aradian, Ashod
2016-09-01
The plasmonic response of a metal nanoparticle in the presence of surrounding gain elements is studied, using a space and time-dependent model, which integrates a quantum formalism to describe the gain and a classical treatment for the metal. Our model fully takes into account the influence of the system geometry (nanosphere) and offers for the first time, the possibility to describe the temporal evolution of the fields and the coupling among the multipolar modes of the particle. We calculate the lasing threshold value for all multipoles of the spaser, and demonstrate that the dipolar one is lowest. The onset of the lasing instability, in the linear regime, is then studied both with and without external field forcing. We also study the behaviour of the system below the lasing threshold, with the external field, demonstrating the existence of an amplification regime where the nanoparticle’s plasmon is strongly enhanced as the threshold is approached. Finally, a qualitative discussion is provided on later, non-linear stages of the dynamics and the approach to the steady-state of the spaser; in particular, it is shown that, for the considered geometry, the spasing is necessarily multi-modal and multipolar modes are always activated.
Veltri, Alessandro; Chipouline, Arkadi; Aradian, Ashod
2016-01-01
The plasmonic response of a metal nanoparticle in the presence of surrounding gain elements is studied, using a space and time-dependent model, which integrates a quantum formalism to describe the gain and a classical treatment for the metal. Our model fully takes into account the influence of the system geometry (nanosphere) and offers for the first time, the possibility to describe the temporal evolution of the fields and the coupling among the multipolar modes of the particle. We calculate the lasing threshold value for all multipoles of the spaser, and demonstrate that the dipolar one is lowest. The onset of the lasing instability, in the linear regime, is then studied both with and without external field forcing. We also study the behaviour of the system below the lasing threshold, with the external field, demonstrating the existence of an amplification regime where the nanoparticle's plasmon is strongly enhanced as the threshold is approached. Finally, a qualitative discussion is provided on later, non-linear stages of the dynamics and the approach to the steady-state of the spaser; in particular, it is shown that, for the considered geometry, the spasing is necessarily multi-modal and multipolar modes are always activated. PMID:27625072
Veltri, Alessandro; Chipouline, Arkadi; Aradian, Ashod
2016-01-01
The plasmonic response of a metal nanoparticle in the presence of surrounding gain elements is studied, using a space and time-dependent model, which integrates a quantum formalism to describe the gain and a classical treatment for the metal. Our model fully takes into account the influence of the system geometry (nanosphere) and offers for the first time, the possibility to describe the temporal evolution of the fields and the coupling among the multipolar modes of the particle. We calculate the lasing threshold value for all multipoles of the spaser, and demonstrate that the dipolar one is lowest. The onset of the lasing instability, in the linear regime, is then studied both with and without external field forcing. We also study the behaviour of the system below the lasing threshold, with the external field, demonstrating the existence of an amplification regime where the nanoparticle’s plasmon is strongly enhanced as the threshold is approached. Finally, a qualitative discussion is provided on later, non-linear stages of the dynamics and the approach to the steady-state of the spaser; in particular, it is shown that, for the considered geometry, the spasing is necessarily multi-modal and multipolar modes are always activated. PMID:27625072
Timing analysis by model checking
NASA Technical Reports Server (NTRS)
Naydich, Dimitri; Guaspari, David
2000-01-01
The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.
ERIC Educational Resources Information Center
Hagger, Martin S.; Chatzisarantis, Nikos L. D.; Barkoukis, Vassilis; Wang, C. K. John; Baranowski, Jaroslaw
2005-01-01
This study tested the replicability and cross-cultural invariance of a trans-contextual model of motivation across 4 samples from diverse cultures. The model proposes a motivational sequence in which perceived autonomy support (PAS) in physical education (PE) predicts autonomous motivation, intentions, and behavior in a leisure-time (LT) physical…
NASA Astrophysics Data System (ADS)
Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas
2010-03-01
Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.
NASA Astrophysics Data System (ADS)
Kirschner, Matthias; Wesarg, Stefan
2011-03-01
Active Shape Models (ASMs) are a popular family of segmentation algorithms which combine local appearance models for boundary detection with a statistical shape model (SSM). They are especially popular in medical imaging due to their ability for fast and accurate segmentation of anatomical structures even in large and noisy 3D images. A well-known limitation of ASMs is that the shape constraints are over-restrictive, because the segmentations are bounded by the Principal Component Analysis (PCA) subspace learned from the training data. To overcome this limitation, we propose a new energy minimization approach which combines an external image energy with an internal shape model energy. Our shape energy uses the Distance From Feature Space (DFFS) concept to allow deviations from the PCA subspace in a theoretically sound and computationally fast way. In contrast to previous approaches, our model does not rely on post-processing with constrained free-form deformation or additional complex local energy models. In addition to the energy minimization approach, we propose a new method for liver detection, a new method for initializing an SSM and an improved k-Nearest Neighbour (kNN)-classifier for boundary detection. Our ASM is evaluated with leave-one-out tests on a data set with 34 tomographic CT scans of the liver and is compared to an ASM with standard shape constraints. The quantitative results of our experiments show that we achieve higher segmentation accuracy with our energy minimization approach than with standard shape constraints.nym
Ganesana, Mallikarjunarao; Erlichman, Joseph S; Andreescu, Silvana
2012-12-15
The overproduction of reactive oxygen species and the resulting damage are central to the pathology of many diseases. The study of the temporal and spatial accumulation of reactive oxygen species has been limited because of the lack of specific probes and techniques capable of continuous measurement. We demonstrate the use of a miniaturized electrochemical cytochrome c (Cyt c) biosensor for real-time measurements and quantitative assessment of superoxide production and inactivation by natural and engineered antioxidants in acutely prepared brain slices from mice. Under control conditions, superoxide radicals produced from the hippocampal region of the brain in 400-μm-thick sections were well within the range of detection of the electrode. Exposure of the slices to ischemic conditions increased the superoxide production twofold and measurements from the slices were stable over a 3- to 4-h period. The stilbene derivative and anion channel inhibitor 4,4'-diisothiocyano-2,2'-disulfonic stilbene markedly reduced the extracellular superoxide signal under control conditions, suggesting that a transmembrane flux of superoxide into the extracellular space may occur as part of normal redox signaling. The specificity of the electrode for superoxide released by cells in the hippocampus was verified by the exogenous addition of superoxide dismutase (SOD), which decreased the superoxide signal in a dose-dependent manner. Similar results were seen with the addition of the SOD mimetic cerium oxide nanoparticles (nanoceria), in that the superoxide anion radical scavenging activity of nanoceria with an average diameter of 15 nm was equivalent to 527 U of SOD for each 1 μg/ml of nanoceria added. This study demonstrates the potential of electrochemical biosensors for studying real-time dynamics of reactive oxygen species in a biological model and the utility of these measurements in defining the relative contribution of superoxide to oxidative injury. PMID:23085519
Ganesana, Mallikarjunarao; Erlichman, Joseph S.; Andreescu, Silvana
2012-01-01
The overproduction of reactive oxygen species and resulting damage are central to the pathology of many diseases. The study of the temporal and spatial accumulation of reactive oxygen species has been limited due to the lack of specific probes and techniques capable of continuous measurement. We demonstrate the use of a miniaturized electrochemical cytochrome C (Cyt C) biosensor for real-time measurements and quantitative assessment of superoxide production and inactivation by natural and engineered antioxidants in acutely prepared brain slices from mice. During control conditions, superoxide radicals produced from the hippocampal region of the brain in 400 μm thick sections were well within the range of detection of the electrode. Exposure of the slices to ischemic conditions increased the superoxide production two fold and measurements from the slices were stable over a 3–4 hour period. The stilbene derivative and anion channel inhibitor, 4,4′-diisothiocyano-2,2′-disulfonic stilbene (DIDS), markedly reduced the extracellular superoxide signal under control conditions suggesting that a transmembrane flux of superoxide into the extracellular space may occur as part of normal redox signaling. The specificity of the electrode for superoxide released by cells in the hippocampus was verified by the exogenous addition of superoxide dismutase (SOD) which decreased the superoxide signal in a dose-dependent manner. Similar results were seen with the addition of the SOD-mimetic, cerium oxide nanoparticles (nanoceria) where the superoxide anion radical scavenging activity of nanoceria with an average diameter of 15 nm was equivalent to 527 U of SOD for each 1 μg/ml of nanoceria added. This study demonstrates the potential of electrochemical biosensors for studying real-time dynamics of reactive oxygen species in a biological model and the utility of these measurements in defining the relative contribution of superoxide to oxidative injury. PMID:23085519
Mouse Activity across Time Scales: Fractal Scenarios
Lima, G. Z. dos Santos; Lobão-Soares, B.; do Nascimento, G. C.; França, Arthur S. C.; Muratori, L.; Ribeiro, S.; Corso, G.
2014-01-01
In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slow-wave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity - a typical 1/f complex pattern - while for large time intervals there is anti-correlation. High correlation of short intervals ( to : waking state and to : SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales ( to : waking state and to : SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anti-correlation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better
Leisure time activities of elementary school children.
Harrell, J S; Gansky, S A; Bradley, C B; McMurray, R G
1997-01-01
The three most common leisure time activities of 2,200 third and fourth grade children (mean age 8.8 + 0.8; 50.7% girls) and the association of the intensity levels of those activities with demographic variables and risk factors for cardiovascular disease are reported. Activities reported most often by boys were playing video games (33%), playing football (32%), bicycling (31%), watching television (28%), and playing basketball (26%). The girls reported doing homework (39%), bicycling (31%), watching television (30%), dancing (27%), and reading (23%). Overall, the children, especially girls, reported fairly sedentary activities, with an average metabolic equivalent level of 4.2 for girls and 4.8 for boys. Among boys, African Americans reported more vigorous activities than Whites, but the activities reported by White girls were somewhat more vigorous than those reported by non-White girls. Children from a higher socioeconomic status (SES), especially boys, reported a greater proportion of sedentary activities than lower SES children. The risk factors of cholesterol, blood pressure, skinfold thickness, and body mass index were not significantly associated with total activity score. However, significantly more nonobese than obese children reported a vigorous (high-intensity) activity as one of their top three activities.
A Model of Classical Space-Times.
ERIC Educational Resources Information Center
Maudlin, Tim
1989-01-01
Discusses some historically important reference systems including those by Newton, Leibniz, and Galileo. Provides models illustrating space-time relationship of the reference systems. Describes building models. (YP)
Liu, Jiamin; Udupa, Jayaram K
2009-04-01
Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks
Tanga, F Y; Raghavendra, V; DeLeo, J A
2004-01-01
Activated spinal glial cells have been strongly implicated in the development and maintenance of persistent pain states following a variety of stimuli including traumatic nerve injury. The present study was conducted to characterize the time course of surface markers indicative of microglial and astrocytic activation at the transcriptional level following an L5 nerve transection that results in behavioral hypersensitivity. Male Sprague-Dawley rats were divided into a normal group, a sham surgery group with an L5 spinal nerve exposure and an L5 spinal nerve transected group. Mechanical allodynia (heightened response to a non-noxious stimulus) of the ipsilateral hind paw was assessed throughout the study. Spinal lumbar mRNA levels of glial fibrillary acidic protein (GFAP), integrin alpha M (ITGAM), toll-like receptor 4 (TLR4) and cluster determinant 14 (CD14) were assayed using real-time reverse transcription polymerase chain reaction (RT-PCR) at 4 h, 1, 4, 7, 14 and 28 days post surgery. The spinal lumbar mRNA expression of ITGAM, TLR4, and CD14 was upregulated at 4 h post surgery, CD14 peaked 4 days after spinal nerve transection while ITGAM and TLR4 continued to increase until day 14 and returned to almost normal levels by postoperative day 28. In contrast, spinal GFAP mRNA did not significantly increase until postoperative day 4 and then continued to increase over the duration of the study. Our optimized real-time RT-PCR method was highly sensitive, specific and reproducible at a wide dynamic range. This study demonstrates that peripheral nerve injury induces an early spinal microglial activation that precedes astrocytic activation using mRNA for surface marker expression; the delayed but sustained expression of mRNA coding for GFAP implicates astrocytes in the maintenance phase of persistent pain states. In summary, these data demonstrate a distinct spinal glial response following nerve injury using real-time RT-PCR. PMID:15145554
Dynamic Factor Analysis Models with Time-Varying Parameters
ERIC Educational Resources Information Center
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian
2011-01-01
Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor model…
Mouse activity across time scales: fractal scenarios.
Lima, G Z dos Santos; Lobão-Soares, B; do Nascimento, G C; França, Arthur S C; Muratori, L; Ribeiro, S; Corso, G
2014-01-01
In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slowwave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity--a typical 1/f complex pattern--while for large time intervals there is anti-correlation. High correlation of short intervals (0.01 s to 2 s: waking state and 0.01 s to 0.1 s: SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales (30 s to 300 s: waking state and 0.3 s to 5 s: SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anticorrelation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep
Mathematical Models of Waiting Time.
ERIC Educational Resources Information Center
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Considered are several mathematical models that can be used to study different waiting situations. Problems involving waiting at a red light, bank, restaurant, and supermarket are discussed. A computer program which may be used with these problems is provided. (CW)
American Time Use Survey: Sleep Time and Its Relationship to Waking Activities
Basner, Mathias; Fomberstein, Kenneth M.; Razavi, Farid M.; Banks, Siobhan; William, Jeffrey H.; Rosa, Roger R.; Dinges, David F.
2007-01-01
Study Objectives: To gain some insight into how various behavioral (lifestyle) factors influence sleep duration, by investigation of the relationship of sleep time to waking activities using the American Time Use Survey (ATUS). Design: Cross-sectional data from ATUS, an annual telephone survey of a population sample of US citizens who are interviewed regarding how they spent their time during a 24-hour period between 04:00 on the previous day and 04:00 on the interview day. Participants: Data were pooled from the 2003, 2004, and 2005 ATUS databases involving N=47,731 respondents older than 14 years of age. Interventions: N/A Results: Adjusted multiple linear regression models showed that the largest reciprocal relationship to sleep was found for work time, followed by travel time, which included commute time. Only shorter than average sleepers (<7.5 h) spent more time socializing, relaxing, and engaging in leisure activities, while both short (<5.5 h) and long sleepers (≥8.5 h) watched more TV than the average sleeper. The extent to which sleep time was exchanged for waking activities was also shown to depend on age and gender. Sleep time was minimal while work time was maximal in the age group 45–54 yr, and sleep time increased both with lower and higher age. Conclusions: Work time, travel time, and time for socializing, relaxing, and leisure are the primary activities reciprocally related to sleep time among Americans. These activities may be confounding the frequently observed association between short and long sleep on one hand and morbidity and mortality on the other hand and should be controlled for in future studies. Citation: Basner M; Fomberstein KM; Razavi FM; Banks S; William JH; Rosa RR; Dinges DF. American time use survey: sleep time and its relationship to waking activities. SLEEP 2007;30(9):1085-1095. PMID:17910380
Models of Time Use in Paid and Unpaid Work
ERIC Educational Resources Information Center
Beaujot, Roderic; Liu, Jianye
2005-01-01
Models of time use need to consider especially the reproductive and productive activities of women and men. For husband-wife families, the breadwinner, one-earner, or complementary-roles model has advantages in terms of efficiency or specialization and stability; however, it is a high-risk model for women and children. The alternate model has been…
Deshpande, Laxmikant S.; Lou, Jeffrey K.; Mian, Ali; Blair, Robert E.; Sombati, Sompong; Attkisson, Elisa; DeLorenzo, Robert J.
2008-01-01
The hippocampus is especially vulnerable to seizure-induced damage and excitotoxic neuronal injury. This study examined the time course of neuronal death in relationship to seizure duration and the pharmacological mechanisms underlying seizure-induced cell death using low magnesium (Mg2+) induced continuous high frequency epileptiform discharges (in vitro status epilepticus) in hippocampal neuronal cultures. Neuronal death was assessed using cell morphology and Fluorescein diacetate-Propidium iodide staining. Effects of low Mg2+ and various receptor antagonists on spike frequency were assessed using patch clamp electrophysiology. We observed a linear and time-dependent increase in neuronal death with increasing durations of status epilepticus. This cell death was dependent upon extracellular calcium that entered primarily through the N-methyl-D-aspartate (NMDA) glutamate receptor channel subtype. Neuronal death was significantly decreased by co-incubation with the NMDA receptor antagonists and was also inhibited by reduction of extracellular calcium (Ca2+) during status epilepticus. In contrast, neuronal death from in vitro status epilepticus was not significantly prevented by inhibition of other glutamate receptor subtypes or voltage-gated Ca2+ channels. Interestingly this NMDA-Ca2+ dependent neuronal death was much more gradual in onset compared to cell death from excitotoxic glutamate exposure. The results provide evidence that in vitro status epilepticus results in increased activation of the NMDA-Ca2+ transduction pathway leading to neuronal death in a time dependent fashion. The results also indicate that there is a significant window of opportunity during the initial time of continuous seizure activity to be able to intervene, protect neurons and decrease the high morbidity and mortality associated with status epilepticus. PMID:18289526
Time-dependent oral absorption models
NASA Technical Reports Server (NTRS)
Higaki, K.; Yamashita, S.; Amidon, G. L.
2001-01-01
The plasma concentration-time profiles following oral administration of drugs are often irregular and cannot be interpreted easily with conventional models based on first- or zero-order absorption kinetics and lag time. Six new models were developed using a time-dependent absorption rate coefficient, ka(t), wherein the time dependency was varied to account for the dynamic processes such as changes in fluid absorption or secretion, in absorption surface area, and in motility with time, in the gastrointestinal tract. In the present study, the plasma concentration profiles of propranolol obtained in human subjects following oral dosing were analyzed using the newly derived models based on mass balance and compared with the conventional models. Nonlinear regression analysis indicated that the conventional compartment model including lag time (CLAG model) could not predict the rapid initial increase in plasma concentration after dosing and the predicted Cmax values were much lower than that observed. On the other hand, all models with the time-dependent absorption rate coefficient, ka(t), were superior to the CLAG model in predicting plasma concentration profiles. Based on Akaike's Information Criterion (AIC), the fluid absorption model without lag time (FA model) exhibited the best overall fit to the data. The two-phase model including lag time, TPLAG model was also found to be a good model judging from the values of sum of squares. This model also described the irregular profiles of plasma concentration with time and frequently predicted Cmax values satisfactorily. A comparison of the absorption rate profiles also suggested that the TPLAG model is better at prediction of irregular absorption kinetics than the FA model. In conclusion, the incorporation of a time-dependent absorption rate coefficient ka(t) allows the prediction of nonlinear absorption characteristics in a more reliable manner.
Connectionist and diffusion models of reaction time.
Ratcliff, R; Van Zandt, T; McKoon, G
1999-04-01
Two connectionist frameworks, GRAIN (J. L. McClelland, 1993) and brain-state-in-a-box (J. A. Anderson, 1991), and R. Ratcliff's (1978) diffusion model were evaluated using data from a signal detection task. Dependent variables included response probabilities, reaction times for correct and error responses, and shapes of reaction-time distributions. The diffusion model accounted for all aspects of the data, including error reaction times that had previously been a problem for all response-time models. The connectionist models accounted for many aspects of the data adequately, but each failed to a greater or lesser degree in important ways except for one model that was similar to the diffusion model. The findings advance the development of the diffusion model and show that the long tradition of reaction-time research and theory is a fertile domain for development and testing of connectionist assumptions about how decisions are generated over time.
Trajectory data analyses for pedestrian space-time activity study.
Qi, Feng; Du, Fei
2013-02-25
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission(1-3). An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data(4). Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an
Trajectory data analyses for pedestrian space-time activity study.
Qi, Feng; Du, Fei
2013-01-01
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission(1-3). An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data(4). Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an
Bootstrapping a time series model
Son, M.S.
1984-01-01
The bootstrap is a methodology for estimating standard errors. The idea is to use a Monte Carlo simulation experiment based on a nonparametric estimate of the error distribution. The main objective of this dissertation was to demonstrate the use of the bootstrap to attach standard errors to coefficient estimates and multi-period forecasts in a second-order autoregressive model fitted by least squares and maximum likelihood estimation. A secondary objective of this article was to present the bootstrap in the context of two econometric equations describing the unemployment rate and individual income tax in the state of Oklahoma. As it turns out, the conventional asymptotic formulae (both the least squares and maximum likelihood estimates) for estimating standard errors appear to overestimate the true standard errors. But there are two problems: 1) the first two observations y/sub 1/ and y/sub 2/ have been fixed, and 2) the residuals have not been inflated. After these two factors are considered in the trial and bootstrap experiment, both the conventional maximum likelihood and bootstrap estimates of the standard errors appear to be performing quite well. At present, there does not seem to be a good rule of thumb for deciding when the conventional asymptotic formulae will give acceptable results.
Modeling Electrically Active Viscoelastic Membranes
Roy, Sitikantha; Brownell, William E.; Spector, Alexander A.
2012-01-01
The membrane protein prestin is native to the cochlear outer hair cell that is crucial to the ear's amplification and frequency selectivity throughout the whole acoustic frequency range. The outer hair cell exhibits interrelated dimensional changes, force generation, and electric charge transfer. Cells transfected with prestin acquire unique active properties similar to those in the native cell that have also been useful in understanding the process. Here we propose a model describing the major electromechanical features of such active membranes. The model derived from thermodynamic principles is in the form of integral relationships between the history of voltage and membrane resultants as independent variables and the charge density and strains as dependent variables. The proposed model is applied to the analysis of an active force produced by the outer hair cell in response to a harmonic electric field. Our analysis reveals the mechanism of the outer hair cell active (isometric) force having an almost constant amplitude and phase up to 80 kHz. We found that the frequency-invariance of the force is a result of interplay between the electrical filtering associated with prestin and power law viscoelasticity of the surrounding membrane. Paradoxically, the membrane viscoelasticity boosts the force balancing the electrical filtering effect. We also consider various modes of electromechanical coupling in membrane with prestin associated with mechanical perturbations in the cell. We consider pressure or strains applied step-wise or at a constant rate and compute the time course of the resulting electric charge. The results obtained here are important for the analysis of electromechanical properties of membranes, cells, and biological materials as well as for a better understanding of the mechanism of hearing and the role of the protein prestin in this mechanism. PMID:22701528
Tajfirouze, E.; Reale, F.; Petralia, A.; Testa, P.
2016-01-01
Evidence of small amounts of very hot plasma has been found in active regions and might be an indication of impulsive heating released at spatial scales smaller than the cross-section of a single loop. We investigate the heating and substructure of coronal loops in the core of one such active region by analyzing the light curves in the smallest resolution elements of solar observations in two EUV channels (94 and 335 Å) from the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory. We model the evolution of a bundle of strands heated by a storm of nanoflares by means of a hydrodynamic 0D loop model (EBTEL). The light curves obtained from a random combination of those of single strands are compared to the observed light curves either in a single pixel or in a row of pixels, simultaneously in the two channels, and using two independent methods: an artificial intelligent system (Probabilistic Neural Network) and a simple cross-correlation technique. We explore the space of the parameters to constrain the distribution of the heat pulses, their duration, their spatial size, and, as a feedback on the data, their signatures on the light curves. From both methods the best agreement is obtained for a relatively large population of events (1000) with a short duration (less than 1 minute) and a relatively shallow distribution (power law with index 1.5) in a limited energy range (1.5 decades). The feedback on the data indicates that bumps in the light curves, especially in the 94 Å channel, are signatures of a heating excess that occurred a few minutes before.
NASA Astrophysics Data System (ADS)
Tajfirouze, E.; Reale, F.; Petralia, A.; Testa, P.
2016-01-01
Evidence of small amounts of very hot plasma has been found in active regions and might be an indication of impulsive heating released at spatial scales smaller than the cross-section of a single loop. We investigate the heating and substructure of coronal loops in the core of one such active region by analyzing the light curves in the smallest resolution elements of solar observations in two EUV channels (94 and 335 Å) from the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory. We model the evolution of a bundle of strands heated by a storm of nanoflares by means of a hydrodynamic 0D loop model (EBTEL). The light curves obtained from a random combination of those of single strands are compared to the observed light curves either in a single pixel or in a row of pixels, simultaneously in the two channels, and using two independent methods: an artificial intelligent system (Probabilistic Neural Network) and a simple cross-correlation technique. We explore the space of the parameters to constrain the distribution of the heat pulses, their duration, their spatial size, and, as a feedback on the data, their signatures on the light curves. From both methods the best agreement is obtained for a relatively large population of events (1000) with a short duration (less than 1 minute) and a relatively shallow distribution (power law with index 1.5) in a limited energy range (1.5 decades). The feedback on the data indicates that bumps in the light curves, especially in the 94 Å channel, are signatures of a heating excess that occurred a few minutes before.
Understanding human activity patterns based on space-time-semantics
NASA Astrophysics Data System (ADS)
Huang, Wei; Li, Songnian
2016-11-01
Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.
Space time ETAS models and an improved extension
NASA Astrophysics Data System (ADS)
Ogata, Yosihiko; Zhuang, Jiancang
2006-02-01
For sensitive detection of anomalous seismicity such as quiescence and activation in a given region, we need a suitable statistical reference model that represents a normal seismic activity in the region. The regional occurrence rate of the earthquakes is modeled as a function of previous activity, the specific form of which is based on empirical laws in time and space such as the modified Omori formula and the Utsu-Seki scaling law of aftershock area against magnitude, respectively. This manuscript summarizes the development of the epidemic type aftershock sequence (ETAS) model and proposes an extended version of the best fitted space-time model that was suggested in Ogata [Ogata, Y., 1998. Space-time point-process models for earthquake occurrences, Ann. Inst. Statist. Math., 50: 379-402.]. This model indicates significantly better fit to seismicity in various regions in and around Japan.
Planning in time - Windows and durations for activities and goals
NASA Technical Reports Server (NTRS)
Vere, S. A.
1983-01-01
The present general purpose automated planner/scheduler generates parallel plans aimed at the achievement of goals having imposed time constraints, with both durations and start time windows being specifiable for sets of goal conditions. Deterministic durations of such parallel plan activities as actions, events triggered by circumstances, inferences, and scheduled events entirely outside the actor's control, are explicitly modeled and may be any computable function of the activity variables. The final plan network resembles a PERT chart. Examples are given from the traditional 'blocksworld', and from a realistic 'Spaceworld' in which an autonomous spacecraft photographs objects in deep space and transmits the information to earth.
REAL TIME DATA FOR REMEDIATION ACTIVITIES [11505
BROCK CT
2011-01-13
Health physicists from the CH2M HILL Plateau Remediation Company collaborated with Berkeley Nucleonics Corporation to modify the SAM 940 isotope identifier instrument to be used for nuclear waste remediation. These modifications coupled with existing capabilities of the SAM 940 have proven to be invaluable during remediation activities, reducing disposal costs by allowing swift remediation of targeted areas that have been identified as having isotopes of concern (IOC), and eliminating multiple visits to sites by declaring an excavation site clear of IOCs before demobilizing from the site. These advantages are enabled by accumulating spectral data for specific isotopes that is nearly 100 percent free of false positives, which are filtered out in 'real time.'
1995-01-01
The aggregation states of the epidermal growth factor receptor (EGFR) on single A431 human epidermoid carcinoma cells were assessed with two new techniques for determining fluorescence resonance energy transfer: donor photobleaching fluorescence resonance energy transfer (pbFRET) microscopy and fluorescence lifetime imaging microscopy (FLIM). Fluorescein-(donor) and rhodamine-(acceptor) labeled EGF were bound to the cells and the extent of oligomerization was monitored by the spatially resolved FRET efficiency as a function of the donor/acceptor ratio and treatment conditions. An average FRET efficiency of 5% was determined after a low temperature (4 degrees C) incubation with the fluorescent EGF analogs for 40 min. A subsequent elevation of the temperature for 5 min caused a substantial increase of the average FRET efficiency to 14% at 20 degrees C and 31% at 37 degrees C. In the context of a two-state (monomer/dimer) model for the EGFR, these FRET efficiencies were consistent with minimal average receptor dimerizations of 13, 36, and 69% at 4, 20, and 37 degrees C, respectively. A431 cells were pretreated with the monoclonal antibody mAb 2E9 that specifically blocks EGF binding to the predominant population of low affinity EGFR (15). The average FRET efficiency increased dramatically to 28% at 4 degrees C, indicative of a minimal receptor dimerization of 65% for the subpopulation of high affinity receptors. These results are in accordance with prior studies indicating that binding of EGF leads to a fast and temperature- dependent microclustering of EGFR, but suggest in addition that the high affinity functional subclass of receptors on quiescent A431 cells are present in a predimerized or oligomerized state. We propose that the transmission of the external ligand-binding signal to the cytoplasmic domain is effected by a concerted relative rotational rearrangement of the monomeric units comprising the dimeric receptor, thereby potentiating a mutual activation of
System-time entanglement in a discrete-time model
NASA Astrophysics Data System (ADS)
Boette, A.; Rossignoli, R.; Gigena, N.; Cerezo, M.
2016-06-01
We present a model of discrete quantum evolution based on quantum correlations between the evolving system and a reference quantum clock system. A quantum circuit for the model is provided, which in the case of a constant Hamiltonian is able to represent the evolution over 2n time steps in terms of just n time qubits and n control gates. We then introduce the concept of system-time entanglement as a measure of distinguishable quantum evolution, based on the entanglement between the system and the reference clock. This quantity vanishes for stationary states and is maximum for systems jumping onto a new orthogonal state at each time step. In the case of a constant Hamiltonian leading to a cyclic evolution it is a measure of the spread over distinct energy eigenstates and satisfies an entropic energy-time uncertainty relation. The evolution of mixed states is also examined. Analytical expressions for the basic case of a qubit clock, as well as for the continuous limit in the evolution between two states, are provided.
Modeling algorithm execution time on processor arrays
NASA Technical Reports Server (NTRS)
Adams, L. M.; Crockett, T. W.
1984-01-01
An approach to modelling the execution time of algorithms on parallel arrays is presented. This time is expressed as a function of the number of processors and system parameters. The resulting model has been applied to a parallel implementation of the conjugate-gradient algorithm on NASA's FEM. Results of experiments performed to compare the model predictions against actual behavior show that the floating-point arithmetic, communication, and synchronization components of the parallel algorithm execution time were correctly modelled. The results also show that the overhead caused by the interaction of the system software and the actual parallel hardware must be reflected in the model parameters. The model has been used to predict the performance of the conjugate gradient algorithm on a given problem as the number of processors and machine characteristics varied.
Lee, Rebecca E; King, Abby C
2003-01-01
Investigation goals were to document discretionary time activities among older adults, determine whether time spent in discretionary activities varied by gender, and investigate whether participation in a prescribed physical activity (P) intervention increased the time that older adults spend in discretionary time physical activities that were not specifically prescribed by interventions. Longitudinal data were drawn from 2 published studies of older adults. Study 1 compared 2 PA interventions in healthy older men and women (N = 103, M =70.2 years), and Study 2 compared a PA intervention with a nutrition intervention in healthy older women (N =93, M =63.1 years). Participants in both studies completed similar assessments of their discretionary time activities using the Community Healthy Activities Model Program for Seniors questionnaire. Across both studies, at baseline, over 95% of participants reported talking on the telephone and reading as frequent sedentary discretionary time activities; over 80% reported visiting with friends and watching television or listening to the radio. Women engaged in significantly greater hours of social activities and household maintenance activities than did men (p <.05). From baseline to 12-month posttest, social, recreational, and household activities remained stable by gender and across time after participating in a PA intervention. Despite previously documented 2- to 3-hr increases in physical activities occurring in response to the study interventions, increases did not generalize for most participants to activities not prescribed by the intervention. Older adults are participating in numerous sedentary social and recreational activities that appear to remain stable across time and in the face of PA intervention prescriptions. PMID:12704013
Ionospheric Electron Density during Magnetically Active Times over Istanbul
NASA Astrophysics Data System (ADS)
Naz Erbaş, Bute; Kaymaz, Zerefsan; Ceren Moral, Aysegul; Emine Ceren Kalafatoglu Eyiguler, R. A..
2016-07-01
In this study, we analyze electron density variations over Istanbul using Dynasonde observations during the magnetically active times. In order to perform statistical analyses, we first determined magnetic storms and magnetospheric substorm intervals from October 2012 to October 2015 using Kyoto's magnetic index data. Corresponding ionospheric parameters, such as critical frequency of F2 region (foF2), maximum electron density height (hmF2), total electron density (TEC) etc. were retrieved from Dynasonde data base at Istanbul Technical University's Space Weather Laboratory. To understand the behavior of electron density during the magnetically active times, we remove the background quiet time variations first and then quantify the anomalies. In this presentation, we will report results from our preliminary analyses from the selected cases corresponding to the strong magnetic storms. Initial results show lower electron densities at noon times and higher electron densities in the late afternoon toward sunset times when compared to the electron densities of magnetically quiet times. We also compare the results with IRI and TIEGCM ionospheric models in order to understand the physical and dynamical causes of these variations. During the presentation we will also discuss the role of these changes during the magnetically active times on the GPS communications through ionosphere.
Modeling approaches for active systems
NASA Astrophysics Data System (ADS)
Herold, Sven; Atzrodt, Heiko; Mayer, Dirk; Thomaier, Martin
2006-03-01
To solve a wide range of vibration problems with the active structures technology, different simulation approaches for several models are needed. The selection of an appropriate modeling strategy is depending, amongst others, on the frequency range, the modal density and the control target. An active system consists of several components: the mechanical structure, at least one sensor and actuator, signal conditioning electronics and the controller. For each individual part of the active system the simulation approaches can be different. To integrate the several modeling approaches into an active system simulation and to ensure a highly efficient and accurate calculation, all sub models must harmonize. For this purpose, structural models considered in this article are modal state-space formulations for the lower frequency range and transfer function based models for the higher frequency range. The modal state-space formulations are derived from finite element models and/or experimental modal analyses. Consequently, the structure models which are based on transfer functions are directly derived from measurements. The transfer functions are identified with the Steiglitz-McBride iteration method. To convert them from the z-domain to the s-domain a least squares solution is implemented. An analytical approach is used to derive models of active interfaces. These models are transferred into impedance formulations. To couple mechanical and electrical sub-systems with the active materials, the concept of impedance modeling was successfully tested. The impedance models are enhanced by adapting them to adequate measurements. The controller design strongly depends on the frequency range and the number of modes to be controlled. To control systems with a small number of modes, techniques such as active damping or independent modal space control may be used, whereas in the case of systems with a large number of modes or with modes that are not well separated, other control
Privileging physical activity over healthy eating: 'Time' to Choose?
Chircop, Andrea; Shearer, Cindy; Pitter, Robert; Sim, Meaghan; Rehman, Laurene; Flannery, Meredith; Kirk, Sara
2015-09-01
Physical activity and healthy eating have long been promoted as key strategies in tackling the 'wicked problem' of obesity. Both practices are assumed to go hand-in-hand, but whether one dominates the other has largely remained unexamined. Moreover, time, a dimension beyond the socio-ecological model, is a critical factor of families' busy lives, but related challenges are rarely articulated. We conducted 47 family interviews as part of a mixed methods study examining environmental influences on youth obesity in Nova Scotia, Eastern Canada. Participants were recruited from six schools at the junior high school level (grades 7-9; age range 12-14 years) based on location (urban, suburban and rural) and neighborhood socioeconomic status (high and low socioeconomic status). Time pressure to meet the demands associated with scheduled physical activity for youth was the dominant theme across interviews from all neighborhoods. Physical activity and healthy eating were valued differently, with greater value placed on physical activity than healthy eating. The pressure to engage youth in organized physical activity appeared to outweigh the importance of healthy eating, which led to neglecting family meals at home and consuming fast food and take out options. Our findings further reinforce the need to move beyond the socio-ecological model and integrate critical dimensions such as 'time', its challenges and opportunities, to allow for a more nuanced understanding of contemporary healthy living. It appears 'timely' to focus on healthy public policy in support of families, instead of unwittingly supporting a fast food industry that profits from time-pressured families.
NASA Astrophysics Data System (ADS)
Smith, D. E.; Minson, S. E.; Langbein, J. O.; Murray, J. R.; Guillemot, C.
2014-12-01
Currently implemented Earthquake Early Warning (EEW) algorithms based on seismic data alone should provide the most robust warnings for most M<6 earthquakes, since real-time GPS positions are too noisy to aid in EEW. However, for larger events, which generate larger fault offsets, GPS data can provide a direct on-scale displacement measurements and has sufficient precision. In such situations, the GPS observations may enable more accurate estimation of magnitude and rupture extent than seismic data. The USGS Earthquake Science Center in Menlo Park currently obtains real-time data from approximately 100 GNSS stations in northern California. These stations, which span the San Andreas fault system from the Mendocino Triple Junction to San Juan Bautista, are operated by USGS-Menlo Park, UC Berkeley, and UNAVCO. We have developed software tools for monitoring and troubleshooting data acquisition and quality. We have evaluated the latency and precision of position estimates obtained through real-time processing and we have found these results satisfactory for EEW. We are now implementing the BEFORES algorithm (Minson et al., 2014) that uses Bayesian analysis to determine the best-fitting coseismic fault orientation and finite fault slip distribution (from which moment and rupture extent are obtained) in real-time. BEFORES has been tested extensively on both simulated and real data (retrospectively) for a variety of earthquakes. We are now focusing on three aspects of its implementation: 1) receiving real-time earthquake locations from independent seismic EEW algorithms, that are obtained through multiple TCP/IP connections, and 3) optimizing the computation of elastic Green's functions. Completion of these tasks plus additional tests using simulated waveforms of earthquakes displacements superimposed on actual data will prepare the algorithm for implementation in the West Coast EEW system.
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience. PMID:24808226
Real time wave forecasting using wind time history and numerical model
NASA Astrophysics Data System (ADS)
Jain, Pooja; Deo, M. C.; Latha, G.; Rajendran, V.
Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired.
Time-varying modeling of cerebral hemodynamics.
Marmarelis, Vasilis Z; Shin, Dae C; Orme, Melissa; Rong Zhang
2014-03-01
The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields "time-averaged models" of physiological and clinical utility.
Modeling Cytoskeletal Active Matter Systems
NASA Astrophysics Data System (ADS)
Blackwell, Robert
Active networks of filamentous proteins and crosslinking motor proteins play a critical role in many important cellular processes. One of the most important microtubule-motor protein assemblies is the mitotic spindle, a self-organized active liquid-crystalline structure that forms during cell division and that ultimately separates chromosomes into two daughter cells. Although the spindle has been intensively studied for decades, the physical principles that govern its self-organization and function remain mysterious. To evolve a better understanding of spindle formation, structure, and dynamics, I investigate course-grained models of active liquid-crystalline networks composed of microtubules, modeled as hard spherocylinders, in diffusive equilibrium with a reservoir of active crosslinks, modeled as hookean springs that can adsorb to microtubules and and translocate at finite velocity along the microtubule axis. This model is investigated using a combination of brownian dynamics and kinetic monte carlo simulation. I have further refined this model to simulate spindle formation and kinetochore capture in the fission yeast S. pombe. I then make predictions for experimentally realizable perturbations in motor protein presence and function in S. pombe.
Using online lectures to make time for active learning.
Prunuske, Amy J; Batzli, Janet; Howell, Evelyn; Miller, Sarah
2012-09-01
To make time in class for group activities devoted to critical thinking, we integrated a series of short online lectures into the homework assignments of a large, introductory biology course at a research university. The majority of students viewed the online lectures before coming to class and reported that the online lectures helped them to complete the in-class activity and did not increase the amount of time they devoted to the course. In addition, students who viewed the online lecture performed better on clicker questions designed to test lower-order cognitive skills. The in-class activities then gave the students practice analyzing the information in groups and provided the instructor with feedback about the students' understanding of the material. On the basis of the results of this study, we support creating hybrid course models that allow students to learn the fundamental information outside of class time, thereby creating time during the class period to be dedicated toward the conceptual understanding of the material.
A Ballistic Model of Choice Response Time
ERIC Educational Resources Information Center
Brown, Scott; Heathcote, Andrew
2005-01-01
Almost all models of response time (RT) use a stochastic accumulation process. To account for the benchmark RT phenomena, researchers have found it necessary to include between-trial variability in the starting point and/or the rate of accumulation, both in linear (R. Ratcliff & J. N. Rouder, 1998) and nonlinear (M. Usher & J. L. McClelland, 2001)…
Accelerated Failure-Time Models of Graduation
ERIC Educational Resources Information Center
Chimka, Justin R.; Wang, Qilu
2009-01-01
This third article in a series describing survival analysis of engineering student retention and graduation introduces accelerated failure-time as an alternative to the Cox proportional hazards model to the context of student data. The new survival analysis of graduation data presented here assumes different distributions including exponential,…
Time-Varying Modeling of Cerebral Hemodynamics
Marmarelis, Vasilis Z.; Shin, Dae C.; Orme, Melissa; Zhang, Rong
2014-01-01
The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, Cerebral Flow Autoregulation (CFA) and CO2 Vasomotor Reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, MCI, Alzheimer’s disease and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e. changes in cerebrovascular characteristics) due to neural, endocrine and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from 10 healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields “time-averaged models” of physiological and clinical utility. PMID:24184697
Active euthanasia--time for a decision.
Jeffrey, D
1994-01-01
There has been renewed interest in the moral arguments surrounding euthanasia. Some patients are now apprehensive of advanced medical technology which they fear may result in a prolonged and undignified death. In the current situation of scarce resources for health care, both patients and doctors could be coerced into considering active euthanasia if it was legally available. In this paper it is argued that doctors now need to make a clear statement rejecting active euthanasia but affirming that in certain cases passive euthanasia, or letting die, may be morally justifiable. PMID:8204323
Time models and cognitive processes: a review
Maniadakis, Michail; Trahanias, Panos
2014-01-01
The sense of time is an essential capacity of humans, with a major role in many of the cognitive processes expressed in our daily lifes. So far, in cognitive science and robotics research, mental capacities have been investigated in a theoretical and modeling framework that largely neglects the flow of time. Only recently there has been a rather limited, but constantly increasing interest in the temporal aspects of cognition, integrating time into a range of different models of perceptuo-motor capacities. The current paper aims to review existing works in the field and suggest directions for fruitful future work. This is particularly important for the newly developed field of artificial temporal cognition that is expected to significantly contribute in the development of sophisticated artificial agents seamlessly integrated into human societies. PMID:24578690
Haida Story Telling Time with Activity Folder.
ERIC Educational Resources Information Center
Cogo, Robert
One in a series of curriculum materials on Southeast Alaska Natives, this booklet contains seven myths and legends from the Haida oral tradition, each accompanied by discussion questions and suggested learning activities. Intended for use in the intermediate grades, the stories are two to four pages long with many Haida words included in the text…
Turnaround Time Modeling for Conceptual Rocket Engines
NASA Technical Reports Server (NTRS)
Nix, Michael; Staton, Eric J.
2004-01-01
Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.
NASA Astrophysics Data System (ADS)
Jiang, Chaowei; Feng, Xueshang; Wu, S. T.; Hu, Qiang
2012-11-01
We apply a data-driven magnetohydrodynamics (MHD) model to investigate the three-dimensional (3D) magnetic field of NOAA active region (AR) 11117 around the time of a C-class confined flare that occurred on 2010 October 25. The MHD model, based on the spacetime conservation-element and solution-element scheme, is designed to focus on the magnetic field evolution and to consider a simplified solar atomsphere with finite plasma β. Magnetic vector-field data derived from the observations at the photosphere is inputted directly to constrain the model. Assuming that the dynamic evolution of the coronal magnetic field can be approximated by successive equilibria, we solve a time sequence of MHD equilibria based on a set of vector magnetograms for AR 11117 taken by the Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory around the time of the flare. The model qualitatively reproduces the basic structures of the 3D magnetic field, as supported by the visual similarity between the field lines and the coronal loops observed by the Atmospheric Imaging Assembly, which shows that the coronal field can indeed be well characterized by the MHD equilibrium in most cases. The magnetic configuration changes very little during the studied time interval of 2 hr. A topological analysis reveals that the small flare is correlated with a bald patch (BP, where the magnetic field is tangent to the photosphere), suggesting that the energy release of the flare can be understood by magnetic reconnection associated with the BP separatrices. The total magnetic flux and energy keep increasing slightly in spite of the flare, while the computed magnetic free energy drops during the flare by ~1030 erg, which seems to be adequate in providing the energy budget of a minor C-class confined flare.
Jiang Chaowei; Feng Xueshang; Wu, S. T.; Hu Qiang E-mail: fengx@spaceweather.ac.cn E-mail: qh0001@uah.edu
2012-11-10
We apply a data-driven magnetohydrodynamics (MHD) model to investigate the three-dimensional (3D) magnetic field of NOAA active region (AR) 11117 around the time of a C-class confined flare that occurred on 2010 October 25. The MHD model, based on the spacetime conservation-element and solution-element scheme, is designed to focus on the magnetic field evolution and to consider a simplified solar atomsphere with finite plasma {beta}. Magnetic vector-field data derived from the observations at the photosphere is inputted directly to constrain the model. Assuming that the dynamic evolution of the coronal magnetic field can be approximated by successive equilibria, we solve a time sequence of MHD equilibria based on a set of vector magnetograms for AR 11117 taken by the Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory around the time of the flare. The model qualitatively reproduces the basic structures of the 3D magnetic field, as supported by the visual similarity between the field lines and the coronal loops observed by the Atmospheric Imaging Assembly, which shows that the coronal field can indeed be well characterized by the MHD equilibrium in most cases. The magnetic configuration changes very little during the studied time interval of 2 hr. A topological analysis reveals that the small flare is correlated with a bald patch (BP, where the magnetic field is tangent to the photosphere), suggesting that the energy release of the flare can be understood by magnetic reconnection associated with the BP separatrices. The total magnetic flux and energy keep increasing slightly in spite of the flare, while the computed magnetic free energy drops during the flare by {approx}10{sup 30} erg, which seems to be adequate in providing the energy budget of a minor C-class confined flare.
Nonlinear time reversal of classical waves: experiment and model.
Frazier, Matthew; Taddese, Biniyam; Xiao, Bo; Antonsen, Thomas; Ott, Edward; Anlage, Steven M
2013-12-01
We consider time reversal of electromagnetic waves in a closed, wave-chaotic system containing a discrete, passive, harmonic-generating nonlinearity. An experimental system is constructed as a time-reversal mirror, in which excitations generated by the nonlinearity are gathered, time-reversed, transmitted, and directed exclusively to the location of the nonlinearity. Here we show that such nonlinear objects can be purely passive (as opposed to the active nonlinearities used in previous work), and we develop a higher data rate exclusive communication system based on nonlinear time reversal. A model of the experimental system is developed, using a star-graph network of transmission lines, with one of the lines terminated by a model diode. The model simulates time reversal of linear and nonlinear signals, demonstrates features seen in the experimental system, and supports our interpretation of the experimental results.
Recent improvements in modeling time limited search
NASA Astrophysics Data System (ADS)
Edwards, Timothy; Vollmerhausen, Richard H.; Cohen, Jeremy; Harris, Tim
2002-07-01
Human perception tests have been performed by Night Vision Electronic Sensor Directorate (NVESD) addressing the process of searching an image with the intent of detecting a target of military importance. Experiments were performed using both real thermal imagery and synthetic imagery generated using 'Paint the Night' simulation. It was demonstrated that trained observers acquire targets much more quickly than previously expected. This insight was gained by changing the instructions the observers were given for the test. Rather than telling the observers that they were being timed, the observers were given a time limit, as short as 3 seconds. When time limited, the observers found targets quicker. Although false alarms per second increased with the shorter time limits, the ratio of false alarms to detected targets did not increase. A modification to the traditional NVESD search model has been developed and incorporated into Army war games and simulations.
Reading Time as Evidence for Mental Models in Understanding Physics
NASA Astrophysics Data System (ADS)
Brookes, David T.; Mestre, José; Stine-Morrow, Elizabeth A. L.
2007-11-01
We present results of a reading study that show the usefulness of probing physics students' cognitive processing by measuring reading time. According to contemporary discourse theory, when people read a text, a network of associated inferences is activated to create a mental model. If the reader encounters an idea in the text that conflicts with existing knowledge, the construction of a coherent mental model is disrupted and reading times are prolonged, as measured using a simple self-paced reading paradigm. We used this effect to study how "non-Newtonian" and "Newtonian" students create mental models of conceptual systems in physics as they read texts related to the ideas of Newton's third law, energy, and momentum. We found significant effects of prior knowledge state on patterns of reading time, suggesting that students attempt to actively integrate physics texts with their existing knowledge.
Time-resolved microrheology of actively remodeling actomyosin networks
NASA Astrophysics Data System (ADS)
Silva, Marina Soares e.; Stuhrmann, Björn; Betz, Timo; Koenderink, Gijsje H.
2014-07-01
Living cells constitute an extraordinary state of matter since they are inherently out of thermal equilibrium due to internal metabolic processes. Indeed, measurements of particle motion in the cytoplasm of animal cells have revealed clear signatures of nonthermal fluctuations superposed on passive thermal motion. However, it has been difficult to pinpoint the exact molecular origin of this activity. Here, we employ time-resolved microrheology based on particle tracking to measure nonequilibrium fluctuations produced by myosin motor proteins in a minimal model system composed of purified actin filaments and myosin motors. We show that the motors generate spatially heterogeneous contractile fluctuations, which become less frequent with time as a consequence of motor-driven network remodeling. We analyze the particle tracking data on different length scales, combining particle image velocimetry, an ensemble analysis of the particle trajectories, and finally a kymograph analysis of individual particle trajectories to quantify the length and time scales associated with active particle displacements. All analyses show clear signatures of nonequilibrium activity: the particles exhibit random motion with an enhanced amplitude compared to passive samples, and they exhibit sporadic contractile fluctuations with ballistic motion over large (up to 30 μm) distances. This nonequilibrium activity diminishes with sample age, even though the adenosine triphosphate level is held constant. We propose that network coarsening concentrates motors in large clusters and depletes them from the network, thus reducing the occurrence of contractile fluctuations. Our data provide valuable insight into the physical processes underlying stress generation within motor-driven actin networks and the analysis framework may prove useful for future microrheology studies in cells and model organisms.
Modeling stylized facts for financial time series
NASA Astrophysics Data System (ADS)
Krivoruchenko, M. I.; Alessio, E.; Frappietro, V.; Streckert, L. J.
2004-12-01
Multivariate probability density functions of returns are constructed in order to model the empirical behavior of returns in a financial time series. They describe the well-established deviations from the Gaussian random walk, such as an approximate scaling and heavy tails of the return distributions, long-ranged volatility-volatility correlations (volatility clustering) and return-volatility correlations (leverage effect). The model is tested successfully to fit joint distributions of the 100+ years of daily price returns of the Dow Jones 30 Industrial Average.
Modeling Activities in Earth Science
NASA Astrophysics Data System (ADS)
Malone, Kathy
2014-05-01
Students usually find science to be quite abstract. This is especially true of disciplines like Earth Science where it is difficult for the students to conduct and design hands-on experiments in areas such as Plate Tectonics that would allow them to develop predictive models. In the United States the new Next Generation Science Standards explicitly requires students to experience the science disciplines via modeling based activities. This poster presentation will discuss an activity that demonstrates how modeling, plate tectonics and student discourse converge in the earth science classroom. The activities featured on the poster will include using cardboard and shaving cream to demonstrate convergent plate boundaries, a Milky Way candy bar to demonstrate divergent boundaries and silly putty to demonstrate a strike slip boundary. I will discuss how students report back to the group about the findings from the lab and the techniques that can be used to heighten the student discourse. The activities outlined in this poster were originally designed for a middle school Earth Science class by Suzi Shoemaker for a graduate thesis at Arizona State University.
Time perspective and physical activity among central Appalachian adolescents.
Gulley, Tauna
2013-04-01
Time perspective is a cultural behavioral concept that reflects individuals' orientations or attitudes toward the past, present, or future. Individuals' time perspectives influence their choices regarding daily activities. Time perspective is an important consideration when teaching adolescents about the importance of being physically active. However, little is known about the relationship between time perspective and physical activity among adolescents. The purpose of this study was to determine the time perspective of central Appalachian adolescents and explore the relationship between time perspective and physical activity. This study was guided by The theory of planned behavior (TPB). One hundred and ninety-three students completed surveys to examine time perspective and physical activity behaviors. Data were collected in one school. Results of this study can inform school nurses and high school guidance counselors about the importance of promoting a future-oriented time perspective to improve physical activity and educational outcomes.
Testing Bayesian models of human coincidence timing.
Miyazaki, Makoto; Nozaki, Daichi; Nakajima, Yasoichi
2005-07-01
A sensorimotor control task often requires an accurate estimation of the timing of the arrival of an external target (e.g., when hitting a pitched ball). Conventional studies of human timing processes have ignored the stochastic features of target timing: e.g., the speed of the pitched ball is not generally constant, but is variable. Interestingly, based on Bayesian theory, it has been recently shown that the human sensorimotor system achieves the optimal estimation by integrating sensory information with prior knowledge of the probabilistic structure of the target variation. In this study, we tested whether Bayesian integration is also implemented while performing a coincidence-timing type of sensorimotor task by manipulating the trial-by-trial variability (i.e., the prior distribution) of the target timing. As a result, within several hundred trials of learning, subjects were able to generate systematic timing behavior according to the width of the prior distribution, as predicted by the optimal Bayesian model. Considering the previous studies showing that the human sensorimotor system uses Bayesian integration in spacing and force-grading tasks, our result indicates that Bayesian integration is fundamental to all aspects of human sensorimotor control. Moreover, it was noteworthy that the subjects could adjust their behavior both when the prior distribution was switched from wide to narrow and vice versa, although the adjustment was slower in the former case. Based on a comparison with observations in a previous study, we discuss the flexibility and adaptability of Bayesian sensorimotor learning.
Real-time Models at the Community Coordinated Modeling Center and their Capabilities
NASA Technical Reports Server (NTRS)
Hesse, Michael
2006-01-01
Real-time models at the Community Coordinated Modeling Center and their capabilities The Community Coordinated Modeling Center serves both scientific research and space weather operations communities through access to and evaluation of modern space environment models. Critical to both objectives is an unbiased assessment of model capabilities, which includes scientific validity, performance verification, and model robustness. While all of these assessments are relevant to operational customers, the latter plays a particularly important role. For this reason, as well as for testing model validity, CCMC established a set of fully automated real-time execution systems, which are based on models provided by the research community. This presentation will provide a summary of these activities, and a report on experiences and model validity. Finally, this presentation will invite feedback from CCMC customers regarding future directions of real time modeling at CCMC.
Modeling utilization distributions in space and time
Keating, K.A.; Cherry, S.
2009-01-01
W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r - 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep {Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed. ?? 2009 by the Ecological Society of America.
Modeling atmospheric O 2 over Phanerozoic time
NASA Astrophysics Data System (ADS)
Berner, R. A.
2001-03-01
A carbon and sulfur isotope mass balance model has been constructed for calculating the variation of atmospheric O 2 over Phanerozoic time. In order to obtain realistic O 2 levels, rapid sediment recycling and O 2-dependent isotope fractionation have been employed by the modelling. The dependence of isotope fractionation on O 2 is based, for carbon, on the results of laboratory photosynthesis experiments and, for sulfur, on the observed relation between oxidation/reduction recycling and S-isotope fractionation during early diagenetic pyrite formation. The range of fractionations used in the modeling agree with measurements of Phanerozoic sediments by others. Results, derived from extensive sensitivity analysis, suggest that there was a positive excursion of O 2 to levels as high as 35% during the Permo-Carboniferous. High O 2 at this time agrees with independent modeling, based on the abundances of organic matter and pyrite in sediments, and with the occurrence of giant insects during this period. The cause of the excursion is believed to be the rise of vascular land plants and the consequent increased production of O 2 by the burial in sediments of lignin-rich organic matter that was resistant to biological decomposition.
Modeling gene expression in time and space.
Rué, Pau; Garcia-Ojalvo, Jordi
2013-01-01
Cell populations rarely exhibit gene-expression profiles that are homogeneous in time and space. In the temporal domain, dynamical behaviors such as oscillations and pulses of protein production pervade cell biology, underlying phenomena as diverse as circadian rhythmicity, cell cycle control, stress and damage responses, and stem-cell pluripotency. In multicellular populations, spatial heterogeneities are crucial for decision making and development, among many other functions. Cells need to exquisitely coordinate this temporal and spatial variation to survive. Although the spatiotemporal character of gene expression is challenging to quantify experimentally at the level of individual cells, it is beneficial from the modeling viewpoint, because it provides strong constraints that can be probed by theoretically analyzing mathematical models of candidate gene and protein circuits. Here, we review recent examples of temporal dynamics and spatial patterning in gene expression to show how modeling such phenomenology can help us unravel the molecular mechanisms of cellular function.
How Young Children Spend Their Time: Television and Other Activities.
ERIC Educational Resources Information Center
Huston, Aletha C.; Wright, John C.; Marquis, Janet; Green, Samuel B.
1999-01-01
Examined television viewing over three years among two cohorts of 2- and 4-year olds. Found that viewing declined with age. With age, time in reading and educational activities increased on weekdays but declined on weekends, and sex differences in time-use patterns increased. Increased time in educational activities, social interaction, and video…
SMART: a system supporting medical activities in real-time.
Pisanelli, D M; Consorti, F; Merialdo, P
1997-01-01
This paper describes the system SMART whose goal is real-time assistance to physicians who execute diagnostic or therapeutic protocols in a clinical context. SMART is able to retrieve a protocol from its knowledge base and to monitor its execution step by step for a single patient. Different protocols for different patients can be followed at the same time in a health care structure. The prototype realized supports the execution of protocols for evaluating surgical risks. It has been implemented according to the specifications given by the 4th Surgical Clinic of "Policlinico Umberto I" and reflects the activities actually performed in that hospital. However, the protocol model defined is general purpose and we envisage an easy application to other contexts and therefore to the informatization of other protocols.
Time Dependence of Joy's Law for Emerging Active Regions
NASA Astrophysics Data System (ADS)
Chintzoglou, Georgios; Zhang, J.; Liu, Y.
2013-07-01
Joy's law governs the tilt of Active Regions (ARs) with respect to their absolute heliographic latitude. Together with Hale's law of hemispheric polarity, it is essential in constraining solar dynamo models. However, previous studies on Joy's law show only a weak positive trend between AR tilt angles and latitudes. In this study, we are focusing on the time dependence of Joy's law, for the cases of emerging ARs of Solar Cycle 24. We selected 40 ARs that emerge on the East hemisphere, effectively maximizing the observing time for each AR. Then, by converting the helioprojective maps into heliographic, we determine the geometrical as well as the magnetic-flux-weighted centroids for each emergence case. That way we are able to track the temporal evolution of their physical properties, including locations, fluxes of positive and negative polarities, as well as the tilt angles of these regions in a continuous manner until emergence stops and the ARs assume their final state.
Cardiac anisotropy: is it negligible regarding noninvasive activation time imaging?
Modre, Robert; Seger, Michael; Fischer, Gerald; Hintermüller, Christoph; Hayn, Dieter; Pfeifer, Bernhard; Hanser, Friedrich; Schreier, Günter; Tilg, Bernhard
2006-04-01
The aim of this study was to quantify the effect of cardiac anisotropy in the activation-based inverse problem of electrocardiography. Differences of the patterns of simulated body surface potential maps for isotropic and anisotropic conditions were investigated with regard to activation time (AT) imaging of ventricular depolarization. AT maps were estimated by solving the nonlinear inverse ill-posed problem employing spatio-temporal regularization. Four different reference AT maps (sinus rhythm, right-ventricular and septal pacing, accessory pathway) were calculated with a bidomain theory based anisotropic finite-element heart model in combination with a cellular automaton. In this heart model a realistic fiber architecture and conduction system was implemented. Although the anisotropy has some effects on forward solutions, effects on inverse solutions are small indicating that cardiac anisotropy might be negligible for some clinical applications (e.g., imaging of focal events) of our AT imaging approach. The main characteristic events of the AT maps were estimated despite neglected electrical anisotropy in the inverse formulation. The worst correlation coefficient of the estimated AT maps was 0.810 in case of sinus rhythm. However, all characteristic events of the activation pattern were found. The results of this study confirm our clinical validation studies of noninvasive AT imaging in which cardiac anisotropy was neglected.
Modeling in Real Time During the Ebola Response.
Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L
2016-01-01
To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in
Innovation diffusion on time-varying activity driven networks
NASA Astrophysics Data System (ADS)
Rizzo, Alessandro; Porfiri, Maurizio
2016-01-01
Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.
Continuous Time Model for the Dst Index
NASA Astrophysics Data System (ADS)
Zhu, D.; Balikhin, M. A.; Billings, S. A.; Wing, S.
2004-12-01
We have used the NARMAX based system identification approach to deduce, directly from measurements of upstream magnetic field and solar wind bulk velocity, a continuous time differential relationship that governs the evolution of the Dst index. This relation has been used to deduce the analytical dependence of the ring current decay rate upon values of VBs and Dst. It is shown that this depends upon a number of previous values of the solar wind parameters and Dst. Therefore the assumption often used previously in empirical models that the magnetosphere is a first order Markov's system is not valid. We show that the continuous time relation derived can be used for a reliable forecast of the Dst index.
Modeling interdependent animal movement in continuous time.
Niu, Mu; Blackwell, Paul G; Skarin, Anna
2016-06-01
This article presents a new approach to modeling group animal movement in continuous time. The movement of a group of animals is modeled as a multivariate Ornstein Uhlenbeck diffusion process in a high-dimensional space. Each individual of the group is attracted to a leading point which is generally unobserved, and the movement of the leading point is also an Ornstein Uhlenbeck process attracted to an unknown attractor. The Ornstein Uhlenbeck bridge is applied to reconstruct the location of the leading point. All movement parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings algorithm. We apply the method to a small group of simultaneously tracked reindeer, Rangifer tarandus tarandus, showing that the method detects dependency in movement between individuals. PMID:26812666
Modelling of nonlinear filtering Poisson time series
NASA Astrophysics Data System (ADS)
Bochkarev, Vladimir V.; Belashova, Inna A.
2016-08-01
In this article, algorithms of non-linear filtering of Poisson time series are tested using statistical modelling. The objective is to find a representation of a time series as a wavelet series with a small number of non-linear coefficients, which allows distinguishing statistically significant details. There are well-known efficient algorithms of non-linear wavelet filtering for the case when the values of a time series have a normal distribution. However, if the distribution is not normal, good results can be expected using the maximum likelihood estimations. The filtration is studied according to the criterion of maximum likelihood by the example of Poisson time series. For direct optimisation of the likelihood function, different stochastic (genetic algorithms, annealing method) and deterministic optimization algorithms are used. Testing of the algorithm using both simulated series and empirical data (series of rare words frequencies according to the Google Books Ngram data were used) showed that filtering based on the criterion of maximum likelihood has a great advantage over well-known algorithms for the case of Poisson series. Also, the most perspective methods of optimisation were selected for this problem.
Modelling and observing Jovian electron propagation times
NASA Astrophysics Data System (ADS)
Toit Strauss, Du; Potgieter, Marius; Kopp, Andreas; Heber, Bernd
2012-07-01
During the Pioneer 10 Jovian encounter, it was observed that the Jovian magnetosphere is a strong source of low energy electrons. These electrons are accelerated in the Jovian magnetosphere and then propagate through the interplanetary medium to reach Earth, sampling the heliospheric magnetic field (HMF) and its embedded turbulence. With the current constellation of near Earth spacecraft (STEREO, SOHO, ACE, ect.) various aspects of Jovian electron transport at/near Earth can be studied in 3D (spatially). During a CME, the plasma between the Earth and Jupiter becomes more disturbed, inhibiting the transport of these electrons to Earth. With the passage of the CME beyond Jupiter, quite-time transport conditions persist and increases of the electron flux at Earth are observed (so-called quite time increases). Using multi-spacecraft observation during such an event, we are able to infer the propagation time of these electrons from Jupiter to Earth. Using a state-of-the-art electron transport model, we study the transport of these electrons from Jupiter and Earth, focusing on their propagation times. These computed values are also compared with observations. We discuss the implications of these results from a particle transport point-of-view.
Modeling orbital changes on tectonic time scales
NASA Technical Reports Server (NTRS)
Crowley, Thomas J.
1992-01-01
Geologic time series indicate significant 100 ka and 400 ka pre-Pleistocene climate fluctuations, prior to the time of such fluctuations in Pleistocene ice sheets. The origin of these fluctuations must therefore depend on phenomena other than the ice sheets. In a previous set of experiments, we tested the sensitivity of an energy balance model to orbital insolation forcing, specifically focusing on the filtering effect of the Earth's geography. We found that in equatorial areas, the twice-yearly passage of the sun across the equator interacts with the precession index to generate 100 ka and 400 ka power in our modeled time series. The effect is proportional to the magnitude of land in equatorial regions. We suggest that such changes may reflect monsoonal variations in the real climate system, and the subsequent wind and weathering changes may transfer some of this signal to the marine record. A comparison with observed fluctuations of Triassic lake levels is quite favorable. A number of problems remain to be studied or clarified: (1) the EBM experiments need to be followed up by a limited number of GCM experiments; (2) the sensitivity to secular changes in orbital forcing needs to be examined; (3) the possible modifying role of sedimentary processes on geologic time series warrants considerably more study; (4) the effect of tectonic changes on Earth's rotation rate needs to be studied; and (5) astronomers need to make explicit which of their predictions are robust and geologists and astronomers have to agree on which of the predictions are most testable in the geologic record.
Examining the Fidelity of Climate model via Shadowing Time
NASA Astrophysics Data System (ADS)
Du, H.; Smith, L. A.
2015-12-01
Fully fledged climate models provide the best available simulations for reflecting the future, yet we have scant insight into their fidelity, in particular as to the duration into the future at which the real world should be expected to evolve in a manner today's models cannot foresee. We know now that our best available models are not adequate for many sought after purposes. To throw some light on the maximum fidelity expected from a given generation of models, and thereby aid both policy making and model development, we can test the weaknesses of a model as a dynamical system to get an informed idea of its potential applicability at various lead times. Shadowing times reflect the duration on which a GCM reflects the observations; extracting the shortcomings of the model which limit shadowing times allows informed speculation regarding the fidelity of the model in the future. More specifically, the relevant phenomena limiting model fidelity can be learned by identifying the reasons models cannot shadow; the time scales on which feedbacks on the system (which are not active in the model) are likely to result in model irrelevance can be discerned. The methodology is developed in the "low dimensional laboratory" of relatively simple dynamical systems, for example Lorenz 95 systems. The results are presented in Lorenz 95 systems, high dimensional fluid dynamical simulations of rotating annulus and GCMs. There are severe limits on the light shadowing experiments can shine on GCM predictions. Never the less, they appear to be one of the brightest lights we can shine to illuminate the likely fidelity of GCM extrapolations into the future.
Optimal design of active and semi-active suspensions including time delays and preview
NASA Astrophysics Data System (ADS)
Hac', A.; Youn, I.
1993-10-01
Several control laws for active and semi-active suspension based on a linear half car model are derived and investigated. The strategies proposed take full advantage of the fact that the road input to the rear wheels is a delayed version of that to the front wheels, which in turn can be obtained either from the measurements of the front wheels and body motions or by direct preview of road irregularities if preview sensors are available. The suspension systems are optimized with respect to ride comfort, road holding and suspension rattle space as expressed by the mean-square-values of body acceleration (including effects of heave and pitch), tire deflections and front and rear suspension travels. The optimal control laws that minimize the given performance index and include passivity constraints in the semi-active case are derived using calculus of variation. The optimal semi-active suspension becomes piecewise linear, varying between passive and fully active systems and combinations of them. The performances of active and semi-active systems with and without preview were evaluated by numerical simulation in the time and frequency domains. The results show that incorporation of time delay between the front and rear axles in controller design improves the dynamic behavior of the rear axle and control of body pitch motion, while additional preview improves front wheel dynamics and body heave.
Adaptive neural models of queuing and timing in fluent action.
Bullock, Daniel
2004-09-01
In biological cognition, specialized representations and associated control processes solve the temporal problems inherent in skilled action. Recent data and neural circuit models highlight three distinct levels of temporal structure: sequence preparation, velocity scaling, and state-sensitive timing. Short sequences of actions are prepared collectively in prefrontal cortex, then queued for performance by a cyclic competitive process that operates on a parallel analog representation. Successful acts like ball-catching depend on coordinated scaling of effector velocities, and velocity scaling, mediated by the basal ganglia, may be coupled to perceived time-to-contact. Making acts accurate at high speeds requires state-sensitive and precisely timed activations of muscle forces in patterns that accelerate and decelerate the effectors. The cerebellum may provide a maximally efficient representational basis for learning to generate such timed activation patterns.
Paolone, Giovanna; Lee, Theresa M.; Sarter, Martin
2012-01-01
Although the impairments in cognitive performance that result from shifting or disrupting daily rhythms have been demonstrated, the neuronal mechanisms that optimize fixed time daily performance are poorly understood. We previously demonstrated that daily practice of a sustained attention task (SAT) evokes a diurnal activity pattern in rats. Here we report that SAT practice at a fixed time produced practice time-stamped increases in prefrontal cholinergic neurotransmission that persisted after SAT practice was terminated and in a different environment. SAT time-stamped cholinergic activation occurred irrespective of whether the SAT was practiced during the light or dark phase or in constant light conditions. In contrast, prior daily practice of an operant schedule of reinforcement, albeit generating more rewards and lever presses per session than the SAT, neither activated the cholinergic system nor affected the animals' nocturnal activity pattern. Likewise, food-restricted animals exhibited strong food anticipatory activity (FAA) and attenuated activity during the dark period but FAA was not associated with increases in prefrontal cholinergic activity. Removal of cholinergic neurons impaired SAT performance and facilitated the reemergence of nocturnality. Shifting SAT practice away from a fixed time resulted in significantly lower performance. In conclusion, these experiments demonstrated that fixed time, daily practice of a task assessing attention generates a precisely practice time-stamped activation of the cortical cholinergic input system. Time-stamped cholinergic activation benefits fixed time performance and, if practiced during the light phase, contributes to a diurnal activity pattern. PMID:22933795
Timing Interactions in Social Simulations: The Voter Model
NASA Astrophysics Data System (ADS)
Fernández-Gracia, Juan; Eguíluz, Víctor M.; Miguel, Maxi San
The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 24 Housing and Urban Development 4 2012-04-01 2012-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 24 Housing and Urban Development 4 2013-04-01 2013-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 24 Housing and Urban Development 4 2011-04-01 2011-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 24 Housing and Urban Development 4 2014-04-01 2014-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
NASA Astrophysics Data System (ADS)
Ogata, Y.
2006-12-01
This paper is concerned with the detection of precursory slip on a rupturing fault, supported by both seismic and geodetic records. Basically, the detection relies on the principle that, assuming precursory slip on the rupturing fault, the seismic activity around the fault should be enhanced or reduced in the zones where increment of the Coulomb failure stress (CFS) is positive or negative, respectively. However, any occurring event also affects the stress changes in neighboring regions, which can trigger further aftershock clusters. Whereas such stress transfers are too difficult to be computed precisely, due to the unknown complex fault system, the ordinary short-term occurrence rate of earthquakes in a region is easily predicted using the ETAS model of triggering seismicity; and any anomalous seismic activity, such as quiescence and activation, can be quantified by identifying a significant deviation from the predicted rate. Such anomalies are revealed to have occurred during several years leading up to the 2004 Chuetsu Earthquake of M6.8, central Honshu, and also the 2005 Western Fukuoka-Ken-Oki Earthquake of M7.0, Kyushu, Japan. Quiescence and activation in the regions coincided with negative and positive increments of the CFS, respectively, and were probably transferred from possible aseismic slips on the focal fault plane. Such slips are further supported by transient crustal movement around the source preceding the rupture. Time series records of the baseline distances between the permanent GPS stations deviated from the predicted trends, with the deviations consistent with the coseismic horizontal displacements of the stations due to these earthquakes. References Ogata, Y. (2006) Report of the Coordinating Committee for Earthquake Prediction, 76 (to appear, in Japanese).
Concepts of disability: the Activity Space Model.
Kopec, J A
1995-03-01
This paper describes a new conceptual framework for functional assessment, the Activity Space Model (ASM). According to this model, functional impairments may lead to restrictions in an individual's activity space, a multidimensional space that represents human potential for activity. For each elementary ability, restrictions in the corresponding dimension of the activity space can be evaluated by deriving a difficulty curve that depicts the relationship between the level of performance and the psychophysical cost of activity. The effect of disease on daily functioning is explained in terms of a tradeoff between the psychophysical cost and the value of each act of behavior to the disabled individual. These two constructs are measured on the same scale and expressed in units of difficulty. The location of each task within the activity space in relation to the difficulty curve determines whether it will be performed or avoided at a given point in time. The ASM has both theoretical and practical implications. It offers a new, integrated perspective on disability and suggests new strategies for developing and evaluating functional assessment measures.
Empirical models of storm time equatorial zonal electric fields
NASA Astrophysics Data System (ADS)
Fejer, Bela G.; Scherliess, Ludger
1997-10-01
Ionospheric plasma drifts often show highly complex and variable signatures during geomagnetically active periods due to the effects of different disturbance processes. We describe initially a methodology for the study of storm time dependent ionospheric electric fields. We present empirical models of equatorial disturbance zonal electric fields obtained using extensive F region vertical plasma drift measurements from the Jicamarca Observatory and auroral electrojet indices. These models determine the plasma drift perturbations due to the combined effects of short-lived prompt penetration and longer lasting disturbance dynamo electric fields. We show that the prompt penetration drifts obtained from a high time resolution empirical model are in excellent agreement with results from the Rice Convection Model for comparable changes in the polar cap potential drop. We also present several case studies comparing observations with results obtained by adding model disturbance drifts and season and solar cycle dependent average quiet time drift patterns. When the disturbance drifts are largely due to changes in magnetospheric convection and to disturbance dynamo effects, the measured and modeled drift velocities are generally in good agreement. However, our results indicate that the equatorial disturbance electric field pattern can be strongly affected by variations in the shielding efficiency, and in the high-latitude potential and energy deposition patterns which are not accounted for in the model. These case studies and earlier results also suggest the possible importance of additional sources of plasmaspheric disturbance electric fields.
Young Urban African American Adolescents' Experience of Discretionary Time Activities
ERIC Educational Resources Information Center
Bohnert, Amy M.; Richards, Maryse H.; Kolmodin, Karen E.; Lakin, Brittany L.
2008-01-01
This cross-sectional study examined the daily discretionary time experiences of 246 (107 boys, 139 girls) fifth through eighth grade urban African American adolescents using the Experience Sampling Method. Relations between the types of activities (i.e., active structured, active unstructured, passive unstructured) engaged in during discretionary…
Time series models of symptoms in schizophrenia.
Tschacher, Wolfgang; Kupper, Zeno
2002-12-15
The symptom courses of 84 schizophrenia patients (mean age: 24.4 years; mean previous admissions: 1.3; 64% males) of a community-based acute ward were examined to identify dynamic patterns of symptoms and to investigate the relation between these patterns and treatment outcome. The symptoms were monitored by systematic daily staff ratings using a scale composed of three factors: psychoticity, excitement, and withdrawal. Patients showed moderate to high symptomatic improvement documented by effect size measures. Each of the 84 symptom trajectories was analyzed by time series methods using vector autoregression (VAR) that models the day-to-day interrelations between symptom factors. Multiple and stepwise regression analyses were then performed on the basis of the VAR models. Two VAR parameters were found to be associated significantly with favorable outcome in this exploratory study: 'withdrawal preceding a reduction of psychoticity' as well as 'excitement preceding an increase of withdrawal'. The findings were interpreted as generating hypotheses about how patients cope with psychotic episodes.
2014-01-01
Background The introduction of the European Working Time Directive (EWTD) has greatly reduced training hours of surgical residents, which translates into 30% less surgical and clinical experience. Such a dramatic drop in attendance has serious implications such compromised quality of medical care. As the surgical department of the University of Heidelberg, our goal was to establish a model that was compliant with the EWTD while avoiding reduction in quality of patient care and surgical training. Methods We first performed workload analyses and performance statistics for all working areas of our department (operation theater, emergency room, specialized consultations, surgical wards and on-call duties) using personal interviews, time cards, medical documentation software as well as data of the financial- and personnel-controlling sector of our administration. Using that information, we specifically designed an EWTD-compatible work model and implemented it. Results Surgical wards and operating rooms (ORs) were not compliant with the EWTD. Between 5 pm and 8 pm, three ORs were still operating two-thirds of the time. By creating an extended work shift (7:30 am-7:30 pm), we effectively reduced the workload to less than 49% from 4 pm and 8 am, allowing the combination of an eight-hour working day with a 16-hour on call duty; thus, maximizing surgical resident training and ensuring patient continuity of care while maintaining EDTW guidelines. Conclusion A precise workload analysis is the key to success. The Heidelberg New Working Time Model provides a legal model, which, by avoiding rotating work shifts, assures quality of patient care and surgical training. PMID:25984433
Multiscale time activity data exploration via temporal clustering visualization spreadsheet.
Woodring, Jonathan; Shen, Han-Wei
2009-01-01
Time-varying data is usually explored by animation or arrays of static images. Neither is particularly effective for classifying data by different temporal activities. Important temporal trends can be missed due to the lack of ability to find them with current visualization methods. In this paper, we propose a method to explore data at different temporal resolutions to discover and highlight data based upon time-varying trends. Using the wavelet transform along the time axis, we transform data points into multi-scale time series curve sets. The time curves are clustered so that data of similar activity are grouped together, at different temporal resolutions. The data are displayed to the user in a global time view spreadsheet where she is able to select temporal clusters of data points, and filter and brush data across temporal scales. With our method, a user can interact with data based on time activities and create expressive visualizations. PMID:19008560
Time Perspective and Physical Activity among Central Appalachian Adolescents
ERIC Educational Resources Information Center
Gulley, Tauna
2013-01-01
Time perspective is a cultural behavioral concept that reflects individuals' orientations or attitudes toward the past, present, or future. Individuals' time perspectives influence their choices regarding daily activities. Time perspective is an important consideration when teaching adolescents about the importance of being physically…
A time dependent anatomically detailed model of cardiac conduction
NASA Technical Reports Server (NTRS)
Saxberg, B. E.; Grumbach, M. P.; Cohen, R. J.
1985-01-01
In order to understand the determinants of transitions in cardiac electrical activity from normal patterns to dysrhythmias such as ventricular fibrillation, we are constructing an anatomically and physiologically detailed finite element simulation of myocardial electrical propagation. A healthy human heart embedded in paraffin was sectioned to provide a detailed anatomical substrate for model calculations. The simulation of propagation includes anisotropy in conduction velocity due to fiber orientation as well as gradients in conduction velocities, absolute and relative refractory periods, action potential duration and electrotonic influence of nearest neighbors. The model also includes changes in the behaviour of myocardial tissue as a function of the past local activity. With this model, we can examine the significance of fiber orientation and time dependence of local propagation parameters on dysrhythmogenesis.
Real-time Neural Network predictions of geomagnetic activity indices
NASA Astrophysics Data System (ADS)
Bala, R.; Reiff, P. H.
2009-12-01
The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction
Modeling Coastal Vulnerability through Space and Time
2016-01-01
Coastal ecosystems experience a wide range of stressors including wave forces, storm surge, sea-level rise, and anthropogenic modification and are thus vulnerable to erosion. Urban coastal ecosystems are especially important due to the large populations these limited ecosystems serve. However, few studies have addressed the issue of urban coastal vulnerability at the landscape scale with spatial data that are finely resolved. The purpose of this study was to model and map coastal vulnerability and the role of natural habitats in reducing vulnerability in Jamaica Bay, New York, in terms of nine coastal vulnerability metrics (relief, wave exposure, geomorphology, natural habitats, exposure, exposure with no habitat, habitat role, erodible shoreline, and surge) under past (1609), current (2015), and future (2080) scenarios using InVEST 3.2.0. We analyzed vulnerability results both spatially and across all time periods, by stakeholder (ownership) and by distance to damage from Hurricane Sandy. We found significant differences in vulnerability metrics between past, current and future scenarios for all nine metrics except relief and wave exposure. The marsh islands in the center of the bay are currently vulnerable. In the future, these islands will likely be inundated, placing additional areas of the shoreline increasingly at risk. Significant differences in vulnerability exist between stakeholders; the Breezy Point Cooperative and Gateway National Recreation Area had the largest erodible shoreline segments. Significant correlations exist for all vulnerability (exposure/surge) and storm damage combinations except for exposure and distance to artificial debris. Coastal protective features, ranging from storm surge barriers and levees to natural features (e.g. wetlands), have been promoted to decrease future flood risk to communities in coastal areas around the world. Our methods of combining coastal vulnerability results with additional data and across multiple time
Time-space modeling of journey-time exposure to traffic-related air pollution using GIS.
Gulliver, John; Briggs, David J
2005-01-01
Journey-time exposures represent an important, though as yet little-studied, component of human exposure to traffic-related air pollution, potentially with important health effects. Methods for assessing journey-time exposures, either as part of epidemiological studies or for policy assessment, are, however, poorly developed. This paper describes the development and testing of a GIS-based system for modeling human journey-time exposures to traffic-related air pollution: STEMS (Space-Time Exposure Modeling System). The model integrates data on source activity, pollutant dispersion, and travel behavior to derive individual- or group-level exposure measures to atmospheric pollution. The model, which is designed to simulate exposures of people as they move through a changing air pollution field, was developed, validated, and trialed in Northampton, UK. The system currently uses ArcInfo to couple four separate submodels: a source activity/emission model (SATURN), a proprietary atmospheric dispersion model (ADMS-Urban), an empirically derived background air pollution model, and a purposely designed time-activity-based exposure model (TOTEM). This paper describes the structure of the modeling system; presents results of field calibration, validation, and sensitivity analysis; and illustrates the use of the model to analyze journey-time exposures of schoolchildren.
The Elasticity of Time: Associations between Physical Activity and Use of Time in Adolescents
ERIC Educational Resources Information Center
Olds, Tim; Ferrar, Katia E.; Gomersall, Sjaan R.; Maher, Carol; Walters, J. L.
2012-01-01
The way an individual uses one's time can greatly affect his or her health. The purpose of this article was to examine the cross-sectional cross-elasticity relationships for use of time domains in a sample of Australian adolescents. This study analyzed 24-hour recall time use data collected using the Multimedia Activity Recall for Children and…
Real-Time System for Water Modeling and Management
NASA Astrophysics Data System (ADS)
Lee, J.; Zhao, T.; David, C. H.; Minsker, B.
2012-12-01
Cyberintegrator workflow system provides RESTful web services for users to provide inputs, execute workflows, and retrieve outputs. Along with REST endpoints, PAW (Publishable Active Workflows) provides the web user interface toolkit for us to develop web applications with scientific workflows. The prototype web application is built on top of workflows with PAW, so that users will have a user-friendly web environment to provide input parameters, execute the model, and visualize/retrieve the results using geospatial mapping tools. In future work the optimization model will be developed and integrated into the workflow.; Real-Time System for Water Modeling and Management
Stratospheric ozone time series analysis using dynamical linear models
NASA Astrophysics Data System (ADS)
Laine, Marko; Kyrölä, Erkki
2013-04-01
We describe a hierarchical statistical state space model for ozone profile time series. The time series are from satellite measurements by the SAGE II and GOMOS instruments spanning years 1984-2012. The original data sets are combined and gridded monthly using 10 degree latitude bands, and covering 20-60 km with 1 km vertical spacing. Model components include level, trend, seasonal effect with solar activity, and quasi biennial oscillations as proxy variables. A typical feature of an atmospheric time series is that they are not stationary but exhibit both slowly varying and abrupt changes in the distributional properties. These are caused by external forcing such as changes in the solar activity or volcanic eruptions. Further, the data sampling is often nonuniform, there are data gaps, and the uncertainty of the observations can vary. When observations are combined from various sources there will be instrument and retrieval method related biases. The differences in sampling lead also to uncertainties. Standard classical ARIMA type of statistical time series methods are mostly useless for atmospheric data. A more general approach makes use of dynamical linear models and Kalman filter type of sequential algorithms. These state space models assume a linear relationship between the unknown state of the system and the observations and for the process evolution of the hidden states. They are still flexible enough to model both smooth trends and sudden changes. The above mentioned methodological challenges are discussed, together with analysis of change points in trends related to recovery of stratospheric ozone. This work is part of the ESA SPIN and ozone CCI projects.
Phase Transitions in Model Active Systems
NASA Astrophysics Data System (ADS)
Redner, Gabriel S.
The amazing collective behaviors of active systems such as bird flocks, schools of fish, and colonies of microorganisms have long amazed scientists and laypeople alike. Understanding the physics of such systems is challenging due to their far-from-equilibrium dynamics, as well as the extreme diversity in their ingredients, relevant time- and length-scales, and emergent phenomenology. To make progress, one can categorize active systems by the symmetries of their constituent particles, as well as how activity is expressed. In this work, we examine two categories of active systems, and explore their phase behavior in detail. First, we study systems of self-propelled spherical particles moving in two dimensions. Despite the absence of an aligning interaction, this system displays complex emergent dynamics, including phase separation into a dense active solid and dilute gas. Using simulations and analytic modeling, we quantify the phase diagram and separation kinetics. We show that this nonequilibrium phase transition is analogous to an equilibrium vapor-liquid system, with binodal and spinodal curves and a critical point. We also characterize the dense active solid phase, a unique material which exhibits the structural signatures of a crystalline solid near the crystal-hexatic transition point, as well as anomalous dynamics including superdiffusive motion on intermediate timescales. We also explore the role of interparticle attraction in this system. We demonstrate that attraction drastically changes the phase diagram, which contains two distinct phase-separated regions and is reentrant as a function of propulsion speed. We interpret this complex situation with a simple kinetic model, which builds from the observed microdynamics of individual particles to a full description of the macroscopic phase behavior. We also study active nematics, liquid crystals driven out of equilibrium by energy-dissipating active stresses. The equilibrium nematic state is unstable in these
Modeling in Real Time During the Ebola Response.
Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L
2016-01-01
To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in
An Active Model for Facial Feature Tracking
NASA Astrophysics Data System (ADS)
Ahlberg, Jörgen
2002-12-01
We present a system for finding and tracking a face and extract global and local animation parameters from a video sequence. The system uses an initial colour processing step for finding a rough estimate of the position, size, and inplane rotation of the face, followed by a refinement step drived by an active model. The latter step refines the previous estimate, and also extracts local animation parameters. The system is able to track the face and some facial features in near real-time, and can compress the result to a bitstream compliant to MPEG-4 face and body animation.
Circadian Activity Rhythms, Time Urgency, and Achievement Concerns.
ERIC Educational Resources Information Center
Watts, Barbara L.
Many physiological and psychological processes fluctuate throughout the day in fairly stable, rhythmic patterns. The relationship between individual differences in circadian activity rhythms and a sense of time urgency were explored as well as a number of achievement-related variables. Undergraduates (N=308), whose circadian activity rhythms were…
A Flexible Latent Trait Model for Response Times in Tests
ERIC Educational Resources Information Center
Ranger, Jochen; Kuhn, Jorg-Tobias
2012-01-01
Latent trait models for response times in tests have become popular recently. One challenge for response time modeling is the fact that the distribution of response times can differ considerably even in similar tests. In order to reduce the need for tailor-made models, a model is proposed that unifies two popular approaches to response time…
Sabiston, Catherine M; Crocker, Peter R E
2008-02-01
This study examined adolescent leisure-time physical activity correlates using the expectancy-value (EV) model. Adolescents (N = 857) completed questionnaires to assess competence and value self-perceptions, social influences, and physical activity. Direct and indirect effects of self-perceptions and parent and best friend influences on physical activity were explored using structural equation modeling. Measurement models were a good fit to the data and gender invariance was supported. The structural mediation model was a reasonable fit to the data, whereby the indirect effects of parents and peers and the direct effects of competence beliefs and values together accounted for 49% of the variance in physical activity. In this model, the pattern of relationships was similar for adolescent males and females. Findings supporting the EV model provide theoretical and practical implications for understanding adolescent physical activity.
Sabiston, Catherine M; Crocker, Peter R E
2008-02-01
This study examined adolescent leisure-time physical activity correlates using the expectancy-value (EV) model. Adolescents (N = 857) completed questionnaires to assess competence and value self-perceptions, social influences, and physical activity. Direct and indirect effects of self-perceptions and parent and best friend influences on physical activity were explored using structural equation modeling. Measurement models were a good fit to the data and gender invariance was supported. The structural mediation model was a reasonable fit to the data, whereby the indirect effects of parents and peers and the direct effects of competence beliefs and values together accounted for 49% of the variance in physical activity. In this model, the pattern of relationships was similar for adolescent males and females. Findings supporting the EV model provide theoretical and practical implications for understanding adolescent physical activity. PMID:18369240
Modeling Information Accumulation in Psychological Tests Using Item Response Times
ERIC Educational Resources Information Center
Ranger, Jochen; Kuhn, Jörg-Tobias
2015-01-01
In this article, a latent trait model is proposed for the response times in psychological tests. The latent trait model is based on the linear transformation model and subsumes popular models from survival analysis, like the proportional hazards model and the proportional odds model. Core of the model is the assumption that an unspecified monotone…
Modeling of active and passive nonlinear metamaterials
NASA Astrophysics Data System (ADS)
Colestock, Patrick L.; Reiten, Matthew T.; O'Hara, John F.
2012-11-01
We develop general results for nonlinear metamaterials based on simple circuit models that reflect the elementary nonlinear behavior of the medium. In particular, we consider both active and passive nonlinearities which can lead to gain, harmonic generation and a variety of nonlinear waves depending on circuit parameters and signal amplitude. We show that the medium can exhibit a phase transition to a synchronized state and derive conditions for the transformation based on a widely used multiple time scale approach that leads to the well-known Complex Ginzburg-Landau equation. Further, we examine the variety of nonlinear waves that can exist in such systems, and we present numerical results for both active and passive metamaterial cases.
Model Eliciting Activities: Fostering 21st Century Learners
ERIC Educational Resources Information Center
Stohlmann, Micah
2013-01-01
Real world mathematical modeling activities can develop needed and valuable 21st century skills. The knowledge and skills to become adept at mathematical modeling need to develop over time and students in the elementary grades should have experiences with mathematical modeling. For this to occur elementary teachers need to have positive…
Volatility modeling of rainfall time series
NASA Astrophysics Data System (ADS)
Yusof, Fadhilah; Kane, Ibrahim Lawal
2013-07-01
Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung-Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA-GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.
Kong, Il Gyu; Lee, Hyo-Jeong; Kim, So Young; Sim, Songyong; Choi, Hyo Geun
2015-01-01
Abstract Low physical activity, long leisure sitting time, and short sleep time are risk factors for obesity, but the association with study sitting time is unknown. The objective of this study was to evaluate the association between these factors and obesity. We analyzed the association between physical activity, study sitting time, leisure sitting time, and sleep time and subject weight (underweight, healthy weight, overweight, and obese), using data from a large population-based survey, the 2013 Korea Youth Risk Behavior Web-based Survey. Data from 53,769 participants were analyzed using multinomial logistic regression analyses with complex sampling. Age, sex, region of residence, economic level, smoking, stress level, physical activity, sitting time for study, sitting time for leisure, and sleep time were adjusted as the confounders. Low physical activity (adjusted odds ratios [AORs] = 1.03, 1.12) and long leisure sitting time (AORs = 1.15, 1.32) were positively associated with overweight and obese. Low physical activity (AOR = 1.33) and long leisure sitting time (AOR = 1.12) were also associated with underweight. Study sitting time was negatively associated with underweight (AOR = 0.86) but was unrelated to overweight (AOR = 0.97, 95% confidence interval [CI] = 0.91–1.03) and obese (AOR = 0.94, 95% CI = 0.84–1.04). Sleep time (<6 hours; ≥6 hours, <7 hours; ≥7 hours, <8 hours) was adversely associated with underweight (AORs = 0.67, 0.79, and 0.88) but positively associated with overweight (AORs = 1.19, 1.17, and 1.08) and obese (AORs = 1.33, 1.36, and 1.30) in a dose–response relationship. In adolescents, increasing physical activity, decreasing leisure sitting time, and obtaining sufficient sleep would be beneficial in maintaining a healthy weight. However, study sitting time was not associated with overweight or obese. PMID:26554807
Evaluating a Model of Youth Physical Activity
Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary
2011-01-01
Objective To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a sample of youth aged 10–17 years (N=720). Results Peer support, parent physical activity, and perceived barriers were directly related to youth activity. The proposed model accounted for 14.7% of the variance in physical activity. Conclusions The results demonstrate a need to further explore additional individual, social, and environmental factors that may influence youth’s regular participation in physical activity. PMID:20524889
The Simplest Complete Model of Choice Response Time: Linear Ballistic Accumulation
ERIC Educational Resources Information Center
Brown, Scott D.; Heathcote, Andrew
2008-01-01
We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows…
Time required for motor activity in lucid dreams.
Erlacher, Daniel; Schredl, Michael
2004-12-01
The present study investigated the relationship between the time required for specific tasks (counting and performing squats) in lucid dreams and in the waking state. Five proficient lucid dreamers (26-34 yr. old, M=29.8, SD=3.0; one woman and four men) participated. Analysis showed that the time needed for counting in a lucid dream is comparable to the time needed for counting in wakefulness, but motor activities required more time in lucid dreams than in the waking state. PMID:15739850
Time required for motor activity in lucid dreams.
Erlacher, Daniel; Schredl, Michael
2004-12-01
The present study investigated the relationship between the time required for specific tasks (counting and performing squats) in lucid dreams and in the waking state. Five proficient lucid dreamers (26-34 yr. old, M=29.8, SD=3.0; one woman and four men) participated. Analysis showed that the time needed for counting in a lucid dream is comparable to the time needed for counting in wakefulness, but motor activities required more time in lucid dreams than in the waking state.
Viscous time lags between starburst and AGN activity
NASA Astrophysics Data System (ADS)
Blank, Marvin; Duschl, Wolfgang J.
2016-10-01
There is strong observational evidence indicating a time lag of order of some 100 Myr between the onset of starburst and AGN activity in galaxies. Dynamical time lags have been invoked to explain this. We extend this approach by introducing a viscous time lag the gas additionally needs to flow through the AGN's accretion disc before it reaches the central black hole. Our calculations reproduce the observed time lags and are in accordance with the observed correlation between black hole mass and stellar velocity dispersion.
Time-dependent global modeling of the inner heliosphere
NASA Astrophysics Data System (ADS)
Merkin, V. G.; Lyon, J.; Arge, C. N.; Lario, D.; Linker, J.; Lionello, R.
2015-12-01
We present results of time-dependent modeling of the inner heliosphere using the Lyon-Fedder-Mobarry (LFM) magnetohydrodynamic (MHD). Two types of simulations are performed: one concentrates on the background solar wind specification, while the other deals with the propagation of coronal mass ejections (CMEs). For simulations of the first type we coupled the LFM-helio code with the ADAPT-driven WSA model. We present some details of the coupling machinery and then simulate selected periods characterized by very low solar activity with no significant energetic particle events or CMEs. The results of the model are compared with MESSENGER, ACE, STEREO A and B spacecraft to probe both radial and temporal evolution of solar wind structure. The results indicate, in particular, the importance of time-dependent modeling for more accurate prediction of high-speed streams and heliospheric current sheet structure when the spacecraft skim its surface. We will comment on the formation of magnetic field reversals in pseudostreamer regions, which is an intrinsically time-dependent phenomenon, and on the current sheet corrugation caused by solar wind momentum shears. For the second type of time-dependent inner heliosphere simulations we have coupled LFM-helio with the MAS MHD model of the corona. We first present results of idealized coupled MAS/LFM-helio simulations with symmetric solar wind background and no rotation intended to test the interface for seamless propagation of transients from the corona into the inner heliosphere domain. We then simulate an event with a CME propagating through a realistic heliosphere background including corotating interaction regions. We show details of propagation of flux-rope CMEs through the boundary between MAS and LFM-helio and compare the results between the two codes in the heliospheric domain. The results indicate that the coupling works well, although some differences in the solutions are observed probably due to differences in numerical
An immune system-tumour interactions model with discrete time delay: Model analysis and validation
NASA Astrophysics Data System (ADS)
Piotrowska, Monika Joanna
2016-05-01
In this article a generalised mathematical model describing the interactions between malignant tumour and immune system with discrete time delay incorporated into the system is considered. Time delay represents the time required to generate an immune response due to the immune system activation by cancer cells. The basic mathematical properties of the considered model, including the global existence, uniqueness, non-negativity of the solutions, the stability of steady sates and the possibility of the existence of the stability switches, are investigated when time delay is treated as a bifurcation parameter. The model is validated with the sets of the experimental data and additional numerical simulations are performed to illustrate, extend, interpret and discuss the analytical results in the context of the tumour progression.
Evaluation of Fast-Time Wake Vortex Prediction Models
NASA Technical Reports Server (NTRS)
Proctor, Fred H.; Hamilton, David W.
2009-01-01
Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.
Single photon time transfer link model for GNSS satellites
NASA Astrophysics Data System (ADS)
Vacek, Michael; Michalek, Vojtech; Peca, Marek; Prochazka, Ivan; Blazej, Josef
2015-05-01
The importance of optical time transfer serving as a complement to traditional microwave links, has been attested for GNSSes and for scientific missions. Single photon time transfer (SPTT) is a process, allowing to compare (subtract) time readings of two distant clocks. Such a comparison may be then used to synchronize less accurate clock to a better reference, to perform clock characterization and calibration, to calculate mean time out of ensemble of several clocks, displaced in space. The single-photon time transfer is well established in field of space geodesy, being supported by passive retro-reflectors within space segment of five known GNSSes. A truly two-way, active terminals work aboard of Jason-2 (T2L2) - multiphoton operation, GNSS Beidou (Compass) - SPTT, and are going to be launched within recent ACES project (ELT) - SPTT, and GNSS GLONASS - multiphoton operation. However, there is still missing comprehensive theoretical model of two-way (using satellite receiver and retroreflector) SPTT link incorporating all crucial parameters of receiver (both ground and space segment receivers), transmitter, atmosphere effects on uplink and downlink path, influence of retroreflector. The input to calculation of SPTT link performance will be among others: link budget (distance, power, apertures, beam divergence, attenuation, scattering), propagating medium (atmosphere scintillation, beam wander, etc.), mutual Tx/Rx velocity, wavelength. The SPTT model will be evaluated without the properties of real components. These will be added in the further development. The ground-to-space SPTT link performance of typical scenarios are modeled. This work is a part of the ESA study "Comparison of optical time-transfer links."
Solar Irradiance Variations on Active Region Time Scales
NASA Technical Reports Server (NTRS)
Labonte, B. J. (Editor); Chapman, G. A. (Editor); Hudson, H. S. (Editor); Willson, R. C. (Editor)
1984-01-01
The variations of the total solar irradiance is an important tool for studying the Sun, thanks to the development of very precise sensors such as the ACRIM instrument on board the Solar Maximum Mission. The largest variations of the total irradiance occur on time scales of a few days are caused by solar active regions, especially sunspots. Efforts were made to describe the active region effects on total and spectral irradiance.
Evidence Against a Central Control Model of Timing in Typing.
ERIC Educational Resources Information Center
Gentner, Donald R.
The evidence for the Terzuolo and Viviani central control model of timing in typing was questioned, using data collected from skilled typists and data published by Terzuolo and Viviani. (In this model keystroke times are generated in parallel from centrally stored, word-specific timing patterns. Differences in overall time to type a given word are…
2D Time-lapse Seismic Tomography Using An Active Time Constraint (ATC) Approach
We propose a 2D seismic time-lapse inversion approach to image the evolution of seismic velocities over time and space. The forward modeling is based on solving the eikonal equation using a second-order fast marching method. The wave-paths are represented by Fresnel volumes rathe...
Stochastic Time Models of Syllable Structure
Shaw, Jason A.; Gafos, Adamantios I.
2015-01-01
Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. PMID:25996153
Shen, Bo; McCaughtry, Nate; Martin, Jeffrey
2007-09-01
Using a multitheory approach, this study was designed to investigate the influence of urban adolescents' perceived autonomy and competence in physical education on their physical activity intentions and behaviors during leisure time. A transcontextual model was hypothesized and tested. Urban adolescents (N=653, ages 11-15 years) completed questionnaires assessing relevant psychological constructs and moderate to vigorous physical activity and then had their cardiorespiratory fitness assessed with the Progressive Aerobic Cardiovascular Endurance Run (PACER) test. Based on our structural equation modeling analyses and fit indexes, the transcontextual model adequately fit the data. We concluded that the two theoretical frameworks--SDT and theory of planned behavior--can be integrated to provide an enhanced understanding of the influence of physical education on leisure-time physical activity. The results revealed that perceived autonomy and competence in physical education are interrelated and function as a whole for enhancing leisure-time physically active intentions and behavior.
Concurrent multi-mode timing model generation for hierarchical timing analysis
NASA Astrophysics Data System (ADS)
Kumar, Naresh; Bhatnagar, Parag; Agarwal, N. K.; Bhatnagar, P. S.
2016-03-01
In this paper, we investigate the challenges in timing model generation for designs operating at various functional modes and timing corners for reducing the overall complexity of timing verification besides preserving the key intent of IP protection. We also propose a method for concurrently generating a model that can address the requirements of timing verification of a set of functional constraint modes belonging to the same corner with a given process, voltage and temperature specifications. Eventually we present a comparison of this proposed technique to the standard timing model generation technique and outline the advantages in three metrics of accuracy, performance and compaction of the timing models.
Microscopic Modelling Circadian and Bursty Pattern of Human Activities
Kim, Jinhong; Lee, Deokjae; Kahng, Byungnam
2013-01-01
Recent studies for a wide range of human activities such as email communication, Web browsing, and library visiting, have revealed the bursty nature of human activities. The distribution of inter-event times (IETs) between two consecutive human activities exhibits a heavy-tailed decay behavior and the oscillating pattern with a one-day period, reflective of the circadian pattern of human life. Even though a priority-based queueing model was successful as a basic model for understanding the heavy-tailed behavior, it ignored important ingredients, such as the diversity of individual activities and the circadian pattern of human life. Here, we collect a large scale of dataset which contains individuals’ time stamps when articles are posted on blog posts, and based on which we construct a theoretical model which can take into account of both ignored ingredients. Once we identify active and inactive time intervals of individuals and remove the inactive time interval, thereby constructing an ad hoc continuous time domain. Therein, the priority-based queueing model is applied by adjusting the arrival and the execution rates of tasks by comparing them with the activity data of individuals. Then, the obtained results are transferred back to the real-time domain, which produces the oscillating and heavy-tailed IET distribution. This microscopic model enables us to develop theoretical understanding towards more empirical results. PMID:23505479
Time-dependent corona models - Scaling laws
NASA Technical Reports Server (NTRS)
Korevaar, P.; Martens, P. C. H.
1989-01-01
Scaling laws are derived for the one-dimensional time-dependent Euler equations that describe the evolution of a spherically symmetric stellar atmosphere. With these scaling laws the results of the time-dependent calculations by Korevaar (1989) obtained for one star are applicable over the whole Hertzsprung-Russell diagram and even to elliptic galaxies. The scaling is exact for stars with the same M/R-ratio and a good approximation for stars with a different M/R-ratio. The global relaxation oscillation found by Korevaar (1989) is scaled to main sequence stars, a solar coronal hole, cool giants and elliptic galaxies.
Wetting and Non-Wetting Models of Black Carbon Activation
NASA Astrophysics Data System (ADS)
Henson, B. F.; Laura, S.
2006-12-01
We present the results of recent modeling studies on the activation of black carbon (BC) aerosol to form cloud condensation nuclei (CCN). We use a model of BC activation based on a general modification of the Koehler equation for insoluble activation in which we introduce a term based on the activity of water adsorbed on the particle surface. We parameterize the model using the free energy of adsorption, a parameter directly comparable to laboratory measurements of water adsorption on carbon. Although the model of the water- surface interaction is general, the form of the activation equation that results depends upon a further model of the distribution of water on the particle. One possible model involves the symmetric growth of a water shell around the isoluble particle core (wetting). This model predicts upper and lower bounding curves for the activation supersaturation given by the range of water interaction energies from hydrophobic to hydrophilic which are in agreement with a large body of recent activation data. The resulting activation diameters are from 3 to 10 times smaller than activation of soluble particles of identical dry diameter. Another possible model involves an exluded liquid droplet growing in contact with the particle (non-wetting). The geometry of this model much more resembles classic assumptions of heterogeneous nucleation theory. This model can yield extremely high activation supersaturation as a function of diameter, as has been observed in some experiments, and enables calculations in agreement with some of these results. We discuss these two geometrical models of water growth, the different behaviors predicted by the resulting activation equation, and the means to determine which model of growth is appropriate for a given BC particle characterized by either water interaction energy or morphology. These simple models enable an efficient and physically reasonable means to calculate the activation of BC aerosol to form CCN based upon a
Modeling Time Series Data for Supervised Learning
ERIC Educational Resources Information Center
Baydogan, Mustafa Gokce
2012-01-01
Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…
Structural Equation Modeling of Multivariate Time Series
ERIC Educational Resources Information Center
du Toit, Stephen H. C.; Browne, Michael W.
2007-01-01
The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…
Gaussian Process for Activity Modeling and Anomaly Detection
NASA Astrophysics Data System (ADS)
Liao, W.; Rosenhahn, B.; Yang, M. Ying
2015-08-01
Complex activity modeling and identification of anomaly is one of the most interesting and desired capabilities for automated video behavior analysis. A number of different approaches have been proposed in the past to tackle this problem. There are two main challenges for activity modeling and anomaly detection: 1) most existing approaches require sufficient data and supervision for learning; 2) the most interesting abnormal activities arise rarely and are ambiguous among typical activities, i.e. hard to be precisely defined. In this paper, we propose a novel approach to model complex activities and detect anomalies by using non-parametric Gaussian Process (GP) models in a crowded and complicated traffic scene. In comparison with parametric models such as HMM, GP models are nonparametric and have their advantages. Our GP models exploit implicit spatial-temporal dependence among local activity patterns. The learned GP regression models give a probabilistic prediction of regional activities at next time interval based on observations at present. An anomaly will be detected by comparing the actual observations with the prediction at real time. We verify the effectiveness and robustness of the proposed model on the QMUL Junction Dataset. Furthermore, we provide a publicly available manually labeled ground truth of this data set.
Oscillatory phase modulates the timing of neuronal activations and resulting behavior.
Coon, W G; Gunduz, A; Brunner, P; Ritaccio, A L; Pesaran, B; Schalk, G
2016-06-01
Human behavioral response timing is highly variable from trial to trial. While it is generally understood that behavioral variability must be due to trial-by-trial variations in brain function, it is still largely unknown which physiological mechanisms govern the timing of neural activity as it travels through networks of neuronal populations, and how variations in the timing of neural activity relate to variations in the timing of behavior. In our study, we submitted recordings from the cortical surface to novel analytic techniques to chart the trajectory of neuronal population activity across the human cortex in single trials, and found joint modulation of the timing of this activity and of consequent behavior by neuronal oscillations in the alpha band (8-12Hz). Specifically, we established that the onset of population activity tends to occur during the trough of oscillatory activity, and that deviations from this preferred relationship are related to changes in the timing of population activity and the speed of the resulting behavioral response. These results indicate that neuronal activity incurs variable delays as it propagates across neuronal populations, and that the duration of each delay is a function of the instantaneous phase of oscillatory activity. We conclude that the results presented in this paper are supportive of a general model for variability in the effective speed of information transmission in the human brain and for variability in the timing of human behavior. PMID:26975551
Rose, V L; Dermott, S C; Murray, B F; McIver, M M; High, K A; Oberhardt, B J
1993-06-01
Previous work has established the precision and accuracy of a portable blood coagulation analysis system using paramagnetic particles contained in a dry reagent on a disposable test card. We examined the deployment of this technology in decentralized hospital settings and compared test results obtained in the surgical intensive care unit, coronary care unit, and outpatient cardiology clinic with those obtained in the central laboratory. Nursing personnel were instructed in the use of the system, and quality control testing was performed daily by the laboratory staff. In the intensive care units, patient subjects included those on whom tests of prothrombin time and activated partial thromboplastin time had been ordered. Immediate determinations were performed by the intensive care unit nursing staff on the same citrated, whole-blood samples that were subsequently sent to the central laboratory. In the outpatient cardiology clinic, fingerstick blood samples were obtained for prothrombin time determinations with the dry chemistry system. Paired prothrombin time samples obtained by venipuncture were run in the hospital laboratory. The study involved multiple users, multiple locations, two lots of activated partial thromboplastin time cards, and several different instruments, over an extended period. Correlation coefficients between the dry chemistry system and the hospital laboratory under these conditions were in an acceptable range in all sites studied. We concluded that, with appropriate training and quality assurance, the dry chemistry system provides an acceptable alternative to the hospital laboratory for prothrombin time and activated partial thromboplastin time determinations. PMID:8503733
5 CFR 551.426 - Time spent in charitable activities.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 5 Administrative Personnel 1 2013-01-01 2013-01-01 false Time spent in charitable activities. 551.426 Section 551.426 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Hours of Work Application of Principles...
5 CFR 551.426 - Time spent in charitable activities.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 5 Administrative Personnel 1 2012-01-01 2012-01-01 false Time spent in charitable activities. 551.426 Section 551.426 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Hours of Work Application of Principles...
5 CFR 551.426 - Time spent in charitable activities.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Time spent in charitable activities. 551.426 Section 551.426 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Hours of Work Application of Principles...
5 CFR 551.426 - Time spent in charitable activities.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 5 Administrative Personnel 1 2014-01-01 2014-01-01 false Time spent in charitable activities. 551.426 Section 551.426 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Hours of Work Application of Principles...
Physical Activity in High School during "Free-Time" Periods
ERIC Educational Resources Information Center
Silva, Pedro; Sousa, Michael; Sá, Carla; Ribeiro, José; Mota, Jorge
2015-01-01
The purpose of this study was to examine youth physical activity (PA) in free-time periods during high school days and their contribution to total PA. Differences in terms of sex, age, body mass index and school level were assessed in a sample of Portuguese adolescents. Participants totalled 213 (135 girls), aged 14.6 ± 1.7, from two different…
Influence of computer work under time pressure on cardiac activity.
Shi, Ping; Hu, Sijung; Yu, Hongliu
2015-03-01
Computer users are often under stress when required to complete computer work within a required time. Work stress has repeatedly been associated with an increased risk for cardiovascular disease. The present study examined the effects of time pressure workload during computer tasks on cardiac activity in 20 healthy subjects. Heart rate, time domain and frequency domain indices of heart rate variability (HRV) and Poincaré plot parameters were compared among five computer tasks and two rest periods. Faster heart rate and decreased standard deviation of R-R interval were noted in response to computer tasks under time pressure. The Poincaré plot parameters showed significant differences between different levels of time pressure workload during computer tasks, and between computer tasks and the rest periods. In contrast, no significant differences were identified for the frequency domain indices of HRV. The results suggest that the quantitative Poincaré plot analysis used in this study was able to reveal the intrinsic nonlinear nature of the autonomically regulated cardiac rhythm. Specifically, heightened vagal tone occurred during the relaxation computer tasks without time pressure. In contrast, the stressful computer tasks with added time pressure stimulated cardiac sympathetic activity.
Time-resolved Spectroscopy of Active Binary Stars
NASA Astrophysics Data System (ADS)
Brown, Alexander
EUVE has provided the first stellar coronal spectra showing individual emission lines, thereby allowing coronal modelling at a level of sophistication previously unattainable. Long EUVE observations have shown the prevalence of large-scale flaring in the coronae of active binary stars. We propose to obtain EUVE DSS spectra and photometry for 8 active binaries, four of which have never been observed by EUVE (EI Eri, AR Psc, V478 Lyr, BY Dra) and four EUV-bright systems that merit reobservation (Sigma CrB, Sigma Gem, Xi UMa, Lambda And). We shall use these observations to derive high quality quiescent coronal spectra for modelling, and to obtain new flare data. We shall try to coordinate these observations with ground-based radio observations and other spacecraft, if the scheduling allows. The proposed observations will significantly increase the available EUVE spectroscopy of active binaries.
Discursive Positionings and Emotions in Modelling Activities
ERIC Educational Resources Information Center
Daher, Wajeeh
2015-01-01
Mathematical modelling is suggested as an activity through which students engage in meaningful mathematics. In the current research, the modelling activity of a group of four seventh-grade students was analysed using the discursive analysis framework. The research findings show that the positionings and emotions of the group members during their…
With string model to time series forecasting
NASA Astrophysics Data System (ADS)
Pinčák, Richard; Bartoš, Erik
2015-10-01
Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial market. We utilize the projections of the real exchange rate dynamics onto the string-like topology in the OANDA market. The latter approach allows us to build the stable prediction models in trading in the financial forex market. The real application of the multi-string structures is provided to demonstrate our ideas for the solution of the problem of the robust portfolio selection. The comparison with the trend following strategies was performed, the stability of the algorithm on the transaction costs for long trade periods was confirmed.
Deterministic Modelling of BAK Activation Kinetics
NASA Astrophysics Data System (ADS)
Grills, C.; Chacko, A.; Crawford, N.; Johnston, P. G.; Fennell, D. A.; O'Rourke, S. F. C.
2009-08-01
The molecular mechanism underlying mitochondrial BAK activation during apoptosis remains highly controversial. Two seemingly conflicting models have been proposed. In the activation model, BAK requires so-called activating BH3 only proteins (aBH3) to initiate its conformation change. In the other, displacement from inhibitory pro-survival BCL-2 proteins (PBPs) and monomerization of BAK by PBP restricted dissociator BH3-only proteins (dBH3) is sufficient. To better understand the kinetic implications of these models and reconcile these conflicting but highly evidence-based models, we have employed dynamical systems analysis to explore the kinetics underlying BAK activation as a non-linear reaction system. Our findings accommodate both pure agonism and dissociation as mutually exclusive mechanisms capable of initiating BAK activation. In addition we find our work supports a modelling based approach for predicting resistance to therapeutically relevant small molecules BH3 mimetics.
Evaluating a Model of Youth Physical Activity
ERIC Educational Resources Information Center
Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary
2010-01-01
Objective: To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods: Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a…
Assimilation of LAI time-series in crop production models
NASA Astrophysics Data System (ADS)
Kooistra, Lammert; Rijk, Bert; Nannes, Louis
2014-05-01
Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor
Developmental patterns and parental correlates of youth leisure-time physical activity.
Lam, Chun Bun; McHale, Susan M
2015-02-01
This study examined the developmental patterns and parental correlates of youth leisure-time physical activity from middle childhood through adolescence. On 5 occasions across 7 years, fathers, mothers, and children who were first- and second born from 201 European American, working- and middle-class families participated in home and multiple nightly phone interviews. Multilevel modeling revealed that, controlling for family socioeconomic status, neighborhood characteristics, and youth overweight status and physical health, leisure-time physical activity increased during middle childhood and declined across adolescence, and the decline was more pronounced for girls than for boys. Moreover, controlling for time-varying, parental work hours and youth interest in sports and outdoor activities, on occasions when fathers and mothers spent proportionally more time on these activities with youth than usual, youth also spent more total time on these activities than usual. The within-person association between mother-youth joint involvement and youth's total involvement in leisure-time physical activity reached statistical significance at the transition to adolescence, and became stronger over time. Findings highlight the importance of maintaining adolescents', especially girls', physical activity levels and targeting both fathers' and mothers' involvement to promote youth's physical activity.
Monetary cost for time spent in everyday physical activities.
Hsu, Anne S; Vlaev, Ivo
2014-05-01
We measured utility curves for the hypothetical monetary costs as a function of time engaged in three everyday physical activities: walking, standing, and sitting. We found that activities requiring more physical exertion resulted in steeper discount curves, i.e., perceived cost as a function of time. We also examined the effects of gain vs. loss framing (whether the activity brought additional rewards or prevented losses) as well as the effects of the individual factors of gender, income, and BMI. Steeper discount curves were associated with higher income (annual household ≥ median of $45,000) and gain framing (which indicates loss aversion). There were interactions between gender and frame, and also income and frame: Females and higher income participants showed loss aversion whereas males and lower income participants were not affected by framing. Males showed less discounting in gain frames relative to females, whereas females showed less discounting in loss frames relative to males. In gain frames, higher income participants discounted more but in loss frames there was no effect of income. We also found individual tendencies for discounting across activities: if an individual exhibited steeper discounting for one activity, they were also more likely to exhibit steeper discounting for the other activities. These results have implications for designers of interventions to encourage non-exercise physical activities, suggesting that loss-framed incentives are more effective for women and those with middle class (or greater) incomes. Furthermore loss framed incentives have more uniform impact across income brackets because people discount loss frames similarly regardless of income whereas those with middle-class incomes are not as motivated by gain frames. Our results also demonstrate a general method for examining the costs of effort associated with everyday activities. PMID:24632051
Monetary cost for time spent in everyday physical activities.
Hsu, Anne S; Vlaev, Ivo
2014-05-01
We measured utility curves for the hypothetical monetary costs as a function of time engaged in three everyday physical activities: walking, standing, and sitting. We found that activities requiring more physical exertion resulted in steeper discount curves, i.e., perceived cost as a function of time. We also examined the effects of gain vs. loss framing (whether the activity brought additional rewards or prevented losses) as well as the effects of the individual factors of gender, income, and BMI. Steeper discount curves were associated with higher income (annual household ≥ median of $45,000) and gain framing (which indicates loss aversion). There were interactions between gender and frame, and also income and frame: Females and higher income participants showed loss aversion whereas males and lower income participants were not affected by framing. Males showed less discounting in gain frames relative to females, whereas females showed less discounting in loss frames relative to males. In gain frames, higher income participants discounted more but in loss frames there was no effect of income. We also found individual tendencies for discounting across activities: if an individual exhibited steeper discounting for one activity, they were also more likely to exhibit steeper discounting for the other activities. These results have implications for designers of interventions to encourage non-exercise physical activities, suggesting that loss-framed incentives are more effective for women and those with middle class (or greater) incomes. Furthermore loss framed incentives have more uniform impact across income brackets because people discount loss frames similarly regardless of income whereas those with middle-class incomes are not as motivated by gain frames. Our results also demonstrate a general method for examining the costs of effort associated with everyday activities.
Time dependent modeling at Mt. Etna volcano: an application to the 2005-2013 time interval
NASA Astrophysics Data System (ADS)
Cannavo', Flavio; McCaffrey, Robert; Palano, Mimmo
2015-04-01
Following the 2004-05 eruption, Mt. Etna activity has been characterized by the occurrence of a number of eruptive episodes (2006, 2008 and 2012) and more than 35 paroxysmal events (mainly during the 2011-2012 time interval). In addition, continuous downslope motion of its eastern flank has affected the volcano. This seaward motion has been characterized by some episodic phases combined with the occurrence of multiple slow slip events (SSEs). In order to obtain a comprehensive view of the time evolution of these observed features and thus provide new insight into the ground deformation pattern of Mt. Etna, here we use time-dependent modeling of the three-component daily time series of all GNSS continuous stations installed on the volcanic edifice. All GNSS data spanning the 2005-2013 time interval were processed using the GAMIT/GLOBK software (Herring et al. 2010) following the strategy described in Gonzalez and Palano (2014). Estimated GNSS daily time series were referred to the "Etn@ref" reference frame (a local reference frame computed to isolate the Mt. Etna volcanic deformation from the background tectonic pattern; Palano et al. 2010). Using these daily time series as input we performed a time-dependent, non-linear inversion using the TDEFNODE code (McCaffrey, 2009). We used TDEFNODE to invert the time series to model simultaneously the steady tectonic kinematics plus the transient volcanic and tectonic sources, thus obtaining a realistic model of the complex area. Preliminary results allow us to track, over the considered time interval, the volume changes associated to the activity of a magmatic reservoir located at a depth of about 5 km b.s.l. beneath the upper western flank of the volcano, as well as the location and associated magnitude of four SSEs below the eastern flank. In addition, we attempted a preliminary subdivision of the southern and eastern flanks of Mt. Etna into four tectonic blocks which provide a reasonable representation of the observed
Logic depth aware context independent timing model generation
NASA Astrophysics Data System (ADS)
Bhatnagar, Parag; Kumar, Naresh; Bhatnagar, P. S.; Agarwal, N. K.
2016-03-01
Logic depth aware static timing analysis involves a pre-characterized library that models the variability over the path on the basis of total timing path depth. With shrinking design geometries and rush to pack more components in a reduced size chip, hierarchical timing analysis has emerged as a stronger alternative to closing the designs however logic depth based timing analysis brings new set of challenges in generating timing models for the multiply instantiated hierarchical blocks at the chip level. In this paper, we discuss challenges imposed by logic depth in creating hierarchical timing analysis and propose a new algorithm in generating a model comprehending logic depths for multiply instantiated blocks. We demonstrate that usage of such timing model generation algorithm can significantly speedup the process of model extraction and process accuracy within 10% of the original block timing.
The Timing of Noise-Sensitive Activities in Residential Areas
NASA Technical Reports Server (NTRS)
Fields, J. M.
1985-01-01
Data from a nationally representative survey of time use was analyzed to provide estimates of the percentage of the population which is engaged in noise sensitive activities during each hour of the day on weekdays, Fridays, Saturdays and Sundays. Estimates are provided of the percentage engaged in aural communication activities at home, sleeping at home, or simply at home. The day can be roughly divided into four noise sensitivity periods consisting of two relatively steady state periods, night and day and the early morning and evening transition periods. Weekends differ from weekdays in that the morning transition period is one hour later and the numbers of people engaged in aural communication during the day at home are approximately one-half to three-quarters greater. The extent and timing of noise sensitive activities was found to be similiar for all parts of the United States, for different sizes of urban areas, and for the three seasons surveyed (September through May). The timing of activity periods does not differ greatly by sex or age even though women and people over 65 are much more likely to be at home during the daytime.
Dynamics of hippocampal ensemble activity realignment: time versus space.
Redish, A D; Rosenzweig, E S; Bohanick, J D; McNaughton, B L; Barnes, C A
2000-12-15
Whether hippocampal map realignment is coupled more strongly to position or time was studied in rats trained to shuttle on a linear track. The rats were required to run from a start box and to pause at a goal location at a fixed location relative to stable distal cues (room-aligned coordinate frame). The origin of each lap was varied by shifting the start box and track as a unit (box-aligned coordinate frame) along the direction of travel. As observed by Gothard et al. (1996a), on each lap the hippocampal activity realigned from a representation that was box-aligned to one that was room-aligned. We studied the dynamics of this transition using a measure of how well the moment-by-moment ensemble activity matched the expected activity given the location of the animal in each coordinate frame. The coherency ratio, defined as the ratio of the matches for the two coordinate systems, provides a quantitative measure of the ensemble activity alignment and was used to compare four possible descriptions of the realignment process. The elapsed time since leaving the box provided a better predictor of the occurrence of the transition than any of the three spatial parameters investigated, suggesting that the shift between coordinate systems is at least partially governed by a stochastic, time-dependent process.
The timing of noise-sensitive activities in residential areas
NASA Astrophysics Data System (ADS)
Fields, J. M.
1985-07-01
Data from a nationally representative survey of time use was analyzed to provide estimates of the percentage of the population which is engaged in noise sensitive activities during each hour of the day on weekdays, Fridays, Saturdays and Sundays. Estimates are provided of the percentage engaged in aural communication activities at home, sleeping at home, or simply at home. The day can be roughly divided into four noise sensitivity periods consisting of two relatively steady state periods, night and day and the early morning and evening transition periods. Weekends differ from weekdays in that the morning transition period is one hour later and the numbers of people engaged in aural communication during the day at home are approximately one-half to three-quarters greater. The extent and timing of noise sensitive activities was found to be similiar for all parts of the United States, for different sizes of urban areas, and for the three seasons surveyed (September through May). The timing of activity periods does not differ greatly by sex or age even though women and people over 65 are much more likely to be at home during the daytime.
Real-time transposable element activity in individual live cells.
Kim, Neil H; Lee, Gloria; Sherer, Nicholas A; Martini, K Michael; Goldenfeld, Nigel; Kuhlman, Thomas E
2016-06-28
The excision and reintegration of transposable elements (TEs) restructure their host genomes, generating cellular diversity involved in evolution, development, and the etiology of human diseases. Our current knowledge of TE behavior primarily results from bulk techniques that generate time and cell ensemble averages, but cannot capture cell-to-cell variation or local environmental and temporal variability. We have developed an experimental system based on the bacterial TE IS608 that uses fluorescent reporters to directly observe single TE excision events in individual cells in real time. We find that TE activity depends upon the TE's orientation in the genome and the amount of transposase protein in the cell. We also find that TE activity is highly variable throughout the lifetime of the cell. Upon entering stationary phase, TE activity increases in cells hereditarily predisposed to TE activity. These direct observations demonstrate that real-time live-cell imaging of evolution at the molecular and individual event level is a powerful tool for the exploration of genome plasticity in stressed cells. PMID:27298350
Real-time transposable element activity in individual live cells
Lee, Gloria; Martini, K. Michael
2016-01-01
The excision and reintegration of transposable elements (TEs) restructure their host genomes, generating cellular diversity involved in evolution, development, and the etiology of human diseases. Our current knowledge of TE behavior primarily results from bulk techniques that generate time and cell ensemble averages, but cannot capture cell-to-cell variation or local environmental and temporal variability. We have developed an experimental system based on the bacterial TE IS608 that uses fluorescent reporters to directly observe single TE excision events in individual cells in real time. We find that TE activity depends upon the TE’s orientation in the genome and the amount of transposase protein in the cell. We also find that TE activity is highly variable throughout the lifetime of the cell. Upon entering stationary phase, TE activity increases in cells hereditarily predisposed to TE activity. These direct observations demonstrate that real-time live-cell imaging of evolution at the molecular and individual event level is a powerful tool for the exploration of genome plasticity in stressed cells. PMID:27298350
A viscoelastic laryngeal muscle model with active components
Smith, Simeon L.; Hunter, Eric J.
2014-01-01
Accurate definitions of both passive and active tissue characteristics are important to laryngeal muscle modeling. This report tested the efficacy of a muscle model which added active stress components to an accurate definition of passive properties. Using the previously developed three-network Ogden model to simulate passive stress, a Hill-based contractile element stress equation was utilized for active stress calculations. Model input parameters were selected based on literature data for the canine cricothyroid muscle, and simulations were performed in order to compare the model behavior to published results for the same muscle. The model results showed good agreement with muscle behavior, including appropriate tetanus response and contraction time for isometric conditions, as well as accurate stress predictions in response to dynamic strain with activation. PMID:25235002
Hierarchical Diffusion Models for Two-Choice Response Times
ERIC Educational Resources Information Center
Vandekerckhove, Joachim; Tuerlinckx, Francis; Lee, Michael D.
2011-01-01
Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times--the Wiener diffusion…
A Lognormal Model for Response Times on Test Items
ERIC Educational Resources Information Center
van der Linden, Wim J.
2006-01-01
A lognormal model for the response times of a person on a set of test items is investigated. The model has a parameter structure analogous to the two-parameter logistic response models in item response theory, with a parameter for the speed of each person as well as parameters for the time intensity and discriminating power of each item. It is…
Time-activity relationships to VOC personal exposure factors
NASA Astrophysics Data System (ADS)
Edwards, Rufus D.; Schweizer, Christian; Llacqua, Vito; Lai, Hak Kan; Jantunen, Matti; Bayer-Oglesby, Lucy; Künzli, Nino
Social and demographic factors have been found to play a significant role in differences between time-activity patterns of population subgroups. Since time-activity patterns largely influence personal exposure to compounds as individuals move across microenvironments, exposure subgroups within the population may be defined by factors that influence daily activity patterns. Socio-demographic and environmental factors that define time-activity subgroups also define quantifiable differences in VOC personal exposures to different sources and individual compounds in the Expolis study. Significant differences in exposures to traffic-related compounds ethylbenzene, m- and p-xylene and o-xylene were observed in relation to gender, number of children and living alone. Categorization of exposures further indicated time exposed to traffic at work and time in a car as important determinants. Increased exposures to decane, nonane and undecane were observed for males, housewives and self-employed. Categorization of exposures indicated exposure subgroups related to workshop use and living downtown. Higher exposures to 3-carene and α-pinene commonly found in household cleaning products and fragrances were associated with more children, while exposures to traffic compounds ethylbenzene, m- and p-xylene and o-xylene were reduced with more children. Considerable unexplained variation remained in categorization of exposures associated with home product use and fragrances, due to individual behavior and product choice. More targeted data collection methods in VOC exposure studies for these sources should be used. Living alone was associated with decreased exposures to 2-methyl-1-propanol and 1-butanol, and traffic-related compounds. Identification of these subgroups may help to reduce the large amount of unexplained variation in VOC exposure studies. Further they may help in assessing impacts of urban planning that result in changes in behavior of individuals, resulting in shifts in
Modified active disturbance rejection control for time-delay systems.
Zhao, Shen; Gao, Zhiqiang
2014-07-01
Industrial processes are typically nonlinear, time-varying and uncertain, to which active disturbance rejection control (ADRC) has been shown to be an effective solution. The control design becomes even more challenging in the presence of time delay. In this paper, a novel modification of ADRC is proposed so that good disturbance rejection is achieved while maintaining system stability. The proposed design is shown to be more effective than the standard ADRC design for time-delay systems and is also a unified solution for stable, critical stable and unstable systems with time delay. Simulation and test results show the effectiveness and practicality of the proposed design. Linear matrix inequality (LMI) based stability analysis is provided as well.
Brain activity during interval timing depends on sensory structure.
Pfeuty, Micha; Ragot, Richard; Pouthas, Viviane
2008-04-14
Precise timing is crucial for accurate perception and action in the range of hundreds of milliseconds. One still unresolved question concerns the influence of sensory information content on timing mechanisms. Numerous studies have converged to suggest that the CNV (Contingent Negative Variation), a slow negative wave that develops between two events, notably reflects temporal processing of the interval between these two events. The present study aimed at investigating CNV activity in duration discrimination tasks using either filled (continuous tones) or empty intervals (silent periods bounded by two brief tones). Participants had to compare a test duration with a 600-ms standard. Time perception was markedly better in the 'empty' than in the 'filled' condition. Electrophysiological analyses performed on the longest test duration (794 ms) of the comparison phase revealed an effect of the sensory structure on both the CNV amplitude and CNV time-course. The CNV amplitude was larger for filled than for empty intervals, suggesting a superimposition of timing-dependent activity and sensory sustained activity. Furthermore, the CNV time-course paralleled the temporal structure of the memorized sensory event: for filled intervals, the CNV amplitude stopped increasing at 600 ms, i.e. the expected end of the continuous tone; for empty intervals, in contrast, the CNV amplitude precisely increased at 600 ms, i.e. the expected onset of the second brief tone. These results suggest that the CNV reflects the mental rehearsal of the memorized sensory event, in line with the idea that temporal processing in the sub-second range is based on sensory information.
Eaves, B.C.; Rothblum, U.G.
1990-08-01
A discounted-cost, continuous-time, infinite-horizon version of a flexible manufacturing and operator scheduling model is solved. The solution procedure is to convexify the discrete operator-assignment constraints to obtain a linear program, and then to regain the discreteness and obtain an approximate manufacturing schedule by deconvexification of the solution of the linear program over time. The strong features of the model are the accommodation of linear inequality relations among the manufacturing activities and the discrete manufacturing scheduling, whereas the weak features are intra-period relaxation of inventory availability constraints, and the absence of inventory costs, setup times, and setup charges.
Time series modeling of system self-assessment of survival
Lu, H.; Kolarik, W.J.
1999-06-01
Self-assessment of survival for a system, subsystem or component is implemented by assessing conditional performance reliability in real-time, which includes modeling and analysis of physical performance data. This paper proposes a time series analysis approach to system self-assessment (prediction) of survival. In the approach, physical performance data are modeled in a time series. The performance forecast is based on the model developed and is converted to the reliability of system survival. In contrast to a standard regression model, a time series model, using on-line data, is suitable for the real-time performance prediction. This paper illustrates an example of time series modeling and survival assessment, regarding an excessive tool edge wear failure mode for a twist drill operation.
Time-Driven Activity-Based Costing in Emergency Medicine.
Yun, Brian J; Prabhakar, Anand M; Warsh, Jonathan; Kaplan, Robert; Brennan, John; Dempsey, Kyle E; Raja, Ali S
2016-06-01
Value in emergency medicine is determined by both patient-important outcomes and the costs associated with achieving them. However, measuring true costs is challenging. Without an understanding of costs, emergency department (ED) leaders will be unable to determine which interventions might improve value for their patients. Although ongoing research may determine which outcomes are meaningful, an accurate costing system is also needed. This article reviews current costing mechanisms in the ED and their pitfalls. It then describes how time-driven activity-based costing may be superior to these current costing systems. Time-driven activity-based costing, in addition to being a more accurate costing system, can be used for process improvements in the ED. PMID:26365921
Time-Driven Activity-Based Costing in Emergency Medicine.
Yun, Brian J; Prabhakar, Anand M; Warsh, Jonathan; Kaplan, Robert; Brennan, John; Dempsey, Kyle E; Raja, Ali S
2016-06-01
Value in emergency medicine is determined by both patient-important outcomes and the costs associated with achieving them. However, measuring true costs is challenging. Without an understanding of costs, emergency department (ED) leaders will be unable to determine which interventions might improve value for their patients. Although ongoing research may determine which outcomes are meaningful, an accurate costing system is also needed. This article reviews current costing mechanisms in the ED and their pitfalls. It then describes how time-driven activity-based costing may be superior to these current costing systems. Time-driven activity-based costing, in addition to being a more accurate costing system, can be used for process improvements in the ED.
An Advanced Time Averaging Modelling Technique for Power Electronic Circuits
NASA Astrophysics Data System (ADS)
Jankuloski, Goce
For stable and efficient performance of power converters, a good mathematical model is needed. This thesis presents a new modelling technique for DC/DC and DC/AC Pulse Width Modulated (PWM) converters. The new model is more accurate than the existing modelling techniques such as State Space Averaging (SSA) and Discrete Time Modelling. Unlike the SSA model, the new modelling technique, the Advanced Time Averaging Model (ATAM) includes the averaging dynamics of the converter's output. In addition to offering enhanced model accuracy, application of linearization techniques to the ATAM enables the use of conventional linear control design tools. A controller design application demonstrates that a controller designed based on the ATAM outperforms one designed using the ubiquitous SSA model. Unlike the SSA model, ATAM for DC/AC augments the system's dynamics with the dynamics needed for subcycle fundamental contribution (SFC) calculation. This allows for controller design that is based on an exact model.
Modeling of linear time-varying systems by linear time-invariant systems of lower order.
NASA Technical Reports Server (NTRS)
Nosrati, H.; Meadows, H. E.
1973-01-01
A method for modeling linear time-varying differential systems by linear time-invariant systems of lower order is proposed, extending the results obtained by Bierman (1972) by resolving such qualities as the model stability, various possible models of differing dimensions, and the uniqueness or nonuniqueness of the model coefficient matrix. In addition to the advantages cited by Heffes and Sarachik (1969) and Bierman, often by modeling a subsystem of a larger system it is possible to analyze the overall system behavior more easily, with resulting savings in computation time.
Negriff, Sonya; Elizabeth, J. Susman; Trickett, Penelope K.
2013-01-01
There is strong evidence that early pubertal timing is associated with adolescent problem behaviors. However, there has been limited investigation of the mechanisms or developmental relationships. The present study examined longitudinal models incorporating pubertal timing, delinquency, and sexual activity in a sample of 454 adolescents (9–13 years old at enrollment; 47% females). Participants were seen for three assessments approximately 1 year apart. Characteristics of friendship networks (older friends, male friends, older male friends) were examined as mediators. Structural equation modeling was used to test these associations as well as temporal relationships between sexual activity and delinquency. Results showed that early pubertal timing at Time 1 was related to more sexual activity at Time 2, which was related to higher delinquency at Time 3, a trend mediation effect. None of the friendship variables mediated these associations. Gender or maltreatment status did not moderate the meditational pathways. The results also supported the temporal sequence of sexual activity preceding increases in delinquency. These findings reveal that early maturing adolescents may actively seek out opportunities to engage in sexual activity which appears to be risk for subsequent delinquency. PMID:21191640
Negriff, Sonya; Susman, Elizabeth J; Trickett, Penelope K
2011-10-01
There is strong evidence that early pubertal timing is associated with adolescent problem behaviors. However, there has been limited investigation of the mechanisms or developmental relationships. The present study examined longitudinal models incorporating pubertal timing, delinquency, and sexual activity in a sample of 454 adolescents (9-13 years old at enrollment; 47% females). Participants were seen for three assessments approximately 1 year apart. Characteristics of friendship networks (older friends, male friends, older male friends) were examined as mediators. Structural equation modeling was used to test these associations as well as temporal relationships between sexual activity and delinquency. Results showed that early pubertal timing at Time 1 was related to more sexual activity at Time 2, which was related to higher delinquency at Time 3, a trend mediation effect. None of the friendship variables mediated these associations. Gender or maltreatment status did not moderate the meditational pathways. The results also supported the temporal sequence of sexual activity preceding increases in delinquency. These findings reveal that early maturing adolescents may actively seek out opportunities to engage in sexual activity which appears to be risk for subsequent delinquency. PMID:21191640
Dynamic Modeling from Flight Data with Unknown Time Skews
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
2016-01-01
A method for estimating dynamic model parameters from flight data with unknown time skews is described and demonstrated. The method combines data reconstruction, nonlinear optimization, and equation-error parameter estimation in the frequency domain to accurately estimate both dynamic model parameters and the relative time skews in the data. Data from a nonlinear F-16 aircraft simulation with realistic noise, instrumentation errors, and arbitrary time skews were used to demonstrate the approach. The approach was further evaluated using flight data from a subscale jet transport aircraft, where the measured data were known to have relative time skews. Comparison of modeling results obtained from time-skewed and time-synchronized data showed that the method accurately estimates both dynamic model parameters and relative time skew parameters from flight data with unknown time skews.
Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.
Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim; Gilbert, Bob; Lake, Larry W.; Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett; Thomas, Sunil G.; Rightley, Michael J.; Rodriguez, Adolfo; Klie, Hector; Banchs, Rafael; Nunez, Emilio J.; Jablonowski, Chris
2006-11-01
survivability issues. Our findings indicate that packaging represents the most significant technical challenge associated with application of sensors in the downhole environment for long periods (5+ years) of time. These issues are described in detail within the report. The impact of successful reservoir monitoring programs and coincident improved reservoir management is measured by the production of additional oil and gas volumes from existing reservoirs, revitalization of nearly depleted reservoirs, possible re-establishment of already abandoned reservoirs, and improved economics for all cases. Smart Well monitoring provides the means to understand how a reservoir process is developing and to provide active reservoir management. At the same time it also provides data for developing high-fidelity simulation models. This work has been a joint effort with Sandia National Laboratories and UT-Austin's Bureau of Economic Geology, Department of Petroleum and Geosystems Engineering, and the Institute of Computational and Engineering Mathematics.
Revisiting the Time Trade-off Hypothesis: Work, Organized Activities, and Academics during College
Maggs, Jennifer L.
2014-01-01
How adolescents spend their time has long-term implications for their educational, health, and labor market outcomes, yet surprisingly little research has explored the time use of students across days and semesters. The current study used longitudinal daily diary data from a sample of college students attending a large public university in the Northeastern US (n = 726, Mage = 18.4) that was followed for 14 days within each of 7 semesters (for up to 98 diary days per student). The study had two primary aims. The first aim was to explore demographic correlates of employment time, organized activity time, and academic time. The second aim was to provide a rigorous test of the time trade-off hypothesis, which suggests that students will spend less time on academics when they spend more time on employment and extracurricular activities. The results demonstrated that time use varied by gender, parental education, and race/ethnicity. Furthermore, the results from multi-level models provided some support for the time trade-off hypothesis, although associations varied by the activity type and whether the day was a weekend. More time spent on employment was linked to less time spent on academics across days and semesters whereas organized activities were associated with less time on academics at the daily level only. The negative associations between employment and academics were most pronounced on weekdays. These results suggest that students may balance certain activities across days, whereas other activities may be in competition over longer time frames (i.e., semesters). PMID:25381597
A Measurement Model for Likert Responses that Incorporates Response Time
ERIC Educational Resources Information Center
Ferrando, Pere J.; Lorenzo-Seva, Urbano
2007-01-01
This article describes a model for response times that is proposed as a supplement to the usual factor-analytic model for responses to graded or more continuous typical-response items. The use of the proposed model together with the factor model provides additional information about the respondent and can potentially increase the accuracy of the…
Grade of Membership Response Time Model for Detecting Guessing Behaviors
ERIC Educational Resources Information Center
Pokropek, Artur
2016-01-01
A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to…
Acoustic FMRI noise: linear time-invariant system model.
Rizzo Sierra, Carlos V; Versluis, Maarten J; Hoogduin, Johannes M; Duifhuis, Hendrikus Diek
2008-09-01
Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic noise is a useful step to its reduction. To study acoustic noise, the MR scanner is modeled as a linear electroacoustical system generating sound pressure signals proportional to the time derivative of the input gradient currents. The transfer function of one MR scanner is determined for two different input specifications: 1) by using the gradient waveform calculated by the scanner software and 2) by using a recording of the gradient current. Up to 4 kHz, the first method is shown as reliable as the second one, and its use is encouraged when direct measurements of gradient currents are not possible. Additionally, the linear order and average damping properties of the gradient coil system are determined by impulse response analysis. Since fMRI is often based on echo planar imaging (EPI) sequences, a useful validation of the transfer function prediction ability can be obtained by calculating the acoustic output for the EPI sequence. We found a predicted sound pressure level (SPL) for the EPI sequence of 104 dB SPL compared to a measured value of 102 dB SPL. As yet, the predicted EPI pressure waveform shows similarity as well as some differences with the directly measured EPI pressure waveform.
Consensus time and conformity in the adaptive voter model
NASA Astrophysics Data System (ADS)
Rogers, Tim; Gross, Thilo
2013-09-01
The adaptive voter model is a paradigmatic model in the study of opinion formation. Here we propose an extension for this model, in which conflicts are resolved by obtaining another opinion, and analytically study the time required for consensus to emerge. Our results shed light on the rich phenomenology of both the original and extended adaptive voter models, including a dynamical phase transition in the scaling behavior of the mean time to consensus.
A Multiscale Survival Process for Modeling Human Activity Patterns
Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang
2016-01-01
Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications. PMID:27023682
Frequency and time domain modeling of high speed amplifier
NASA Astrophysics Data System (ADS)
Opalska, Katarzyna
2015-09-01
The paper presents the lumped model of high speed amplifier useful for frequency and time domain (also large signal) simulation. Model is constructed on the basis of two-domain device measurements, namely small signal frequency parameters and time response to the input step of varying amplitude. Rational approximation of frequency domain data leads to small signal model composed of RLC subcircuits and controlled sources. Next, the model is complimented with the nonlinearities identified from time-domain measurements, including those taken for large input signals. Final amplifier model implemented in SPICE simulator is shown to correctly render the behavior of the device over the wide variety of operating conditions.
Discursive positionings and emotions in modelling activities
NASA Astrophysics Data System (ADS)
Daher, Wajeeh
2015-11-01
Mathematical modelling is suggested as an activity through which students engage in meaningful mathematics. In the current research, the modelling activity of a group of four seventh-grade students was analysed using the discursive analysis framework. The research findings show that the positionings and emotions of the group members during their participation in the modelling activity changed as the activity proceeded. Overall, it can be said that three of the four group members acted as insiders, while the fourth acted as an outsider, and only, towards the end of the group's work on the activity, he acted as an insider. Moreover, the research findings point at four factors that affected the group members' positionings and emotions during the modelling activity: the member's characteristics, the member's history of learning experiences, the activity characteristics and the modelling phases. Furthermore, the different positionings of the group members in the different modelling phases were accompanied by different emotions experienced by them, where being an insider and a collaborator resulted in positive emotions, while being an outsider resulted in negative emotions.
Model Assessment and Optimization Using a Flow Time Transformation
NASA Astrophysics Data System (ADS)
Smith, T. J.; Marshall, L. A.; McGlynn, B. L.
2012-12-01
Hydrologic modeling is a particularly complex problem that is commonly confronted with complications due to multiple dominant streamflow states, temporal switching of streamflow generation mechanisms, and dynamic responses to model inputs based on antecedent conditions. These complexities can inhibit the development of model structures and their fitting to observed data. As a result of these complexities and the heterogeneity that can exist within a catchment, optimization techniques are typically employed to obtain reasonable estimates of model parameters. However, when calibrating a model, the cost function itself plays a large role in determining the "optimal" model parameters. In this study, we introduce a transformation that allows for the estimation of model parameters in the "flow time" domain. The flow time transformation dynamically weights streamflows in the time domain, effectively stretching time during high streamflows and compressing time during low streamflows. Given the impact of cost functions on model optimization, such transformations focus on the hydrologic fluxes themselves rather than on equal time weighting common to traditional approaches. The utility of such a transform is of particular note to applications concerned with total hydrologic flux (water resources management, nutrient loading, etc.). The flow time approach can improve the predictive consistency of total fluxes in hydrologic models and provide insights into model performance by highlighting model strengths and deficiencies in an alternate modeling domain. Flow time transformations can also better remove positive skew from the streamflow time series, resulting in improved model fits, satisfaction of the normality assumption of model residuals, and enhanced uncertainty quantification. We illustrate the value of this transformation for two distinct sets of catchment conditions (snow-dominated and subtropical).
Refining Time-Activity Classification of Human Subjects Using the Global Positioning System
Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun
2016-01-01
Background Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Methods Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Results Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. Conclusions The random forests classification model can achieve high accuracy for the four major time-activity
Activity Time Budget during Foraging Trips of Emperor Penguins
Watanabe, Shinichi; Sato, Katsufumi; Ponganis, Paul J.
2012-01-01
We developed an automated method using depth and one axis of body acceleration data recorded by animal-borne data loggers to identify activities of penguins over long-term deployments. Using this technique, we evaluated the activity time budget of emperor penguins (n = 10) both in water and on sea ice during foraging trips in chick-rearing season. During the foraging trips, emperor penguins alternated dive bouts (4.8±4.5 h) and rest periods on sea ice (2.5±2.3 h). After recorder deployment and release near the colony, the birds spent 17.9±8.4% of their time traveling until they reached the ice edge. Once at the ice edge, they stayed there more than 4 hours before the first dive. After the first dive, the mean proportions of time spent on the ice and in water were 30.8±7.4% and 69.2±7.4%, respectively. When in the water, they spent 67.9±3.1% of time making dives deeper than 5 m. Dive activity had no typical diurnal pattern for individual birds. While in the water between dives, the birds had short resting periods (1.2±1.7 min) and periods of swimming at depths shallower than 5 m (0.25±0.38 min). When the birds were on the ice, they primarily used time for resting (90.3±4.1% of time) and spent only 9.7±4.1% of time traveling. Thus, it appears that, during foraging trips at sea, emperor penguins traveled during dives >5 m depth, and that sea ice was primarily used for resting. Sea ice probably provides refuge from natural predators such as leopard seals. We also suggest that 24 hours of sunlight and the cycling of dive bouts with short rest periods on sea ice allow emperor penguins to dive continuously throughout the day during foraging trips to sea. PMID:23185608
NASA Technical Reports Server (NTRS)
Eckhardt, D. E., Jr.
1979-01-01
A model of a central processor (CPU) which services background applications in the presence of time critical activity is presented. The CPU is viewed as an M/M/1 queueing system subject to periodic interrupts by deterministic, time critical process. The Laplace transform of the distribution of service times for the background applications is developed. The use of state of the art queueing models for studying the background processing capability of time critical computer systems is discussed and the results of a model validation study which support this application of queueing models are presented.
Efficient Fully Implicit Time Integration Methods for Modeling Cardiac Dynamics
Rose, Donald J.; Henriquez, Craig S.
2013-01-01
Implicit methods are well known to have greater stability than explicit methods for stiff systems, but they often are not used in practice due to perceived computational complexity. This paper applies the Backward Euler method and a second-order one-step two-stage composite backward differentiation formula (C-BDF2) for the monodomain equations arising from mathematically modeling the electrical activity of the heart. The C-BDF2 scheme is an L-stable implicit time integration method and easily implementable. It uses the simplest Forward Euler and Backward Euler methods as fundamental building blocks. The nonlinear system resulting from application of the Backward Euler method for the monodomain equations is solved for the first time by a nonlinear elimination method, which eliminates local and non-symmetric components by using a Jacobian-free Newton solver, called Newton-Krylov solver. Unlike other fully implicit methods proposed for the monodomain equations in the literature, the Jacobian of the global system after the nonlinear elimination has much smaller size, is symmetric and possibly positive definite, which can be solved efficiently by standard optimal solvers. Numerical results are presented demonstrating that the C-BDF2 scheme can yield accurate results with less CPU times than explicit methods for both a single patch and spatially extended domains. PMID:19126449
Multiple time scales in multi-state models.
Iacobelli, Simona; Carstensen, Bendix
2013-12-30
In multi-state models, it has been the tradition to model all transition intensities on one time scale, usually the time since entry into the study ('clock-forward' approach). The effect of time since an intermediate event has been accommodated either by changing the time scale to time since entry to the new state ('clock-back' approach) or by including the time at entry to the new state as a covariate. In this paper, we argue that the choice of time scale for the various transitions in a multi-state model should be dealt with as an empirical question, as also the question of whether a single time scale is sufficient. We illustrate that these questions are best addressed by using parametric models for the transition rates, as opposed to the traditional Cox-model-based approaches. Specific advantages are that dependence of failure rates on multiple time scales can be made explicit and described in informative graphical displays. Using a single common time scale for all transitions greatly facilitates computations of probabilities of being in a particular state at a given time, because the machinery from the theory of Markov chains can be applied. However, a realistic model for transition rates is preferable, especially when the focus is not on prediction of final outcomes from start but on the analysis of instantaneous risk or on dynamic prediction. We illustrate the various approaches using a data set from stem cell transplant in leukemia and provide supplementary online material in R. PMID:24027131
NASA Astrophysics Data System (ADS)
Smith, T. J.; Marshall, L. A.; McGlynn, B. L.
2015-12-01
Streamflow modeling is highly complex. Beyond the identification and mapping of dominant runoff processes to mathematical models, additional challenges are posed by the switching of dominant streamflow generation mechanisms temporally and dynamic catchment responses to precipitation inputs based on antecedent conditions. As a result, model calibration is required to obtain parameter values that produce acceptable simulations of the streamflow hydrograph. Typical calibration approaches assign equal weight to all observations to determine the best fit over the simulation period. However, the objective function can be biased toward (i.e., implicitly weight) certain parts of the hydrograph (e.g., high streamflows). Data transformations (e.g., logarithmic or square root) scale the magnitude of the observations and are commonly used in the calibration process to reduce implicit weighting or better represent assumptions about the model residuals. Here, we consider a time domain data transformation rather than the more common data domain approaches. Flow-corrected time was previously employed in the transit time modeling literature. Conceptually, it stretches time during high streamflow and compresses time during low streamflow periods. Therefore, streamflow is dynamically weighted in the time domain, with greater weight assigned to periods with larger hydrologic flux. Here, we explore the utility of the flow-corrected time transformation in improving model performance of the Catchment Connectivity Model. Model process fidelity was assessed directly using shallow groundwater connectivity data collected at Tenderfoot Creek Experimental Forest. Our analysis highlights the impact of data transformations on model consistency and parameter sensitivity.
Interpersonal distance modeling during fighting activities.
Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves
2010-10-01
The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities. PMID:21051791
Modeling highway travel time distribution with conditional probability models
Oliveira Neto, Francisco Moraes; Chin, Shih-Miao; Hwang, Ho-Ling; Han, Lee
2014-01-01
ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).
Analysis of the Palierne model by relaxation time spectrum
NASA Astrophysics Data System (ADS)
Kwon, Mi Kyung; Cho, Kwang Soo
2016-02-01
Viscoelasticity of immiscible polymer blends is affected by relaxation of the interface. Several attempts have been made for linear viscoelasticity of immiscible polymer blends. The Palierne model (1990) and the Gramespacher-Meissner model (1992) are representative. The Gramespacher-Meissner model consists of two parts: ingredients and interface. Moreover, it provides us the formula of the peak of interface in weighted relaxation time spectrum, which enables us to analyze the characteristics relating to interface more obviously. However, the Gramespacher-Meissner model is a kind of empirical model. Contrary to the Gramespacher-Meissner model, the Palierne model was derived in a rigorous manner. In this study, we investigated the Palierne model through the picture of the Gramespacher-Meissner model. We calculated moduli of immiscible blend using two models and obtained the weighted relaxation time spectra of them. The fixed-point iteration of Cho and Park (2013) was used in order to determine the weighted relaxation spectra.
Integrated active sensor system for real time vibration monitoring
Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue
2015-01-01
We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems. PMID:26538293
Integrated active sensor system for real time vibration monitoring.
Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue
2015-11-05
We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.
Computational Modeling of Semiconductor Dynamics at Femtosecond Time Scales
NASA Technical Reports Server (NTRS)
Agrawal, Govind P.; Goorjian, Peter M.
1998-01-01
The Interchange No. NCC2-5149 deals with the emerging technology of photonic (or optoelectronic) integrated circuits (PICs or OEICs). In PICs, optical and electronic components are grown together on the same chip. To build such devices and subsystems, one needs to model the entire chip. PICs are useful for building components for integrated optical transmitters, integrated optical receivers, optical data storage systems, optical interconnects, and optical computers. For example, the current commercial rate for optical data transmission is 2.5 gigabits per second, whereas the use of shorter pulses to improve optical transmission rates would yield an increase of 400 to 1000 times. The improved optical data transmitters would be used in telecommunications networks and computer local-area networks. Also, these components can be applied to activities in space, such as satellite to satellite communications, when the data transmissions are made at optical frequencies. The research project consisted of developing accurate computer modeling of electromagnetic wave propagation in semiconductors. Such modeling is necessary for the successful development of PICs. More specifically, these computer codes would enable the modeling of such devices, including their subsystems, such as semiconductor lasers and semiconductor amplifiers in which there is femtosecond pulse propagation. Presently, there are no computer codes that could provide this modeling. Current codes do not solve the full vector, nonlinear, Maxwell's equations, which are required for these short pulses and also current codes do not solve the semiconductor Bloch equations, which are required to accurately describe the material's interaction with femtosecond pulses. The research performed under NCC2-5149 solves the combined Maxwell's and Bloch's equations.
Latent Hierarchical Model of Temporal Structure for Complex Activity Classification.
Wang, Limin; Qiao, Yu; Tang, Xiaoou
2014-02-01
Modeling the temporal structure of sub-activities is an important yet challenging problem in complex activity classification. This paper proposes a latent hierarchical model (LHM) to describe the decomposition of complex activity into sub-activities in a hierarchical way. The LHM has a tree-structure, where each node corresponds to a video segment (sub-activity) at certain temporal scale. The starting and ending time points of each sub-activity are represented by two latent variables, which are automatically determined during the inference process. We formulate the training problem of the LHM in a latent kernelized SVM framework and develop an efficient cascade inference method to speed up classification. The advantages of our methods come from: 1) LHM models the complex activity with a deep structure, which is decomposed into sub-activities in a coarse-to-fine manner and 2) the starting and ending time points of each segment are adaptively determined to deal with the temporal displacement and duration variation of sub-activity. We conduct experiments on three datasets: 1) the KTH; 2) the Hollywood2; and 3) the Olympic Sports. The experimental results show the effectiveness of the LHM in complex activity classification. With dense features, our LHM achieves the state-of-the-art performance on the Hollywood2 dataset and the Olympic Sports dataset.
Investigating Nitrogen Pollution: Activities and Models.
ERIC Educational Resources Information Center
Green Teacher, 2000
2000-01-01
Introduces activities on nitrogen, nitrogen pollution from school commuters, nitrogen response in native and introduced species, and nutrient loading models. These activities help students determine the nitrogen contribution from their parents' cars, test native plant responses to nitrogen, and experiment with the results of removing water from…
Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models
ERIC Educational Resources Information Center
Price, Larry R.
2012-01-01
The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…
Modeling stream fish distributions using interval-censored detection times.
Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro
2016-08-01
Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it
Motivation and Barriers for Leisure-Time Physical Activity in Socioeconomically Disadvantaged Women
Santos, Inês; Ball, Kylie; Crawford, David; Teixeira, Pedro J.
2016-01-01
Introduction The aim of this study was to examine cross-sectional and longitudinal associations between motivation and barriers for physical activity, and physical activity behavior in women living in socioeconomic disadvantage. This study also examined whether weight control intentions moderate those associations. Methods Data from 1664 women aged 18–46 years was collected at baseline and three-year follow-up as part of the Resilience for Eating and Activity Despite Inequality study. In mail-based surveys, women reported sociodemographic and neighborhood environmental characteristics, intrinsic motivation, goals and perceived family barriers to be active, weight control intentions and leisure-time physical activity (assessed through the IPAQ-L). Linear regression models assessed the association of intrinsic motivation, goals and barriers with physical activity at baseline and follow-up, adjusting for environmental characteristics and also physical activity at baseline (for longitudinal analyses), and the moderating effects of weight control intentions were examined. Results Intrinsic motivation and, to a lesser extent, appearance and relaxation goals for being physically active were consistently associated with leisure-time physical activity at baseline and follow-up. Perceived family barriers, health, fitness, weight and stress relief goals were associated with leisure-time physical activity only at baseline. Moderated regression analyses revealed that weight control intentions significantly moderated the association between weight goals and leisure-time physical activity at baseline (β = 0.538, 99% CI = 0.057, 0.990) and between intrinsic motivation and leisure-time physical activity at follow-up (β = 0.666, 99% CI = 0.188, 1.145). For women actively trying to control their weight, intrinsic motivation was significantly associated with leisure-time physical activity at follow-up (β = 0.184, 99% CI = 0.097, 0.313). Conclusions Results suggest that
Time delay between cardiac and brain activity during sleep transitions
NASA Astrophysics Data System (ADS)
Long, Xi; Arends, Johan B.; Aarts, Ronald M.; Haakma, Reinder; Fonseca, Pedro; Rolink, Jérôme
2015-04-01
Human sleep consists of wake, rapid-eye-movement (REM) sleep, and non-REM (NREM) sleep that includes light and deep sleep stages. This work investigated the time delay between changes of cardiac and brain activity for sleep transitions. Here, the brain activity was quantified by electroencephalographic (EEG) mean frequency and the cardiac parameters included heart rate, standard deviation of heartbeat intervals, and their low- and high-frequency spectral powers. Using a cross-correlation analysis, we found that the cardiac variations during wake-sleep and NREM sleep transitions preceded the EEG changes by 1-3 min but this was not the case for REM sleep transitions. These important findings can be further used to predict the onset and ending of some sleep stages in an early manner.
Phenotypic models of T cell activation.
Lever, Melissa; Maini, Philip K; van der Merwe, P Anton; Dushek, Omer
2014-09-01
T cell activation is a crucial checkpoint in adaptive immunity, and this activation depends on the binding parameters that govern the interactions between T cell receptors (TCRs) and peptide-MHC complexes (pMHC complexes). Despite extensive experimental studies, the relationship between the TCR-pMHC binding parameters and T cell activation remains controversial. To make sense of conflicting experimental data, a variety of verbal and mathematical models have been proposed. However, it is currently unclear which model or models are consistent or inconsistent with experimental data. A key problem is that a direct comparison between the models has not been carried out, in part because they have been formulated in different frameworks. For this Analysis article, we reformulated published models of T cell activation into phenotypic models, which allowed us to directly compare them. We find that a kinetic proofreading model that is modified to include limited signalling is consistent with the majority of published data. This model makes the intriguing prediction that the stimulation hierarchy of two different pMHC complexes (or two different TCRs that are specific for the same pMHC complex) may reverse at different pMHC concentrations.
Multi-model Cross Pollination in Time via Data Assimilation
NASA Astrophysics Data System (ADS)
Du, H.; Smith, L. A.
2015-12-01
Nonlinear dynamical systems are frequently used to model physical processes including the fluid dynamics, weather and climate. Uncertainty in the observations makes identification of the exact state impossible for a chaotic nonlinear system, this suggests forecasts based on an ensemble of initial conditions to reflect the inescapable uncertainty in the observations. In general, when forecasting real systems the model class from which the particular model equations are drawn does not contain a process that is able to generate trajectories consistent with the data. Multi-model ensembles have become popular tools to account for uncertainties due to observational noise and structural model error in weather and climate simulation-based predictions on time scales from days to seasons and centuries. There have been some promising results suggesting that the multi-model ensemble forecasts outperform the single model forecasts. The current multi-model ensemble forecasts are focused on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently, every single model is likely to contain different local dynamical information from that of other models. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information from each individual model operationally in time. The proposed method generates model states in time via applying advanced nonlinear data assimilation scheme(s) over the multi-model forecasts. The proposed approach is demonstrated to outperform the traditional statistically post-processing in the 40-dimensional Lorenz96 flow. It is suggested that this illustration could form the basis for more general results which
Nonlinear techniques for forecasting solar activity directly from its time series
NASA Technical Reports Server (NTRS)
Ashrafi, S.; Roszman, L.; Cooley, J.
1993-01-01
This paper presents numerical techniques for constructing nonlinear predictive models to forecast solar flux directly from its time series. This approach makes it possible to extract dynamical in variants of our system without reference to any underlying solar physics. We consider the dynamical evolution of solar activity in a reconstructed phase space that captures the attractor (strange), give a procedure for constructing a predictor of future solar activity, and discuss extraction of dynamical invariants such as Lyapunov exponents and attractor dimension.
Nonlinear techniques for forecasting solar activity directly from its time series
NASA Technical Reports Server (NTRS)
Ashrafi, S.; Roszman, L.; Cooley, J.
1992-01-01
Numerical techniques for constructing nonlinear predictive models to forecast solar flux directly from its time series are presented. This approach makes it possible to extract dynamical invariants of our system without reference to any underlying solar physics. We consider the dynamical evolution of solar activity in a reconstructed phase space that captures the attractor (strange), given a procedure for constructing a predictor of future solar activity, and discuss extraction of dynamical invariants such as Lyapunov exponents and attractor dimension.
Modelling the Active Hearing Process in Mosquitoes
NASA Astrophysics Data System (ADS)
Avitabile, Daniele; Homer, Martin; Jackson, Joe; Robert, Daniel; Champneys, Alan
2011-11-01
A simple microscopic mechanistic model is described of the active amplification within the Johnston's organ of the mosquito species Toxorhynchites brevipalpis. The model is based on the description of the antenna as a forced-damped oscillator coupled to a set of active threads (ensembles of scolopidia) that provide an impulsive force when they twitch. This twitching is in turn controlled by channels that are opened and closed if the antennal oscillation reaches a critical amplitude. The model matches both qualitatively and quantitatively with recent experiments. New results are presented using mathematical homogenization techniques to derive a mesoscopic model as a simple oscillator with nonlinear force and damping characteristics. It is shown how the results from this new model closely resemble those from the microscopic model as the number of threads approach physiologically correct values.
Electromagnetic modeling of active silicon nanocrystal waveguides.
Redding, Brandon; Shi, Shouyuan; Creazzo, Tim; Prather, Dennis W
2008-06-01
In this paper we propose an electromagnetic analysis of active silicon nano-crystal (Si-nc) waveguide devices. To account for the nonlinearity in the active medium we introduce a four level rate equation model whose parameters are based on experimentally reported material properties. The electromagnetic polarization serves to couple the quantum mechanical and electromagnetic behavior within the ADE-FDTD scheme. The developed modeling tool is used to simulate waveguide amplifiers, enhanced spontaneous emission microcavities, and the temporal lasing dynamics of active Si-nc based devices.
Time-frequency analysis of rhythmic masticatory muscle activity.
Farella, Mauro; Palla, Sandro; Gallo, Luigi Maria
2009-06-01
The aim of this study was to develop and validate under laboratory conditions an algorithm for a time-frequency analysis of rhythmic masticatory muscle activity (RMMA). The algorithm baseband demodulated the electromyographic (EMG) signal to provide a frequency versus time representation. Using appropriate thresholds for frequency and power parameters, it was possible to automatically assess the features of RMMA without examiner interaction. The algorithm was first tested using synthetic EMG signals and then using real EMG signals obtained from the masticatory muscles of 11 human subjects who underwent well-defined rhythmic, static, and possible confounding oral tasks. The accuracy of detection was quantified by receiver operating characteristics (ROC) curves. Sensitivity and specificity values were > or =90% and > or =96%, respectively. The areas under the ROC curves were > or =95% (standard error +/-0.1%). The proposed approach represents a promising tool to effectively investigate rhythmical contractions of the masticatory muscles.
A Markov switching model for annual hydrologic time series
NASA Astrophysics Data System (ADS)
Akıntuǧ, B.; Rasmussen, P. F.
2005-09-01
This paper investigates the properties of Markov switching (MS) models (also known as hidden Markov models) for generating annual time series. This type of model has been used in a number of recent studies in the water resources literature. The model considered here assumes that climate is switching between M states and that the state sequence can be described by a Markov chain. Observations are assumed to be drawn from a normal distribution whose parameters depend on the state variable. We present the stochastic properties of this class of models along with procedures for model identification and parameter estimation. Although, at a first glance, MS models appear to be quite different from ARMA models, we show that it is possible to find an ARMA model that has the same autocorrelation function and the same marginal distribution as any given MS model. Hence, despite the difference in model structure, there are strong similarities between MS and ARMA models. MS and ARMA models are applied to the time series of mean annual discharge of the Niagara River. Although it is difficult to draw any general conclusion from a single case study, it appears that MS models (and ARMA models derived from MS models) generally have stronger autocorrelation at higher lags than ARMA models estimated by conventional maximum likelihood. This may be an important property if the purpose of the study is the analysis of multiyear droughts.
Model for the Distribution of Aftershock Interoccurrence Times
Shcherbakov, Robert; Yakovlev, Gleb; Rundle, John B.; Turcotte, Donald L.
2005-11-18
In this work the distribution of interoccurrence times between earthquakes in aftershock sequences is analyzed and a model based on a nonhomogeneous Poisson (NHP) process is proposed to quantify the observed scaling. In this model the generalized Omori's law for the decay of aftershocks is used as a time-dependent rate in the NHP process. The analytically derived distribution of interoccurrence times is applied to several major aftershock sequences in California to confirm the validity of the proposed hypothesis.
Model for the distribution of aftershock interoccurrence times.
Shcherbakov, Robert; Yakovlev, Gleb; Turcotte, Donald L; Rundle, John B
2005-11-18
In this work the distribution of interoccurrence times between earthquakes in aftershock sequences is analyzed and a model based on a nonhomogeneous Poisson (NHP) process is proposed to quantify the observed scaling. In this model the generalized Omori's law for the decay of aftershocks is used as a time-dependent rate in the NHP process. The analytically derived distribution of interoccurrence times is applied to several major aftershock sequences in California to confirm the validity of the proposed hypothesis.
Networks maximizing the consensus time of voter models
NASA Astrophysics Data System (ADS)
Iwamasa, Yuni; Masuda, Naoki
2014-07-01
We explore the networks that yield the largest mean consensus time of voter models under different update rules. By analytical and numerical means, we show that the so-called lollipop graph, barbell graph, and double-star graph maximize the mean consensus time under the update rules called the link dynamics, voter model, and invasion process, respectively. For each update rule, the largest mean consensus time scales as O (N3), where N is the number of nodes in the network.
The use of synthetic input sequences in time series modeling
NASA Astrophysics Data System (ADS)
de Oliveira, Dair José; Letellier, Christophe; Gomes, Murilo E. D.; Aguirre, Luis A.
2008-08-01
In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure.
The Influence of Self-Determination in Physical Education on Leisure-Time Physical Activity Behavior
ERIC Educational Resources Information Center
Shen, Bo; McCaughtry, Nate; Martin, Jeffrey
2007-01-01
Using a multitheory approach, this study was designed to investigate the influence of urban adolescents' perceived autonomy and competence in physical education on their physical activity intentions and behaviors during leisure time. A transcontextual model was hypothesized and tested. Urban adolescents (N = 653, ages 11-15 years) completed…
Timetabling and Extracurricular Activities: A Study of Teachers' Attitudes towards Preparation Time
ERIC Educational Resources Information Center
Whiteley, Robert F.; Richard, George
2012-01-01
Many models of timetabling exist in secondary schools in Western educational jurisdictions. This study examines whether or not teachers teaching a full course load without preparation time during a semester are willing to volunteer to participate in extracurricular activities. This research was conducted in a rural school district in British…
Out-of-School Time Activity Participation among US-Immigrant Youth
ERIC Educational Resources Information Center
Yu, Stella M.; Newport-Berra, McHale; Liu, Jihong
2015-01-01
Background: Structured out-of-school time (OST) activities are associated with positive academic and psychosocial outcomes. Methods: Data came from the 2007 National Survey of Children's Health, restricted to 36,132 youth aged 12-17?years. Logistic regression models were used to examine the joint effects of race/ethnicity and immigrant family type…
Space-time with a fluctuating metric tensor model
NASA Astrophysics Data System (ADS)
Morozov, A. N.
2016-07-01
A presented physical time model is based on the assumption that time is a random Poisson process, the intensity of which depends on natural irreversible processes. The introduction of metric tensor space-time fluctuations allowing describing the impact of stochastic gravitational background has been demonstrated. The use of spectral lines broadening measurement for the registration of relic gravitational waves has been suggested.
A Kinetic Model of Active Extensile Bundles
NASA Astrophysics Data System (ADS)
Goldstein, Daniel; Chakraborty, Bulbul; Baskaran, Aparna
Recent experiments in active filament networks reveal interesting rheological properties (Dan Chen: APS March Meeting 2015 D49.00001). This system consumes ATP to produce an extensile motion in bundles of microtubules. This extension then leads to self generated stresses and spontaneous flows. We propose a minimal model where the activity is modeled by self-extending bundles that are part of a cross linked network. This network can reorganize itself through buckling of extending filaments and merging events that alter the topology of the network. We numerically simulate this minimal kinetic model and examine the emergent rheological properties and determine how stresses are generated by the extensile activity. We will present results that focus on the effects of confinement and network connectivity of the bundles on stress fluctuations and response of an active gel.
Pre & Postsynaptic Tuning of Action Potential Timing by Spontaneous GABAergic Activity
Caillard, Olivier
2011-01-01
Frequency and timing of action potential discharge are key elements for coding and transfer of information between neurons. The nature and location of the synaptic contacts, the biophysical parameters of the receptor-operated channels and their kinetics of activation are major determinants of the firing behaviour of each individual neuron. Ultimately the intrinsic excitability of each neuron determines the input-output function. Here we evaluate the influence of spontaneous GABAergic synaptic activity on the timing of action potentials in Layer 2/3 pyramidal neurones in acute brain slices from the somatosensory cortex of young rats. Somatic dynamic current injection to mimic synaptic input events was employed, together with a simple computational model that reproduce subthreshold membrane properties. Besides the well-documented control of neuronal excitability, spontaneous background GABAergic activity has a major detrimental effect on spike timing. In fact, GABAA receptors tune the relationship between the excitability and fidelity of pyramidal neurons via a postsynaptic (the reversal potential for GABAA activity) and a presynaptic (the frequency of spontaneous activity) mechanism. GABAergic activity can decrease or increase the excitability of pyramidal neurones, depending on the difference between the reversal potential for GABAA receptors and the threshold for action potential. In contrast, spike time jitter can only be increased proportionally to the difference between these two membrane potentials. Changes in excitability by background GABAergic activity can therefore only be associated with deterioration of the reliability of spike timing. PMID:21789249
Yang, Xiaobao; Abdel-Aty, Mohamed; Huan, Mei; Peng, Yichuan; Gao, Ziyou
2015-09-01
The waiting process is crucial to pedestrians in the street-crossing behavior. Once pedestrians terminate their waiting behavior during the red light period, they would cross against the red light and put themselves in danger. A joint hazard-based duration model is developed to investigate the effect of various covariates on pedestrian crossing behavior and to estimate pedestrian waiting times at signalized intersections. A total of 1181 pedestrians approaching the intersections during red light periods were observed in Beijing, China. Pedestrian crossing behaviors are classified into immediate crossing behavior and waiting behavior. The probability and effect of various covariates for pedestrians' immediate crossing behavior are identified by a logit model. Four accelerated failure time duration models based on the exponential, Weibull, lognormal and log-logistic distributions are proposed to examine the significant risk factors affecting duration times for pedestrians' waiting behavior. A joint duration model is developed to estimate pedestrian waiting times. Moreover, unobserved heterogeneity is considered in the proposed model. The results indicate that the Weibull AFT model with shared frailty is appropriate for modelling pedestrian waiting durations. Failure to account for heterogeneity would significantly underestimate the effects of covariates on waiting duration times. The proposed model provides a better understanding of pedestrian crossing behavior and more accurate estimation of pedestrian waiting times. It may be applicable in traffic system analysis in developing countries with high flow of mixed traffic.
NASA Technical Reports Server (NTRS)
He, Yuning
2015-01-01
Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.
NASA Astrophysics Data System (ADS)
Mojtaba Tabatabaeipour, Seyed
2015-08-01
Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed. In set-membership approaches, instead of a point-wise estimation of the states, a set-valued estimation of them is computed. If this set becomes empty the given model of the system is not consistent with the measurements. Therefore, the model is falsified. When more than one model of the system remains un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved by a number of linear and quadratic programming problems, which result in a computationally efficient algorithm. The method is tested on a numerical example as well as on the pitch actuator of a benchmark wind turbine.
Time representation in reinforcement learning models of the basal ganglia
Gershman, Samuel J.; Moustafa, Ahmed A.; Ludvig, Elliot A.
2014-01-01
Reinforcement learning (RL) models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between RL models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both RL and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired. PMID:24409138
Madsen, Kristine A.; McCulloch, Charles; Crawford, Patricia B.
2009-01-01
Objectives To determine if parent modeling of physical activity has a differential impact on girls’ physical activity (PA) by race, if the association declines over time, and to assess the contribution of parent modeling to girls’ activity relative to other potential predictors. Study design Longitudinal examination of parent modeling’s impact on future log transformed metabolic equivalents (log METs) of leisure-time PA among 1213 African-American and 1166 Caucasian girls in the NHLBI Growth and Health Study, from age 9-10 through 18-19 years, using linear regression. Race interaction terms and time trends were examined. Results Girls’ perceptions of parent modeling significantly predicted future log METs in each study year; associations remained stable over time and were similar by race. Girls’ perception of parent PA better predicted girl log METs than did parent self-report. On average, girls reporting that their parents exercised ≥3x/week were about 50% more active than girls with sedentary parents. Conclusions Girls’ perception of parent activity predicts PA for girls throughout adolescence, despite age-associated decreases in PA. We did not find differences in this association by race. Interventions designed to increase parental activity may improve parent health, positively influence daughters’ activity, and begin to address disparities in cardiovascular health. PMID:18789455
Finite-frequency model reduction of continuous-time switched linear systems with average dwell time
NASA Astrophysics Data System (ADS)
Ding, Da-Wei; Du, Xin
2016-11-01
This paper deals with the model reduction problem of continuous-time switched linear systems with finite-frequency input signals. The objective of the paper is to propose a finite-frequency model reduction method for such systems. A finite-frequency ? performance index is first defined in frequency domain, and then a finite-frequency performance analysis condition is derived by Parseval's theorem. Combined with the average dwell time approach, sufficient conditions for the existence of exponentially stable reduced-order models are derived. An algorithm is proposed to construct the desired reduced-order models. The effectiveness of the proposed method is illustrated by a numerical example.
Finite difference time domain grid generation from AMC helicopter models
NASA Technical Reports Server (NTRS)
Cravey, Robin L.
1992-01-01
A simple technique is presented which forms a cubic grid model of a helicopter from an Aircraft Modeling Code (AMC) input file. The AMC input file defines the helicopter fuselage as a series of polygonal cross sections. The cubic grid model is used as an input to a Finite Difference Time Domain (FDTD) code to obtain predictions of antenna performance on a generic helicopter model. The predictions compare reasonably well with measured data.
NASA AVOSS Fast-Time Wake Prediction Models: User's Guide
NASA Technical Reports Server (NTRS)
Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew
2014-01-01
The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.
Continuous-time discrete-space models for animal movement
Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.
2015-01-01
The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.
Method for Real-Time Model Based Structural Anomaly Detection
NASA Technical Reports Server (NTRS)
Smith, Timothy A. (Inventor); Urnes, James M., Sr. (Inventor); Reichenbach, Eric Y. (Inventor)
2015-01-01
A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.
Modeling and optimum time performance for concurrent processing
NASA Technical Reports Server (NTRS)
Mielke, Roland R.; Stoughton, John W.; Som, Sukhamoy
1988-01-01
The development of a new graph theoretic model for describing the relation between a decomposed algorithm and its execution in a data flow environment is presented. Called ATAMM, the model consists of a set of Petri net marked graphs useful for representing decision-free algorithms having large-grained, computationally complex primitive operations. Performance time measures which determine computing speed and throughput capacity are defined, and the ATAMM model is used to develop lower bounds for these times. A concurrent processing operating strategy for achieving optimum time performance is presented and illustrated by example.
A tool for modeling concurrent real-time computation
NASA Technical Reports Server (NTRS)
Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.
1990-01-01
Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.
School playgrounds and physical activity policies as predictors of school and home time activity
2011-01-01
Background Previous work has suggested that the number of permanent play facilities in school playgrounds and school-based policies on physical activity can influence physical activity in children. However, few comparable studies have used objective measures of physical activity or have had little adjustment for multiple confounders. Methods Physical activity was measured by accelerometry over 5 recess periods and 3 full school days in 441 children from 16 primary schools in Dunedin, New Zealand. The number of permanent play facilities (swing, fort, slide, obstacle course, climbing wall etc) in each school playground was counted on three occasions by three researchers following a standardized protocol. Information on school policies pertaining to physical activity and participation in organized sport was collected by questionnaire. Results Measurement of school playgrounds proved to be reliable (ICC 0.89) and consistent over time. Boys were significantly more active than girls (P < 0.001), but little time overall was spent in moderate-vigorous physical activity (MVPA). Boys engaged in MVPA for 32 (SD 17) minutes each day of which 17 (10) took place at school compared with 23 (14) and 11 (7) minutes respectively in girls. Each additional 10-unit increase in play facilities was associated with 3.2% (95% CI 0.0-6.4%) more total activity and 8.3% (0.8-16.3%) more MVPA during recess. By contrast, school policy score was not associated with physical activity in children. Conclusion The number of permanent play facilities in school playgrounds is associated with higher physical activity in children, whereas no relationship was observed for school policies relating to physical activity. Increasing the number of permanent play facilities may offer a cost-effective long-term approach to increasing activity levels in children. PMID:21521530
Infrared optical activity: electric field approaches in time domain.
Rhee, Hanju; Choi, Jun-Ho; Cho, Minhaeng
2010-12-21
Vibrational circular dichroism (VCD) spectroscopy provides detailed information about the absolute configurations of chiral molecules including biomolecules and synthetic drugs. This method is the infrared (IR) analogue of the more popular electronic CD spectroscopy that uses the ultraviolet and visible ranges of the electromagnetic spectrum. Because conventional electronic CD spectroscopy measures the difference in signal intensity, problems such as weak signal and low time-resolution can limit its utility. To overcome the difficulties associated with that approach, we have recently developed femtosecond IR optical activity (IOA) spectrometry, which directly measures the IOA free-induction-decay (FID), the impulsive chiroptical IR response that occurs over time. In this Account, we review the time-domain electric field measurement and calculation methods used to simultaneously characterize VCD and related vibrational optical rotatory dispersion (VORD) spectra. Although conventional methods measure the electric field intensity, this vibrational technique is based on a direct phase-and-amplitude measurement of the electric field of the chiroptical signal over time. This method uses a cross-polarization analyzer to carry out heterodyned spectral interferometry. The cross-polarization scheme enables us to selectively remove the achiral background signal, which is the dominant noise component present in differential intensity measurement techniques. Because we can detect the IOA FID signal in a phase-amplitude-sensitive manner, we can directly characterize the time-dependent electric dipole/magnetic dipole response function and the complex chiral susceptibility that contain information about the angular oscillations of charged particles. These parameters yield information about the VCD and VORD spectra. In parallel with such experimental developments, we have also calculated the IOA FID signal and the resulting VCD spectrum. These simulations use a quantum mechanical
Infrared optical activity: electric field approaches in time domain.
Rhee, Hanju; Choi, Jun-Ho; Cho, Minhaeng
2010-12-21
Vibrational circular dichroism (VCD) spectroscopy provides detailed information about the absolute configurations of chiral molecules including biomolecules and synthetic drugs. This method is the infrared (IR) analogue of the more popular electronic CD spectroscopy that uses the ultraviolet and visible ranges of the electromagnetic spectrum. Because conventional electronic CD spectroscopy measures the difference in signal intensity, problems such as weak signal and low time-resolution can limit its utility. To overcome the difficulties associated with that approach, we have recently developed femtosecond IR optical activity (IOA) spectrometry, which directly measures the IOA free-induction-decay (FID), the impulsive chiroptical IR response that occurs over time. In this Account, we review the time-domain electric field measurement and calculation methods used to simultaneously characterize VCD and related vibrational optical rotatory dispersion (VORD) spectra. Although conventional methods measure the electric field intensity, this vibrational technique is based on a direct phase-and-amplitude measurement of the electric field of the chiroptical signal over time. This method uses a cross-polarization analyzer to carry out heterodyned spectral interferometry. The cross-polarization scheme enables us to selectively remove the achiral background signal, which is the dominant noise component present in differential intensity measurement techniques. Because we can detect the IOA FID signal in a phase-amplitude-sensitive manner, we can directly characterize the time-dependent electric dipole/magnetic dipole response function and the complex chiral susceptibility that contain information about the angular oscillations of charged particles. These parameters yield information about the VCD and VORD spectra. In parallel with such experimental developments, we have also calculated the IOA FID signal and the resulting VCD spectrum. These simulations use a quantum mechanical
The drug-target residence time model: a 10-year retrospective.
Copeland, Robert A
2016-02-01
The drug-target residence time model was first introduced in 2006 and has been broadly adopted across the chemical biology, biotechnology and pharmaceutical communities. While traditional in vitro methods view drug-target interactions exclusively in terms of equilibrium affinity, the residence time model takes into account the conformational dynamics of target macromolecules that affect drug binding and dissociation. The key tenet of this model is that the lifetime (or residence time) of the binary drug-target complex, and not the binding affinity per se, dictates much of the in vivo pharmacological activity. Here, this model is revisited and key applications of it over the past 10 years are highlighted.
Experience of Time Passage:. Phenomenology, Psychophysics, and Biophysical Modelling
NASA Astrophysics Data System (ADS)
Wackermann, Jiří
2005-10-01
The experience of time's passing appears, from the 1st person perspective, to be a primordial subjective experience, seemingly inaccessible to the 3rd person accounts of time perception (psychophysics, cognitive psychology). In our analysis of the `dual klepsydra' model of reproduction of temporal durations, time passage occurs as a cognitive construct, based upon more elementary (`proto-cognitive') function of the psychophysical organism. This conclusion contradicts the common concepts of `subjective' or `psychological' time as readings of an `internal clock'. Our study shows how phenomenological, experimental and modelling approaches can be fruitfully combined.
Moore, Justin B; Beets, Michael W; Barr-Anderson, Daheia J; Evenson, Kelly R
2013-01-01
The purpose of this cross-sectional study was to examine the relationship between objectively measured physical activity, sedentary time, and cardiorespiratory fitness in a diverse sample of youth. Participants were recruited from three middle schools and completed assessments of height, weight, cardiorespiratory fitness, and wore an accelerometer for a minimum of four days. Hierarchical general linear models controlling for age, body mass index (BMI) percentile, and sex were used to evaluate the association of time (minutes per day) spent sedentary, and in moderate physical activity and vigorous physical activity with cardiorespiratory fitness (i.e., heart rate response [beats per minute], dependent variable). Results indicated age (β = -0.16, P < 0.05), BMI percentile (β = 0.33, P <0.05), being male (β = 0.17, P < 0.05), sedentary time (β = 0.11, P <0.05), moderate (β = -0.03, P > 0.05) and vigorous (β = -0.22, P < 0.05) physical activity explained 29% of the variance in cardiorespiratory fitness. Evaluation of fitness among high sedentary/high vigorous, high sedentary/low vigorous, low sedentary/low vigorous, and low sedentary/high vigorous groups (defined by the median split) showed that high levels of vigorous activity removed the detrimental effect of high levels of sedentary time on cardiorespiratory fitness. These analyses suggest that the negative impact of sedentary time can be mitigated by engaging in vigorous activity.
Time Use Patterns between Maintenance, Subsistence and Leisure Activities: A Case Study in China
ERIC Educational Resources Information Center
Hui-fen, Zhou; Zhen-shan, Li; Dong-qian, Xue; Yang, Lei
2012-01-01
The Chinese government conducted its first time use survey of the activities of Chinese individuals in 2008. Activities were classified into three broad types, maintenance activities, subsistence activities and leisure activities. Time use patterns were defined by an individuals' time spent on maintenance, subsistence and leisure activities each…
A dissipative network model with neighboring activation
NASA Astrophysics Data System (ADS)
Xiong, Fei; Liu, Yun; Zhu, Jiang; Jiang Zhang, Zhen; Chao Zhang, Yan; Zhang, Ying
2011-11-01
We propose a network model with dissipative structure taking into consideration the effect of neighboring activation and individual dissipation. Nodes may feel tired of interactions with new nodes step by step, and drop out of the network evolution. However, these dormant nodes can become active again following neighbors. During the whole evolution only active nodes have opportunities to receive new links. We analyze user behavior of a real Internet forum, and the statistical characteristics of this forum are analogous to our model. Under the influence of motivation and dissipation, the degree distribution of our network model decays as a power law with a diversity of tunable power exponents. Furthermore, the network has high clustering, small average path length and positive assortativity coefficients.
Real-Time GNSS Positioning Along Canada's Active Coastal Margin
NASA Astrophysics Data System (ADS)
Henton, J. A.; Dragert, H.; Lu, Y.
2014-12-01
High-rate, low-latency Global Navigation Satellite System (GNSS) data are being refined for real-time applications to monitor and report motions related to large earthquakes in coastal British Columbia. Given the tectonic setting of Canada's west coast, specific goals for real-time regional geodetic monitoring are: (1) the collection of GNSS data with adequate station density to identify the deformation field for regional earthquakes with M>7.3; (2) the robust, continuous real-time analyses of GNSS data with a precision of 1-2 cm and a latency of less than 10s; and (3) the display of results with attending automated alarms and estimations of earthquake parameters. Megathrust earthquakes (M>8) are the primary targets for immediate identification, since the tsunamis they generate will strike the coast within 15 to 20 min. However, large (6.0
Short-time scale behavior modeling within long-time scale fuel cycle evaluations
Johnson, M.; Tsvetkov, P.; Lucas, S.
2012-07-01
Typically, short-time and long-time scales in nuclear energy system behavior are accounted for with entirely separate models. However, long-term changes in system characteristics do affect short-term transients through material variations. This paper presents an approach to consistently account for short-time scales within a nuclear system lifespan. The reported findings and developments are of significant importance for small modular reactors and other nuclear energy systems operating in autonomous modes. It is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by the Bateman equations. (authors)
NASA Astrophysics Data System (ADS)
Ahrens, H.; Argin, F.; Klinkenbusch, L.
2013-07-01
The non-invasive and radiation-free imaging of the electrical activity of the heart with Electrocardiography (ECG) or Magnetocardiography (MCG) can be helpful for physicians for instance in the localization of the origin of cardiac arrhythmia. In this paper we compare two Kalman Filter algorithms for the solution of a nonlinear state-space model and for the subsequent imaging of the activation/depolarization times of the heart muscle: the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The algorithms are compared for simulations of a (6×6) magnetometer array, a torso model with piecewise homogeneous conductivities, 946 current dipoles located in a small part of the heart (apex), and several noise levels. It is found that for all tested noise levels the convergence of the activation times is faster for the UKF.
Nonlinear modeling of chaotic time series: Theory and applications
NASA Astrophysics Data System (ADS)
Casdagli, M.; Eubank, S.; Farmer, J. D.; Gibson, J.; Desjardins, D.; Hunter, N.; Theiler, J.
We review recent developments in the modeling and prediction of nonlinear time series. In some cases, apparent randomness in time series may be due to chaotic behavior of a nonlinear but deterministic system. In such cases, it is possible to exploit the determinism to make short term forecasts that are much more accurate than one could make from a linear stochastic model. This is done by first reconstructing a state space, and then using nonlinear function approximation methods to create a dynamical model. Nonlinear models are valuable not only as short term forecasters, but also as diagnostic tools for identifying and quantifying low-dimensional chaotic behavior. During the past few years, methods for nonlinear modeling have developed rapidly, and have already led to several applications where nonlinear models motivated by chaotic dynamics provide superior predictions to linear models. These applications include prediction of fluid flows, sunspots, mechanical vibrations, ice ages, measles epidemics, and human speech.
A hybrid deformable model for real-time surgical simulation.
Zhu, Bo; Gu, Lixu
2012-07-01
Modeling organ deformation in real remains a challenge in virtual minimally invasive (MIS) surgery simulation. In this paper, we propose a new hybrid deformable model to simulate deformable organs in the real-time surgical training system. Our hybrid model uses boundary element method (BEM) to compute global deformation based on a coarse surface mesh and uses a mass-spring model to simulate the dynamic behaviors of soft tissue interacting with surgical instruments. The simulation result is coupled with a high-resolution rendering mesh through a particle surface interpolation algorithm. Accurate visual and haptic feedbacks are provided in real time and temporal behaviors of biological soft tissues including viscosity and creeping are modeled as well. We prove our model to be suitable to work in complex virtual surgical environment by integrating it into a MIS training system. The hybrid model is evaluated with respect to efficiency, accuracy and robustness by a series of experiments. PMID:22483053
Nonlinear modeling of chaotic time series: Theory and applications
Casdagli, M.; Eubank, S.; Farmer, J.D.; Gibson, J. Santa Fe Inst., NM ); Des Jardins, D.; Hunter, N.; Theiler, J. )
1990-01-01
We review recent developments in the modeling and prediction of nonlinear time series. In some cases apparent randomness in time series may be due to chaotic behavior of a nonlinear but deterministic system. In such cases it is possible to exploit the determinism to make short term forecasts that are much more accurate than one could make from a linear stochastic model. This is done by first reconstructing a state space, and then using nonlinear function approximation methods to create a dynamical model. Nonlinear models are valuable not only as short term forecasters, but also as diagnostic tools for identifying and quantifying low-dimensional chaotic behavior. During the past few years methods for nonlinear modeling have developed rapidly, and have already led to several applications where nonlinear models motivated by chaotic dynamics provide superior predictions to linear models. These applications include prediction of fluid flows, sunspots, mechanical vibrations, ice ages, measles epidemics and human speech. 162 refs., 13 figs.
Linear system identification via backward-time observer models
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh Q.
1992-01-01
Presented here is an algorithm to compute the Markov parameters of a backward-time observer for a backward-time model from experimental input and output data. The backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) for the backward-time system identification. The identified backward-time system Markov parameters are used in the Eigensystem Realization Algorithm to identify a backward-time state-space model, which can be easily converted to the usual forward-time representation. If one reverses time in the model to be identified, what were damped true system modes become modes with negative damping, growing as the reversed time increases. On the other hand, the noise modes in the identification still maintain the property that they are stable. The shift from positive damping to negative damping of the true system modes allows one to distinguish these modes from noise modes. Experimental results are given to illustrate when and to what extent this concept works.
Applying Transtheoretical Model to Promote Physical Activities Among Women
Pirzadeh, Asiyeh; Mostafavi, Firoozeh; Ghofranipour, Fazllolah; Feizi, Awat
2015-01-01
Background: Physical activity is one of the most important indicators of health in communities but different studies conducted in the provinces of Iran showed that inactivity is prevalent, especially among women. Objectives: Inadequate regular physical activities among women, the importance of education in promoting the physical activities, and lack of studies on the women using transtheoretical model, persuaded us to conduct this study with the aim of determining the application of transtheoretical model in promoting the physical activities among women of Isfahan. Materials and Methods: This research was a quasi-experimental study which was conducted on 141 women residing in Isfahan, Iran. They were randomly divided into case and control groups. In addition to the demographic information, their physical activities and the constructs of the transtheoretical model (stages of change, processes of change, decisional balance, and self-efficacy) were measured at 3 time points; preintervention, 3 months, and 6 months after intervention. Finally, the obtained data were analyzed through t test and repeated measures ANOVA test using SPSS version 16. Results: The results showed that education based on the transtheoretical model significantly increased physical activities in 2 aspects of intensive physical activities and walking, in the case group over the time. Also, a high percentage of people have shown progress during the stages of change, the mean of the constructs of processes of change, as well as pros and cons. On the whole, a significant difference was observed over the time in the case group (P < 0.01). Conclusions: This study showed that interventions based on the transtheoretical model can promote the physical activity behavior among women. PMID:26834796
Time dependent turbulence modeling and analytical theories of turbulence
NASA Technical Reports Server (NTRS)
Rubinstein, R.
1993-01-01
By simplifying the direct interaction approximation (DIA) for turbulent shear flow, time dependent formulas are derived for the Reynolds stresses which can be included in two equation models. The Green's function is treated phenomenologically, however, following Smith and Yakhot, we insist on the short and long time limits required by DIA. For small strain rates, perturbative evaluation of the correlation function yields a time dependent theory which includes normal stress effects in simple shear flows. From this standpoint, the phenomenological Launder-Reece-Rodi model is obtained by replacing the Green's function by its long time limit. Eddy damping corrections to short time behavior initiate too quickly in this model; in contrast, the present theory exhibits strong suppression of eddy damping at short times. A time dependent theory for large strain rates is proposed in which large scales are governed by rapid distortion theory while small scales are governed by Kolmogorov inertial range dynamics. At short times and large strain rates, the theory closely matches rapid distortion theory, but at long times it relaxes to an eddy damping model.
Analysis of time-resolved interaction force mode AFM imaging using active and passive probes.
Giray Oral, Hasan; Parlak, Zehra; Levent Degertekin, F
2012-09-01
We present an in-depth analysis of time-resolved interaction force (TRIF) mode imaging for atomic force microscopy (AFM). A nonlinear model of an active AFM probe, performing simultaneous topography and material property imaging on samples with varying elasticity and adhesion is implemented in Simulink®. The model is capable of simulating various imaging modes, probe structures, sample material properties, tip-sample interaction force models, and actuation and feedback schemes. For passive AFM cantilevers, the model is verified by comparing results from the literature. As an example of an active probe, the force sensing integrated readout and active tip (FIRAT) probe is used. Simulation results indicate that the active and damped nature of FIRAT provides a significant level of control over the force applied to the sample, minimizing sample indentation and topography error. Active tip control (ATC) preserves constant contact time during force control for stable contact while preventing the loss of material property information such as elasticity and adhesive force. Simulation results are verified by TRIF mode imaging of the samples with both soft and stiff regions. PMID:22813887
Statistical time-dependent model for the interstellar gas
NASA Technical Reports Server (NTRS)
Gerola, H.; Kafatos, M.; Mccray, R.
1974-01-01
We present models for temperature and ionization structure of low, uniform-density (approximately 0.3 per cu cm) interstellar gas in a galactic disk which is exposed to soft X rays from supernova outbursts occurring randomly in space and time. The structure was calculated by computing the time record of temperature and ionization at a given point by Monte Carlo simulation. The calculation yields probability distribution functions for ionized fraction, temperature, and their various observable moments. These time-dependent models predict a bimodal temperature distribution of the gas that agrees with various observations. Cold regions in the low-density gas may have the appearance of clouds in 21-cm absorption. The time-dependent model, in contrast to the steady-state model, predicts large fluctuations in ionization rate and the existence of cold (approximately 30 K), ionized (ionized fraction equal to about 0.1) regions.
Distributed real-time model-based diagnosis
NASA Technical Reports Server (NTRS)
Barrett, A. C.; Chung, S. H.
2003-01-01
This paper presents an approach to onboard anomaly diagnosis that combines the simplicity and real-time guarantee of a rule-based diagnosis system with the specification ease and coverage guarantees of a model-based diagnosis system.
Equilibrium and Disequilibrium Dynamics in Cobweb Models with Time Delays
NASA Astrophysics Data System (ADS)
Gori, Luca; Guerrini, Luca; Sodini, Mauro
2015-06-01
This paper aims to study price dynamics in two different continuous time cobweb models with delays close to [Hommes, 1994]. In both cases, the stationary equilibrium may be not representative of the long-term dynamics of the model, since it is possible to observe endogenous and persistent fluctuations (supercritical Hopf bifurcations) even if a deterministic context without external shocks is considered. In the model in which markets are in equilibrium every time, we show that the existence of time delays in the expectations formation mechanism may cause chaotic dynamics similar to those obtained in [Hommes, 1994] in a discrete time context. From a mathematical point of view, we apply the Poincaré-Lindstedt perturbation method to study the local dynamic properties of the models. In addition, several numerical experiments are used to investigate global properties of the systems.
Generalized Dynamic Factor Models for Mixed-Measurement Time Series
Cui, Kai; Dunson, David B.
2013-01-01
In this article, we propose generalized Bayesian dynamic factor models for jointly modeling mixed-measurement time series. The framework allows mixed-scale measurements associated with each time series, with different measurements having different distributions in the exponential family conditionally on time-varying latent factor(s). Efficient Bayesian computational algorithms are developed for posterior inference on both the latent factors and model parameters, based on a Metropolis Hastings algorithm with adaptive proposals. The algorithm relies on a Greedy Density Kernel Approximation (GDKA) and parameter expansion with latent factor normalization. We tested the framework and algorithms in simulated studies and applied them to the analysis of intertwined credit and recovery risk for Moody’s rated firms from 1982–2008, illustrating the importance of jointly modeling mixed-measurement time series. The article has supplemental materials available online. PMID:24791133
Practical overview of ARIMA models for time-series forecasting
Pack, D.J.
1980-01-01
Single series analysis methodology is illustrated. The commentary summarizes the Box-Jenkins philosophy and the ARIMA model structure, with particular emphasis on practical aspects of application, forecast interpretation, strengths weaknesses, and comparison to other time series forecasting approaches. (GHT)
A dynamic P53-MDM2 model with time delay
NASA Astrophysics Data System (ADS)
Mihalaş, Gh. I.; Neamţu, M.; Opriş, D.; Horhat, R. F.
2006-11-01
Specific activator and repressor transcription factors which bind to specific regulator DNA sequences, play an important role in gene activity control. Interactions between genes coding such transcription factors should explain the different stable or sometimes oscillatory gene activities characteristic for different tissues. Starting with the model P53-MDM2 described into [6] and the process described into [5] we developed a new model of this interaction. Choosing the delay as a bifurcation parameter we study the direction and stability of the bifurcating periodic solutions. Some numerical examples are finally given for justifying the theoretical results.
On the precision of automated activation time estimation
NASA Technical Reports Server (NTRS)
Kaplan, D. T.; Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.
1988-01-01
We examined how the assignment of local activation times in epicardial and endocardial electrograms is affected by sampling rate, ambient signal-to-noise ratio, and sinx/x waveform interpolation. Algorithms used for the estimation of fiducial point locations included dV/dtmax, and a matched filter detection algorithm. Test signals included epicardial and endocardial electrograms overlying both normal and infarcted regions of dog myocardium. Signal-to-noise levels were adjusted by combining known data sets with white noise "colored" to match the spectral characteristics of experimentally recorded noise. For typical signal-to-noise ratios and sampling rates, the template-matching algorithm provided the greatest precision in reproducibly estimating fiducial point location, and sinx/x interpolation allowed for an additional significant improvement. With few restrictions, combining these two techniques may allow for use of digitization rates below the Nyquist rate without significant loss of precision.
Timing substorm onsets via travel-time magnetoseismology: A case for the outside-in model
NASA Astrophysics Data System (ADS)
Chi, Peter; Russell, Christopher; Ohtani, Shin
The time history of events during substorms is an important, outstanding problem in magnetospheric physics. The sequence has been described either by the "outside-in" model, in which the fast plasma flow ejected by reconnection in the mid-tail moves Earthward, or by the "inside-out" model, in which the onset starts with the cross-tail current sheet collapse at 8 to 12 RE in the tail that later initiates reconnection further downtail. In this study we examined the Pi 2 pulsations observed by ground magnetometers and the observations of auroral brightening to lay out the time history of events during a substorm on July 22, 1998. The arrival time of Pi 2, which refers to the first peak in Pi 2 amplitude, observed by IGPP-LANL and CARISMA magnetometers presents a strong function of latitude. Using the Tamao travel time as the forward model, the inversion from the observed Pi 2 arrival time infers that the onset in the magnetotail started at X = -22 RE at 0653:40 UT, or approximately one minute earlier than the Pi 2 onset time identified in ground data. The CARISMA photometer data at Fort Smith and Gillam show that the auroral brightening started at approximately 0656 UT, or more than two minutes after the estimated onset time in the magnetotail. The comparison between the impulse start time in the tail and the onset time of auroral brightening presents a clear case where the time history of events follows the outside-in model. The model identification is made more confidently by using the magnetoseismic method that can time substorm onsets in the magnetotail.
Linear Time Invariant Models for Integrated Flight and Rotor Control
NASA Astrophysics Data System (ADS)
Olcer, Fahri Ersel
2011-12-01
Recent developments on individual blade control (IBC) and physics based reduced order models of various on-blade control (OBC) actuation concepts are opening up opportunities to explore innovative rotor control strategies for improved rotor aerodynamic performance, reduced vibration and BVI noise, and improved rotor stability, etc. Further, recent developments in computationally efficient algorithms for the extraction of Linear Time Invariant (LTI) models are providing a convenient framework for exploring integrated flight and rotor control, while accounting for the important couplings that exist between body and low frequency rotor response and high frequency rotor response. Formulation of linear time invariant (LTI) models of a nonlinear system about a periodic equilibrium using the harmonic domain representation of LTI model states has been studied in the literature. This thesis presents an alternative method and a computationally efficient scheme for implementation of the developed method for extraction of linear time invariant (LTI) models from a helicopter nonlinear model in forward flight. The fidelity of the extracted LTI models is evaluated using response comparisons between the extracted LTI models and the nonlinear model in both time and frequency domains. Moreover, the fidelity of stability properties is studied through the eigenvalue and eigenvector comparisons between LTI and LTP models by making use of the Floquet Transition Matrix. For time domain evaluations, individual blade control (IBC) and On-Blade Control (OBC) inputs that have been tried in the literature for vibration and noise control studies are used. For frequency domain evaluations, frequency sweep inputs are used to obtain frequency responses of fixed system hub loads to a single blade IBC input. The evaluation results demonstrate the fidelity of the extracted LTI models, and thus, establish the validity of the LTI model extraction process for use in integrated flight and rotor control
Modeling past, current, and future time in medical databases.
Kouramajian, V.; Fowler, J.
1994-01-01
Recent research has focused on increasing the power of medical information systems by incorporating time into the database system. A problem with much of this research is that it fails to differentiate between historical time and future time. The concept of bitemporal lifespan presented in this paper overcomes this deficiency. Bitemporal lifespan supports the concepts of valid time and transaction time and allows the integration of past, current, and future information in a unified model. The concept of bitemporal lifespan is presented within the framework of the Extended Entity-Relationship model. This model permits the characterization of temporal properties of entities, relationships, and attributes. Bitemporal constraints are defined that must hold between entities forming "isa" hierarchies and between entities and relationships. Finally, bitemporal extensions are presented for database query languages in order to provide natural high-level operators for bitemporal query expressions. PMID:7949941
Activated partial thromboplastin time: new tricks for an old dogma.
Lippi, Giuseppe; Favaloro, Emmanuel J
2008-10-01
The activated partial thromboplastin time (APTT) is the most common coagulation test procedure performed in routine laboratories, apart from the prothrombin time. The test is traditionally used for identifying quantitative and qualitative abnormalities in the intrinsic and common pathways of coagulation, monitoring anticoagulant therapy with unfractionated heparin, and detecting inhibitors of blood coagulation, the most common of which is the lupus anticoagulant. Whereas short APTT values have been mostly overlooked in the past, recent evidence suggests that these might be associated with hypercoagulability. Although clinical relevance is yet to be clearly defined, hypercoagulability detected by a shortened APTT appears to be significantly associated with a major risk of venous thromboembolism independently from other variables such as blood group, the presence of inherited thrombophilia, and factor VIII levels. This novel finding suggests that this traditional, simple, and inexpensive test might have renewed utility along with traditional thrombophilic tests in the evaluation of venous thromboembolic risk. In addition, APTT waveform analysis is also providing mounting evidence of added utility, in particular for identifying sepsis and disseminated intravascular coagulation in critically ill patients (particularly where this might worsen the prognosis), for monitoring therapy in patients with inhibitors, and as a diagnostic aid to identify patients with antiphospholipid antibodies. In total, such emerging evidence suggests that the APTT is either an old dogma displaying new tricks or else might describe a new dogma for an old laboratory trick. PMID:19085761
Investigating the American Time Use Survey from an Exposure Modeling Perspective
This paper describes an evaluation of the U.S. Bureau of Labor Statistics' American Time Use Survey (ATUS) for potential use in modeling human exposures to environmental pollutants. The ATUS is a large, on-going, cross-sectional survey of where Americans spend time and what activ...
Time-Resolved Spectroscopy of Active Binary Stars
NASA Technical Reports Server (NTRS)
Brown, Alexander
2000-01-01
This NASA grant covered EUVE observing and data analysis programs during EUVE Cycle 5 GO observing. The research involved a single Guest Observer project 97-EUVE-061 "Time-Resolved Spectroscopy of Active Binary Stars". The grant provided funding that covered 1.25 months of the PI's salary. The activities undertaken included observation planning and data analysis (both temporal and spectral). This project was awarded 910 ksec of observing time to study seven active binary stars, all but one of which were actually observed. Lambda-And was observed on 1997 Jul 30 - Aug 3 and Aug 7-14 for a total of 297 ksec; these observations showed two large complex flares that were analyzed by Osten & Brown (1999). AR Psc, observed for 350 ksec on 1997 Aug 27 - Sep 13, showed only relatively small flares that were also discussed by Osten & Brown (1999). EUVE observations of El Eri were obtained on 1994 August 24-28, simultaneous with ASCA X-ray spectra. Four flares were detected by EUVE with one of these also observed simultaneously, by ASCA. The other three EUVE observations were of the stars BY Dra (1997 Sep 22-28), V478 Lyr (1998 May 18-27), and sigma Gem (1998 Dec 10-22). The first two stars showed a few small flares. The sigma Gem data shows a beautiful complete flare with a factor of ten peak brightness compared to quiescence. The flare rise and almost all the decay phase are observed. Unfortunately no observations in other spectral regions were obtained for these stars. Analysis of the lambda-And and AR Psc observations is complete and the results were published in Osten & Brown (1999). Analysis of the BY Dra, V478 Lyr and sigma Gem EUVE data is complete and will be published in Osten (2000, in prep.). The El Eri EUV analysis is also completed and the simultaneous EUV/X-ray study will be published in Osten et al. (2000, in prep.). Both these latter papers will be submitted in summer 2000. All these results will form part of Rachel Osten's PhD thesis.
Stochastic modeling of hourly rainfall times series in Campania (Italy)
NASA Astrophysics Data System (ADS)
Giorgio, M.; Greco, R.
2009-04-01
Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil
Numerical bifurcation analysis of immunological models with time delays
NASA Astrophysics Data System (ADS)
Luzyanina, Tatyana; Roose, Dirk; Bocharov, Gennady
2005-12-01
In recent years, a large number of mathematical models that are described by delay differential equations (DDEs) have appeared in the life sciences. To analyze the models' dynamics, numerical methods are necessary, since analytical studies can only give limited results. In turn, the availability of efficient numerical methods and software packages encourages the use of time delays in mathematical modelling, which may lead to more realistic models. We outline recently developed numerical methods for bifurcation analysis of DDEs and illustrate the use of these methods in the analysis of a mathematical model of human hepatitis B virus infection.
A model of interval timing by neural integration.
Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip
2011-06-22
We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.
A model of interval timing by neural integration
Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip
2011-01-01
We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374
MSW Time to Tumor Model and Supporting Documentation
The multistage Weibull (MSW) time-to-tumor model and related documentation were developed principally (but not exclusively) for conducting time-to-tumor analyses to support risk assessments under the IRIS program. These programs and related docum...
CCD Observing and Dynamical Time Series Analysis of Active Galactic Nuclei.
NASA Astrophysics Data System (ADS)
Nair, Achotham Damodaran
1995-01-01
The properties, working and operations procedure of the Charge Coupled Device (CCD) at the 30" telescope at Rosemary Hill Observatory (RHO) are discussed together with the details of data reduction. Several nonlinear techniques of time series analysis, based on the behavior of the nearest neighbors, have been used to analyze the time series of the quasar 3C 345. A technique using Artificial Neural Networks based on prediction of the time series is used to study the dynamical properties of 3C 345. Finally, a heuristic model for variability of Active Galactic Nuclei is discussed.
Snyder-de Sitter model from two-time physics
Carrisi, M. C.; Mignemi, S.
2010-11-15
We show that the symplectic structure of the Snyder model on a de Sitter background can be derived from two-time physics in seven dimensions and propose a Hamiltonian for a free particle consistent with the symmetries of the model.
Separability of Item and Person Parameters in Response Time Models.
ERIC Educational Resources Information Center
Van Breukelen, Gerard J. P.
1997-01-01
Discusses two forms of separability of item and person parameters in the context of response time models. The first is "separate sufficiency," and the second is "ranking independence." For each form a theorem stating sufficient conditions is proved. The two forms are shown to include several cases of models from psychometric and biometric…
Separation of time scales in the HCA model for sand
NASA Astrophysics Data System (ADS)
Niemunis, Andrzej; Wichtmann, Torsten
2014-10-01
Separation of time scales is used in a high cycle accumulation (HCA) model for sand. An important difficulty of the model is the limited applicability of the Miner's rule to multiaxial cyclic loadings applied simultaneously or in a combination with monotonic loading. Another problem is the lack of simplified objective HCA formulas for geotechnical settlement problems. Possible solutions of these problems are discussed.
A Mixture Rasch Model with Item Response Time Components
ERIC Educational Resources Information Center
Meyer, J. Patrick
2010-01-01
An examinee faced with a test item will engage in solution behavior or rapid-guessing behavior. These qualitatively different test-taking behaviors bias parameter estimates for item response models that do not control for such behavior. A mixture Rasch model with item response time components was proposed and evaluated through application to real…
ERIC Educational Resources Information Center
Sinclair, Christina D.; Stellino, Megan Babkes; Partidge, Julie A.
2008-01-01
Childhood obesity and inactivity levels among young Americans have risen steadily over the last few decades, and has become a major concern. Participation in regular physical activity helps prevent excess adiposity in children and youth. Recess is a regularly occurring period of time in school children's days which is an opportunity to help them…
Rodriguez-Perez, S; Fermoso, F G; Arnaiz, C
2016-01-01
Medium-sized wastewater treatment plants are considered too small to implement anaerobic digestion technologies and too large for extensive treatments. A promising option as a sewage sludge reduction method is the inclusion of anoxic time exposures. In the present study, three different anoxic time exposures of 12, 6 and 4 hours have been studied to reduce sewage sludge production. The best anoxic time exposure was observed under anoxic/oxic cycles of 6 hours, which reduced 29.63% of the biomass production compared with the oxic control conditions. The sludge under different anoxic time exposures, even with a lower active biomass concentration than the oxic control conditions, showed a much higher metabolic activity than the oxic control conditions. Microbiological results suggested that both protozoa density and abundance of filamentous bacteria decrease under anoxic time exposures compared to oxic control conditions. The anoxic time exposures 6/6 showed the highest reduction in both protozoa density, 37.5%, and abundance of filamentous bacteria, 41.1%, in comparison to the oxic control conditions. The groups of crawling ciliates, carnivorous ciliates and filamentous bacteria were highly influenced by the anoxic time exposures. Protozoa density and abundance of filamentous bacteria have been shown as promising bioindicators of biomass production reduction.
Rodriguez-Perez, S; Fermoso, F G; Arnaiz, C
2016-01-01
Medium-sized wastewater treatment plants are considered too small to implement anaerobic digestion technologies and too large for extensive treatments. A promising option as a sewage sludge reduction method is the inclusion of anoxic time exposures. In the present study, three different anoxic time exposures of 12, 6 and 4 hours have been studied to reduce sewage sludge production. The best anoxic time exposure was observed under anoxic/oxic cycles of 6 hours, which reduced 29.63% of the biomass production compared with the oxic control conditions. The sludge under different anoxic time exposures, even with a lower active biomass concentration than the oxic control conditions, showed a much higher metabolic activity than the oxic control conditions. Microbiological results suggested that both protozoa density and abundance of filamentous bacteria decrease under anoxic time exposures compared to oxic control conditions. The anoxic time exposures 6/6 showed the highest reduction in both protozoa density, 37.5%, and abundance of filamentous bacteria, 41.1%, in comparison to the oxic control conditions. The groups of crawling ciliates, carnivorous ciliates and filamentous bacteria were highly influenced by the anoxic time exposures. Protozoa density and abundance of filamentous bacteria have been shown as promising bioindicators of biomass production reduction. PMID:27508364
Modeling an Application's Theoretical Minimum and Average Transactional Response Times
Paiz, Mary Rose
2015-04-01
The theoretical minimum transactional response time of an application serves as a ba- sis for the expected response time. The lower threshold for the minimum response time represents the minimum amount of time that the application should take to complete a transaction. Knowing the lower threshold is beneficial in detecting anomalies that are re- sults of unsuccessful transactions. On the converse, when an application's response time falls above an upper threshold, there is likely an anomaly in the application that is causing unusual performance issues in the transaction. This report explains how the non-stationary Generalized Extreme Value distribution is used to estimate the lower threshold of an ap- plication's daily minimum transactional response time. It also explains how the seasonal Autoregressive Integrated Moving Average time series model is used to estimate the upper threshold for an application's average transactional response time.
Kālī: Time series data modeler
NASA Astrophysics Data System (ADS)
Kasliwal, Vishal P.
2016-07-01
The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālimacr; is written in c++ with Python language bindings for ease of use. K¯lī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.
Studies in astronomical time series analysis: Modeling random processes in the time domain
NASA Technical Reports Server (NTRS)
Scargle, J. D.
1979-01-01
Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.
Gamma time-dependency in Blaxter's compartmental model.
NASA Technical Reports Server (NTRS)
Matis, J. H.
1972-01-01
A new two-compartment model for the passage of particles through the gastro-intestinal tract of ruminants is proposed. In this model, a gamma distribution of lifetimes is introduced in the first compartment; thereby, passage from that compartment becomes time-dependent. This modification is strongly suggested by the physical alteration which certain substances, e.g. hay particles, undergo in the digestive process. The proposed model is applied to experimental data.
Evaluating mallard adaptive management models with time series
Conn, P.B.; Kendall, W.L.
2004-01-01
Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these
Sanquist, Thomas F.; Greitzer, Frank L.; Slavich, Antoinette L.; Littlefield, Rik J.; Littlefield, Janis S.; Cowley, Paula J.
2004-09-28
Technology-based enhancement of information analysis requires a detailed understanding of the cognitive tasks involved in the process. The information search and report production tasks of the information analysis process were investigated through evaluation of time-stamped workstation data gathered with custom software. Model tasks simulated the search and production activities, and a sample of actual analyst data were also evaluated. Task event durations were calculated on the basis of millisecond-level time stamps, and distributions were plotted for analysis. The data indicate that task event time shows a cyclic pattern of variation, with shorter event durations (< 2 sec) reflecting information search and filtering, and longer event durations (> 10 sec) reflecting information evaluation. Application of cognitive principles to the interpretation of task event time data provides a basis for developing “cognitive signatures” of complex activities, and can facilitate the development of technology aids for information intensive tasks.
The Seasons Explained by Refutational Modeling Activities
ERIC Educational Resources Information Center
Frede, Valerie
2008-01-01
This article describes the principles and investigation of a small-group laboratory activity based on refutational modeling to teach the concept of seasons to preservice elementary teachers. The results show that these teachers improved significantly when they had to refute their initial misconceptions practically. (Contains 8 figures and 1 table.)
Using Hybrid Modeling to Develop Innovative Activities
ERIC Educational Resources Information Center
Lichtman, Brenda; Avans, Diana
2005-01-01
This article describes a hybrid activities model that physical educators can use with students in grades four and above to create virtually a limitless array of novel games. A brief introduction to the basic theory is followed by descriptions of some hybrid games. Hybrid games are typically the result of merging two traditional sports or other…
The Kolb Model Modified for Classroom Activities.
ERIC Educational Resources Information Center
Svinicki, Marilla D.; Dixon, Nancy M.
1987-01-01
The experiential learning model of Kolb provides a framework for examining the selection of a broader range of classroom activities than is in current use. Experiential learning cycle, experiential learning as instructional design, and student as actor versus student as receiver are discussed. (MLW)
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Model activities. 1006.225 Section 1006.225 Housing and Urban Development Regulations Relating to Housing and Urban Development (Continued) OFFICE OF ASSISTANT SECRETARY FOR PUBLIC AND INDIAN HOUSING, DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT NATIVE HAWAIIAN HOUSING BLOCK...
MODELING MERCURY CONTROL WITH POWDERED ACTIVATED CARBON
The paper presents a mathematical model of total mercury removed from the flue gas at coal-fired plants equipped with powdered activated carbon (PAC) injection for Mercury control. The developed algorithms account for mercury removal by both existing equipment and an added PAC in...
Spots and Flares: Stellar Activity in the Time Domain Era
NASA Astrophysics Data System (ADS)
Davenport, James
2015-08-01
Time domain photometric surveys for large numbers of stars have ushered in a new era of statistical studies of astrophysics. This new parameter space allows us to observe how stars behave and change on a human timescale, and facilitates ensemble studies to understand how stars change over cosmic timescales. With current and planned time domain stellar surveys, we will be able to put the Sun in a Galactic context, and discover how typical or unique our parent star truly is. The goal of this thesis is to develop techniques for detecting and analyzing the most prominent forms of magnetic activity from low-mass stars in modern time domain surveys: starspots and flares. Magnetic field strength is a fundamental property that decays over a star's life. As a result, flux modulations from both flares and starspots become smaller amplitude and more infrequent in light curves. Methods for detecting these forms of magnetic activity will be extensible to future time domain surveys, and helpful in characterizing the properties of stars as they age. Flares can be detected in sparsely sampled wide field surveys by searching for bright single-point outliers in light curves. Using both red optical and near infrared data from ground-based surveys over many years, I have constrained the rate of flares in multiple wavelengths for an ensemble of M dwarfs. Studying flares in these existing ground-based datasets will enable predictions for future survey yields. Space-based photometry enables continuous and precise monitoring of stars for many years, which is crucial for obtaining a complete census of flares from a single star. Using 11 months of 1-minute photometry for the M dwarf GJ 1243, I have amassed over 6100 flare events, the largest sample of white light flares for any low-mass star. I have also created the first high fidelity empirical white light flare template, which shows three distinct phases in typical flare light curves. With this template, I demonstrate that complex multi
Spots and Flares: Stellar Activity in the Time Domain Era
NASA Astrophysics Data System (ADS)
Davenport, James R. A.
Time domain photometric surveys for large numbers of stars have ushered in a new era of statistical studies of astrophysics. This new parameter space allows us to observe how stars behave and change on a human timescale, and facilitates ensemble studies to understand how stars change over cosmic timescales. With current and planned time domain stellar surveys, we will be able to put the Sun in a Galactic context, and discover how typical or unique our parent star truly is. The goal of this thesis is to develop techniques for detecting and analyzing the most prominent forms of magnetic activity from low-mass stars in modern time domain surveys: starspots and flares. Magnetic field strength is a fundamental property that decays over a star's life. As a result, flux modulations from both flares and starspots become smaller amplitude and more infrequent in light curves. Methods for detecting these forms of magnetic activity will be extensible to future time domain surveys, and helpful in characterizing the properties of stars as they age. Flares can be detected in sparsely sampled wide field surveys by searching for bright single-point outliers in light curves. Using both red optical and near infrared data from ground-based surveys over many years, I have constrained the rate of flares in multiple wavelengths for an ensemble of M dwarfs. Studying flares in these existing ground-based datasets will enable predictions for future survey yields. Space-based photometry enables continuous and precise monitoring of stars for many years, which is crucial for obtaining a complete census of flares from a single star. Using 11 months of 1-minute photometry for the M dwarf GJ 1243, I have amassed over 6100 flare events, the largest sample of white light flares for any low-mass star. I have also created the first high fidelity empirical white light flare template, which shows three distinct phases in typical flare light curves. With this template, I demonstrate that complex multi
Time dependent modeling of non-LTE plasmas: Final report
Not Available
1988-06-01
During the period of performance of this contract Science Applications International Corporation (SAIC) has aided Lawrence Livermore National Laboratory (LLNL) in the development of an unclassified modeling tool for studying time evolution of high temperature ionizing and recombining plasmas. This report covers the numerical code developed, (D)ynamic (D)etailed (C)onfiguration (A)ccounting (DDCA), which was written to run on the National Magnetic Fusion Energy Computing Center (NMFECC) network as well as the classified Livermore Computer Center (OCTOPUS) network. DDCA is a One-Dimensional (1D) time dependent hydrodynamic model which makes use of the non-LTE detailed atomic physics ionization model DCA. 5 refs.
ARTEMIS: Ares Real Time Environments for Modeling, Integration, and Simulation
NASA Technical Reports Server (NTRS)
Hughes, Ryan; Walker, David
2009-01-01
This slide presentation reviews the use of ARTEMIS in the development and testing of the ARES launch vehicles. Ares Real Time Environment for Modeling, Simulation and Integration (ARTEMIS) is the real time simulation supporting Ares I hardware-in-the-loop (HWIL) testing. ARTEMIS accurately models all Ares/Orion/Ground subsystems which interact with Ares avionics components from pre-launch through orbit insertion The ARTEMIS System integration Lab, and the STIF architecture is reviewed. The functional components of ARTEMIS are outlined. An overview of the models and a block diagram is presented.
Application of nonlinear time series models to driven systems
Hunter, N.F. Jr.
1990-01-01
In our laboratory we have been engaged in an effort to model nonlinear systems using time series methods. Our objectives have been, first, to understand how the time series response of a nonlinear system unfolds as a function of the underlying state variables, second, to model the evolution of the state variables, and finally, to predict nonlinear system responses. We hope to address the relationship between model parameters and system parameters in the near future. Control of nonlinear systems based on experimentally derived parameters is also a planned topic of future research. 28 refs., 15 figs., 2 tabs.
Prompts to Disrupt Sitting Time and Increase Physical Activity at Work, 2011–2012
Rote, Aubrianne E.; Welch, Whitney A.; Maeda, Hotaka; Hart, Teresa L.; Cho, Young Ik; Strath, Scott J.
2014-01-01
Introduction The objective of this study was to assess change in sitting and physical activity behavior in response to a workplace intervention to disrupt prolonged sitting time. Methods Sixty office workers were randomized to either a Stand group (n = 29), which received hourly prompts (computer-based and wrist-worn) to stand up, or a Step group (n = 31), which received the same hourly prompts and an additional prompt to walk 100 steps or more upon standing. An ActivPAL monitor was used to assess sitting and physical activity behavior on the same 3 consecutive workdays during baseline and intervention periods. Mixed-effect models with random intercepts and random slopes for time were performed to assess change between groups and across time. Results Both groups significantly reduced duration of average sitting bouts (Stand group, by 16%; Step group, by 19%) and the number of sitting bouts of 60 minutes or more (Step group, by 36%; Stand group, by 54%). The Stand group significantly reduced total sitting time (by 6.6%), duration of the longest sitting bout (by 29%), and number of sitting bouts of 30 minutes or more (by 13%) and increased the number of sit-to-stand transitions (by 15%) and standing time (by 23%). Stepping time significantly increased in the Stand (by 14%) and Step (by 29%) groups, but only the Step group significantly increased (by 35%) the number of steps per workday. Differences in changes from baseline to intervention between groups were not significant for any outcome. Conclusion Interventions that focus on disrupting sitting time only in the workplace may result in less sitting. When sitting time disruptions are paired with a physical activity prompt, people may be more likely to increase their workday physical activity, but the effect on sitting time may be attenuated. PMID:24784909
Modeling Real-Time Applications with Reusable Design Patterns
NASA Astrophysics Data System (ADS)
Rekhis, Saoussen; Bouassida, Nadia; Bouaziz, Rafik
Real-Time (RT) applications, which manipulate important volumes of data, need to be managed with RT databases that deal with time-constrained data and time-constrained transactions. In spite of their numerous advantages, RT databases development remains a complex task, since developers must study many design issues related to the RT domain. In this paper, we tackle this problem by proposing RT design patterns that allow the modeling of structural and behavioral aspects of RT databases. We show how RT design patterns can provide design assistance through architecture reuse of reoccurring design problems. In addition, we present an UML profile that represents patterns and facilitates further their reuse. This profile proposes, on one hand, UML extensions allowing to model the variability of patterns in the RT context and, on another hand, extensions inspired from the MARTE (Modeling and Analysis of Real-Time Embedded systems) profile.
Chromospheric extents predicted by time-dependent acoustic wave models
NASA Technical Reports Server (NTRS)
Cuntz, Manfred
1990-01-01
Theoretical models for chromospheric structures of late-type giant stars are computed, including the time-dependent propagation of acoustic waves. Models with short-period monochromatic shock waves as well as a spectrum of acoustic waves are discussed, and the method is applied to the stars Arcturus, Aldebaran, and Betelgeuse. Chromospheric extent, defined as the monotonic decrease with height of the time-averaged electron densities, are found to be 1.12, 1.13, and 1.22 stellar radii for the three stars, respectively; this corresponds to a time-averaged electron density of 10 to the 7th/cu cm. Predictions of the extended chromospheric obtained using a simple scaling law agree well with those obtained by the time-dependent wave models; thus, the chromospheres of all stars for which the scaling law is valid consist of the same number of pressure scale heights.
Time Outdoors, Visual Activity, and Myopia Progression in Juvenile-Onset Myopes
Jones-Jordan, Lisa A.; Sinnott, Loraine T.; Cotter, Susan A.; Kleinstein, Robert N.; Manny, Ruth E.; Mutti, Donald O.; Twelker, J. Daniel; Zadnik,, Karla
2012-01-01
Purpose. To investigate the association between myopia progression and time spent outdoors and in various visual activities. Methods. Subjects were 835 myopes (both principal meridians −0.75 diopters [D] or more myopia by cycloplegic autorefraction) in the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) Study with both progression data and at least one measure of activity associated with a progression interval. Activity data were collected by parental survey. Average activity level (mean of the activity at the beginning and the end of a 1-year progression interval) was the primary predictor in a repeated-measures mixed model. The model controlled for age, sex, ethnicity, refractive error at the beginning of the progression interval, clinic site, and type of autorefractor used. Effects were scaled based on performing an additional 10 hours per week of an activity. Results. In the multivariate model, the number of hours of reading for pleasure per week was not significantly associated with annual myopia progression at an a priori level of P ≤ 0.01, nor were the other near activities, the near-work composite variable diopter-hours, or outdoor/sports activity. The magnitude of effects was clinically small. For example, the largest multivariate effect was that each additional 10 hours of reading for pleasure per week at the end of a progression interval was associated with an increase in average annual progression by −0.08 D. Conclusions. Despite protective associations previously reported for time outdoors reducing the risk of myopia onset, outdoor/sports activity was not associated with less myopia progression following onset. Near work also had little meaningful effect on the rate of myopia progression. PMID:22977132
Kinetic model of excess activated sludge thermohydrolysis.
Imbierowicz, Mirosław; Chacuk, Andrzej
2012-11-01
Thermal hydrolysis of excess activated sludge suspensions was carried at temperatures ranging from 423 K to 523 K and under pressure 0.2-4.0 MPa. Changes of total organic carbon (TOC) concentration in a solid and liquid phase were measured during these studies. At the temperature 423 K, after 2 h of the process, TOC concentration in the reaction mixture decreased by 15-18% of the initial value. At 473 K total organic carbon removal from activated sludge suspension increased to 30%. It was also found that the solubilisation of particulate organic matter strongly depended on the process temperature. At 423 K the transfer of TOC from solid particles into liquid phase after 1 h of the process reached 25% of the initial value, however, at the temperature of 523 K the conversion degree of 'solid' TOC attained 50% just after 15 min of the process. In the article a lumped kinetic model of the process of activated sludge thermohydrolysis has been proposed. It was assumed that during heating of the activated sludge suspension to a temperature in the range of 423-523 K two parallel reactions occurred. One, connected with thermal destruction of activated sludge particles, caused solubilisation of organic carbon and an increase of dissolved organic carbon concentration in the liquid phase (hydrolysate). The parallel reaction led to a new kind of unsolvable solid phase, which was further decomposed into gaseous products (CO(2)). The collected experimental data were used to identify unknown parameters of the model, i.e. activation energies and pre-exponential factors of elementary reactions. The mathematical model of activated sludge thermohydrolysis appropriately describes the kinetics of reactions occurring in the studied system. PMID:22951329
ERIC Educational Resources Information Center
Motl, Robert W.; McAuley, Edward; Birnbaum, Amanda S.; Lytle, Leslie A.
2006-01-01
In this longitudinal study, we examined the relationship between changes in time spent watching television and playing video games with frequency of leisure-time physical activity across a 2-year period among adolescent boys and girls (N=4594). Latent growth modelling indicated that a decrease in time spent watching television was associated with…
Logic Model Checking of Time-Periodic Real-Time Systems
NASA Technical Reports Server (NTRS)
Florian, Mihai; Gamble, Ed; Holzmann, Gerard
2012-01-01
In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.
Multi-scale gravity field modeling in space and time
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2016-04-01
The Earth constantly deforms as it undergoes dynamic phenomena, such as earthquakes, post-glacial rebound and water displacement in its fluid envelopes. These processes have different spatial and temporal scales and are accompanied by mass displacements, which create temporal variations of the gravity field. Since 2002, the GRACE satellite missions provide an unprecedented view of the gravity field spatial and temporal variations. Gravity models built from these satellite data are essential to study the Earth's dynamic processes (Tapley et al., 2004). Up to present, time variations of the gravity field are often modelled using spatial spherical harmonics functions averaged over a fixed period, as 10 days or 1 month. This approach is well suited for modeling global phenomena. To better estimate gravity related to local and/or transient processes, such as earthquakes or floods, and adapt the temporal resolution of the model to its spatial resolution, we propose to model the gravity field using localized functions in space and time. For that, we build a model of the gravity field in space and time with a four-dimensional wavelet basis, well localized in space and time. First we design the 4D basis, then, we study the inverse problem to model the gravity field from the potential differences between the twin GRACE satellites, and its regularization using prior knowledge on the water cycle. Our demonstration of surface water mass signals decomposition in time and space is based on the use of synthetic along-track gravitational potential data. We test the developed approach on one year of 4D gravity modeling and compare the reconstructed water heights to those of the input hydrological model. Perspectives of this work is to apply the approach on real GRACE data, addressing the challenge of a realistic noise, to better describe and understand physical processus with high temporal resolution/low spatial resolution or the contrary.
Impact activation of Martian permafrost: Numerical modeling
NASA Astrophysics Data System (ADS)
Ivanov, B.; Melosh, H. J.
2011-12-01
For the last decade the team of Dr. Elisabetta (Betty) Pierazzo (LPL+PSI) study physical and mechanical processes involved in impact melting of Martian permafrost. The idea is that on Mars large enough impact craters would start substantial hydrothermal activity underneath the crater for thousands of years (possibly for >1 Myr, if a crater is larger than about 200 km in diameter). Numerical efforts to predict the extent and time scale of hydrothermal activity in Martian impact craters have mostly relied on numerical simulations of impact cratering into uniform or layered ice-rock targets. We conduct a case modeling study of impact melting of permafrost on Mars to investigate the general thermal state of the rock layers modified in the formation of hyper-velocity impact craters. We model the formation of a mid-size crater, about 30 km in diameter, formed on target consisting of a mixture of large particles of H2O-ice and rock (something like ice lenses in rock fractures) and fine mix equilibrated in temperature with an ice/water content variable with depth. The model results indicate that for craters larger than about 30 km in diameter the onset of post-impact hydrothermal circulation is characterized by two stages: first, the formation of a mostly dry, hot central uplift, followed by water beginning to flow in and circulate through the initially dry and hot uplifted crustal rocks. The post-impact thermal field in the periphery of the crater is dependent on crater size: in mid-size craters, 30-50 km in diameter, crater walls are not strongly heated in the impact event, and even though ice present in the rock may initially be heated enough to melt, overall temperatures in the rock remain below melting, undermining the development of a crater-wide hydrothermal circulation. We speculate that salt deposition from supercritical water may occur immediately after impact in some locations before the normal water circulation starts. In larger craters, crater walls are heated
Multiaxial Temperature- and Time-Dependent Failure Model
NASA Technical Reports Server (NTRS)
Richardson, David; McLennan, Michael; Anderson, Gregory; Macon, David; Batista-Rodriquez, Alicia
2003-01-01
A temperature- and time-dependent mathematical model predicts the conditions for failure of a material subjected to multiaxial stress. The model was initially applied to a filled epoxy below its glass-transition temperature, and is expected to be applicable to other materials, at least below their glass-transition temperatures. The model is justified simply by the fact that it closely approximates the experimentally observed failure behavior of this material: The multiaxiality of the model has been confirmed (see figure) and the model has been shown to be applicable at temperatures from -20 to 115 F (-29 to 46 C) and to predict tensile failures of constant-load and constant-load-rate specimens with failure times ranging from minutes to months..
A continuous-time neural model for sequential action.
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard
2014-11-01
Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions.
A continuous-time neural model for sequential action
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C.; de Kleijn, Roy; Hommel, Bernhard
2014-01-01
Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. PMID:25267830
Exact solution for the time evolution of network rewiring models
NASA Astrophysics Data System (ADS)
Evans, T. S.; Plato, A. D. K.
2007-05-01
We consider the rewiring of a bipartite graph using a mixture of random and preferential attachment. The full mean-field equations for the degree distribution and its generating function are given. The exact solution of these equations for all finite parameter values at any time is found in terms of standard functions. It is demonstrated that these solutions are an excellent fit to numerical simulations of the model. We discuss the relationship between our model and several others in the literature, including examples of urn, backgammon, and balls-in-boxes models, the Watts and Strogatz rewiring problem, and some models of zero range processes. Our model is also equivalent to those used in various applications including cultural transmission, family name and gene frequencies, glasses, and wealth distributions. Finally some Voter models and an example of a minority game also show features described by our model.
Generating survival times to simulate Cox proportional hazards models with time-varying covariates.
Austin, Peter C
2012-12-20
Simulations and Monte Carlo methods serve an important role in modern statistical research. They allow for an examination of the performance of statistical procedures in settings in which analytic and mathematical derivations may not be feasible. A key element in any statistical simulation is the existence of an appropriate data-generating process: one must be able to simulate data from a specified statistical model. We describe data-generating processes for the Cox proportional hazards model with time-varying covariates when event times follow an exponential, Weibull, or Gompertz distribution. We consider three types of time-varying covariates: first, a dichotomous time-varying covariate that can change at most once from untreated to treated (e.g., organ transplant); second, a continuous time-varying covariate such as cumulative exposure at a constant dose to radiation or to a pharmaceutical agent used for a chronic condition; third, a dichotomous time-varying covariate with a subject being able to move repeatedly between treatment states (e.g., current compliance or use of a medication). In each setting, we derive closed-form expressions that allow one to simulate survival times so that survival times are related to a vector of fixed or time-invariant covariates and to a single time-varying covariate. We illustrate the utility of our closed-form expressions for simulating event times by using Monte Carlo simulations to estimate the statistical power to detect as statistically significant the effect of different types of binary time-varying covariates. This is compared with the statistical power to detect as statistically significant a binary time-invariant covariate.
Reading and a diffusion model analysis of reaction time.
Naples, Adam; Katz, Leonard; Grigorenko, Elena L
2012-01-01
Processing speed is associated with reading performance. However, the literature is not clear either on the definition of processing speed or on why and how it contributes to reading performance. In this study we demonstrated that processing speed, as measured by reaction time, is not a unitary construct. Using the diffusion model of two-choice reaction time, we assessed processing speed in a series of same-different reaction time tasks for letter and number strings. We demonstrated that the association between reaction time and reading performance is driven by processing speed for reading-related information, but not motor or sensory encoding speed.
Reading and a Diffusion Model Analysis of Reaction Time
Naples, Adam; Katz, Leonard; Grigorenko, Elena L.
2012-01-01
Processing speed is associated with reading performance. However, the literature is not clear either on the definition of processing speed or on why and how it contributes to reading performance. In this study we demonstrated that processing speed, as measured by reaction time, is not a unitary construct. Using the diffusion model of two-choice reaction time, we assessed processing speed in a series of same-different reaction time tasks for letter and number strings. We demonstrated that the association between reaction time and reading performance is driven by processing speed for reading-related information, but not motor or sensory encoding speed. PMID:22612543
Time-partitioning simulation models for calculation on parallel computers
NASA Technical Reports Server (NTRS)
Milner, Edward J.; Blech, Richard A.; Chima, Rodrick V.
1987-01-01
A technique allowing time-staggered solution of partial differential equations is presented in this report. Using this technique, called time-partitioning, simulation execution speedup is proportional to the number of processors used because all processors operate simultaneously, with each updating of the solution grid at a different time point. The technique is limited by neither the number of processors available nor by the dimension of the solution grid. Time-partitioning was used to obtain the flow pattern through a cascade of airfoils, modeled by the Euler partial differential equations. An execution speedup factor of 1.77 was achieved using a two processor Cray X-MP/24 computer.
A novel trauma leadership model reflective of changing times.
DʼHuyvetter, Cecile; Cogbill, Thomas H
2014-01-01
As a result of generational changes in the health care workforce, we sought to evaluate our current Trauma Medical Director Leadership model. We assessed the responsibilities, accountability, time requirements, cost, and provider satisfaction with the current leadership model. Three new providers who had recently completed fellowship training were hired, each with unique professional desires, skill sets, and experience. Our goal was to establish a comprehensive, cost-effective, accountable leadership model that enabled provider satisfaction and equalized leadership responsibilities. A 3-pronged team model was established with a Medical Director title and responsibilities rotating per the American College of Surgeons verification cycle to develop leadership skills and lessen hierarchical differences.
Multiple-relaxation-time model for the correct thermohydrodynamic equations.
Zheng, Lin; Shi, Baochang; Guo, Zhaoli
2008-08-01
A coupling lattice Boltzmann equation (LBE) model with multiple relaxation times is proposed for thermal flows with viscous heat dissipation and compression work. In this model the fixed Prandtl number and the viscous dissipation problems in the energy equation, which exist in most of the LBE models, are successfully overcome. The model is validated by simulating the two-dimensional Couette flow, thermal Poiseuille flow, and the natural convection flow in a square cavity. It is found that the numerical results agree well with the analytical solutions and/or other numerical results.
Time-Delayed Models of Gene Regulatory Networks
Parmar, K.; Blyuss, K. B.; Kyrychko, Y. N.; Hogan, S. J.
2015-01-01
We discuss different mathematical models of gene regulatory networks as relevant to the onset and development of cancer. After discussion of alternative modelling approaches, we use a paradigmatic two-gene network to focus on the role played by time delays in the dynamics of gene regulatory networks. We contrast the dynamics of the reduced model arising in the limit of fast mRNA dynamics with that of the full model. The review concludes with the discussion of some open problems. PMID:26576197
Virtual sensor models for real-time applications
NASA Astrophysics Data System (ADS)
Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin
2016-09-01
Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.
Time series ARIMA models for daily price of palm oil
NASA Astrophysics Data System (ADS)
Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu
2015-02-01
Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.
A model for discriminating reinforcers in time and space.
Cowie, Sarah; Davison, Michael; Elliffe, Douglas
2016-06-01
Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a
A model for discriminating reinforcers in time and space.
Cowie, Sarah; Davison, Michael; Elliffe, Douglas
2016-06-01
Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a
Innovative techniques to analyze time series of geomagnetic activity indices
NASA Astrophysics Data System (ADS)
Balasis, Georgios; Papadimitriou, Constantinos; Daglis, Ioannis A.; Potirakis, Stelios M.; Eftaxias, Konstantinos
2016-04-01
Magnetic storms are undoubtedly among the most important phenomena in space physics and also a central subject of space weather. The non-extensive Tsallis entropy has been recently introduced, as an effective complexity measure for the analysis of the geomagnetic activity Dst index. The Tsallis entropy sensitively shows the complexity dissimilarity among different "physiological" (normal) and "pathological" states (intense magnetic storms). More precisely, the Tsallis entropy implies the emergence of two distinct patterns: (i) a pattern associated with the intense magnetic storms, which is characterized by a higher degree of organization, and (ii) a pattern associated with normal periods, which is characterized by a lower degree of organization. Other entropy measures such as Block Entropy, T-Complexity, Approximate Entropy, Sample Entropy and Fuzzy Entropy verify the above mentioned result. Importantly, the wavelet spectral analysis in terms of Hurst exponent, H, also shows the existence of two different patterns: (i) a pattern associated with the intense magnetic storms, which is characterized by a fractional Brownian persistent behavior (ii) a pattern associated with normal periods, which is characterized by a fractional Brownian anti-persistent behavior. Finally, we observe universality in the magnetic storm and earthquake dynamics, on a basis of a modified form of the Gutenberg-Richter law for the Tsallis statistics. This finding suggests a common approach to the interpretation of both phenomena in terms of the same driving physical mechanism. Signatures of discrete scale invariance in Dst time series further supports the aforementioned proposal.
Activity in prelimbic cortex subserves fear memory reconsolidation over time
Stern, Cristina A.J.; Gazarini, Lucas; Vanvossen, Ana C.; Hames, Mayara S.; Bertoglio, Leandro J.
2014-01-01
The prelimbic cortex has been implicated in the consolidation of previously learned fear. Herein, we report that temporarily inactivating this medial prefrontal cortex subregion with the GABAA agonist muscimol (4.0 nmol in 0.2 μL per hemisphere) was able to equally disrupt 1-, 7-, and 21-d-old contextual fear memories after their brief retrieval in rats. In all cases, this effect was prevented when memory reactivation was omitted. These results indicate that recent and remote fear memories are susceptible to reconsolidation blockade induced by prelimbic cortex inactivation. It was also demonstrated that the disrupting effect of prelimbic cortex inactivation on fear memory persisted over 11 d, and did not show extinction-related features, such as reinstatement. Infusing the same dose and volume of muscimol bilaterally into the infralimbic cortex after brief retrieval/reactivation of the fear memory did not disrupt it, as seen in prelimbic cortex-inactivated animals. The expression of Zif268/Egr1, the product of an immediate early gene related to memory reconsolidation, was also less pronounced in the infralimbic cortex than in prelimbic cortex following memory retrieval/reactivation. Altogether, the present findings highlight that activity in the prelimbic cortex may reestablish reactivated aversive memories and, therefore, contribute to their maintenance over time. PMID:24344180
A Time-Varying Effect Model for Intensive Longitudinal Data
Tan, Xianming; Shiyko, Mariya P.; Li, Runze; Li, Yuelin; Dierker, Lisa
2011-01-01
Understanding temporal change in human behavior and psychological processes is a central issue in the behavioral sciences. With technological advances, intensive longitudinal data (ILD) are increasingly generated by studies of human behavior that repeatedly administer assessments over time. ILD offer unique opportunities to describe temporal behavioral changes in detail and identify related environmental and psychosocial antecedents and consequences. Traditional analytical approaches impose strong parametric assumptions about the nature of change in the relationship between time-varying covariates and outcomes of interest. This paper introduces time-varying effect models (TVEM) that explicitly model changes in the association between ILD covariates and ILD outcomes over time in a flexible manner. In this article, we describes unique research questions that the TVEM addresses, outline the model-estimation procedure, share a SAS macro for implementing the model, demonstrate model utility with a simulated example, and illustrate model applications in ILD collected as part of a smoking-cessation study to explore the relationship between smoking urges and self-efficacy during the course of the pre- and post- cessation period. PMID:22103434
Modeling chloride transport using travel time distributions at Plynlimon, Wales
NASA Astrophysics Data System (ADS)
Benettin, Paolo; Kirchner, James W.; Rinaldo, Andrea; Botter, Gianluca
2015-05-01
Here we present a theoretical interpretation of high-frequency, high-quality tracer time series from the Hafren catchment at Plynlimon in mid-Wales. We make use of the formulation of transport by travel time distributions to model chloride transport originating from atmospheric deposition and compute catchment-scale travel time distributions. The relevance of the approach lies in the explanatory power of the chosen tools, particularly to highlight hydrologic processes otherwise clouded by the integrated nature of the measured outflux signal. The analysis reveals the key role of residual storages that are poorly visible in the hydrological response, but are shown to strongly affect water quality dynamics. A significant accuracy in reproducing data is shown by our calibrated model. A detailed representation of catchment-scale travel time distributions has been derived, including the time evolution of the overall dispersion processes (which can be expressed in terms of time-varying storage sampling functions). Mean computed travel times span a broad range of values (from 80 to 800 days) depending on the catchment state. Results also suggest that, in the average, discharge waters are younger than storage water. The model proves able to capture high-frequency fluctuations in the measured chloride concentrations, which are broadly explained by the sharp transition between groundwaters and faster flows originating from topsoil layers. This article was corrected on 22 JUN 2015. See the end of the full text for details.
American Time-Styles: A Finite-Mixture Allocation Model for Time-Use Analysis
ERIC Educational Resources Information Center
Kamakura, Wagner A.
2009-01-01
Time-use has already been the subject of numerous studies across multiple disciplines such as economics, marketing, sociology, transportation and urban planning. However, most of this research has focused on comparing demographic groups on a few broadly defined activities (e.g., work for pay, leisure, housework, etc.). In this study we take a…
Time series models based on generalized linear models: some further results.
Li, W K
1994-06-01
This paper considers the problem of extending the classical moving average models to time series with conditional distributions given by generalized linear models. These models have the advantage of easy construction and estimation. Statistical modelling techniques are also proposed. Some simulation results and an illustrative example are reported to illustrate the methodology. The models will have potential applications in longitudinal data analysis. PMID:8068850
Minimal state space realisation of continuous-time linear time-variant input-output models
NASA Astrophysics Data System (ADS)
Goos, J.; Pintelon, R.
2016-04-01
In the linear time-invariant (LTI) framework, the transformation from an input-output equation into state space representation is well understood. Several canonical forms exist that realise the same dynamic behaviour. If the coefficients become time-varying however, the LTI transformation no longer holds. We prove by induction that there exists a closed-form expression for the observability canonical state space model, using binomial coefficients.
Reaction times to weak test lights. [psychophysics biological model
NASA Technical Reports Server (NTRS)
Wandell, B. A.; Ahumada, P.; Welsh, D.
1984-01-01
Maloney and Wandell (1984) describe a model of the response of a single visual channel to weak test lights. The initial channel response is a linearly filtered version of the stimulus. The filter output is randomly sampled over time. Each time a sample occurs there is some probability increasing with the magnitude of the sampled response - that a discrete detection event is generated. Maloney and Wandell derive the statistics of the detection events. In this paper a test is conducted of the hypothesis that the reaction time responses to the presence of a weak test light are initiated at the first detection event. This makes it possible to extend the application of the model to lights that are slightly above threshold, but still within the linear operating range of the visual system. A parameter-free prediction of the model proposed by Maloney and Wandell for lights detected by this statistic is tested. The data are in agreement with the prediction.
Time series segmentation with shifting means hidden markov models
NASA Astrophysics Data System (ADS)
Kehagias, Ath.; Fortin, V.
2006-08-01
We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means models introduced by Chernoff and Zacks and by Salas and Boes. An estimation method inspired from the EM algorithm is proposed, and we show that it can accurately identify multiple change-points in a time series. We also show that the solution obtained using this algorithm can serve as a starting point for a Monte-Carlo Markov chain Bayesian estimation method, thus reducing the computing time needed for the Markov chain to converge to a stationary distribution.
Bifurcation and chaotic in a model for activated sludge reactors
NASA Astrophysics Data System (ADS)
El-Marouf, S. A. A.; Bahaa, G. M.
2015-04-01
A dynamical model of an activated sludge process system is considered and analyzed. Numerical techniques are used to show when the system exhibits chaos. Three choices of bifurcation parameters produce different pictures of solution behavior in the form of limit cycles, two-torus and chaotic behavior. For some range of the reactor residence time the model exhibits chaotic behavior as well. Practical criteria are also derived for the effects of feed conditions and purge fraction on the dynamic characteristics of the bioreactor model.
Variability of single trial brain activation predicts fluctuations in reaction time.
Bender, Stephan; Banaschewski, Tobias; Roessner, Veit; Klein, Christoph; Rietschel, Marcella; Feige, Bernd; Brandeis, Daniel; Laucht, Manfred
2015-03-01
Brain activation stability is crucial to understanding attention lapses. EEG methods could provide excellent markers to assess neuronal response variability with respect to temporal (intertrial coherence) and spatial variability (topographic consistency) as well as variations in activation intensity (low frequency variability of single trial global field power). We calculated intertrial coherence, topographic consistency and low frequency amplitude variability during target P300 in a continuous performance test in 263 15-year-olds from a cohort with psychosocial and biological risk factors. Topographic consistency and low frequency amplitude variability predicted reaction time fluctuations (RTSD) in a linear model. Higher RTSD was only associated with higher psychosocial adversity in the presence of the homozygous 6R-10R dopamine transporter haplotype. We propose that topographic variability of single trial P300 reflects noise as well as variability in evoked cortical activation patterns. Dopaminergic neuromodulation interacted with environmental and biological risk factors to predict behavioural reaction time variability.
Discrete-time pilot model. [human dynamics and digital simulation
NASA Technical Reports Server (NTRS)
Cavalli, D.
1978-01-01
Pilot behavior is considered as a discrete-time process where the decision making has a sequential nature. This model differs from both the quasilinear model which follows from classical control theory and from the optimal control model which considers the human operator as a Kalman estimator-predictor. An additional factor considered is that the pilot's objective may not be adequately formulated as a quadratic cost functional to be minimized, but rather as a more fuzzy measure of the closeness with which the aircraft follows a reference trajectory. All model parameters, in the digital program simulating the pilot's behavior, were successfully compared in terms of standard-deviation and performance with those of professional pilots in IFR configuration. The first practical application of the model was in the study of its performance degradation when the aircraft model static margin decreases.
Time domain analysis of the weighted distributed order rheological model
NASA Astrophysics Data System (ADS)
Cao, Lili; Pu, Hai; Li, Yan; Li, Ming
2016-05-01
This paper presents the fundamental solution and relevant properties of the weighted distributed order rheological model in the time domain. Based on the construction of distributed order damper and the idea of distributed order element networks, this paper studies the weighted distributed order operator of the rheological model, a generalization of distributed order linear rheological model. The inverse Laplace transform on weighted distributed order operators of rheological model has been obtained by cutting the complex plane and computing the complex path integral along the Hankel path, which leads to the asymptotic property and boundary discussions. The relaxation response to weighted distributed order rheological model is analyzed, and it is closely related to many physical phenomena. A number of novel characteristics of weighted distributed order rheological model, such as power-law decay and intermediate phenomenon, have been discovered as well. And meanwhile several illustrated examples play important role in validating these results.
Modeling Reaction Time and Accuracy of Multiple-Alternative Decisions
Leite, Fábio P.; Ratcliff, Roger
2009-01-01
Several sequential sampling models using racing diffusion processes for multiple-alternative decisions were evaluated using data from two perceptual discrimination experiments. The structures of the models differed on a number of dimensions, including whether there was lateral inhibition between accumulators, whether there was decay in evidence, whether evidence could be negative, and whether there was variability in starting points. Data were collected from a letter discrimination task in which stimulus difficulty and probability of the response alternatives were varied along with number of response alternatives. Model fitting results ruled out a large number of model classes in favor of a smaller number of specific models, most of which showed a moderate to high degree of mimicking. The best-fitting models had zero to moderate values of decay, no inhibition, and assumed that the addition of alternatives either affected the subprocesses contributing to the nondecisional time, the degree of caution, or the quality of evidence extracted from stimuli. PMID:20045893
Going up in time and length scales in modeling polymers
NASA Astrophysics Data System (ADS)
Grest, Gary S.
Polymer properties depend on a wide range of coupled length and time scales, with unique macroscopic viscoelastic behavior stemming from interactions at the atomistic level. The need to probe polymers across time and length scales and particularly computational modeling is inherently challenging. Here new paths to probing long time and length scales including introducing interactions into traditional bead-spring models and coarse graining of atomistic simulations will be compared and discussed. Using linear polyethylene as a model system, the degree of coarse graining with two to six methylene groups per coarse-grained bead derived from a fully atomistic melt simulation were probed. We show that the degree of coarse graining affects the measured dynamic. Using these models we were successful in probing highly entangled melts and were able reach the long-time diffusive regime which is computationally inaccessible using atomistic simulations. We simulated the relaxation modulus and shear viscosity of well-entangled polyethylene melts for scaled times of 500 µs. Results for plateau modulus are in good agreement with experiment. The long time and length scale is coupled to the macroscopic viscoelasticity where the degree of coarse graining sets the minimum length scale instrumental in defining polymer properties and dynamics. Results will be compared to those obtained from simple bead-spring models to demonstrate the additional insight that can be gained from atomistically inspired coarse grained models. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Monitoring volcano activity through Hidden Markov Model
NASA Astrophysics Data System (ADS)
Cassisi, C.; Montalto, P.; Prestifilippo, M.; Aliotta, M.; Cannata, A.; Patanè, D.
2013-12-01
During 2011-2013, Mt. Etna was mainly characterized by cyclic occurrences of lava fountains, totaling to 38 episodes. During this time interval Etna volcano's states (QUIET, PRE-FOUNTAIN, FOUNTAIN, POST-FOUNTAIN), whose automatic recognition is very useful for monitoring purposes, turned out to be strongly related to the trend of RMS (Root Mean Square) of the seismic signal recorded by stations close to the summit area. Since RMS time series behavior is considered to be stochastic, we can try to model the system generating its values, assuming to be a Markov process, by using Hidden Markov models (HMMs). HMMs are a powerful tool in modeling any time-varying series. HMMs analysis seeks to recover the sequence of hidden states from the observed emissions. In our framework, observed emissions are characters generated by the SAX (Symbolic Aggregate approXimation) technique, which maps RMS time series values with discrete literal emissions. The experiments show how it is possible to guess volcano states by means of HMMs and SAX.
REAL-TIME MODEL-BASED ELECTRICAL POWERED WHEELCHAIR CONTROL
Wang, Hongwu; Salatin, Benjamin; Grindle, Garrett G.; Ding, Dan; Cooper, Rory A.
2009-01-01
The purpose of this study was to evaluate the effects of three different control methods on driving speed variation and wheel-slip of an electric-powered wheelchair (EPW). A kinematic model as well as 3-D dynamic model was developed to control the velocity and traction of the wheelchair. A smart wheelchair platform was designed and built with a computerized controller and encoders to record wheel speeds and to detect the slip. A model based, a proportional-integral-derivative (PID) and an open-loop controller were applied with the EPW driving on four different surfaces at three specified speeds. The speed errors, variation, rise time, settling time and slip coefficient were calculated and compared for a speed step-response input. Experimental results showed that model based control performed best on all surfaces across the speeds. PMID:19733494
Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis
NASA Astrophysics Data System (ADS)
Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.
2015-06-01
This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.
Estimation of Time-Varying Pilot Model Parameters
NASA Technical Reports Server (NTRS)
Zaal, Peter M. T.; Sweet, Barbara T.
2011-01-01
Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.
Nonlinear parametric model for Granger causality of time series
NASA Astrophysics Data System (ADS)
Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano
2006-06-01
The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.
Assessing global vegetation activity using spatio-temporal Bayesian modelling
NASA Astrophysics Data System (ADS)
Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.
2016-04-01
This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support
Psychophysics of time perception and intertemporal choice models
NASA Astrophysics Data System (ADS)
Takahashi, Taiki; Oono, Hidemi; Radford, Mark H. B.
2008-03-01
Intertemporal choice and psychophysics of time perception have been attracting attention in econophysics and neuroeconomics. Several models have been proposed for intertemporal choice: exponential discounting, general hyperbolic discounting (exponential discounting with logarithmic time perception of the Weber-Fechner law, a q-exponential discount model based on Tsallis's statistics), simple hyperbolic discounting, and Stevens' power law-exponential discounting (exponential discounting with Stevens' power time perception). In order to examine the fitness of the models for behavioral data, we estimated the parameters and AICc (Akaike Information Criterion with small sample correction) of the intertemporal choice models by assessing the points of subjective equality (indifference points) at seven delays. Our results have shown that the orders of the goodness-of-fit for both group and individual data were [Weber-Fechner discounting (general hyperbola) > Stevens' power law discounting > Simple hyperbolic discounting > Exponential discounting], indicating that human time perception in intertemporal choice may follow the Weber-Fechner law. Indications of the results for neuropsychopharmacological treatments of addiction and biophysical processing underlying temporal discounting and time perception are discussed.
Positive outcomes increase over time with the implementation of a semiflipped teaching model.
Gorres-Martens, Brittany K; Segovia, Angela R; Pfefer, Mark T
2016-03-01
The flipped teaching model can engage students in the learning process and improve learning outcomes. The purpose of the present study was to assess the outcomes of a semiflipped teaching model over time. Neurophysiology students spent the majority of class time listening to traditional didactic lectures, but they also listened to 5 online lectures and spent 8-10 class periods completing an active learning assignment. At the end of the term, students completed a survey to assess the outcomes of the active learning assignments. The positive outcomes were greater the second time the course was taught in a semiflipped manner. While completely flipping a course takes a tremendous amount of time, instructors can still obtain positive outcomes by implementing a semiflipped teaching model. PMID:26847255
Positive outcomes increase over time with the implementation of a semiflipped teaching model.
Gorres-Martens, Brittany K; Segovia, Angela R; Pfefer, Mark T
2016-03-01
The flipped teaching model can engage students in the learning process and improve learning outcomes. The purpose of the present study was to assess the outcomes of a semiflipped teaching model over time. Neurophysiology students spent the majority of class time listening to traditional didactic lectures, but they also listened to 5 online lectures and spent 8-10 class periods completing an active learning assignment. At the end of the term, students completed a survey to assess the outcomes of the active learning assignments. The positive outcomes were greater the second time the course was taught in a semiflipped manner. While completely flipping a course takes a tremendous amount of time, instructors can still obtain positive outcomes by implementing a semiflipped teaching model.
Bayesian latent structure models with space-time-dependent covariates.
Cai, Bo; Lawson, Andrew B; Hossain, Md Monir; Choi, Jungsoon
2012-04-01
Spatial-temporal data requires flexible regression models which can model the dependence of responses on space- and time-dependent covariates. In this paper, we describe a semiparametric space-time model from a Bayesian perspective. Nonlinear time dependence of covariates and the interactions among the covariates are constructed by local linear and piecewise linear models, allowing for more flexible orientation and position of the covariate plane by using time-varying basis functions. Space-varying covariate linkage coefficients are also incorporated to allow for the variation of space structures across the geographical location. The formulation accommodates uncertainty in the number and locations of the piecewise basis functions to characterize the global effects, spatially structured and unstructured random effects in relation to covariates. The proposed approach relies on variable selection-type mixture priors for uncertainty in the number and locations of basis functions and in the space-varying linkage coefficients. A simulation example is presented to evaluate the performance of the proposed approach with the competing models. A real data example is used for illustration.
Short‐term time step convergence in a climate model
Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane
2015-01-01
Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities.
Time variability of α from realistic models of Oklo reactors
NASA Astrophysics Data System (ADS)
Gould, C. R.; Sharapov, E. I.; Lamoreaux, S. K.
2006-08-01
We reanalyze Oklo Sm149 data using realistic models of the natural nuclear reactors. Disagreements among recent Oklo determinations of the time evolution of α, the electromagnetic fine structure constant, are shown to be due to different reactor models, which led to different neutron spectra used in the calculations. We use known Oklo reactor epithermal spectral indices as criteria for selecting realistic reactor models. Two Oklo reactors, RZ2 and RZ10, were modeled with MCNP. The resulting neutron spectra were used to calculate the change in the Sm149 effective neutron capture cross section as a function of a possible shift in the energy of the 97.3-meV resonance. We independently deduce ancient Sm149 effective cross sections and use these values to set limits on the time variation of α. Our study resolves a contradictory situation with previous Oklo α results. Our suggested 2σ bound on a possible time variation of α over 2 billion years is stringent: -0.11≤Δα/α≤0.24, in units of 10-7, but model dependent in that it assumes only α has varied over time.
Multiple-Relaxation-Time Lattice Boltzmann Models in 3D
NASA Technical Reports Server (NTRS)
dHumieres, Dominique; Ginzburg, Irina; Krafczyk, Manfred; Lallemand, Pierre; Luo, Li-Shi; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
This article provides a concise exposition of the multiple-relaxation-time lattice Boltzmann equation, with examples of fifteen-velocity and nineteen-velocity models in three dimensions. Simulation of a diagonally lid-driven cavity flow in three dimensions at Re=500 and 2000 is performed. The results clearly demonstrate the superior numerical stability of the multiple-relaxation-time lattice Boltzmann equation over the popular lattice Bhatnagar-Gross-Krook equation.
A real-time groundwater management model using data assimilation
NASA Astrophysics Data System (ADS)
Cheng, Wei-Chen; Putti, Mario; Kendall, Donald R.; Yeh, William W.-G.
2011-06-01
This study develops a groundwater management model for real-time operation of an aquifer system. A groundwater flow model is allied with a nudging data assimilation algorithm that reduces the forecast error, minimizes the risk of system failure, and improves management strategies. The nudging algorithm treats the unknown private pumping as an additional sink term in the groundwater flow equation and provides a consistently physical interpretation for the identification of pumping rates. The system response due to pumping and injection is represented by a response matrix that is generated by the influence coefficient method. The response matrix (with a much smaller dimension) is used as a reduced model and is embedded directly in the management model as a part of the constraint set. Additionally, the influence coefficient method is utilized to include the nudging effect in the reduced model. The management model optimizes the monthly operation for 12 months into the future and determines the optimal strategy using the information provided by nudging. The management model is updated at the beginning of each month when new head observations and pumping data become available. We also discuss the utility, accuracy, and efficiency of the proposed management model for real-time operation.
A mixture hierarchical model for response times and response accuracy.
Wang, Chun; Xu, Gongjun
2015-11-01
In real testing, examinees may manifest different types of test-taking behaviours. In this paper we focus on two types that appear to be among the more frequently occurring behaviours – solution behaviour and rapid guessing behaviour. Rapid guessing usually happens in high-stakes tests when there is insufficient time, and in low-stakes tests when there is lack of effort. These two qualitatively different test-taking behaviours, if ignored, will lead to violation of the local independence assumption and, as a result, yield biased item/person parameter estimation. We propose a mixture hierarchical model to account for differences among item responses and response time patterns arising from these two behaviours. The model is also able to identify the specific behaviour an examinee engages in when answering an item. A Monte Carlo expectation maximization algorithm is proposed for model calibration. A simulation study shows that the new model yields more accurate item and person parameter estimates than a non-mixture model when the data indeed come from two types of behaviour. The model also fits real, high-stakes test data better than a non-mixture model, and therefore the new model can better identify the underlying test-taking behaviour an examinee engages in on a certain item. PMID:25873487
Empirical modeling of the quiet time nightside magnetosphere
NASA Technical Reports Server (NTRS)
Lui, A. T. Y.; Spence, H. E.; Stern, D. P.
1993-01-01
Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko (1989) but is modified by the addition of an inner eastward ring current at a radial distance of approximately 3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko (1987) such that the former dominates the magnetic field in the inner magnetosphere while the latter prevails in the distant tail. The distribution of plasma pressure which is required to balance the magnetic force for each of these two field models is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This represents the first effort to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of approximately 3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between approximately 2 and approximately 35 RE.
How valuable are animal models in defining antidepressant activity?
Bourin, M; Fiocco, A. J; Clenet, F
2001-01-01
Animal models of depression have been utilised to screen novel compounds with antidepressant potential although uncertainty lingers concerning their clinical relevance. In order for a model to be considered of any value, it must possess predictive validity (does drug action in the model correspond to that in the clinic?), face validity (are there phenomenological similarities between the model and the clinic?) and construct validity (does the model possess a strong theoretical rationale?). On the one hand, there are models based on stress such as the learned helplessness model, the forced swimming test and the chronic mild stress model and, on the other hand, models based on neuronal deficits such as the olfactory bulbectomy model. To date, among models more frequently used in depression, none of them meet all these criteria. Moreover, improvements to tests are often poorly validated and estimating time of onset of action of antidepressants remains a major challenge in animal model research. Finally, reproducing the tests outside the laboratory of origin continues to be problematic and leads to variability in results. Although animal models of depression fail to be unequivocally valid, they represent the best tool to define potential antidepressant activity of drugs, to investigate their mechanism of action and, to a greater extent, explore this complex heterogeneous illness. Copyright 2001 John Wiley & Sons, Ltd.
Active walker models: tracks and landscapes
NASA Astrophysics Data System (ADS)
Kayser, D. R.; Aberle, L. K.; Pochy, R. D.; Lam, L.
1992-12-01
The track patterns from the active walker models (AWMs) are compared with experimental retinal neuron and dielectric breakdown of liquid patterns, respectively. Excellent qualitative and quantitative agreements are obtained. The landscapes from the Boltzmann AWM in 1 + 1 dimensions form rough surfaces, with a first-order phase transition as the height of the landscaping function W0 is varied. Landscapes and statistics of the tracks from the probabilistic AWM in 2 + 1 dimensions are presented.
A two-stage model of radiological inspection: spending time
Brown, William S.
2000-07-30
The paper describes a model that visually portrays radiological survey performance as basic parameters (surveyor efficiency and criteria, duration of pause, and probe speed) are varied; field and laboratory tests provided typical parameter values. The model is used to illustrate how practical constraints on the time allotted to the task can affect radiological inspection performance. Similar analyses are applicable to a variety of other tasks (airport baggage inspection, and certain types of non-destructive testing) with similar characteristics and constraints.
Staiano, Amanda E; Broyles, Stephanie T; Katzmarzyk, Peter T
2015-07-30
This cross-sectional study examined differences in children's health behaviors during school term (ST) versus school holiday (SH: June-July) and how associations changed when weather characteristics were considered. Children aged 5-18 years (n = 406) from a subtropical climate reported behaviors over 20 months. Multivariable regression models controlling for age, sex, race and body mass index z-score (BMIz) were used to examine associations between SH and each behavior. A second model included heat index, precipitation and daylight hours. Strenuous activity, moderate activity, total activity and TV viewing were significantly higher during SH than ST. After adjusting for weather characteristics, total activity remained significantly higher during SH, but the association with TV viewing was attenuated. Youth surveyed during high precipitation were significantly less likely to meet physical activity guidelines. There were no significant associations between SH and meeting sleep, physical activity or screen-time guidelines. Weather characteristics influenced associations between SH and youth's physical activity and TV viewing.
Neuron type processor modeling using a timed Petri net.
Habib, M K; Newcomb, R W
1990-01-01
The basic operation of a digital neuron is reviewed, and the theory of time Petri nets used for modeling, representation, and analysis of the neuron-type processor (NTP) is reviewed. The timed Petri net is utilized to produce a model for the digital NTP. The neuron-type processor performs input temporal and spatial summation, as well as thresholding. The timed Petri net of the NTP operates asynchronously and sequentially takes on a series of distinct internal states, so that each of these states can concurrently realize a distinct set of steering switching functions depending on the pattern of steering inputs applied to it at the time. This model is structured using several subnets, called essential module units. Depending on the desired number of input dendrites required for the NTP, the essential module units (EMU) are interconnected to produce the required timed Petri net. The timed Petri net and representation facilitates a method of analysis of neural net works containing NTPs prior to hardware implementation.
Motivation and timing: clues for modeling the reward system.
Galtress, Tiffany; Marshall, Andrew T; Kirkpatrick, Kimberly
2012-05-01
There is growing evidence that a change in reward magnitude or value alters interval timing, indicating that motivation and timing are not independent processes as was previously believed. The present paper reviews several recent studies, as well as presenting some new evidence with further manipulations of reward value during training vs. testing on a peak procedure. The combined results cannot be accounted for by any of the current psychological timing theories. However, in examining the neural circuitry of the reward system, it is not surprising that motivation has an impact on timing because the motivation/valuation system directly interfaces with the timing system. A new approach is proposed for the development of the next generation of timing models, which utilizes knowledge of the neuroanatomy and neurophysiology of the reward system to guide the development of a neurocomputational model of the reward system. The initial foundation along with heuristics for proceeding with developing such a model is unveiled in an attempt to stimulate new theoretical approaches in the field. PMID:22421220
Motivation and timing: clues for modeling the reward system.
Galtress, Tiffany; Marshall, Andrew T; Kirkpatrick, Kimberly
2012-05-01
There is growing evidence that a change in reward magnitude or value alters interval timing, indicating that motivation and timing are not independent processes as was previously believed. The present paper reviews several recent studies, as well as presenting some new evidence with further manipulations of reward value during training vs. testing on a peak procedure. The combined results cannot be accounted for by any of the current psychological timing theories. However, in examining the neural circuitry of the reward system, it is not surprising that motivation has an impact on timing because the motivation/valuation system directly interfaces with the timing system. A new approach is proposed for the development of the next generation of timing models, which utilizes knowledge of the neuroanatomy and neurophysiology of the reward system to guide the development of a neurocomputational model of the reward system. The initial foundation along with heuristics for proceeding with developing such a model is unveiled in an attempt to stimulate new theoretical approaches in the field.
van der Vinne, V; Akkerman, J; Lanting, G D; Riede, S J; Hut, R A
2015-09-24
Circadian clocks drive daily rhythms in physiology and behavior which allow organisms to anticipate predictable daily changes in the environment. In most mammals, circadian rhythms result in nocturnal activity patterns although plasticity of the circadian system allows activity patterns to shift to different times of day. Such plasticity is seen when food access is restricted to a few hours during the resting (light) phase resulting in food anticipatory activity (FAA) in the hours preceding food availability. The mechanisms underlying FAA are unknown but data suggest the involvement of the reward system and homeostatic regulation of metabolism. We previously demonstrated the isolated effect of metabolism by inducing diurnality in response to energetic challenges. Here the importance of reward timing in inducing daytime activity is assessed. The daily activity distribution of mice earning palatable chocolate at their preferred time by working in a running wheel was compared with that of mice receiving a timed palatable meal at noon. Mice working for chocolate (WFC) without being energetically challenged increased their total daily activity but this did not result in a shift to diurnality. Providing a chocolate meal at noon each day increased daytime activity, identifying food timing as a factor capable of altering the daily distribution of activity and rest. These results show that timing of food reward and energetic challenges are both independently sufficient to induce diurnality in nocturnal mammals. FAA observed following timed food restriction is likely the result of an additive effect of distinct regulatory pathways activated by energetic challenges and food reward.
van der Vinne, V; Akkerman, J; Lanting, G D; Riede, S J; Hut, R A
2015-09-24
Circadian clocks drive daily rhythms in physiology and behavior which allow organisms to anticipate predictable daily changes in the environment. In most mammals, circadian rhythms result in nocturnal activity patterns although plasticity of the circadian system allows activity patterns to shift to different times of day. Such plasticity is seen when food access is restricted to a few hours during the resting (light) phase resulting in food anticipatory activity (FAA) in the hours preceding food availability. The mechanisms underlying FAA are unknown but data suggest the involvement of the reward system and homeostatic regulation of metabolism. We previously demonstrated the isolated effect of metabolism by inducing diurnality in response to energetic challenges. Here the importance of reward timing in inducing daytime activity is assessed. The daily activity distribution of mice earning palatable chocolate at their preferred time by working in a running wheel was compared with that of mice receiving a timed palatable meal at noon. Mice working for chocolate (WFC) without being energetically challenged increased their total daily activity but this did not result in a shift to diurnality. Providing a chocolate meal at noon each day increased daytime activity, identifying food timing as a factor capable of altering the daily distribution of activity and rest. These results show that timing of food reward and energetic challenges are both independently sufficient to induce diurnality in nocturnal mammals. FAA observed following timed food restriction is likely the result of an additive effect of distinct regulatory pathways activated by energetic challenges and food reward. PMID:26215921
Breeding return times and abundance in capture-recapture models.
Pledger, Shirley; Baker, Edward; Scribner, Kim
2013-12-01
For many long-lived animal species, individuals do not breed every year, and are often not accessible during non-breeding periods. Individuals exhibit site fidelity if they return to the same breeding colony or spawning ground when they breed. If capture and recapture is only possible at the breeding site, temporary emigration models are used to allow for only a subset of the animals being present in any given year. Most temporary emigration models require the use of the robust sampling design, and their focus is usually on probabilities of annual survival and of transition between breeding and non-breeding states. We use lake sturgeon (Acipenser fulvescens) data from a closed population where only a simple (one sample per year) sampling scheme is possible, and we also wish to estimate abundance as well as sex-specific survival and breeding return time probabilities. By adding return time parameters to the Schwarz-Arnason version of the Jolly-Seber model, we have developed a new likelihood-based model which yields plausible estimates of abundance, survival, transition and return time parameters. An important new finding from investigation of the model is the overestimation of abundance if a Jolly-Seber model is used when Markovian temporary emigration is present.
Modeling Pubertal Timing and Tempo and Examining Links to Behavior Problems
Beltz, Adriene M.; Corley, Robin P.; Bricker, Josh B.; Wadsworth, Sally J.; Berenbaum, Sheri A.
2014-01-01
Research on the role of puberty in adolescent psychological development requires attention to the meaning and measurement of pubertal development. Particular questions concern the utility of self report, the need for complex models to describe pubertal development, the psychological significance of pubertal timing versus tempo, and sex differences in the nature and psychological significance of pubertal development. We used longitudinal self-report data to model linear and logistic trajectories of pubertal development, and used timing and tempo estimates from these models, and from traditional approaches (age at menarche and time from onset of breast development to menarche), to predict psychological outcomes of internalizing and externalizing behavior problems, and early sexual activity. Participants (738 girls, 781 boys) reported annually from ages 9 through 15 on their pubertal development, and they and their parents reported on their behavior in mid-to-late adolescence and early adulthood. Self reports of pubertal development provided meaningful data for both boys and girls, producing good trajectories, and estimates of individuals’ pubertal timing and tempo. A logistic model best fit the group data. Pubertal timing was estimated to be earlier in the logistic compared to linear model, but linear, logistic, and traditional estimates of pubertal timing correlated highly with each other and similarly with psychological outcomes. Pubertal tempo was not consistently estimated, and associations of tempo with timing and with behavior were model dependent. Advances in modeling facilitate the study of some questions about pubertal development, but assumptions of the models affect their utility in psychological studies. PMID:25437757
Modeling pubertal timing and tempo and examining links to behavior problems.
Beltz, Adriene M; Corley, Robin P; Bricker, Josh B; Wadsworth, Sally J; Berenbaum, Sheri A
2014-12-01
Research on the role of puberty in adolescent psychological development requires attention to the meaning and measurement of pubertal development. Particular questions concern the utility of self-report, the need for complex models to describe pubertal development, the psychological significance of pubertal timing vs. tempo, and sex differences in the nature and psychological significance of pubertal development. We used longitudinal self-report data to model linear and logistic trajectories of pubertal development, and used timing and tempo estimates from these models, and from traditional approaches (age at menarche and time from onset of breast development to menarche), to predict psychological outcomes of internalizing and externalizing behavior problems, and early sexual activity. Participants (738 girls, 781 boys) reported annually from ages 9 through 15 on their pubertal development, and they and their parents reported on their behavior in mid-to-late adolescence and early adulthood. Self-reports of pubertal development provided meaningful data for both boys and girls, producing good trajectories, and estimates of individuals' pubertal timing and tempo. A logistic model best fit the group data. Pubertal timing was estimated to be earlier in the logistic compared to linear model, but linear, logistic, and traditional estimates of pubertal timing correlated highly with each other and similarly with psychological outcomes. Pubertal tempo was not consistently estimated, and associations of tempo with timing and with behavior were model dependent. Advances in modeling facilitate the study of some questions about pubertal development, but assumptions of the models affect their utility in psychological studies.
Models of emergency departments for reducing patient waiting times.
Laskowski, Marek; McLeod, Robert D; Friesen, Marcia R; Podaima, Blake W; Alfa, Attahiru S
2009-07-02
In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial-topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed.
Models of Emergency Departments for Reducing Patient Waiting Times
Laskowski, Marek; McLeod, Robert D.; Friesen, Marcia R.; Podaima, Blake W.; Alfa, Attahiru S.
2009-01-01
In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial–topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed. PMID:19572015
NASA Astrophysics Data System (ADS)
Altenkirch, Nora; Mutz, Michael; Molkenthin, Frank; Zlatanovic, Sanja; Trauth, Nico
2016-04-01
The interaction of the water residence time in hyporheic sediments with the sediment metabolic rates is believed to be a key factor controlling whole stream metabolism. However, due to the methodological difficulties, there is little data that investigates this fundamental theory of aquatic ecology. Here, we report on progress made to combine numerical modeling with a series of manipulation to laboratory flumes overcoming methodological difficulties. In these flumes, hydraulic conditions were assessed using non-reactive tracer and heat pulse sensor. Metabolic activity was measured as the consumption and production of oxygen and the turnover of reactive tracers. Residence time and metabolic processes were modeled using a multicomponent reactive transport code called Min3P and calibrated with regard to the hydraulic conditions using the results obtained from the flume experiments. The metabolic activity was implemented in the model via Monod type expressions e.g. for aerobic respiration rates. A number of sediment structures differing in residence time distributions were introduced in both, the model and the flumes, specifically to model the biogeochemical performance and to validate the model results. Furthermore, the DOC supply and surface water flow velocity were altered to test the whole stream metabolic response. Using the results of the hydrological process model, a sensitivity analysis of the impact of residence time distributions on the metabolic activity could yield supporting proof of an existing link between the two.
Applying the multivariate time-rescaling theorem to neural population models
Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon
2011-01-01
Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436
Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H
2016-09-01
Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time
Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H
2016-09-01
Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time
NASA Astrophysics Data System (ADS)
Shiau, Lie-Ding; Wang, Hsu-Pei
2016-05-01
A model is developed in this work to calculate the interfacial energy and growth activation energy of a crystallized substance from induction time data without the knowledge of the actual growth rate. Induction time data for αL-glutamic acid measured with a turbidity probe for various supersaturations at temperatures from 293 to 313 K are employed to verify the developed model. In the model a simple empirical growth rate with growth order 2 is assumed because experiments are conducted at low supersaturation. The results indicate for αL-glutamic acid that the growth activation energy is 39 kJ/mol, which suggests that the growth rate of small nuclei in the agitated induction time experiments is integration controlled. The interfacial energy obtained from the current model is in the range of 5.2-7.4 mJ/m2, which is slightly greater than that obtained from the traditional method (ti-1∝ J) for which the value is in the range 4.1-5.7 mJ/m2.
Hamilton, Kyra; Thomson, Courtney E; White, Katherine M
2013-07-01
Given increasing trends of obesity being noted from early in life and that active lifestyles track across time, it is important that children at a very young age be active to combat a foundation of unhealthy behaviours forming. This study investigated, within a theory of planned behaviour (TPB) framework, factors which influence mothers' decisions about their child's (1) adequate physical activity (PA) and (2) limited screen time behaviours. Mothers (N = 162) completed a main questionnaire, via on-line or paper-based administration, which comprised standard TPB items in addition to measures of planning and background demographic variables. One week later, consenting mothers completed a follow-up telephone questionnaire which assessed the decisions they had made regarding their child's PA and screen time behaviours during the previous week. Hierarchical multiple regression analyses revealed support for the predictive model, explaining an overall 73 and 78 % of the variance in mothers' intention and 38 and 53 % of the variance in mothers' decisions to ensure their child engages in adequate PA and limited screen time, respectively. Attitude and subjective norms predicted intention in both target behaviours, as did intentions with behaviour. Contrary to predictions, perceived behavioural control (PBC) in PA behaviour and planning in screen time behaviour were not significant predictors of intention, neither was PBC a predictor of either behaviour. The findings illustrate the various roles that psycho-social factors play in mothers' decisions to ensure their child engages in active lifestyle behaviours which can help to inform future intervention programs aimed at combating very young children's inactivity. PMID:22833334
A simple physical model for deep moonquake occurrence times
Weber, R.C.; Bills, B.G.; Johnson, C.L.
2010-01-01
The physical process that results in moonquakes is not yet fully understood. The periodic occurrence times of events from individual clusters are clearly related to tidal stress, but also exhibit departures from the temporal regularity this relationship would seem to imply. Even simplified models that capture some of the relevant physics require a large number of variables. However, a single, easily accessible variable - the time interval I(n) between events - can be used to reveal behavior not readily observed using typical periodicity analyses (e.g., Fourier analyses). The delay-coordinate (DC) map, a particularly revealing way to display data from a time series, is a map of successive intervals: I(n+. 1) plotted vs. I(n). We use a DC approach to characterize the dynamics of moonquake occurrence. Moonquake-like DC maps can be reproduced by combining sequences of synthetic events that occur with variable probability at tidal periods. Though this model gives a good description of what happens, it has little physical content, thus providing only little insight into why moonquakes occur. We investigate a more mechanistic model. In this study, we present a series of simple models of deep moonquake occurrence, with consideration of both tidal stress and stress drop during events. We first examine the behavior of inter-event times in a delay-coordinate context, and then examine the output, in that context, of a sequence of simple models of tidal forcing and stress relief. We find, as might be expected, that the stress relieved by moonquakes influences their occurrence times. Our models may also provide an explanation for the opposite-polarity events observed at some clusters. ?? 2010.
Modeling error analysis of stationary linear discrete-time filters
NASA Technical Reports Server (NTRS)
Patel, R.; Toda, M.
1977-01-01
The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available.
Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions
Huddleston, R L
2004-01-27
A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.
On a Quantum Model of Brain Activities
NASA Astrophysics Data System (ADS)
Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.
2010-01-01
One of the main activities of the brain is the recognition of signals. A first attempt to explain the process of recognition in terms of quantum statistics was given in [6]. Subsequently, details of the mathematical model were presented in a (still incomplete) series of papers (cf. [7, 2, 5, 10]). In the present note we want to give a general view of the principal ideas of this approach. We will introduce the basic spaces and justify the choice of spaces and operations. Further, we bring the model face to face with basic postulates any statistical model of the recognition process should fulfill. These postulates are in accordance with the opinion widely accepted in psychology and neurology.
Model-free quantification of time-series predictability
NASA Astrophysics Data System (ADS)
Garland, Joshua; James, Ryan; Bradley, Elizabeth
2014-11-01
This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that redundancy is an effective way to measure complexity and predictive structure in an experimental time series and that weighted permutation entropy is an effective way to estimate that redundancy. To validate these conjectures, we study 120 different time-series data sets. For each time series, we construct predictions using a wide variety of forecast models, then compare the accuracy of the predictions with the permutation entropy of that time series. We use the results to develop a model-free heuristic that can help practitioners recognize when a particular prediction method is not well matched to the task at hand: that is, when the time series has more predictive structure than that method can capture and exploit.
Model-free quantification of time-series predictability.
Garland, Joshua; James, Ryan; Bradley, Elizabeth
2014-11-01
This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that redundancy is an effective way to measure complexity and predictive structure in an experimental time series and that weighted permutation entropy is an effective way to estimate that redundancy. To validate these conjectures, we study 120 different time-series data sets. For each time series, we construct predictions using a wide variety of forecast models, then compare the accuracy of the predictions with the permutation entropy of that time series. We use the results to develop a model-free heuristic that can help practitioners recognize when a particular prediction method is not well matched to the task at hand: that is, when the time series has more predictive structure than that method can capture and exploit.
Joint space-time geostatistical model for air quality surveillance
NASA Astrophysics Data System (ADS)
Russo, A.; Soares, A.; Pereira, M. J.
2009-04-01
Air pollution and peoples' generalized concern about air quality are, nowadays, considered to be a global problem. Although the introduction of rigid air pollution regulations has reduced pollution from industry and power stations, the growing number of cars on the road poses a new pollution problem. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. As most natural phenomena, air quality can be seen as a space-time process, where space-time relationships have usually quite different characteristics and levels of uncertainty. As a result, the simultaneous integration of space and time is not an easy task to perform. This problem is overcome by a variety of methodologies. The use of stochastic models and neural networks to characterize space-time dispersion of air quality is becoming a common practice. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of a hybrid approach, based on the combined use of neural network models and stochastic simulations. A stochastic simulation of the spatial component with a space-time trend model is proposed to characterize critical situations, taking into account data from the past and a space-time trend from the recent past. To identify near future critical episodes, predicted values from neural networks are used at each monitoring station. In this paper, we describe the design of a hybrid forecasting tool for ambient NO2 concentrations in Lisbon, Portugal.
State-time spectrum of signal transduction logic models
NASA Astrophysics Data System (ADS)
MacNamara, Aidan; Terfve, Camille; Henriques, David; Peñalver Bernabé, Beatriz; Saez-Rodriguez, Julio
2012-08-01
Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments.
Clark, L A; Denby, L; Pregibon, D; Harshfield, G A; Pickering, T G; Blank, S; Laragh, J H
1987-01-01
The effects of activity and time of day on blood pressure (BP) were analyzed in 461 patients with untreated hypertension who wore a noninvasive portable BP recorder which took readings every 15 minutes for 24 hours. Patients recorded activity and location in a diary. The data were analyzed separately for two groups of patients: the 190 who stayed at home and the 271 who went to work. The effects of 16 different activities on BP were estimated by relating the BP to the associated activity and to the individual's clinic BP. Blood pressure was higher at work than at home, but the increment of BP for individual activities was similar in the two locations. The overall effect of activities on BP variability was computed using a one-way analysis of covariance model. For the patients who went to work this model accounted for 40% of the observed variation (R2) for systolic and 39% for diastolic BP. A similar model using time of day instead of activity accounted for 33% of variability in both systolic and diastolic BP. Combining activity and time of day was little better than activity alone (41% for both). After allowing for the effects of activity on BP, where sleep is one of the activities, there was no significant diurnal variation of BP. We conclude that there is no important circadian rhythm of BP which is independent of activity. PMID:3597670
A Symmetric Time-Varying Cluster Rate of Descent Model
NASA Technical Reports Server (NTRS)
Ray, Eric S.
2015-01-01
A model of the time-varying rate of descent of the Orion vehicle was developed based on the observed correlation between canopy projected area and drag coefficient. This initial version of the model assumes cluster symmetry and only varies the vertical component of velocity. The cluster fly-out angle is modeled as a series of sine waves based on flight test data. The projected area of each canopy is synchronized with the primary fly-out angle mode. The sudden loss of projected area during canopy collisions is modeled at minimum fly-out angles, leading to brief increases in rate of descent. The cluster geometry is converted to drag coefficient using empirically derived constants. A more complete model is under development, which computes the aerodynamic response of each canopy to its local incidence angle.
TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information
Kim, Yongsoo; Jang, Jin-Hyeok; Choi, Seungjin; Hwang, Daehee
2014-01-01
Motivation: Time-evolving differential protein–protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time. Results: Here, we present a probabilistic model for estimating Time-Evolving differential PPI networks with MultiPle Information (TEMPI). This model describes probabilistic relationships among network structures, time-course gene expression data and Gene Ontology biological processes (GOBPs). By maximizing the likelihood of the probabilistic model, TEMPI estimates jointly the time-evolving differential PPI networks (TDNs) describing temporal transition of PPI network structures together with serial activation of DRPs associated with transiting networks. This joint estimation enables us to interpret the TDNs in terms of temporal transition of the DRPs. To demonstrate the utility of TEMPI, we applied it to two time-course datasets. TEMPI identified the TDNs that correctly delineated temporal transition of DRPs and time-dependent associations between the DRPs. These TDNs provide hypotheses for mechanisms underlying serial activation of key DRPs and their temporal associations. Availability and implementation: Source code and sample data files are available at http://sbm.postech.ac.kr/tempi/sources.zip. Contact: seungjin@postech.ac.kr or dhwang@dgist.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161233
The diminishing criterion model for metacognitive regulation of time investment.
Ackerman, Rakefet
2014-06-01
According to the Discrepancy Reduction Model for metacognitive regulation, people invest time in cognitive tasks in a goal-driven manner until their metacognitive judgment, either judgment of learning (JOL) or confidence, meets their preset goal. This stopping rule should lead to judgments above the goal, regardless of invested time. However, in many tasks, time is negatively correlated with JOL and confidence, with low judgments after effortful processing. This pattern has often been explained as stemming from bottom-up fluency effects on the judgments. While accepting this explanation for simple tasks, like memorizing pairs of familiar words, the proposed Diminishing Criterion Model (DCM) challenges this explanation for complex tasks, like problem solving. Under the DCM, people indeed invest effort in a goal-driven manner. However, investing more time leads to increasing compromise on the goal, resulting in negative time-judgment correlations. Experiment 1 exposed that with word-pair memorization, negative correlations are found only with minimal fluency and difficulty variability, whereas in problem solving, they are found consistently. As predicted, manipulations of low incentives (Experiment 2) and time pressure (Experiment 3) in problem solving revealed greater compromise as more time was invested in a problem. Although intermediate confidence ratings rose during the solving process, the result was negative time-confidence correlations (Experiments 3, 4, and 5), and this was not eliminated by the opportunity to respond "don't know" (Experiments 4 and 5). The results suggest that negative time-judgment correlations in complex tasks stem from top-down regulatory processes with a criterion that diminishes with invested time.
Analytical model of coincidence resolving time in TOF-PET
NASA Astrophysics Data System (ADS)
Wieczorek, H.; Thon, A.; Dey, T.; Khanin, V.; Rodnyi, P.
2016-06-01
The coincidence resolving time (CRT) of scintillation detectors is the parameter determining noise reduction in time-of-flight PET. We derive an analytical CRT model based on the statistical distribution of photons for two different prototype scintillators. For the first one, characterized by single exponential decay, CRT is proportional to the decay time and inversely proportional to the number of photons, with a square root dependence on the trigger level. For the second scintillator prototype, characterized by exponential rise and decay, CRT is proportional to the square root of the product of rise time and decay time divided by the doubled number of photons, and it is nearly independent of the trigger level. This theory is verified by measurements of scintillation time constants, light yield and CRT on scintillator sticks. Trapping effects are taken into account by defining an effective decay time. We show that in terms of signal-to-noise ratio, CRT is as important as patient dose, imaging time or PET system sensitivity. The noise reduction effect of better timing resolution is verified and visualized by Monte Carlo simulation of a NEMA image quality phantom.
Excess screen time in US children: association with family rules and alternative activities.
Gingold, Janet A; Simon, Alan E; Schoendorf, Kenneth C
2014-01-01
We describe the association of screen time in excess of American Academy of Pediatrics recommendations (≤2 h/d) with family television-use policies and regular nonscreen activities among US school-aged children. Data from the 2007 National Survey of Children's Health were used. The sum of minutes spent on television, videos, video games, and recreational computer use was calculated for children 6 to 17 years old. Bivariate and multivariate logistic regression models were used to calculate relative odds of exceeding American Academy of Pediatrics guidelines and of heavy screen use (>4 h/d) for varying family media-use policies and frequency of alternative activities (physical activity and family meals). In all, 49% of school-aged children had screen time >2 h/d and 16% had screen time >4 h/d. Lower frequency of family meals, presence of TV in the bedroom, absence of rules about TV viewing, and less physical activity were associated with both >2 and >4 hours per day of screen time. PMID:23922251
Excess screen time in US children: association with family rules and alternative activities.
Gingold, Janet A; Simon, Alan E; Schoendorf, Kenneth C
2014-01-01
We describe the association of screen time in excess of American Academy of Pediatrics recommendations (≤2 h/d) with family television-use policies and regular nonscreen activities among US school-aged children. Data from the 2007 National Survey of Children's Health were used. The sum of minutes spent on television, videos, video games, and recreational computer use was calculated for children 6 to 17 years old. Bivariate and multivariate logistic regression models were used to calculate relative odds of exceeding American Academy of Pediatrics guidelines and of heavy screen use (>4 h/d) for varying family media-use policies and frequency of alternative activities (physical activity and family meals). In all, 49% of school-aged children had screen time >2 h/d and 16% had screen time >4 h/d. Lower frequency of family meals, presence of TV in the bedroom, absence of rules about TV viewing, and less physical activity were associated with both >2 and >4 hours per day of screen time.
Multilayer Model: A New Regional Ionospheric Model For Near Real-Time Applications
NASA Astrophysics Data System (ADS)
Magnet, N.; Weber, R.
2012-12-01
The ionosphere is part of the upper atmosphere which affects electromagnetic waves by its ionization. The resulting propagation delay is frequency dependent, so it can be determined with dual frequency measurements. In case of single frequency users ionospheric models are used to correct the measurements. At the Institute of Geodesy and Geophysics (Vienna University of Technology) a new ionospheric model, labeled Multilayer Model, is under development. It consists of nine horizontal equidistant electron layers within the height range of the F2 layer, where the maximum of the ionization can be found. The remaining ionospheric layers (e.g. the E-layers) are currently not considered. The electron content of each of the nine layers is obtained from a simple model with very few parameters, like the current maximum VTEC and weighting functions to account for the spherical distance between the coordinates of the electron maximum and the IPP-points of interest. All parameters are calculated with hourly time resolution from a combination of global (IGS-stations) and regional GNSS observation data. The Multilayer Model focuses on regional densification of global ionosphere models (e.g. IGS VTEC SH models) by means of a small and easy predictable set of parameters. The final ionospheric TEC grids provided by IGS (International GNSS Service) have a resolution of 2 hours x 5° Longitude x 2.5° Latitude. Daily files can be downloaded from the IGS web page (http://www.igs.org/). IRI (International Reference Ionosphere) is a joint project of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI). An empirical standard model of the ionosphere is provided which is based on a worldwide network of ionosondes, incoherent scatter radars and other data sources. In this presentation the VTEC values calculated with the regional Multilayer Model are compared to the results of the IGS global TEC grids and IRI. This comparison covers days with low
Time Ordering in Frontal Lobe Patients: A Stochastic Model Approach
ERIC Educational Resources Information Center
Magherini, Anna; Saetti, Maria Cristina; Berta, Emilia; Botti, Claudio; Faglioni, Pietro
2005-01-01
Frontal lobe patients reproduced a sequence of capital letters or abstract shapes. Immediate and delayed reproduction trials allowed the analysis of short- and long-term memory for time order by means of suitable Markov chain stochastic models. Patients were as proficient as healthy subjects on the immediate reproduction trial, thus showing spared…
Time-to-Compromise Model for Cyber Risk Reduction Estimation
Miles A. McQueen; Wayne F. Boyer; Mark A. Flynn; George A. Beitel
2005-09-01
We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.
A Real-Time Groundwater Management Model Using Data Assimilation
NASA Astrophysics Data System (ADS)
Cheng, W.; Putti, M.; Kendall, D.; Yeh, W. W.
2009-12-01
This study develops a groundwater management model for real time operation of an aquifer system. A groundwater flow model is allied with a nudging data assimilation algorithm that reduces the forecast error, minimizes the risk of system failure, and improves management strategies. The nudging algorithm treats the unknown private pumping as an additional sink term in the groundwater flow equations and provides a consistently physical interpretation for pumping rates identification. The response of the groundwater simulation model due to pumping/injection is represented by a response matrix which is generated by the influence coefficient method. The response matrix with a much smaller dimension (referred to as the reduced simulation model) is directly embedded in the management model as a part of the constraint set. Additionally, the influence coefficient method is utilized to include the nudging effect as additional terms in the reduced simulation model. The management model optimizes monthly operational policy for 12 months into the future with given initial condition and system constraints. We apply the developed management model to the Aquifer Storage and Recovery (ASR) project of the Las Posas Groundwater Basin in southern California. We consider both the injection and pumping scenarios. In the case studies, six unknown pumping rates from private wells are estimated using measured heads from four observation wells. The management model determines the optimal operational strategies using the information provided by nudging and is updated at the beginning of each month when new head observations become available. We also discuss the utility, accuracy, and efficiency of the proposed management model for real time operation.
Activity-Dependent Model for Neuronal Avalanches
NASA Astrophysics Data System (ADS)
de Arcangelis, L.
Networks of living neurons represent one of the most fascinating systems of modern biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behavior of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behavior is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. This fundamental problem in neurobiology has recently shown a number of features in common to other complex systems. These features mainly concern the morphology of the network, namely the spatial organization of the established connections, and a novel kind of neuronal activity. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. Both features have been found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behavior. In this contribution, we apply a statistical mechanical model to describe the complex activity in a neuronal network. The network is chosen to have a number of connections in long range, as found for neurons in vitro. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. The numerical power spectra for electrical activity reproduces also the power law behavior measured in an EEG of man resting with the eyes closed.
Time-variant clustering model for understanding cell fate decisions.
Huang, Wei; Cao, Xiaoyi; Biase, Fernando H; Yu, Pengfei; Zhong, Sheng
2014-11-01
Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development. PMID:25339442
Time-variant clustering model for understanding cell fate decisions
Huang, Wei; Cao, Xiaoyi; Biase, Fernando H.; Yu, Pengfei; Zhong, Sheng
2014-01-01
Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development. PMID:25339442
Modelling of HVDC converters for real-time transient simulators
NASA Astrophysics Data System (ADS)
Acevedo, Salvador
This thesis presents developments in the computer modelling of High Voltage Direct Current (HVDC) converters and other FACTS devices for EMTP-type simulators. The high number and frequency of switching operations in power electronic converters cause numerical difficulties that require additional computational effort. The additional computational burden requires the development of techniques that can accelerate the simulation speeds of conventional electromagnetic transient modelling and may allow real-time simulations. The main results are two models that effectively reduce the computational time required to obtain the solution of an electrical network containing HVDC converters. Both approaches have in common the principle of subdividing an electrical circuit containing a 6n-valve converter into at least n subsystems. For each 6-valve subsystem, the 64 matrix combinations are precalculated and prestored in computer memory. The interaction between subsystems to obtain the network solution is particular to each approach. With this criterion, the number of precalculated combinations for a 24-valve HVDC substation is reduced from more than 16 million to only 256. Both models present a considerable reduction in the computational time required to simulate circuits containing HVDC converters. The most efficient model has been successfully implemented in the real time power systems simulator under development by the power research group at the University of British Columbia. The exact calculation of the network solution at switching events is another important aspect required to accurately simulate power electronic converters in power systems. The thesis proposes the zero crossing detection algorithm, which eliminates the erroneous delays present in traditional EMTP simulators. The proposed algorithm resynchronizes the solution to the original simulation time increment. To solve the problem originated by the forced commutation of Gate Turn Off Thyristors, an exploratory
Modeling the Quiet Time Outflow Solution in the Polar Cap
NASA Technical Reports Server (NTRS)
Glocer, Alex
2011-01-01
We use the Polar Wind Outflow Model (PWOM) to study the geomagnetically quiet conditions in the polar cap during solar maximum, The PWOM solves the gyrotropic transport equations for O(+), H(+), and He(+) along several magnetic field lines in the polar region in order to reconstruct the full 3D solution. We directly compare our simulation results to the data based empirical model of Kitamura et al. [2011] of electron density, which is based on 63 months of Akebono satellite observations. The modeled ion and electron temperatures are also compared with a statistical compilation of quiet time data obtained by the EISCAT Svalbard Radar (ESR) and Intercosmos Satellites (Kitamura et al. [2011]). The data and model agree reasonably well. This study shows that photoelectrons play an important role in explaining the differences between sunlit and dark results, ion composition, as well as ion and electron temperatures of the quiet time polar wind solution. Moreover, these results provide validation of the PWOM's ability to model the quiet time ((background" solution.
Segregation time-scales in model granular flows
NASA Astrophysics Data System (ADS)
Staron, Lydie; Phillips, Jeremy C.
2016-04-01
Segregation patterns in natural granular systems offer a singular picture of the systems evolution. In many cases, understanding segregation dynamics may help understanding the system's history as well as its future evolution. Among the key questions, one concerns the typical time-scales at which segregation occurs. In this contribution, we present model granular flows simulated by means of the discrete Contact Dynamics method. The granular flows are bi-disperse, namely exhibiting two grain sizes. The flow composition and its dynamics are systematically varied, and the segregation dynamics carefully analyzed. We propose a physical model for the segregation that gives account of the observed dependence of segregation time scales on composition and dynamics. References L. Staron and J. C. Phillips, Stress partition and micro-structure in size-segregating granular flows, Phys. Rev. E 92 022210 (2015) L. Staron and J. C. Phillips, Segregation time-scales in bi-disperse granular flows, Phys. Fluids 26 (3), 033302 (2014)
Prediction of Solar Activity Based on Neuro-Fuzzy Modeling
NASA Astrophysics Data System (ADS)
Attia, Abdel-Fattah; Abdel-Hamid, Rabab; Quassim, Maha
2005-03-01
This paper presents an application of the neuro-fuzzy modeling to analyze the time series of solar activity, as measured through the relative Wolf number. The neuro-fuzzy structure is optimized based on the linear adapted genetic algorithm with controlling population size (LAGA-POP). Initially, the dimension of the time series characteristic attractor is obtained based on the smallest regularity criterion (RC) and the neuro-fuzzy model. Then the performance of the proposed approach, in forecasting yearly sunspot numbers, is favorably compared to that of other published methods. Finally, a comparison predictions for the remaining part of the 22nd and the whole 23rd cycle of the solar activity are presented.
Time to Absorption for a Heterogeneous Neutral Competition Model
NASA Astrophysics Data System (ADS)
Borile, Claudio; Pra, Paolo Dai; Fischer, Markus; Formentin, Marco; Maritan, Amos
2014-07-01
Neutral models aspire to explain biodiversity patterns in ecosystems where species difference can be neglected and perfect symmetry is assumed between species. Voter-like models capture the essential ingredients of the neutral hypothesis and represent a paradigm for other disciplines like social studies and chemical reactions. In a system where each individual can interact with all the other members of the community, the typical time to reach an absorbing state with a single species scales linearly with the community size. Here we show, by using a rigorous approach based on a large deviation principle and confirming previous approximate and numerical results, that in a mean-field heterogeneous voter model the typical time to reach an absorbing state scales exponentially with the system size.
A multiscale statistical model for time series forecasting
NASA Astrophysics Data System (ADS)
Wang, W.; Pollak, I.
2007-02-01
We propose a stochastic grammar model for random-walk-like time series that has features at several temporal scales. We use a tree structure to model these multiscale features. The inside-outside algorithm is used to estimate the model parameters. We develop an algorithm to forecast the sign of the first difference of a time series. We illustrate the algorithm using log-price series of several stocks and compare with linear prediction and a neural network approach. We furthermore illustrate our algorithm using synthetic data and show that it significantly outperforms both the linear predictor and the neural network. The construction of our synthetic data indicates what types of signals our algorithm is well suited for.
A channel dynamics model for real-time flood forecasting
Hoos, A.B.; Koussis, A.D.; Beale, G.O.
1989-01-01
A new channel dynamics scheme ASPIRE (alternative system predictor in real time), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio. -Authors
A Circuit Model of Real Time Human Body Hydration.
Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H
2016-06-01
Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration. PMID:26485354
A Circuit Model of Real Time Human Body Hydration.
Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H
2016-06-01
Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration.
The comparison of immobility time in experimental rat swimming models.
Calil, Caroline Morini; Marcondes, Fernanda Klein
2006-09-27
Rat swimming models have been used in studies about stress and depression. However, there is no consensus about interpreting immobility (helplessness or adaptation) in the literature. In the present study, immobility time, glucose and glycogen mobilization, corticosterone and the effect of desipramine and diazepam were investigated in two different models: swimming stress and the forced swimming test. Immobility time was lower in swimming stress than in the forced swimming test. Both swimming models increased corticosterone levels in comparison with control animal levels. Moreover, swimming stress induced higher corticosterone levels than the forced swimming test did [F(2,14)=59.52; p<0.001]. Liver glycogen content values differed from one another (swimming stress
A Hidden Markov Approach to Modeling Interevent Earthquake Times
NASA Astrophysics Data System (ADS)
Chambers, D.; Ebel, J. E.; Kafka, A. L.; Baglivo, J.
2003-12-01
A hidden Markov process, in which the interevent time distribution is a mixture of exponential distributions with different rates, is explored as a model for seismicity that does not follow a Poisson process. In a general hidden Markov model, one assumes that a system can be in any of a finite number k of states and there is a random variable of interest whose distribution depends on the state in which the system resides. The system moves probabilistically among the states according to a Markov chain; that is, given the history of visited states up to the present, the conditional probability that the next state is a specified one depends only on the present state. Thus the transition probabilities are specified by a k by k stochastic matrix. Furthermore, it is assumed that the actual states are unobserved (hidden) and that only the values of the random variable are seen. From these values, one wishes to estimate the sequence of states, the transition probability matrix, and any parameters used in the state-specific distributions. The hidden Markov process was applied to a data set of 110 interevent times for earthquakes in New England from 1975 to 2000. Using the Baum-Welch method (Baum et al., Ann. Math. Statist. 41, 164-171), we estimate the transition probabilities, find the most likely sequence of states, and estimate the k means of the exponential distributions. Using k=2 states, we found the data were fit well by a mixture of two exponential distributions, with means of approximately 5 days and 95 days. The steady state model indicates that after approximately one fourth of the earthquakes, the waiting time until the next event had the first exponential distribution and three fourths of the time it had the second. Three and four state models were also fit to the data; the data were inconsistent with a three state model but were well fit by a four state model.
Time series regression model for infectious disease and weather.
Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro
2015-10-01
Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context.
Upper D region chemical kinetic modeling of LORE relaxation times
NASA Astrophysics Data System (ADS)
Gordillo-Vázquez, F. J.; Luque, A.; Haldoupis, C.
2016-04-01
The recovery times of upper D region electron density elevations, caused by lightning-induced electromagnetic pulses (EMP), are modeled. The work was motivated from the need to understand a recently identified narrowband VLF perturbation named LOREs, an acronym for LOng Recovery Early VLF events. LOREs associate with long-living electron density perturbations in the upper D region ionosphere; they are generated by strong EMP radiated from large peak current intensities of ±CG (cloud to ground) lightning discharges, known also to be capable of producing elves. Relaxation model scenarios are considered first for a weak enhancement in electron density and then for a much stronger one caused by an intense lightning EMP acting as an impulsive ionization source. The full nonequilibrium kinetic modeling of the perturbed mesosphere in the 76 to 92 km range during LORE-occurring conditions predicts that the electron density relaxation time is controlled by electron attachment at lower altitudes, whereas above 79 km attachment is balanced totally by associative electron detachment so that electron loss at these higher altitudes is controlled mainly by electron recombination with hydrated positive clusters H+(H2O)n and secondarily by dissociative recombination with NO+ ions, a process which gradually dominates at altitudes >88 km. The calculated recovery times agree fairly well with LORE observations. In addition, a simplified (quasi-analytic) model build for the key charged species and chemical reactions is applied, which arrives at similar results with those of the full kinetic model. Finally, the modeled recovery estimates for lower altitudes, that is <79 km, are in good agreement with the observed short recovery times of typical early VLF events, which are known to be associated with sprites.
Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.
2014-01-01
Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256
Time-series models for border inspection data.
Decrouez, Geoffrey; Robinson, Andrew
2013-12-01
We propose a new modeling approach for inspection data that provides a more useful interpretation of the patterns of detections of invasive pests, using cargo inspection as a motivating example. Methods that are currently in use generally classify shipments according to their likelihood of carrying biosecurity risk material, given available historical and contextual data. Ideally, decisions regarding which cargo containers to inspect should be made in real time, and the models used should be able to focus efforts when the risk is higher. In this study, we propose a dynamic approach that treats the data as a time series in order to detect periods of high risk. A regulatory organization will respond differently to evidence of systematic problems than evidence of random problems, so testing for serial correlation is of major interest. We compare three models that account for various degrees of serial dependence within the data. First is the independence model where the prediction of the arrival of a risky shipment is made solely on the basis of contextual information. We also consider a Markov chain that allows dependence between successive observations, and a hidden Markov model that allows further dependence on past data. The predictive performance of the models is then evaluated using ROC and leakage curves. We illustrate this methodology on two sets of real inspection data. PMID:23682814
Physics based modeling for time-frequency damage classification
NASA Astrophysics Data System (ADS)
Chakraborty, Debejyo; Soni, Sunilkumar; Wei, Jun; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Cochran, Douglas; Chattopadhyay, Aditi
2008-03-01
We have recently proposed a method for classifying waveforms from healthy and damaged structures in a structural health monitoring framework. This method is based on the use of hidden Markov models with preselected feature vectors obtained from the time-frequency based matching pursuit decomposition. In order to investigate the performance of the classifier for different signal-to-noise ratios (SNR), we simulate the response of a lug joint sample with different crack lengths using finite element modeling (FEM). Unlike experimental noisy data, the modeled data is noise free. As a result, different levels of noise can be added to the modeled data in order to obtain the true performance of the classifier under additive white Gaussian noise. We use the finite element package ABAQUS to simulate a lug joint sample with different crack lengths and piezoelectric sensor signals. A mesoscale internal state variable damage model defines the progressive damage and is incorporated in the macroscale model. We furthermore use a hybrid method (boundary element-finite element method) to model wave reflection as well as mode conversion of the Lamb waves from the free edges and scattering of the waves from the internal defects. The hybrid method simplifies the modeling problem and provides better performance in the analysis of high stress gradient problems.
The Time Is Right to Focus on Model Organism Metabolomes.
Edison, Arthur S; Hall, Robert D; Junot, Christophe; Karp, Peter D; Kurland, Irwin J; Mistrik, Robert; Reed, Laura K; Saito, Kazuki; Salek, Reza M; Steinbeck, Christoph; Sumner, Lloyd W; Viant, Mark R
2016-02-15
Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.
The Time Is Right to Focus on Model Organism Metabolomes
Edison, Arthur S.; Hall, Robert D.; Junot, Christophe; Karp, Peter D.; Kurland, Irwin J.; Mistrik, Robert; Reed, Laura K.; Saito, Kazuki; Salek, Reza M.; Steinbeck, Christoph; Sumner, Lloyd W.; Viant, Mark R.
2016-01-01
Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research. PMID:26891337
Molecular radiotherapy: The NUKFIT software for calculating the time-integrated activity coefficient
Kletting, P.; Schimmel, S.; Luster, M.; Kestler, H. A.; Hänscheid, H.; Fernández, M.; Lassmann, M.; Bröer, J. H.; Nosske, D.; Glatting, G.
2013-10-15
Purpose: Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error.Methods: The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB.Results: To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit
2015-01-01
Background Though bivariate relationships between childhood obesity, physical activity, friendships and television viewing are well documented, empirical assessment of the extent to which links between obesity and television may be mediated by these factors is scarce. This study examines the possibility that time with friends and physical activity are potential mechanisms linking overweight/obesity to television viewing in youth. Methods Data were drawn from children ages 10-18 years old (M = 13.81, SD = 2.55) participating in the 2002 wave of Child Development Supplement (CDS) to the Panel Study of Income Dynamics (PSID) (n = 1,545). Data were collected both directly and via self-report from children and their parents. Path analysis was employed to examine a model whereby the relationships between youth overweight/obesity and television viewing were mediated by time spent with friends and moderate-to-vigorous physical activity (MVPA). Results Overweight/obesity was directly related to less time spent with friends, but not to MVPA. Time spent with friends was directly and positively related to MVPA, and directly and negatively related to time spent watching television without friends. In turn, MVPA was directly and negatively related to watching television without friends. There were significant indirect effects of both overweight/obesity and time with friends on television viewing through MVPA, and of overweight/obesity on MVPA through time with friends. Net of any indirect effects, the direct effect of overweight/obesity on television viewing remained. The final model fit the data extremely well (χ2 = 5.77, df = 5, p<0.0001, RMSEA = 0.01, CFI = 0.99, TLI =0.99). Conclusions We found good evidence that the positive relationships between time with friends and physical activity are important mediators of links between overweight/obesity and television viewing in youth. These findings highlight the importance of moving from examinations of bivariate relationships
DNA replication origin activation in space and time.
Fragkos, Michalis; Ganier, Olivier; Coulombe, Philippe; Méchali, Marcel
2015-06-01
DNA replication begins with the assembly of pre-replication complexes (pre-RCs) at thousands of DNA replication origins during the G1 phase of the cell cycle. At the G1-S-phase transition, pre-RCs are converted into pre-initiation complexes, in which the replicative helicase is activated, leading to DNA unwinding and initiation of DNA synthesis. However, only a subset of origins are activated during any S phase. Recent insights into the mechanisms underlying this choice reveal how flexibility in origin usage and temporal activation are linked to chromosome structure and organization, cell growth and differentiation, and replication stress.
Modeling a Transient Pressurization with Active Cooling Sizing Tool
NASA Technical Reports Server (NTRS)
Guzik, Monica C.; Plachta, David W.; Elchert, Justin P.
2011-01-01
As interest in the area of in-space zero boil-off cryogenic propellant storage develops, the need to visualize and quantify cryogen behavior during ventless tank self-pressurization and subsequent cool-down with active thermal control has become apparent. During the course of a mission, such as the launch ascent phase, there are periods that power to the active cooling system will be unavailable. In addition, because it is not feasible to install vacuum jackets on large propellant tanks, as is typically done for in-space cryogenic applications for science payloads, instances like the launch ascent heating phase are important to study. Numerous efforts have been made to characterize cryogenic tank pressurization during ventless cryogen storage without active cooling, but few tools exist to model this behavior in a user-friendly environment for general use, and none exist that quantify the marginal active cooling system size needed for power down periods to manage tank pressure response once active cooling is resumed. This paper describes the Transient pressurization with Active Cooling Tool (TACT), which is based on a ventless three-lump homogeneous thermodynamic self-pressurization model1 coupled with an active cooling system estimator. TACT has been designed to estimate the pressurization of a heated but unvented cryogenic tank, assuming an unavailable power period followed by a given cryocooler heat removal rate. By receiving input data on the tank material and geometry, propellant initial conditions, and passive and transient heating rates, a pressurization and recovery profile can be found, which establishes the time needed to return to a designated pressure. This provides the ability to understand the effect that launch ascent and unpowered mission segments have on the size of an active cooling system. A sample of the trends found show that an active cooling system sized for twice the steady state heating rate would results in a reasonable time for tank
Active versus Passive Screen Time for Young Children
ERIC Educational Resources Information Center
Sweetser, Penelope; Johnson, Daniel; Ozdowska, Anne; Wyeth, Peta
2012-01-01
In this paper we report some initial findings from our investigations into the Australian Government's Longitudinal Study of Australian Children dataset. It is revealed that the majority of Australian children are exceeding the government's Screen Time recommendations and that most of their screen time is spent as TV viewing, as opposed to video…
Family Time Activities and Adolescents' Emotional Well-Being
ERIC Educational Resources Information Center
Offer, Shira
2013-01-01
The literature is divided on the issue of what matters for adolescents' well-being, with one approach focusing on quality and the other on routine family time. Using the experience sampling method, a unique form of time diary, and survey data drawn from the 500 Family Study ("N" = 237 adolescents with 8,122 observations), this study examined the…
Intrinsically Motivated, Free-Time Physical Activity: Considerations for Recess
ERIC Educational Resources Information Center
Stellino, Megan Babkes; Sinclair, Christina D.
2008-01-01
The current childhood obesity rates raise concern about youths' health and the role that a sedentary lifestyle plays in this growing trend. Focusing on how children choose to spend their free time is one approach that may yield ideas for reducing childhood obesity. Recess is a regularly occurring "free time" period in elementary schools. It is,…
An SIRS Epidemic Model Incorporating Media Coverage with Time Delay
Lin, Yiping; Dai, Yunxian
2014-01-01
An SIRS epidemic model incorporating media coverage with time delay is proposed. The positivity and boundedness are studied firstly. The locally asymptotical stability of the disease-free equilibrium and endemic equilibrium is studied in succession. And then, the conditions on which periodic orbits bifurcate are given. Furthermore, we show that the local Hopf bifurcation implies the global Hopf bifurcation after the second critical value of the delay. The obtained results show that the time delay in media coverage can not affect the stability of the disease-free equilibrium when the basic reproduction number R0 < 1. However, when R0 > 1, the stability of the endemic equilibrium will be affected by the time delay; there will be a family of periodic orbits bifurcating from the endemic equilibrium when the time delay increases through a critical value. Finally, some examples for numerical simulations are also included. PMID:24723967
Stochastic Modeling Approach to the Incubation Time of Prionic Diseases
NASA Astrophysics Data System (ADS)
Ferreira, A. S.; da Silva, M. A.; Cressoni, J. C.
2003-05-01
Transmissible spongiform encephalopathies are neurodegenerative diseases for which prions are the attributed pathogenic agents. A widely accepted theory assumes that prion replication is due to a direct interaction between the pathologic (PrPSc) form and the host-encoded (PrPC) conformation, in a kind of autocatalytic process. Here we show that the overall features of the incubation time of prion diseases are readily obtained if the prion reaction is described by a simple mean-field model. An analytical expression for the incubation time distribution then follows by associating the rate constant to a stochastic variable log normally distributed. The incubation time distribution is then also shown to be log normal and fits the observed BSE (bovine spongiform encephalopathy) data very well. Computer simulation results also yield the correct BSE incubation time distribution at low PrPC densities.
Optimization of Time-Course Experiments for Kinetic Model Discrimination
Lages, Nuno F.; Cordeiro, Carlos; Sousa Silva, Marta; Ponces Freire, Ana; Ferreira, António E. N.
2012-01-01
Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network. In those cases, one is faced with a problem of model discrimination, the procedure of rejecting inappropriate models from a set of candidates in order to elect one as the best model to use for prediction. In this work, a method is proposed to optimize the design of enzyme kinetic assays with the goal of selecting a model among a set of candidates. We focus on models with systems of ordinary differential equations as the underlying mathematical description. The method provides a design where an extension of the Kullback-Leibler distance, computed over the time courses predicted by the models, is maximized. Given the asymmetric nature this measure, a generalized differential evolution algorithm for multi-objective optimization problems was used. The kinetics of yeast glyoxalase I (EC 4.4.1.5) was chosen as a difficult test case to evaluate the method. Although a single-substrate kinetic model is usually considered, a two-substrate mechanism has also been proposed for this enzyme. We designed an experiment capable of discriminating between the two models by optimizing the initial substrate concentrations of glyoxalase I, in the presence of the subsequent pathway enzyme, glyoxalase II (EC 3.1.2.6). This discriminatory experiment was conducted in the laboratory and the results indicate a two-substrate mechanism for the kinetics of yeast glyoxalase I. PMID:22403703
Unsteady aerodynamic modeling and active aeroelastic control
NASA Technical Reports Server (NTRS)
Edwards, J. W.
1977-01-01
Unsteady aerodynamic modeling techniques are developed and applied to the study of active control of elastic vehicles. The problem of active control of a supercritical flutter mode poses a definite design goal stability, and is treated in detail. The transfer functions relating the arbitrary airfoil motions to the airloads are derived from the Laplace transforms of the linearized airload expressions for incompressible two dimensional flow. The transfer function relating the motions to the circulatory part of these loads is recognized as the Theodorsen function extended to complex values of reduced frequency, and is termed the generalized Theodorsen function. Inversion of the Laplace transforms yields exact transient airloads and airfoil motions. Exact root loci of aeroelastic modes are calculated, providing quantitative information regarding subcritical and supercritical flutter conditions.
CFD Modeling for Active Flow Control
NASA Technical Reports Server (NTRS)
Buning, Pieter G.
2001-01-01
This presentation describes current work under UEET Active Flow Control CFD Research Tool Development. The goal of this work is to develop computational tools for inlet active flow control design. This year s objectives were to perform CFD simulations of fully gridded vane vortex generators, micro-vortex genera- tors, and synthetic jets, and to compare flowfield results with wind tunnel tests of simple geometries with flow control devices. Comparisons are shown for a single micro-vortex generator on a flat plate, and for flow over an expansion ramp with sidewall effects. Vortex core location, pressure gradient and oil flow patterns are compared between experiment and computation. This work lays the groundwork for evaluating simplified modeling of arrays of devices, and provides the opportunity to test simple flow control device/sensor/ control loop interaction.
Growth exponents in surface models with non-active sites
NASA Astrophysics Data System (ADS)
Santos, M.; Figueiredo, W.; Aarão Reis, F. D. A.
2006-11-01
In this work, we studied the role played by the inactive sites present on the substrate of a growing surface. In our model, one particle sticks at the surface if the site where it falls is an active site. However, we allow the deposited particle to diffuse along the surface in accordance with some mechanism previously defined. Using Monte Carlo simulations, and some analytical results, we have investigated the model in (1+1) and (2+1) dimensions considering different relaxation mechanisms. We show that the consideration of non-active sites is a crucial point in the model. In fact, we have seen that the saturation regime is not observed for any value of the density of inactive sites. Besides, the growth exponent β turns to be one, at long times, whatever the mechanism of diffusion we consider in one and two dimensions.
A hidden Markov model for space-time precipitation
Zucchini, W. ); Guttorp, P. )
1991-08-01
Stochastic models for precipitation events in space and time over mesoscale spatial areas have important applications in hydrology, both as input to runoff models and as parts of general circulation models (GCMs) of global climate. A family of multivariate models for the occurrence/nonoccurrence of precipitation at N sites is constructed by assuming a different probability of events at the sites for each of a number of unobservable climate states. The climate process is assumed to follow a Markov chain. Simple formulae for first- and second-order parameter functions are derived, and used to find starting values for a numerical maximization of the likelihood. The method is illustrated by applying it to data for one site in Washington and to data for a network in the Great plains.
Instrumented Shoes for Real-Time Activity Monitoring Applications.
Moufawad El Achkar, Christopher; Lenoble-Hoskovec, Constanze; Major, Kristof; Paraschiv-Ionescu, Anisoara; Büla, Christophe; Aminian, Kamiar
2016-01-01
Activity monitoring in daily life is gaining momentum as a health assessment tool, especially in older adults and at-risk populations. Several research-based and commercial systems have been proposed with varying performances in classification accuracy. Configurations with many sensors are generally accurate but cumbersome, whereas single sensors tend to have lower accuracies. To this end, we propose an instrumented shoes system capable of accurate activity classification and gait analysis that contains sensors located entirely at the level of the shoes. One challenge in daily activity monitoring is providing punctual and subject-tailored feedback to improve mobility. Therefore, the instrumented shoe system was equipped with a Bluetooth® module to transmit data to a smartphone and perform detailed activity profiling of the monitored subjects. The potential applications of such a system are numerous in mobility and fall risk-assessment as well as in fall prevention. PMID:27332298
Decoding coalescent hidden Markov models in linear time
Harris, Kelley; Sheehan, Sara; Kamm, John A.; Song, Yun S.
2014-01-01
In many areas of computational biology, hidden Markov models (HMMs) have been used to model local genomic features. In particular, coalescent HMMs have been used to infer ancient population sizes, migration rates, divergence times, and other parameters such as mutation and recombination rates. As more loci, sequences, and hidden states are added to the model, however, the runtime of coalescent HMMs can quickly become prohibitive. Here we present a new algorithm for reducing the runtime of coalescent HMMs from quadratic in the number of hidden time states to linear, without making any additional approximations. Our algorithm can be incorporated into various coalescent HMMs, including the popular method PSMC for inferring variable effective population sizes. Here we implement this algorithm to speed up our demographic inference method diCal, which is equivalent to PSMC when applied to a sample of two haplotypes. We demonstrate that the linear-time method can reconstruct a population size change history more accurately than the quadratic-time method, given similar computation resources. We also apply the method to data from the 1000 Genomes project, inferring a high-resolution history of size changes in the European population. PMID:25340178
Modeling the relaxation time of DNA confined in a nanochannel
Tree, Douglas R.; Wang, Yanwei; Dorfman, Kevin D.
2013-01-01
Using a mapping between a Rouse dumbbell model and fine-grained Monte Carlo simulations, we have computed the relaxation time of λ-DNA in a high ionic strength buffer confined in a nanochannel. The relaxation time thus obtained agrees quantitatively with experimental data [Reisner et al., Phys. Rev. Lett. 94, 196101 (2005)] using only a single O(1) fitting parameter to account for the uncertainty in model parameters. In addition to validating our mapping, this agreement supports our previous estimates of the friction coefficient of DNA confined in a nanochannel [Tree et al., Phys. Rev. Lett. 108, 228105 (2012)], which have been difficult to validate due to the lack of direct experimental data. Furthermore, the model calculation shows that as the channel size passes below approximately 100 nm (or roughly the Kuhn length of DNA) there is a dramatic drop in the relaxation time. Inasmuch as the chain friction rises with decreasing channel size, the reduction in the relaxation time can be solely attributed to the sharp decline in the fluctuations of the chain extension. Practically, the low variance in the observed DNA extension in such small channels has important implications for genome mapping. PMID:24309551
Waste collection multi objective model with real time traceability data.
Faccio, Maurizio; Persona, Alessandro; Zanin, Giorgia
2011-12-01
Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems, plus it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel, maintenances) and environmental costs (i.e. emissions, noise and traffic congestions). Modern traceability devices, like volumetric sensors, identification RFID (Radio Frequency Identification) systems, GPRS (General Packet Radio Service) and GPS (Global Positioning System) technology, permit to obtain data in real time, which is fundamental to implement an efficient and innovative waste collection routing model. The basic idea is that knowing the real time data of each vehicle and the real time replenishment level at each bin makes it possible to decide, in function of the waste generation pattern, what bin should be emptied and what should not, optimizing different aspects like the total covered distance, the necessary number of vehicles and the environmental impact. This paper describes a framework about the traceability technology available in the optimization of solid waste collection, and introduces an innovative vehicle routing model integrated with the real time traceability data, starting the application in an Italian city of about 100,000 inhabitants. The model is tested and validated using simulation and an economical feasibility study is reported at the end of the paper.
On the maximum-entropy/autoregressive modeling of time series
NASA Technical Reports Server (NTRS)
Chao, B. F.
1984-01-01
The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relation which relates a complex conjugate pair of poles of the AR process in the z-plane (or the z domain) on the one hand, to the complex frequency of one complex harmonic function in the time domain on the other. Thus the AR model of a time series is one that models the time series as a linear combination of complex harmonic functions, which include pure sinusoids and real exponentials as special cases. An AR model is completely determined by its z-domain pole configuration. The maximum-entropy/autogressive (ME/AR) spectrum, defined on the unit circle of the z-plane (or the frequency domain), is nothing but a convenient, but ambiguous visual representation. It is asserted that the position and shape of a spectral peak is determined by the corresponding complex frequency, and the height of the spectral peak contains little information about the complex amplitude of the complex harmonic functions.
Unconditionally stable time marching scheme for Reynolds stress models
NASA Astrophysics Data System (ADS)
Mor-Yossef, Y.
2014-11-01
Progress toward a stable and efficient numerical treatment for the compressible Favre-Reynolds-averaged Navier-Stokes equations with a Reynolds-stress model (RSM) is presented. The mean-flow and the Reynolds stress model equations are discretized using finite differences on a curvilinear coordinates mesh. The convective flux is approximated by a third-order upwind biased MUSCL scheme. The diffusive flux is approximated using second-order central differencing, based on a full-viscous stencil. The novel time-marching approach relies on decoupled, implicit time integration, that is, the five mean-flow equations are solved separately from the seven Reynolds-stress closure equations. The key idea is the use of the unconditionally positive-convergent implicit scheme (UPC), originally developed for two-equation turbulence models. The extension of the UPC scheme for RSM guarantees the positivity of the normal Reynolds-stress components and the turbulence (specific) dissipation rate for any time step. Thanks to the UPC matrix-free structure and the decoupled approach, the resulting computational scheme is very efficient. Special care is dedicated to maintain the implicit operator compact, involving only nearest neighbor grid points, while fully supporting the larger discretized residual stencil. Results obtained from two- and three-dimensional numerical simulations demonstrate the significant progress achieved in this work toward optimally convergent solution of Reynolds stress models. Furthermore, the scheme is shown to be unconditionally stable and positive.
Real-time application of the drag based model
NASA Astrophysics Data System (ADS)
Žic, Tomislav; Temmer, Manuela; Vršnak, Bojan
2016-04-01
The drag-based model (DBM) is an analytical model which is usually used for calculating kinematics of coronal mass ejections (CMEs) in the interplanetary space, prediction of the CME arrival times and impact speeds at arbitrary targets in the heliosphere. The main assumption of the model is that beyond a distance of about 20 solar radii from the Sun, the drag is dominant in the interplanetary space. The previous version of DBM relied on the rough assumption of averaged, unperturbed and constant environmental conditions as well as constant CME properties throughout the entire interplanetary CME propagation. The continuation of our work consists of enhancing the model into a form which uses a time dependent and perturbed environment without constraints on CME properties and distance forecasting. The extension provides the possibility of application in various scenarios, such as automatic least-square fitting on initial CME kinematic data suitable for a real-time forecasting of CME kinematics, or embedding the DBM into pre-calculated interplanetary ambient conditions provided by advanced numerical simulations (for example, codes of ENLIL, EUHFORIA, etc.). A demonstration of the enhanced DBM is available on the web-site: http://www.geof.unizg.hr/~tzic/dbm.html. We acknowledge the support of European Social Fund under the "PoKRet" project.
Mathematical models for predicting indoor air quality from smoking activity.
Ott, W R
1999-01-01
Much progress has been made over four decades in developing, testing, and evaluating the performance of mathematical models for predicting pollutant concentrations from smoking in indoor settings. Although largely overlooked by the regulatory community, these models provide regulators and risk assessors with practical tools for quantitatively estimating the exposure level that people receive indoors for a given level of smoking activity. This article reviews the development of the mass balance model and its application to predicting indoor pollutant concentrations from cigarette smoke and derives the time-averaged version of the model from the basic laws of conservation of mass. A simple table is provided of computed respirable particulate concentrations for any indoor location for which the active smoking count, volume, and concentration decay rate (deposition rate combined with air exchange rate) are known. Using the indoor ventilatory air exchange rate causes slightly higher indoor concentrations and therefore errs on the side of protecting health, since it excludes particle deposition effects, whereas using the observed particle decay rate gives a more accurate prediction of indoor concentrations. This table permits easy comparisons of indoor concentrations with air quality guidelines and indoor standards for different combinations of active smoking counts and air exchange rates. The published literature on mathematical models of environmental tobacco smoke also is reviewed and indicates that these models generally give good agreement between predicted concentrations and actual indoor measurements. PMID:10350523
Bitew, Menberu; Jackson, Rhett
2015-02-01
The objective of this report is to document the methodology used to calculate the three hydro-geomorphic indices: C Index, Nhot spot, and Interflow Contributing Area (IFC Area). These indices were applied in the Upper Four Mile Creek Watershed in order to better understand the potential mechanisms controlling retention time, path lengths, and potential for nutrient and solute metabolism and exchange associated with the geomorphic configurations of the upland contributing areas, groundwater, the riparian zone, and stream channels.
A comparison of cosmological models using time delay lenses
Wei, Jun-Jie; Wu, Xue-Feng; Melia, Fulvio E-mail: xfwu@pmo.ac.cn
2014-06-20
The use of time-delay gravitational lenses to examine the cosmological expansion introduces a new standard ruler with which to test theoretical models. The sample suitable for this kind of work now includes 12 lens systems, which have thus far been used solely for optimizing the parameters of ΛCDM. In this paper, we broaden the base of support for this new, important cosmic probe by using these observations to carry out a one-on-one comparison between competing models. The currently available sample indicates a likelihood of ∼70%-80% that the R {sub h} = ct universe is the correct cosmology versus ∼20%-30% for the standard model. This possibly interesting result reinforces the need to greatly expand the sample of time-delay lenses, e.g., with the successful implementation of the Dark Energy Survey, the VST ATLAS survey, and the Large Synoptic Survey Telescope. In anticipation of a greatly expanded catalog of time-delay lenses identified with these surveys, we have produced synthetic samples to estimate how large they would have to be in order to rule out either model at a ∼99.7% confidence level. We find that if the real cosmology is ΛCDM, a sample of ∼150 time-delay lenses would be sufficient to rule out R {sub h} = ct at this level of accuracy, while ∼1000 time-delay lenses would be required to rule out ΛCDM if the real universe is instead R {sub h} = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with ΛCDM.
Receptor modeling for multiple time resolved species: The Baltimore supersite
NASA Astrophysics Data System (ADS)
Ogulei, David; Hopke, Philip K.; Zhou, Liming; Paatero, Pentti; Park, Seung Shik; Ondov, John M.
A number of advances have been made toward solving receptor modeling problems using advanced factor analysis methods. Most recently, a factor analysis method has been developed for source apportionment utilizing aerosol compositional data with varying temporal resolution. The data used in that study had time resolutions ranged from 10 min to 1 h. In this work, this expanded model is tested using a data set from the Ponca Street site of the Baltimore supersite with time resolutions ranging from 30 min to 24 h. The nature of this data set implies that traditional eigenvalue-based methods cannot adequately resolve source factors for the atmospheric situation under consideration. Also, valuable temporal information is lost if one averaged or interpolated data in an attempt to produce a data set of the identical time resolution. Each data point has been used in its original time schedule and the source contributions were averaged to correspond to the specific sampling time interval. A weighting coefficient, w24, was incorporated in the modeling equations in order to improve data fitting for the 24-h data in the model. A total of nine sources were resolved: oil-fired power plant (2%), diesel emissions (1%), secondary sulfate (23%), coal-fired power plant (3%), incinerator (9%), steel plant (12%), aged sea salt (1%), secondary nitrate (23%), and spark-ignition emissions (26%). The results showed the very strong influence of the adjacent interstate highways I-95 and I-895 as well as the tunnel toll booths located to the south of the sampling site. Most of the sulfate observed was found to be associated with distant coal-fired power plants situated in the heavily industrialized midwestern parts of the United States. The contribution of the steel plant (<10 miles, 141°SE) to the observed PM concentrations (12%) was also significant.
Short‐term time step convergence in a climate model
Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane
2015-01-01
Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities. PMID:27660669
A nonlinear dynamical analogue model of geomagnetic activity
NASA Technical Reports Server (NTRS)
Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Buechner, J.
1992-01-01
Consideration is given to the solar wind-magnetosphere interaction within the framework of deterministic nonlinear dynamics. An earlier dripping faucet analog model of the low-dimensional solar wind-magnetosphere system is reviewed, and a plasma physical counterpart to that model is constructed. A Faraday loop in the magnetotail is considered, and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. The model is characterized as an elementary time-dependent global convection model. The convection evolves within a magnetotail shape that varies in a prescribed manner in response to the dynamical evolution of the convection. The result is a nonlinear model capable of exhibiting a transition from regular to chaotic loading and unloading. The model's behavior under steady loading and also some elementary forms of time-dependent loading is discussed.
Computing moment-to-moment BOLD activation for real-time neurofeedback.
Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W; Yoo, Julie J; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D E
2011-01-01
Estimating moment-to-moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment-to-moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment-to-moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI time series, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method.
D Model Visualization Enhancements in Real-Time Game Engines
NASA Astrophysics Data System (ADS)
Merlo, A.; Sánchez Belenguer, C.; Vendrell Vidal, E.; Fantini, F.; Aliperta, A.
2013-02-01
This paper describes two procedures used to disseminate tangible cultural heritage through real-time 3D simulations providing accurate-scientific representations. The main idea is to create simple geometries (with low-poly count) and apply two different texture maps to them: a normal map and a displacement map. There are two ways to achieve models that fit with normal or displacement maps: with the former (normal maps), the number of polygons in the reality-based model may be dramatically reduced by decimation algorithms and then normals may be calculated by rendering them to texture solutions (baking). With the latter, a LOD model is needed; its topology has to be quad-dominant for it to be converted to a good quality subdivision surface (with consistent tangency and curvature all over). The subdivision surface is constructed using methodologies for the construction of assets borrowed from character animation: these techniques have been recently implemented in many entertainment applications known as "retopology". The normal map is used as usual, in order to shade the surface of the model in a realistic way. The displacement map is used to finish, in real-time, the flat faces of the object, by adding the geometric detail missing in the low-poly models. The accuracy of the resulting geometry is progressively refined based on the distance from the viewing point, so the result is like a continuous level of detail, the only difference being that there is no need to create different 3D models for one and the same object. All geometric detail is calculated in real-time according to the displacement map. This approach can be used in Unity, a real-time 3D engine originally designed for developing computer games. It provides a powerful rendering engine, fully integrated with a complete set of intuitive tools and rapid workflows that allow users to easily create interactive 3D contents. With the release of Unity 4.0, new rendering features have been added, including Direct
On the time to steady state: insights from numerical modeling
NASA Astrophysics Data System (ADS)
Goren, L.; Willett, S.; McCoy, S. W.; Perron, J.
2013-12-01
How fast do fluvial landscapes approach steady state after an application of tectonic or climatic perturbation? While theory and some numerical models predict that the celerity of the advective wave (knickpoint) controls the response time for perturbations, experiments and other landscape evolution models demonstrate that the time to steady state is much longer than the theoretically predicted response time. We posit that the longevity of transient features and the time to steady state are controlled by the stability of the topology and geometry of channel networks. Evolution of a channel network occurs by a combination of discrete capture events and continuous migration of water divides, processes, which are difficult to represent accurately in landscape evolution models. We therefore address the question of the time to steady state using the DAC landscape evolution model that solves accurately for the location of water divides, using a combination of analytical solution for hillslopes and low-order channels together with a numerical solution for higher order channels. DAC also includes an explicit capture criterion. We have tested fundamental predictions from DAC and show that modeled networks reproduce natural network characteristics such as the Hack's exponent and coefficient and the fractal dimension. We define two steady-state criteria: a topographic steady state, defined by global, pointwise steady elevation, and a topological steady state defined as the state in which no further reorganization of the drainage network takes place. Analyzing block uplift simulations, we find that the time to achieve either topographic or topological steady state exceeds by an order of magnitude the theoretical response time of the fluvial network. The longevity of the transient state is the result of the area feedback, by which, migration of a divide changes the local contributing area. This change propagates downstream as a slope adjustment, forcing further divide migrations
Time well spent? Assessing nursing-supply chain activities.
Ferenc, Jeff
2010-02-01
The amount of time nurses spend providing direct patient care seems to be continually eroding. So it's little wonder a survey conducted last year of critical care, OR nurses and nurse executives found that half of the 1600 respondents feel they spend too much time on supply chain duties. Most also said their supply chain duties impact patient safe ty and their ability to provide bedside care. Experts interviewed for this report believe it's time for supply chain leaders and nurses to develop a closer working partnership. Included are their recommendations to improve performance.
Hubble expansion and structure formation in time varying vacuum models
Basilakos, Spyros; Plionis, Manolis; Sola, Joan
2009-10-15
We investigate the properties of the FLRW flat cosmological models in which the vacuum energy density evolves with time, {lambda}(t). Using different versions of the {lambda}(t) model, namely, quantum field vacuum, power series vacuum and power law vacuum, we find that the main cosmological functions such as the scale factor of the Universe, the Hubble expansion rate H, and the energy densities are defined analytically. Performing a joint likelihood analysis of the recent supernovae type Ia data, the cosmic microwave background shift parameter and the baryonic acoustic oscillations traced by the Sloan Digital Sky Survey galaxies, we put tight constraints on the main cosmological parameters of the {lambda}(t) scenarios. Furthermore, we study the linear matter fluctuation field of the above vacuum models. We find that the patterns of the power series vacuum {lambda}=n{sub 1}H+n{sub 2}H{sup 2} predict stronger small scale dynamics, which implies a faster growth rate of perturbations with respect to the other two vacuum cases (quantum field and power law), despite the fact that all the cosmological models share the same equation of state parameter. In the case of the quantum field vacuum {lambda}=n{sub 0}+n{sub 2}H{sup 2}, the corresponding matter fluctuation field resembles that of the traditional {lambda} cosmology. The power law vacuum ({lambda}{proportional_to}a{sup -n}) mimics the classical quintessence cosmology, the best fit being tilted in the phantom phase. In this framework, we compare the observed growth rate of clustering measured from the optical galaxies with those predicted by the current {lambda}(t) models. Performing a Kolmogorov-Smirnov statistical test we show that the cosmological models which contain a constant vacuum ({lambda}CDM), quantum field vacuum, and power law vacuum provide growth rates that match well with the observed growth rate. However, this is not the case for the power series vacuum models (in particular, the frequently adduced
A time-dependent model for improved biogalvanic tissue characterisation.
Chandler, J H; Culmer, P R; Jayne, D G; Neville, A
2015-10-01
Measurement of the passive electrical resistance of biological tissues through biogalvanic characterisation has been proposed as a simple means of distinguishing healthy from diseased tissue. This method has the potential to provide valuable real-time information when integrated into surgical tools. Characterised tissue resistance values have been shown to be particularly sensitive to external load switching direction and rate, bringing into question the stability and efficacy of the technique. These errors are due to transient variations observed in measurement data that are not accounted for in current electrical models. The presented research proposes the addition of a time-dependent element to the characterisation model to account for losses associated with this transient behaviour. Influence of switching rate has been examined, with the inclusion of transient elements improving the repeatability of the characterised tissue resistance. Application of this model to repeat biogalvanic measurements on a single ex vivo human colon tissue sample with healthy and cancerous (adenocarcinoma) regions showed a statistically significant difference (p < 0.05) between tissue types. In contrast, an insignificant difference (p > 0.05) between tissue types was found when measurements were subjected to the current model, suggesting that the proposed model may allow for improved biogalvanic tissue characterisation. PMID:26298197
Storm-time ring current: model-dependent results
NASA Astrophysics Data System (ADS)
Ganushkina, N. Yu.; Liemohn, M. W.; Pulkkinen, T. I.
2012-01-01
The main point of the paper is to investigate how much the modeled ring current depends on the representations of magnetic and electric fields and boundary conditions used in simulations. Two storm events, one moderate (SymH minimum of -120 nT) on 6-7 November 1997 and one intense (SymH minimum of -230 nT) on 21-22 October 1999, are modeled. A rather simple ring current model is employed, namely, the Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM), in order to make the results most evident. Four different magnetic field and two electric field representations and four boundary conditions are used. We find that different combinations of the magnetic and electric field configurations and boundary conditions result in very different modeled ring current, and, therefore, the physical conclusions based on simulation results can differ significantly. A time-dependent boundary outside of 6.6 RE gives a possibility to take into account the particles in the transition region (between dipole and stretched field lines) forming partial ring current and near-Earth tail current in that region. Calculating the model SymH* by Biot-Savart's law instead of the widely used Dessler-Parker-Sckopke (DPS) relation gives larger and more realistic values, since the currents are calculated in the regions with nondipolar magnetic field. Therefore, the boundary location and the method of SymH* calculation are of key importance for ring current data-model comparisons to be correctly interpreted.