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…
Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition
Munoz-Organero, Mario; Ruiz-Blazquez, Ramona
2017-01-01
Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. PMID
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…
Time structure of the activity in neural network models
NASA Astrophysics Data System (ADS)
Gerstner, Wulfram
1995-01-01
Several neural network models in continuous time are reconsidered in the framework of a general mean-field theory which is exact in the limit of a large and fully connected network. The theory assumes pointlike spikes which are generated by a renewal process. The effect of spikes on a receiving neuron is described by a linear response kernel which is the dominant term in a weak-coupling expansion. It is shown that the resulting ``spike response model'' is the most general renewal model with linear inputs. The standard integrate-and-fire model forms a special case. In a network structure with several pools of identical spiking neurons, the global states and the dynamic evolution are determined by a nonlinear integral equation which describes the effective interaction within and between different pools. We derive explicit stability criteria for stationary (incoherent) and oscillatory (coherent) solutions. It is shown that the stationary state of noiseless systems is ``almost always'' unstable. Noise suppresses fast oscillations and stabilizes the system. Furthermore, collective oscillations are stable only if the firing occurs while the synaptic potential is increasing. In particular, collective oscillations in a network with delayless excitatory interaction are at most semistable. Inhibitory interactions with short delays or excitatory interactions with long delays lead to stable oscillations. Our general results allow a straightforward application to different network models with spiking neurons. Furthermore, the theory allows an estimation of the errors introduced in firing rate or ``graded-response'' models.
Reachability and Real-Time Actuation Strategies for the Active SLIP Model
2015-06-01
reachability space of the actuated SLIP model by acti- vating the series elastic actuator at any possible time during the stance phase. Starting from the...University of California Santa Barbara Reachability and Real- Time Actuation Strategies for the Active SLIP Model A dissertation submitted in partial...Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions
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
2016-02-18
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
NASA Astrophysics Data System (ADS)
Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen
2016-02-01
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.
Spontaneous otoacoustic emissions in an active nonlinear cochlear model in the time domain
NASA Astrophysics Data System (ADS)
Fruth, Florian; Jülicher, Frank; Lindner, Benjamin
2015-12-01
A large fraction of human cochleas emits sounds even in the absence of external stimulation. These so-called spontaneous otoacoustic emissions (SOAEs) are a hallmark of the active nonlinear amplification process taking place in the cochlea. Here, we extend a previously proposed frequency domain model and put forward an active nonlinear one-dimensional model of the cochlea in the time domain describing human SOAEs [5]. In our model, oscillatory elements are close to an instability (Hopf bifurcation), they are subject to dynamical noise and coupled by hydrodynamic, elastic and dissipative interactions. Furthermore, oscillators are subject to a weak spatial irregularity in their activity (normally distributed and exponentially correlated in space) that gives rise to the individuality of each simulated cochlea. Our model captures main statistical features of the distribution of emission frequencies, the distribution of the numbers of emissions per cochlea, and the distribution of the distances between neighboring emissions as were previously measured in experiment [14].
Statistical properties of longitudinal time-activity data for use in human exposure modeling.
Isaacs, Kristin; McCurdy, Thomas; Glen, Graham; Nysewander, Melissa; Errickson, April; Forbes, Susan; Graham, Stephen; McCurdy, Lisa; Smith, Luther; Tulve, Nicolle; Vallero, Daniel
2013-01-01
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 of improving the parameterization of human activity algorithms in EPA's exposure modeling efforts. Despite the longitudinal, multi-season nature of the study, participant non-compliance with the protocol over time did not play a major role in data collection. The diversity (D)--a ranked intraclass correlation coefficient (ICC)-- and lag-one autocorrelation (A) statistics of study participants are presented for time spent in outdoor, motor vehicle, residential, and other-indoor locations. Day-type (workday versus non-workday, and weekday versus weekend), season, temperature, and gender differences in the time spent in selected locations and activities are described, and D & A statistics are presented. The overall D and ICC values ranged from approximately 0.08-0.26, while the mean population rank A values ranged from approximately 0.19-0.36. These statistics indicate that intra-individual variability exceeds explained inter-individual variability, and low day-to-day correlations among locations. Most exposure models do not address these behavioral characteristics, and thus underestimate population exposure distributions and subsequent health risks associated with environmental exposures.
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.
Analysis of the activated partial thromboplastin time test using mathematical modeling.
Kogan, A E; Kardakov, D V; Khanin, M A
2001-02-15
Activated partial thromboplastin time (APTT) is a laboratory test for the diagnosis of blood coagulation disorders. The test consists of two stages: The first one is the preincubation of a plasma sample with negatively charged materials (kaolin, ellagic acid etc.) to activate factors XII and XI; the second stage begins after the addition of calcium ions that triggers a chain of calcium-dependent enzymatic reactions resulting in fibrinogen clotting. Mathematical modeling was used for the analysis of the APTT test. The process of coagulation was described by a set of coupled differential equations that were solved by the numerical method. It was found that as little as 2.3 x 10(-9) microM of factor XIIa (1/10000 of its plasma concentration) is enough to cause the complete activation of factor XII and prekallikrein (PK) during the first 20 s of the preincubation phase. By the end of this phase, kallikrein (K) is completely inhibited, residual activity of factor XIIa is 54%, and factor XI is activated by 26%. Once a clot is formed, factor II is activated by 4%, factor X by 5%, factor IX by 90%, and factor XI by 39%. Calculated clotting time using protein concentrations found in the blood of healthy people was 40.5 s. The most pronounced prolongation of APTT is caused by a decrease in factor X concentration.
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.
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.
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…
Activated partial thromboplastin time.
Ignjatovic, Vera
2013-01-01
Activated partial thromboplastin time (APTT) is a commonly used coagulation assay that is easy to perform, is affordable, and is therefore performed in most coagulation laboratories, both clinical and research, worldwide. The APTT is based on the principle that in citrated plasma, the addition of a platelet substitute, factor XII activator, and CaCl2 allows for formation of a stable clot. The time required for the formation of a stable clot is recorded in seconds and represents the actual APTT result.
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.
Timing of mTOR activation affects tuberous sclerosis complex neuropathology in mouse models.
Magri, Laura; Cominelli, Manuela; Cambiaghi, Marco; Cursi, Marco; Leocani, Letizia; Minicucci, Fabio; Poliani, Pietro Luigi; Galli, Rossella
2013-09-01
Tuberous sclerosis complex (TSC) is a dominantly inherited disease with high penetrance and morbidity, and is caused by mutations in either of two genes, TSC1 or TSC2. Most affected individuals display severe neurological manifestations - such as intractable epilepsy, mental retardation and autism - that are intimately associated with peculiar CNS lesions known as cortical tubers (CTs). The existence of a significant genotype-phenotype correlation in individuals bearing mutations in either TSC1 or TSC2 is highly controversial. Similar to observations in humans, mouse modeling has suggested that a more severe phenotype is associated with mutation in Tsc2 rather than in Tsc1. However, in these mutant mice, deletion of either gene was achieved in differentiated astrocytes. Here, we report that loss of Tsc1 expression in undifferentiated radial glia cells (RGCs) early during development yields the same phenotype detected upon deletion of Tsc2 in the same cells. Indeed, the same aberrations in cortical cytoarchitecture, hippocampal disturbances and spontaneous epilepsy that have been detected in RGC-targeted Tsc2 mutants were observed in RGC-targeted Tsc1 mutant mice. Remarkably, thorough characterization of RGC-targeted Tsc1 mutants also highlighted subventricular zone (SVZ) disturbances as well as STAT3-dependent and -independent developmental-stage-specific defects in the differentiation potential of ex-vivo-derived embryonic and postnatal neural stem cells (NSCs). As such, deletion of either Tsc1 or Tsc2 induces mostly overlapping phenotypic neuropathological features when performed early during neurogenesis, thus suggesting that the timing of mTOR activation is a key event in proper neural development.
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.
Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M
2016-01-01
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
Geller, Karly S; Nigg, Claudio R; Motl, Robert W; Horwath, Caroline; Dishman, Rod K
2012-09-01
OBJECTIVES: Physical activity (PA) research applying the Transtheoretical Model (TTM) to examine group differences and/or change over time requires preliminary evidence of factorial validity and invariance. The current study examined the factorial validity and longitudinal invariance of TTM constructs recently revised for PA. METHOD: Participants from an ethnically diverse sample in Hawaii (N=700) completed questionnaires capturing each TTM construct. RESULTS: Factorial validity was confirmed for each construct using confirmatory factor analysis with full-information maximum likelihood. Longitudinal invariance was evidenced across a shorter (3-month) and longer (6-month) time period via nested model comparisons. CONCLUSIONS: The questionnaires for each validated TTM construct are provided, and can now be generalized across similar subgroups and time points. Further validation of the provided measures is suggested in additional populations and across extended time points.
Nigg, Claudio R; Motl, Robert W; Horwath, Caroline; Dishman, Rod K
2012-01-01
Objectives Physical activity (PA) research applying the Transtheoretical Model (TTM) to examine group differences and/or change over time requires preliminary evidence of factorial validity and invariance. The current study examined the factorial validity and longitudinal invariance of TTM constructs recently revised for PA. Method Participants from an ethnically diverse sample in Hawaii (N=700) completed questionnaires capturing each TTM construct. Results Factorial validity was confirmed for each construct using confirmatory factor analysis with full-information maximum likelihood. Longitudinal invariance was evidenced across a shorter (3-month) and longer (6-month) time period via nested model comparisons. Conclusions The questionnaires for each validated TTM construct are provided, and can now be generalized across similar subgroups and time points. Further validation of the provided measures is suggested in additional populations and across extended time points. PMID:22778669
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
The residence time of an active versus a passive tracer in the Gulf of Aqaba: A box model approach
NASA Astrophysics Data System (ADS)
Silverman, Jacob; Gildor, Hezi
A simple box model of the Gulf of Aqaba, northern Red Sea, was used in order to study the effects of large scale processes in the Gulf and Red Sea (e.g. changes in thermohaline circulation or heat input from the Red Sea) as well as the influence of human activities (e.g. tourism, urbanization and mariculture) on the nutrient budget of the Gulf. The model employs available data from the literature together with General Circulation Model output data for monthly average temperature and salinity in the upper 200 m of the northern Red Sea, and monthly average meteorological data from the northern Gulf of Aqaba for heat flux and evaporation calculations. The model was shown to be most sensitive to changes in the thermohaline flux of Red Sea water through the Tiran Strait. Simulations of temperature and salinity best agreed with measurements when an annually varying thermohaline flux (0.045 Sv in January and 0.005 Sv in July) with decoupling of the thermohaline flow from the intermediate boxes during the summer (April-October) was employed. Additionally, periodic decrease of heat input from the Red Sea associated with regional weather patterns caused prolonged vertical mixing periods during the winters and shortening the residence time of phosphate in the Gulf. Hence, warming of Red Sea water would result in shorter periods of vertical mixing in the Gulf during the winter and accumulation of phosphate in the deep reservoir. The increase in deep reservoir phosphate can also be caused by an increase in the export flux of particulate organic matter to the deep reservoir. Hence, even a small increase in net primary production perhaps resulting from external nutrient input to the Gulf will result in nutrient accumulation in the deep reservoir. According to our model a return to pre-perturbation levels of phosphate in the Gulf would take on the order of 10 2 years.
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.
1994-12-01
Time Section, and have been available, in the form of computer-readable files, in the BIPM INTERNET anonymous FTP since 5 April 1994. For yrars...TIME ACTIVITIES AT THE BIPM Claudine Thomas Bureau International des Poids et Mesures Pa,villion de Breteuil 32312 Skvres Cedex France...Abstract The generation and dissemination of International Atomic Time, TAI, and of Coordinated Universal Time, UTC, are explicitly mentioned in the list
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,…
A physical model for the X-ray time lags of narrow-line Seyfert type 1 active galactic nuclei
NASA Astrophysics Data System (ADS)
Gardner, Emma; Done, Chris
2014-08-01
We study the origin of the soft X-ray excess seen in the `simple' narrow-line Seyfert 1 galaxy PG1244+026 using all available spectral-timing information. This object shows the now ubiquitous switch between soft leading the hard band on long time-scales, to the opposite behaviour on short time-scales. This is interpreted as a combination of intrinsic fluctuations propagating down through the accretion flow giving the soft lead, together with reflection of the hard X-rays giving the soft lag. We build a full model of the spectral and time variability including both propagation and reflection, and compare our model with the observed power spectra, coherence, covariance, lag-frequency and lag-energy spectra. We compare models based on a separate soft excess component with those based on reflection-dominated soft emission. Reflection-dominated spectra have difficulty reproducing the soft lead at low frequency since reflection will always lag. They also suffer from high coherence and nearly identical hard- and soft-band power spectra in disagreement with the observations. This is a direct result of the power-law and reflection components both contributing to the hard and soft energy bands, and the small radii over which the relativistically smeared reflection is produced allowing too much high-frequency power to be transmitted into the soft band. Conversely, we find the separate soft excess models (where the inner disc radius is >6Rg) have difficulty reproducing the soft lag at high frequency, as reflected flux does not contribute enough signal to overwhelm the soft lead. However, reflection should also be accompanied by reprocessing and this should add to the soft excess at low energies. This model can quantitatively reproduce the switch from soft lead to soft lag seen in the data and reproduces well the observed power spectra and other timing features which reflection-dominated models cannot.
Nielsen, Elisabet I.; Viberg, Anders; Löwdin, Elisabeth; Cars, Otto; Karlsson, Mats O.; Sandström, Marie
2007-01-01
Dosing of antibacterial agents is generally based on point estimates of the effect, even though bacteria exposed to antibiotics show complex kinetic behaviors. The use of the whole time course of the observed effects would be more advantageous. The aim of the present study was to develop a semimechanistic pharmacokinetic (PK)/pharmacodynamic (PD) model characterizing the events seen in a bacterial system when it is exposed to antibacterial agents with different mechanisms of action. Time-kill curve experiments were performed with a strain of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics: benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. Bacterial counts were monitored with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. The degradation of the drugs was monitored and corrected for in the model, and a link model was used to account for an effect delay. In the final PK/PD model, the total bacterial population was divided into two subpopulations: one growing drug-susceptible population and one resting insusceptible population. The drug effect was included as an increase of the killing rate of bacteria in the susceptible state, according to a maximum-effect (Emax) model. An internal model validation showed that the model was robust and had good predictability. In conclusion, for all drugs, the final PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to different antibiotic concentrations. The semimechanistic model that was developed might, after further refinement, serve as a tool for the development of optimal dosing strategies for antibacterial agents. PMID:17060524
Bartl, Martin; Li, Pu; Schuster, Stefan
2010-07-01
The time course of enzyme concentrations in metabolic pathways can be predicted on the basis of the optimality criterion of minimizing the time period in which an essential product is generated. This criterion is in line with the widely accepted view that high fitness requires high pathway flux. Here, based on Pontryagin's Maximum Principle, a method is developed to solve the corresponding constrained optimal control problem in an almost exclusively analytical way and, thus, to calculate optimal enzyme profiles, when linear, irreversible rate laws are assumed. Three different problem formulations are considered and the corresponding optimization results are derived. Besides the minimization of transition time, we consider an operation time in which 90% of the substrate has been converted into product. In that case, only the enzyme at the lower end of the pathway rather than all enzymes are active in the last phase. In all cases, biphasic or multiphasic time courses are obtained. The biological meaning of the results in terms of a consecutive just-in-time expression of metabolic genes is discussed. For the special case of two-enzyme systems, the role of the Golden section in the solution is outlined.
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.
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.
Characteristic Time Model Validation
1988-09-01
combustors (Rizk and Mongia , 1986). The only practical m.thod for ascertaining the validity of these models it to develop a well defined experimental datum...layer around the recirculation zone found in the primary zone of a gas turbine combustor . Experi- mental results are used to investigate CTM parameters...Length Scale ....................................... 80 4.3.6 Relation of rsglobal to Combustors ............................... 80 4.4 Spray
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.
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…
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
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.
NASA Astrophysics Data System (ADS)
Gulyaeva, Tamara
2016-08-01
The International Reference Ionosphere (IRI) imports global effective ionospheric IG12 index based on ionosonde measurements of the critical frequency foF2 as a proxy of solar activity. Similarly, the global electron content (GEC), smoothed by the sliding 12-months window (GEC12), is used as a solar proxy in the ionospheric and plasmaspheric model IRI-Plas. GEC has been calculated from global ionospheric maps of total electron content (TEC) since 1998 whereas its productions for the preceding years and predictions for the future are made with the empirical model of the linear dependence of GEC on solar activity. At present there is a need to re-evaluate solar and ionospheric indices in the ionospheric models due to the recent revision of sunspot number (SSN2) time series, which has been conducted since 1st July, 2015 [Clette et al., 2014]. Implementation of SSN2 instead of the former SSN1 series with the ionospheric model could increase model prediction errors. A formula is proposed to transform the smoothed SSN212 series to the proxy of the former basic SSN112=R12 index, which is used by IRI and IRI-Plas models for long-term ionospheric predictions. Regression relationships are established between GEC12, the sunspot number R12, and the proxy solar index of 10.7 cm microwave radio flux, F10.712. Comparison of calculations by the IRI-Plas and IRI models with observations and predictions for Moscow during solar cycles 23 and 24 has shown the advantage of implementation of GEC12 index with the IRI-Plas model.
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.
Aranha Junior, Ayrton Alves; Arend, Lavinia Nery; Ribeiro, Vanessa; Zavascki, Alexandre Prehn; Tuon, Felipe Francisco
2015-01-01
This study evaluated the efficacy of tigecycline (TIG), polymyxin B (PMB), and meropenem (MER) in 80 rats challenged with Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae infection. A time-kill assay was performed with the same strain. Triple therapy and PMB+TIG were synergistic, promoted 100% survival, and produced negative peritoneal cultures, while MER+TIG showed lower survival and higher culture positivity than other regimens (P = 0.018) and was antagonistic. In vivo and in vitro studies showed that combined regimens, except MER+TIG, were more effective than monotherapies for this KPC-producing strain. PMID:25896686
Tao, Yang; Li, Yong; Zhou, Ruiyun; Chu, Dinh-Toi; Su, Lijuan; Han, Yongbin; Zhou, Jianzhong
2016-10-01
In the study, osmotically dehydrated cherry tomatoes were partially dried to water activity between 0.746 and 0.868, vacuum-packed and stored at 4-30 °C for 60 days. Adaptive neuro-fuzzy inference system (ANFIS) was utilized to predict the physicochemical and microbiological parameters of these partially dried cherry tomatoes during storage. Satisfactory accuracies were obtained when ANFIS was used to predict the lycopene and total phenolic contents, color and microbial contamination. The coefficients of determination for all the ANFIS models were higher than 0.86 and showed better performance for prediction compared with models developed by response surface methodology. Through ANFIS modeling, the effects of storage conditions on the properties of partially dried cherry tomatoes were visualized. Generally, contents of lycopene and total phenolics decreased with the increase in water activity, temperature and storage time, while aerobic plate count and number of yeasts and molds increased at high water activities and temperatures. Overall, ANFIS approach can be used as an effective tool to study the quality decrease and microbial pollution of partially dried cherry tomatoes during storage, as well as identify the suitable preservation conditions.
Cohen-Mansfield, Jiska; Thein, Khin; Dakheel-Ali, Maha; Marx, Marcia S.
2011-01-01
We examined the impact of setting characteristics and presentation effects on engagement with stimuli in a group of 193 nursing home residents with dementia (recruited from a total of seven nursing homes). Engagement was assessed through systematic observations using the Observational Measurement of Engagement (OME), and data pertaining to setting characteristics (background noise, light, and number of persons in proximity) were recorded via the environmental portion of the Agitation Behavior Mapping Inventory (ABMI; Cohen-Mansfield, Werner, & Marx, (1989). An observational study of agitation in agitated nursing home residents. International Psychogeriatrics, 1, 153–165). Results revealed that study participants were engaged more often with moderate levels of sound and in the presence of a small group of people (from four to nine people). As to the presentation effects, multiple presentations of the same stimulus were found to be appropriate for the severely impaired as well as the moderately cognitively impaired. Moreover, modeling of the appropriate behavior significantly increased engagement, with the severely cognitively impaired residents receiving the greatest benefit from modeling. These findings have direct implications for the way in which caregivers could structure the environment in the nursing home and how they could present stimuli to residents in order to optimize engagement in persons with dementia. PMID:20455123
Modeling North Pacific Time Series
NASA Astrophysics Data System (ADS)
Overland, J. E.; Percival, D. B.; Mofjeld, H. O.
2002-05-01
We present a case study in modeling the North Pacific (NP) index, a time series of the wintertime Aleutian low sea level pressure from 1900 to 1999. We consider three statistical models, namely, a Gaussian stationary autoregressive process, a Gaussian fractionally difference (FD) or ``long-memory" process, and a ``signal plus noise" process consisting of a square wave oscillation with a pentadecadal period embedded in Gaussian white noise. Each model depends upon three parameters, so all three models are equally simple. The shortness of the time series makes it unrealistic to formally prefer one model over the other: we estimate it would take a 300 year record to differentiate between the models. Although the models fit equally well, they have quite different implications for the long-term behavior of the NP index, e.g. generation of regimes of characteristic lengths. Additional information and physical arguments may add support for a particular model. The FD - ``long memory" process suggests multiple physical contributions with different damping constants many North Pacific biological time series which are influenced by atmospheric and oceanic processes, show regime-like ecosystem reorganizations.
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.
Eckert, Saskia; Eyer, Peter; Mückter, Harald; Worek, Franz
2006-07-28
Quantitative predictions of the course of acetylcholinesterase (AChE) activity, following interference of inhibitors and reactivators, are usually obscured by the time-dependent changes of all reaction partners. To mimic these dynamics we developed an in vitro model. Immobilized human erythrocyte ghosts in a bioreactor were continuously perfused while AChE activity was monitored by a modified Ellman method. The perfusion system consisted of two HPLC pumps with integrated quaternary low-pressure gradient formers that were programmed by a computer using commercial HPLC software. The combined eluates passed a particle filter (Millex-GS, 0.22 microm) containing a thin layer of erythrocytes that was immersed in a temperature-controlled water bath. The effluent passed a flow cell in a UV-vis detector, the signal of which was digitized, written to disc and calculated with curve fitting programs. AChE activity decreased by 3.4% within 2.5 h. The day-to-day variation of the freshly prepared bioreactor using the same enzyme source was +/-3.3%. Residual activity of 0.2% marked the limit of quantification. Following perfusion with paraoxon, pseudo first-order rate constants of inhibition were established that did not differ from results obtained in conventional assays. The same holds true for reactivation with obidoxime. The set-up presented allows freely programmable time-dependent changes of up to eight solvents to mimic pharmacokinetic profiles without accumulation of products. Due to some hysteresis in the system, reaction half-lives should be >3 min and concentration changes in critical compounds should exceed half-lives of 5 min. Otherwise, the system offers much flexibility and operates with high precision.
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
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.
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.
Examining Model Fidelity via Shadowing Time
NASA Astrophysics Data System (ADS)
Du, H.; Smith, L. A.
2014-12-01
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 observed dynamics of the Earth; extracting the shortcomings of the model which limit shadowing times allows informed speculation regarding the fidelity of the model in the future. More specifically, by identifying the reasons models cannot shadow we learn the relevant phenomena limiting model fidelity, we can then look at the time scales on which feedbacks on the system (which are not active in the model) are likely to result in model irrelevance. 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 as well as 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.
Worek, Franz; Herkert, Nadja M; Koller, Marianne; Thiermann, Horst; Wille, Timo
2015-12-25
Tabun-inhibited acetylcholinesterase (AChE) is rather resistant towards reactivation by oximes in vitro while in vivo experiments showed some protection of animals poisoned by this chemical warfare nerve agent after treatment with an oxime and atropine. In addition, AChE inhibited by close tabun analogues, N,N-diethyltabun and N,N-di-n-propyltabun was completely resistant towards reactivation by oximes. In order to get more insight into potential mechanisms of this oxime resistance experiments with these toxic agents and the oximes obidoxime, 2-PAM, MMB-4 and HI-6 were performed utilizing a dynamic model with real-time determination of AChE activity. This experimental setup allowed the investigation of reactivation with minimized side reactions. The determined reactivation constants with tabun-inhibited human AChE were in good agreement with previously reported constants determined with a static model. N,N-diethyl- and N,N-di-n-propyltabun-inhibited human AChE could not be reactivated by oximes which indicates that the inadequate oxime effect was not due to re-inhibition by phosphonyloximes. Additional experiments with tabun-inhibited human and Rhesus monkey AChE revealed that no reactivation occurred with HI-6. These data give further support to the assumption that an interaction of tabun with residues in the active site gorge of AChE prevents effective reactivation by oximes, a mechanism which may also be the reason for the total oxime resistance of N,N-diethyl- and N,N-di-n-propyltabun-inhibited human AChE.
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.
Kalai, Safaa; Anzala, Lexane; Bensoussan, Maurice; Dantigny, Philippe
2017-01-02
In this study, the influence of environmental factors on the germination time of Penicillium camemberti and Penicillium roqueforti conidia was evaluated. To do so, the effects of i/temperature, pH, water activity, and ii/organic acids were determined using models based on i/cardinal values, and ii/minimum inhibitory concentration (MIC) respectively. Cardinal values for germination of conidia were not observed to be species dependent. Minimum temperatures were estimated to be below the freezing point, with an optimum of 26.9°C, and a maximum of 33.5°C. For both species, minimal and optimal aw values were found to be 0.83 and 0.99, respectively, while for pH these values corresponded to 2.9, and 5.6. MIC values could not be determined for lactic acid because conidia of both species germinated in up to 1M concentrations, the highest concentration tested. At pH5.6, P. camemberti (MIC=0.197M) was more sensitive to propionic acid than P. roqueforti (MIC=0.796M).
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
Multiple Indicator Stationary Time Series Models.
ERIC Educational Resources Information Center
Sivo, Stephen A.
2001-01-01
Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…
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
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…
Abnormal activated partial thromboplastin time and malignancy.
Delicata, M; Hambley, H
2011-08-01
Malignancy often results in clotting abnormalities. The aetiology of haemostasis problems in cancer is complex, and is still not completely understood. We describe a case of a patient with malignant mesothelioma, who was found to have elevated activated partial thromboplastin time, due to lupus anticoagulant. We suggest that patients with malignancy should have their coagulation checked prior to any invasive procedures.
Identifying healthcare activities using a real-time location system.
Cagle, Rick; Darling, Erika; Kim, Bo
2014-01-01
This article discusses human resource allocation in a Veterans Health Administration audiology clinic as a model for clinics facing similar challenges in maximizing quality, safety, and effectiveness of care. A framework is proposed combining automatic identification technology with simulation and visualization software, asserting a relationship between location of staff within the facility and clinical activity, focusing healthcare staff on high-value activities to deliver safe, quality care. This enables "what-if" analyses of potential resource allocation scenarios, correlating location information from radiofrequency identification tags worn by clinicians and technicians in the clinic as part of a real-time location system, then inferring probable activity from the data. Once the baseline "as-is" can be established, the model will be refined to supply predictive analyses of resource allocation and management. Simulations of activities in specialized spaces saves time managing resources, which means more time can be spent on patient safety and increased satisfaction.
Leisure-time physical activity in relation to occupational physical activity among women
Ekenga, Christine C.; Parks, Christine G.; Wilson, Lauren E.; Sandler, Dale P.
2017-01-01
Objective To examine the association between occupational physical activity and leisure-time physical activity among US women in the Sister Study. Methods We conducted a cross-sectional study of 26,334 women who had been employed in their current job for at least 1 year at baseline (2004–2009). Occupational physical activity was self-reported and leisure-time physical activity was estimated in metabolic equivalent hours per week. Log multinomial regression was used to evaluate associations between occupational (sitting, standing, manually active) and leisure-time (insufficient, moderate, high) activity. Models were adjusted for age, race/ethnicity, education, income, geographic region, and body mass index. Results Only 54% of women met or exceeded minimum recommended levels of leisure-time physical activity (moderate 32% and high 22%). Women who reported sitting (PR = 0.82, 95% CI: 0.74–0.92) or standing (PR = 0.84, 95% CI: 0.75–0.94) most of the time at work were less likely to meet the requirements for high leisure-time physical activity than manually active workers. Associations were strongest among women living in the Northeast and the South. Conclusion In this nationwide study, low occupational activity was associated with lower leisure-time physical activity. Women who are not active in the workplace may benefit from strategies to promote leisure-time physical activity. PMID:25773471
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
Inductive time series modeling program
Kirk, B.L.; Rust, B.W.
1985-10-01
A number of features that comprise environmental time series share a common mathematical behavior. Analysis of the Mauna Loa carbon dioxide record and other time series is aimed at constructing mathematical functions which describe as many major features of the data as possible. A trend function is fit to the data, removed, and the resulting residuals analyzed for any significant behavior. This is repeated until the residuals are driven to white noise. In the following discussion, the concept of trend will include cyclic components. The mathematical tools and program packages used are VARPRO (Golub and Pereyra 1973), for the least squares fit, and a modified version of our spectral analysis program (Kirk et al. 1979), for spectrum and noise analysis. The program is written in FORTRAN. All computations are done in double precision, except for the plotting calls where the DISSPLA package is used. The core requirement varies between 600 K and 700 K. The program is implemented on the IBM 360/370. Currently, the program can analyze up to five different time series where each series contains no more than 300 points. 12 refs.
Continuous Time Dynamic Topic Models
2008-06-20
called topics, can be used to explain the observed collection. LDA is a probabilistic extension of latent semantic indexing (LSI) [5] and probabilistic... latent semantic indexing (pLSI) [11]. Owing to its formal generative semantics, LDA has been extended and applied to authorship [19], email [15...Steyvers. Probabilistic topic models. In Latent Semantic Analysis: A Road to Meaning. 2006. [9] T. L. Griffiths and M. Steyvers. Finding scientific
Stratospheric Transport Times From Observations and Models
NASA Astrophysics Data System (ADS)
Hoor, P. M.; Lelieveld, J.; Boenisch, H.; Joeckel, P.; Steil, B.; Bruehl, C.; Strahan, S.
2007-12-01
Transport time scales in the stratosphere are crucial to understand and calculate the effects of chemical active species on stratospheric chemistry. In general CO2 or SF6 have been used to calculate mean ages of air in the stratosphere, whereas shorter lived trace gases like CO are used to investigate cross tropopause transport and mixing on short time-scales close to the tropopause. Besides mean ages and their assocated mean trace gas mixing ratios at a given point in the atmosphere other quantities of the trace gas distributions can be used to constrain stratospheric transport times, such as variability and slope. In particular the younger part of the age spectrum needs to be constrained since it determines the extent to which shorter lived compounds can be transported into the stratosphere. We investigate transport times in the stratosphere based on observations of CO, N2O and CO2 and test a new approach to deduce transport times. For that purpose we compare observations from the ER-2 and other platforms. The approach is applied to global models (ECHAM5/MESSy, Combo GMI) to identify barriers as well as regions of rapid mixing and transport.
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.
Solar activity affects avian timing of reproduction
Visser, Marcel E.; Sanz, Juan José
2009-01-01
Avian timing of reproduction is strongly affected by ambient temperature. Here we show that there is an additional effect of sunspots on laying date, from five long-term population studies of great and blue tits (Parus major and Cyanistes caeruleus), demonstrating for the first time that solar activity not only has an effect on population numbers but that it also affects the timing of animal behaviour. This effect is statistically independent of ambient temperature. In years with few sunspots, birds initiate laying late while they are often early in years with many sunspots. The sunspot effect may be owing to a crucial difference between the method of temperature measurements by meteorological stations (in the shade) and the temperatures experienced by the birds. A better understanding of the impact of all the thermal components of weather on the phenology of ecosystems is essential when predicting their responses to climate change. PMID:19574283
Lai, Y-Y; Hsieh, K-C; Nguyen, D; Peever, J; Siegel, J M
2008-06-23
There is no adequate animal model of restless legs syndrome (RLS) and periodic leg movements disorder (PLMD), disorders affecting 10% of the population. Similarly, there is no model of rapid eye movement (REM) sleep behavior disorder (RBD) that explains its symptoms and its link to Parkinsonism. We previously reported that the motor inhibitory system in the brainstem extends from the medulla to the ventral mesopontine junction (VMPJ). We now examine the effects of damage to the VMPJ in the cat. Based on the lesion sites and the changes in sleep pattern and behavior, we saw three distinct syndromes resulting from such lesions; the rostrolateral, rostromedial and caudal VMPJ syndromes. The change in sleep pattern was dependent on the lesion site, but was not significantly correlated with the number of dopaminergic neurons lost. An increase in wakefulness and a decrease in slow wave sleep (SWS) and REM sleep were seen in the rostrolateral VMPJ-lesioned animals. In contrast, the sleep pattern was not significantly changed in the rostromedial and caudal VMPJ-lesioned animals. All three groups of animals showed a significant increase in periodic and isolated leg movements in SWS and increased tonic muscle activity in REM sleep. Beyond these common symptoms, an increase in phasic motor activity in REM sleep, resembling that seen in human RBD, was found in the caudal VMPJ-lesioned animals. In contrast, the increase in motor activity in SWS in rostral VMPJ-lesioned animals is similar to that seen in human RLS/PLMD patients. The proximity of the VMPJ region to the substantia nigra suggests that the link between RLS/PLMD and Parkinsonism, as well as the progression from RBD to Parkinsonism may be mediated by the spread of damage from the regions identified here into the substantia nigra.
Simple Reaction Time and Statistical Facilitation: A Parallel Grains Model
ERIC Educational Resources Information Center
Miller, Jeff; Ulrich, Rolf
2003-01-01
A race-like model is developed to account for various phenomena arising in simple reaction time (RT) tasks. Within the model, each stimulus is represented by a number of grains of information or activation processed in parallel. The stimulus is detected when a criterion number of activated grains reaches a decision center. Using the concept of…
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 transmission1-3. 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 data4. 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
2013-02-25
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
NASA Astrophysics Data System (ADS)
Cionco, Rodolfo Gustavo; Soon, Willie
2015-01-01
We numerically integrate the Sun’s orbital movement around the barycenter of the solar system under the persistent perturbation of the planets from the epoch J2000.0, backward for about one millennium, and forward for another millennium to 3000 AD. Under the Sun-Planets Interaction (SPI) framework and interpretation of Wolff and Patrone (2010), we calculated the corresponding variations of the most important storage of the specific potential energy (PE) within the Sun that could be released by the exchanges between two rotating, fluid-mass elements that conserve its angular momentum. This energy comes about as a result of the roto-translational dynamics of the cell around the solar system barycenter. We find that the maximum variations of this PE storage correspond remarkably well with the occurrences of well-documented Grand Minima (GM) solar events throughout the available proxy solar magnetic activity records for the past 1000 yr. It is also clear that the maximum changes in PE precede the GM events in that we can identify precursor warnings to the imminent weakening of solar activity for an extended period. The dynamical explanation of these PE minima is connected to the minima of the Sun’s position relative to the barycenter as well as the significant amount of time the Sun’s inertial motion revolving near and close to the barycenter. We presented our calculation of PE forward by another 1000 yr until 3000 AD. If the assumption of the solar activity minima corresponding to PE minima is correct, then we can identify quite a few significant future solar activity GM events with a clustering of PE minima pulses starting at around 2150 AD, 2310 AD, 2500 AD, 2700 AD and 2850 AD.
Assessing working memory capacity through time-constrained elementary activities.
Lucidi, Annalisa; Loaiza, Vanessa; Camos, Valérie; Barrouillet, Pierre
2014-01-01
Working memory (WM) capacity measured through complex span tasks is among the best predictors of fluid intelligence (Gf). These tasks usually involve maintaining memoranda while performing complex cognitive activities that require a rather high level of education (e.g., reading comprehension, arithmetic), restricting their range of applicability. Because individual differences in such complex activities are nothing more than the concatenation of small differences in their elementary constituents, complex span tasks involving elementary processes should be as good of predictors of Gf as traditional tasks. The present study showed that two latent variables issued from either traditional or new span tasks involving time-constrained elementary activities were similarly correlated with Gf. Moreover, a model with a single unitary WM factor had a similar fit as a model with two distinct WM factors. Thus, time-constrained elementary activities can be integrated in WM tasks, permitting the assessment of WM in a wider range of populations.
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
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.
Activated partial thromboplastin time and minor coagulopathies.
Hathaway, W E; Assmus, S L; Montgomery, R R; Dubansky, A S
1979-01-01
Five commercially available activated partial thromboplastin time (APTT) test systems were compared with the kaolin partial thromboplastin time (KPTT) method to determine sensitivity in detecting minor coagulation defects. All reagent systems detected severe factor VIII-, IX-, and XI-deficient hemophilia. Homozygous states of factor XII deficiency, Fletcher factor deficiency, and high-molecular-weight kininogen deficiency (Fitzgerald trait) also showed abnormally long APTTs by all systems. Of 19 samples from patients with deficiencies of factors XII, VIII, IX, XI, and II ranging from 2.5 to 52%, eight had deficiencies that were not detected by reagent A (ellagic acid); two, by reagent B (ellagic acid); two, by reagent C (kaolin); one, by reagent D (silica); one, by the KPTT method. All deficiencies were detected by reagent E (celite). Heparin effect on plasma was less well detected by reagent A (ellagic acid) than with the other test systems. APTT test systems can vary greatly in their abilities to detect minor coagulation abnormalities.
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.
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.
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.
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.'
Kosegarten, Carlos E; Ramírez-Corona, Nelly; Mani-López, Emma; Palou, Enrique; López-Malo, Aurelio
2017-01-02
A Box-Behnken design was used to determine the effect of protein concentration (0, 5, or 10g of casein/100g), fat (0, 3, or 6g of corn oil/100g), aw (0.900, 0.945, or 0.990), pH (3.5, 5.0, or 6.5), concentration of cinnamon essential oil (CEO, 0, 200, or 400μL/kg) and incubation temperature (15, 25, or 35°C) on the growth of Aspergillus flavus during 50days of incubation. Mold response under the evaluated conditions was modeled by the modified Gompertz equation, logistic regression, and time-to-detection model. The obtained polynomial regression models allow the significant coefficients (p<0.05) for linear, quadratic and interaction effects for the Gompertz equation's parameters to be identified, which adequately described (R(2)>0.967) the studied mold responses. After 50days of incubation, every tested model system was classified according to the observed response as 1 (growth) or 0 (no growth), then a binary logistic regression was utilized to model A. flavus growth interface, allowing to predict the probability of mold growth under selected combinations of tested factors. The time-to-detection model was utilized to estimate the time at which A. flavus visible growth begins. Water activity, temperature, and CEO concentration were the most important factors affecting fungal growth. It was observed that there is a range of possible combinations that may induce growth, such that incubation conditions and the amount of essential oil necessary for fungal growth inhibition strongly depend on protein and fat concentrations as well as on the pH of studied model systems. The probabilistic model and the time-to-detection models constitute another option to determine appropriate storage/processing conditions and accurately predict the probability and/or the time at which A. flavus growth occurs.
Active Mining from Process Time Series by Learning Classifier System
NASA Astrophysics Data System (ADS)
Kurahashi, Setsuya; Terano, Takao
Continuation processes in chemical and/or biotechnical plants always generate a large amount of time series data. However, since conventional process models are described as a set of control models, it is difficult to explain the complicated and active plant behaviors. Based on the background, this research proposes a novel method to develop a process response model from continuous time-series data. The method consists of the following phases: 1) Collect continuous process data at each tag point in a target plant; 2) Normalize the data in the interval between zero and one; 3) Get the delay time, which maximizes the correlation between given two time series data; 4) Select tags with the higher correlation; 5) Develop a process response model to describe the relations among the process data using the delay time and the correlation values; 6) Develop a process prediction model via several tag points data using a neural network; 1) Discover control rules from the process prediction model using Learning Classifier system. The main contribution of the research is to establish a method to mine a set of meaningful control rules from Learning Classifier System using the Minimal Description Length criteria. The proposed method has been applied to an actual process of a biochemical plant and has shown the validity and the effectiveness.
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
Dynamic Factor Analysis Models With Time-Varying Parameters.
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian
2011-04-11
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 with vector autoregressive relations and time-varying cross-regression parameters at the factor level. Using techniques drawn from the state-space literature, the model was fitted to a set of daily affect data (over 71 days) from 10 participants who had been diagnosed with Parkinson's disease. Our empirical results lend partial support and some potential refinement to the Dynamic Model of Activation with regard to how the time dependencies between positive and negative affects change over time. A simulation study is conducted to examine the performance of the proposed techniques when (a) changes in the time-varying parameters are represented using the true model of change, (b) supposedly time-invariant parameters are represented as time-varying, and
Modeling Response Signal and Response Time Data
ERIC Educational Resources Information Center
Ratcliff, Roger
2006-01-01
The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of…
A mixed time series model of binomial counts
NASA Astrophysics Data System (ADS)
Khoo, Wooi Chen; Ong, Seng Huat
2015-10-01
Continuous time series modelling has been an active research in the past few decades. However, time series data in terms of correlated counts appear in many situations such as the counts of rainy days and access downloading. Therefore, the study on count data has become popular in time series modelling recently. This article introduces a new mixture model, which is an univariate non-negative stationary time series model with binomial marginal distribution, arising from the combination of the well-known binomial thinning and Pegram's operators. A brief review of important properties will be carried out and the EM algorithm is applied in parameter estimation. A numerical study is presented to show the performance of the model. Finally, a potential real application will be presented to illustrate the advantage of the new mixture model.
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.
Toward a unified model of developmental timing
Monsalve, Gabriela C.; Frand, Alison R.
2012-01-01
Animal development requires temporal coordination between recurrent processes and sequential events, but the underlying timing mechanisms are not yet understood. The molting cycle of C. elegans provides an ideal system to study this basic problem. We recently characterized LIN-42, which is related to the circadian clock protein PERIOD, as a key component of the developmental timer underlying rhythmic molting cycles. In this context, LIN-42 coordinates epithelial stem cell dynamics with progression of the molting cycle. Repeated actions of LIN-42 may enable the reprogramming of seam cell temporal fates, while stage-specific actions of LIN-42 and other heterochronic genes select fates appropriate for upcoming, rather than passing, life stages. Here, we discuss the possible configuration of the molting timer, which may include interconnected positive and negative regulatory loops among lin-42, conserved nuclear hormone receptors such as NHR-23 and -25, and the let-7 family of microRNAs. Physiological and environmental conditions may modulate the activities of particular components of this molting timer. Finding that LIN-42 regulates both a sleep-like behavioral state and epidermal stem cell dynamics further supports the model of functional conservation between LIN-42 and mammalian PERIOD proteins. The molting timer may therefore represent a primitive form of a central biological clock and provide a general paradigm for the integration of rhythmic and developmental processes. PMID:24058853
Multipoint measurements of substorm timing and activations
NASA Astrophysics Data System (ADS)
Zuyin, Pu; Cao, X.; Zhang, H.; Ma, Z. W.; Mishin, M. V.; Kubyshkina, M. V.; Pulkkinen, T.; Reeves, G. D.; Escoubet, C. Philippe
Substorm timing and activations are studied based on Double Star TC1, Cluster, Polar, IM- AGE, LANL satellites and ground-based Pi2 measurements. Substorm expansion onset is found to begin in the near-Earth tail around X= -(8-9) Re, then progresses both earthward and tailward. About 8-10 minutes before aurora breakup, Cluster measured an earthward flow associated with plasma sheet thinning. A couple of minutes after the breakup, TC1 first detects plasma sheet expansion and then LANL satellites near the midnight measure energetic electron injections, or vise versus. About 20 minutes (or more) later, Cluster and Polar observe plasma sheet expansion successively. Of interest are also the following findings. Auroral bulge is found to quickly broaden and expand poleward when the open magnetic flux of the polar cap is rapidly dissipated, indicating the role of tail lobe reconnection of open field lines in the development of the expansion phase. In addition, poleward expansion of auroral bulges and tailward progression of substorm expansion are shown to be closely related. An initial dipolarization in the near-Earth eventually evolve to enable disruption of the cross-tail current in a wide range of the magnetotail, until the open magnetic flux of the polar cap reaches its minimum. Acknowledgements This work is supported by the NSFC Grants 40390152 and 40536030 and Chinese Key Research Project Grant 2006CB806300. The authors acknowledge all PIs of instruments onboard Double Star and Cluster spacecraft. We also appreciate the useful discussions with R. L. McPherron and A. T. Y. Lui.
Space Station Active Thermal Control System modeling
NASA Technical Reports Server (NTRS)
Hye, Abdul; Lin, Chin H.
1988-01-01
The Space Station Active Thermal Control System (ATCS) has been modeled using modified SINDA/SINFLO programs to solve two-phase Thermo-fluid problems. The modifications include changes in several subroutines to incorporate implicit solution which allows larger time step as compared to that for explicit solutions. Larger time step saves computer time but involves larger computational error. Several runs were made using various time steps for the ATCS model. It has been found that for a reasonable approach, three times larger time step as compared to that used in explicit method is a good value which will reduce the computer time by approximately 50 percent and still maintain the accuracy of the output data to within 90 percent of the explicit values.
Energy Model of Neuron Activation.
Romanyshyn, Yuriy; Smerdov, Andriy; Petrytska, Svitlana
2017-02-01
On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activation model, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.
Fluxon Modeling of Active Region Evolution
NASA Astrophysics Data System (ADS)
Deforest, C. E.; Kankelborg, C. C.; Davey, A. R.; Rachmeler, L.
2006-12-01
We present current results and status on fluxon modeling of free energy buildup and release in active regions. Our publicly available code, FLUX, has the unique ability to track magnetic energy buildup with a truly constrained topology in evolving, nonlinear force-free conditions. Recent work includes validation of the model against Low &Lou force-free field solutions, initial evolution studies of idealized active regions, and inclusion of locally parameterized reconnection into the model. FLUX is uniquely able to simulate complete active regions in 3-D on a single workstation; we estimate that a parallelized fluxon model, together with computer vision code to ingest solar data, could run faster than real time on a cluster of \\textasciitilde 30 CPUs and hence provide a true predictive space weather model in the style of predictive simulations of terrestrial weather.
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.
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.
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.
Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.
Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi
2015-02-01
We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.
Real-time remote scientific model validation
NASA Technical Reports Server (NTRS)
Frainier, Richard; Groleau, Nicolas
1994-01-01
This paper describes flight results from the use of a CLIPS-based validation facility to compare analyzed data from a space life sciences (SLS) experiment to an investigator's preflight model. The comparison, performed in real-time, either confirms or refutes the model and its predictions. This result then becomes the basis for continuing or modifying the investigator's experiment protocol. Typically, neither the astronaut crew in Spacelab nor the ground-based investigator team are able to react to their experiment data in real time. This facility, part of a larger science advisor system called Principal Investigator in a Box, was flown on the space shuttle in October, 1993. The software system aided the conduct of a human vestibular physiology experiment and was able to outperform humans in the tasks of data integrity assurance, data analysis, and scientific model validation. Of twelve preflight hypotheses associated with investigator's model, seven were confirmed and five were rejected or compromised.
Time-dependent freezing rate parcel model
NASA Astrophysics Data System (ADS)
Vali, G.; Snider, J. R.
2015-02-01
The time-dependent freezing rate (TDFR) model here described represents the formation of ice particles by immersion freezing within an air parcel. The air parcel trajectory follows an adiabatic ascent and includes a period in time when the parcel remains stationary at the top of its ascent. The description of the ice nucleating particles (INPs) in the air parcel is taken from laboratory experiments with cloud and precipitation samples and is assumed to represent the INP content of the cloud droplets in the parcel. Time dependence is included to account for variations in updraft velocity and for the continued formation of ice particles under isothermal conditions. The magnitudes of these factors are assessed on the basis of laboratory measurements. Results show that both factors give rise to three-fold variations in ice concentration for a realistic range of the input parameters. Refinements of the parameters specifying time dependence and INP concentrations are needed to make the results more specific to different atmospheric aerosol types. The simple model framework described in this paper can be adapted to more elaborate cloud models. The results here presented can help guide decisions on whether to include a time-dependent ice nucleation scheme or a simpler singular description in models.
Time-dependent freezing rate parcel model
NASA Astrophysics Data System (ADS)
Vali, G.; Snider, J. R.
2014-11-01
The Time-Dependent Freezing Rate (TDFR) model here described represents the formation of ice particles by immersion freezing within an air parcel. The air parcel trajectory follows an adiabatic ascent and includes a period at time with the parcel remaining stationary at the top of its ascent. The description of the ice nucleating particles (INPs) in the air parcel is taken from laboratory experiments with cloud and precipitation samples and is assumed to represent the INP content of the cloud droplets in the parcel. Time-dependence is included to account for variations in updraft velocity and for the continued formation of ice particles at isothermal conditions. The magnitudes of these factors are assessed on the basis of laboratory measurements. Results show that both factors give rise to factors of about 3 variations in ice concentration for a realistic range of the input parameters. Refinements of the parameters specifying time-dependence and INP concentrations are needed to make the results more specific to different atmospheric aerosol types. The simple model framework described in this paper can be adapted to more elaborate cloud models. The results here presented can help guide decisions on whether to include a time-dependent ice nucleation scheme or a simpler singular description in models.
Model Selection for Cox Models with Time-Varying Coefficients
Yan, Jun; Huang, Jian
2011-01-01
Summary Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right censored failure times. Since not all covariate coefficients are time-varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time-varying coefficient from those with time-independent coefficient. We propose an adaptive group lasso method that not only selects important variables but also selects between time-independent and time-varying specifications of their presence in the model. Each covariate effect is partitioned into a time-independent part and a time-varying part, the latter of which is characterized by a group of coefficients of basis splines without intercept. Model selection and estimation are carried out through a fast, iterative group shooting algorithm. Our approach is shown to have good properties in a simulation study that mimics realistic situations with up to 20 variables. A real example illustrates the utility of the method. PMID:22506825
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.
Time and Frequency Transfer Activities at NIST
2008-12-01
Metrologia (SIM) Time Network The Sistema Interamericano de Metrologia (SIM) consists of national metrology institutes (NMIs) located in the 34...2003, “Time Transfer to TAI Using Geodetic Receivers,” Metrologia , 40, 184-188. [5] K. M. Larson, J. Levine, L. M. Nelson, and T. E. Parker, 2000... Metrologia , 40, 270-288. [7] G. Petit and Z. Jiang, 2008, “Precise point positioning for TAI computation,” International Journal of Navigation
Active gel model of amoeboid cell motility
NASA Astrophysics Data System (ADS)
Callan-Jones, A. C.; Voituriez, R.
2013-02-01
We develop a model of amoeboid cell motility based on active gel theory. Modeling the motile apparatus of a eukaryotic cell as a confined layer of finite length of poroelastic active gel permeated by a solvent, we first show that, due to active stress and gel turnover, an initially static and homogeneous layer can undergo a contractile-type instability to a polarized moving state in which the rear is enriched in gel polymer. This agrees qualitatively with motile cells containing an actomyosin-rich uropod at their rear. We find that the gel layer settles into a steadily moving, inhomogeneous state at long times, sustained by a balance between contractility and filament turnover. In addition, our model predicts an optimal value of the gel-substrate adhesion leading to maximum layer speed, in agreement with cell motility assays. The model may be relevant to motility of cells translocating in complex, confining environments that can be mimicked experimentally by cell migration through microchannels.
Physical terms and leisure time activities
NASA Astrophysics Data System (ADS)
Valovičová, Ä½ubomíra; Siptáková, Mária; ŠtubÅa, Martin
2017-01-01
People have to educate not only in school but also outside it. One approach to acquire new knowledge are leisure activities such as hobby groups or camps. Leisure activities, more and more seem to be the appropriate form for informal learning of physics concepts. Within leisure activities pupils have the possibility to acquire new concepts in unusual and interesting way. It is possible to inspire their intrinsic motivation on the matter or the phenomenon which is the aim of all teachers. This article deals with the description of and insights on acquisition of the concept of uniform and non-uniform rectilinear movement during a physics camp where pupils had the opportunity to use modern technologies which are despite of modernization of education still unconventional teaching methods in our schools.
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)…
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
Time series for blind biosignal classification model.
Wong, Derek F; Chao, Lidia S; Zeng, Xiaodong; Vai, Mang-I; Lam, Heng-Leong
2014-11-01
Biosignals such as electrocardiograms (ECG), electroencephalograms (EEG), and electromyograms (EMG), are important noninvasive measurements useful for making diagnostic decisions. Recently, considerable research has been conducted in order to potentially automate signal classification for assisting in disease diagnosis. However, the biosignal type (ECG, EEG, EMG or other) needs to be known prior to the classification process. If the given biosignal is of an unknown type, none of the existing methodologies can be utilized. In this paper, a blind biosignal classification model (B(2)SC Model) is proposed in order to identify the source biosignal type automatically, and thus ultimately benefit the diagnostic decision. The approach employs time series algorithms for constructing the model. It uses a dynamic time warping (DTW) algorithm with clustering to discover the similarity between two biosignals, and consequently classifies disease without prior knowledge of the source signal type. The empirical experiments presented in this paper demonstrate the effectiveness of the method as well as the scalability of the approach.
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…
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.
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.
Capturing Cognitive Processing Time for Active Authentication
2014-02-01
biometrics, extracted from keystroke dynamics , as “something a user is” for active authentication. This scheme performs continual verification in the...fingerprint for continuous authentication. Its effectiveness has been verified through a large-scale dataset. 2.0 INTRODUCTION Keystroke dynamics —the...measure the similarity. A recent survey on biometric authentication using keystroke dynamics classified research papers on the basis of their
Basophil activation tests: time for a reconsideration.
Uyttebroek, Astrid P; Sabato, Vito; Faber, Margaretha A; Cop, Nathalie; Bridts, Chris H; Lapeere, Hilde; De Clerck, Luc S; Ebo, Didier G
2014-10-01
Challenges in in vitro allergy diagnostics lie in the development of accessible and reliable assays allowing identification of all offending allergens and cross-reactive structures. Flow-assisted analysis and quantification of in vitro activated basophils serves as a diagnostic instrument with increasing applications developed over the years. From the earliest days it was clear that the test could constitute a diagnostic asset in basophil-mediated hypersensitivity. However, utility of the basophil activation test should be reassessed regarding difficulties with preparation, characterization and validation of allergen extracts; availability and the potential of more accessible diagnostics. Today, the added value mainly lies in diagnosis of immediate drug hypersensitivity. Other potential indications are monitoring venom-immunotherapy and follow-up of natural history of food allergies. However, results in these nondiagnostic applications are preliminary. We review the most relevant clinical applications of the basophil activation test. Some personal comments and views about perspectives and challenges about flow-assisted allergy diagnosis are made.
Time to trust: longitudinal integrated clerkships and entrustable professional activities.
Hirsh, David A; Holmboe, Eric S; ten Cate, Olle
2014-02-01
Medical education shaped by the learning sciences can better serve medical students, residents, faculty, health care institutions, and patients. With increasing innovation in undergraduate and graduate medical education and more focused attention on educational principles and how people learn, this era of educational transformation offers promise. Principles manifest in "educational continuity" are informing changes in educational structures and venues and are enriching new discourse in educational pedagogy, assessment, and scholarship. The articles by Myhre and colleagues and Woloschuk and colleagues in this issue, along with mounting evidence preceding these works, should reassure that principle-driven innovation in medical education is not only possible but can be achieved safely. In this commentary, the authors draw from these works and the wider literature on longitudinal integrated educational design. They suggest that the confluences of movements for longitudinal integrated clerkships and entrustable professional activities open new possibilities for other educational and practice advancements in quality and safety. With the advent of competency-based education, explicit milestones, and improved assessment regimens, overseers will increasingly evaluate students, trainees, and other learners on their ability rather than relying solely on time spent in an activity. The authors suggest that, for such oversight to have the most value, assessors and learners need adequate oversight time, and redesign of educational models will serve this operational imperative. As education leaders are reassessing old medical school and training models, rotational blocks, and other barriers to progress, the authors explore the dynamic interplay between longitudinal integrated learning models and entrustment.
Neurocomputational Models of Interval and Pattern Timing
Hardy, Nicholas F.; Buonomano, Dean V.
2016-01-01
Most of the computations and tasks performed by the brain require the ability to tell time, and process and generate temporal patterns. Thus, there is a diverse set of neural mechanisms in place to allow the brain to tell time across a wide range of scales: from interaural delays on the order of microseconds to circadian rhythms and beyond. Temporal processing is most sophisticated on the scale of tens of milliseconds to a few seconds, because it is within this range that the brain must recognize and produce complex temporal patterns—such as those that characterize speech and music. Most models of timing, however, have focused primarily on simple intervals and durations, thus it is not clear whether they will generalize to complex pattern-based temporal tasks. Here, we review neurobiologically based models of timing in the subsecond range, focusing on whether they generalize to tasks that require placing consecutive intervals in the context of an overall pattern, that is, pattern timing. PMID:27790629
Discrete time modelization of human pilot behavior
NASA Technical Reports Server (NTRS)
Cavalli, D.; Soulatges, D.
1975-01-01
This modelization starts from the following hypotheses: pilot's behavior is a time discrete process, he can perform only one task at a time and his operating mode depends on the considered flight subphase. Pilot's behavior was observed using an electro oculometer and a simulator cockpit. A FORTRAN program has been elaborated using two strategies. The first one is a Markovian process in which the successive instrument readings are governed by a matrix of conditional probabilities. In the second one, strategy is an heuristic process and the concepts of mental load and performance are described. The results of the two aspects have been compared with simulation data.
Time series modeling for automatic target recognition
NASA Astrophysics Data System (ADS)
Sokolnikov, Andre
2012-05-01
Time series modeling is proposed for identification of targets whose images are not clearly seen. The model building takes into account air turbulence, precipitation, fog, smoke and other factors obscuring and distorting the image. The complex of library data (of images, etc.) serving as a basis for identification provides the deterministic part of the identification process, while the partial image features, distorted parts, irrelevant pieces and absence of particular features comprise the stochastic part of the target identification. The missing data approach is elaborated that helps the prediction process for the image creation or reconstruction. The results are provided.
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.
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.
NASA Astrophysics Data System (ADS)
Keddam, M.; Kulka, M.; Makuch, N.; Pertek, A.; Małdziński, L.
2014-04-01
The present work deals with a simulation of the growth kinetics of boride layers grown on Armco iron substrate. The formed boride layers (FeB + Fe2B) are obtained by the gas-boriding in the temperature range of 1073-1273 K during a time duration ranging from 80 to 240 min. The used approach solves the mass balance equations at the two growing fronts: (FeB/Fe2B) and (Fe2B/Fe) under certain assumptions. To consider the effect of the incubation times for the borides formation, the temperature-dependent function Φ(T) was incorporated in the model. The following input data: (the boriding temperature, the treatment time, the upper and lower values of boron concentrations in FeB and Fe2B and the experimental parabolic growth constants) are needed to determine the boron activation energies in the FeB and Fe2B layers. The obtained values of boron activation energies were then compared with the values available in the literature. Finally, a good agreement was obtained between the simulated values of boride layers thicknesses and the experimental ones in the temperature range of 1073-1273 K.
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.
Onicescu, Georgiana; Lawson, Andrew; Zhang, Jiajia; Gebregziabher, Mulugeta; Wallace, Kristin; Eberth, Jan M
2016-01-01
In this paper, we extend the spatially explicit survival model for small area cancer data by allowing dependency between space and time and using accelerated failure time models. Spatial dependency is modeled directly in the definition of the survival, density, and hazard functions. The models are developed in the context of county level aggregated data. Two cases are considered: the first assumes that the spatial and temporal distributions are independent; the second allows for dependency between the spatial and temporal components. We apply the models to prostate cancer data from the Louisiana SEER cancer registry. PMID:26220537
Neural Network Retinal Model Real Time Implementation
1992-09-02
addresses the specific needs of vision processing. The goal of this SBIR Phase I project has been to take a significant neural network vision...application and to map it onto dedicated hardware for real time implementation. The neural network was already demonstrated using software simulation on a...general purpose computer. During Phase 1, HNC took a neural network model of the retina and, using HNC’s Vision Processor (ViP) prototype hardware
Real-Time Ocean Modeling Systems
2013-10-22
2002 2. REPORT TYPE 3. DATES COVERED (From - To) Journal Article 4 . TITLE AND SUBTITLE Real-time 16iebaf Modeling Systems \\&&»A 5a...Director NCST E.O. Hartwig, 7000 Public Affairs (Unclassified/ Unlimited Only), Code 7n30 4 Division, Code Author, Code HQ-NRL 5511/6 (Rev. 12-93...according to the routing in Section 4 . 1. NRL Reports Submit the diskette (if available), manuscript, typed double-spaced, complete with tables
Modelling population change from time series data
Barker, R.J.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.
1992-01-01
Information on change in population size over time is among the most basic inputs for population management. Unfortunately, population changes are generally difficult to identify, and once identified difficult to explain. Sources of variald (patterns) in population data include: changes in environment that affect carrying capaciyy and produce trend, autocorrelative processes, irregular environmentally induced perturbations, and stochasticity arising from population processes. In addition. populations are almost never censused and many surveys (e.g., the North American Breeding Bird Survey) produce multiple, incomplete time series of population indices, providing further sampling complications. We suggest that each source of pattern should be used to address specific hypotheses regarding population change, but that failure to correctly model each source can lead to false conclusions about the dynamics of populations. We consider hypothesis tests based on each source of pattern, and the effects of autocorrelated observations and sampling error. We identify important constraints on analyses of time series that limit their use in identifying underlying relationships.
Modeling utilization distributions in space and time.
Keating, Kim A; Cherry, Steve
2009-07-01
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.
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 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.
Identities in flux: cognitive network activation in times of change.
Menon, Tanya; Smith, Edward Bishop
2014-05-01
Using a dynamic cognitive model, we experimentally test two competing hypotheses that link identity and cognitive network activation during times of change. On one hand, affirming people's sense of power might give them confidence to think beyond the densest subsections of their social networks. Alternatively, if such power affirmations conflict with people's more stable status characteristics, this could create tension, deterring people from considering their networks' diversity. We test these competing hypotheses experimentally by priming people at varying levels of status with power (high/low) and asking them to report their social networks. We show that confirming identity-not affirming power-cognitively prepares people to broaden their social networks when the world is changing around them. The emotional signature of having a confirmed identity is feeling comfortable and in control, which mediates network activation. We suggest that stable, confirmed identities are the foundation from which people can exhibit greater network responsiveness.
Free Time Motivation and Physical Activity in Middle School Children
ERIC Educational Resources Information Center
Kozub, Francis M.; Farmer, James
2011-01-01
This study examined free time motivation and physical activity in 68 middle school children from a rural public school system (N = 24) and a private school located in the same area of the Midwest (N = 44). Results indicated that free time motivation did not explain variability in physical activity behavior during free time or while students were…
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 active.…
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.
Real-time segmentation by Active Geometric Functions.
Duan, Qi; Angelini, Elsa D; Laine, Andrew F
2010-06-01
Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the enormous amount of information contained in these data has also raised a challenge for traditional image analysis algorithms in terms of efficiency. In this paper, a novel deformable model framework, Active Geometric Functions (AGF), is introduced to tackle the real-time segmentation problem. As an implicit framework paralleling to level-set, AGF has mathematical advantages in efficiency and computational complexity as well as several flexible feature similar to level-set framework. AGF is demonstrated in two cardiac applications: endocardial segmentation in 4D ultrasound and myocardial segmentation in MRI with super high temporal resolution. In both applications, AGF can perform real-time segmentation in several milliseconds per frame, which was less than the acquisition time per frame. Segmentation results are compared to manual tracing with comparable performance with inter-observer variability. The ability of such real-time segmentation will not only facilitate the diagnoses and workflow, but also enables novel applications such as interventional guidance and interactive image acquisition with online segmentation.
Modeling ventilation time in forage tower silos.
Bahloul, A; Chavez, M; Reggio, M; Roberge, B; Goyer, N
2012-10-01
The fermentation process in forage tower silos produces a significant amount of gases, which can easily reach dangerous concentrations and constitute a hazard for silo operators. To maintain a non-toxic environment, silo ventilation is applied. Literature reviews show that the fermentation gases reach high concentrations in the headspace of a silo and flow down the silo from the chute door to the feed room. In this article, a detailed parametric analysis of forced ventilation scenarios built via numerical simulation was performed. The methodology is based on the solution of the Navier-Stokes equations, coupled with transport equations for the gas concentrations. Validation was achieved by comparing the numerical results with experimental data obtained from a scale model silo using the tracer gas testing method for O2 and CO2 concentrations. Good agreement was found between the experimental and numerical results. The set of numerical simulations made it possible to establish a simple analytical model to predict the minimum time required to ventilate a silo to make it safe to enter. This ventilation time takes into account the headspace above the forage, the airflow rate, and the initial concentrations of O2 and CO2. The final analytical model was validated with available results from the literature.
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.
How young children spend their time: television and other activities.
Huston, A C; Wright, J C; Marquis, J; Green, S B
1999-07-01
Time-use diaries were collected over a 3-year period for 2 cohorts of 2- and 4-year-old children. TV viewing declined with age. Time spent in reading and educational activities increased with age on weekdays but declined on weekends. Time-use patterns were sex-stereotyped, and sex differences increased with age. As individuals' time in educational activities, social interaction, and video games increased, their time watching entertainment TV declined, but time spent playing covaried positively with entertainment TV. Educational TV viewing was not related to time spent in non-TV activities. Maternal education and home environment quality predicted frequent viewing of educational TV programs and infrequent viewing of entertainment TV. The results do not support a simple displacement hypothesis; the relations of TV viewing to other activities depend on the program content, the nature of the competing activity, and the environmental context.
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.
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.
Real-time DIRCM system modeling
NASA Astrophysics Data System (ADS)
Petersson, Mikael
2004-12-01
Directed infrared countermeasures (DIRCM) play an increasingly important role in electronic warfare to counteract threats posed by infrared seekers. The usefulness and performance of such countermeasures depend, for example, on atmospheric conditions (attenuation and turbulence) and platform vibrations, causing pointing and tracking errors for the laser beam and reducing the power transferred to the seeker aperture. These problems make it interesting to simulate the performance of a DIRCM system in order to understand how easy or difficult it is to counteract an approaching threat and evaluate limiting factors in various situations. This paper describes a DIRCM model that has been developed, including atmospheric effects such as attenuation and turbulence as well as closed loop tracking algorithms, where the retro reflex of the laser is used for the pointing control of the beam. The DIRCM model is part of a large simulation framework (EWSim), which also incorporates several descriptions of different seekers (e.g. reticle, rosette, centroid, nutating cross) and models of robot dynamics. Effects of a jamming laser on a specific threat can be readily verified by simulations within this framework. The duel between missile and countermeasure is simulated in near real-time and visualized graphically in 3D. A typical simulation with a reticle seeker jammed by a modulated laser is included in the paper.
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).
Mobile phone usage in complex urban systems: a space-time, aggregated human activity study
NASA Astrophysics Data System (ADS)
Tranos, Emmanouil; Nijkamp, Peter
2015-04-01
The present study aims to demonstrate the importance of digital data for investigating space-time dynamics of aggregated human activity in urban systems. Such dynamics can be monitored and modelled using data from mobile phone operators regarding mobile telephone usage. Using such an extensive dataset from the city of Amsterdam, this paper introduces space-time explanatory models of aggregated human activity patterns. Various modelling experiments and results are presented, which demonstrate that mobile telephone data are a good proxy of the space-time dynamics of aggregated human activity in the city.
Modeling neural activity with cumulative damage distributions.
Leiva, Víctor; Tejo, Mauricio; Guiraud, Pierre; Schmachtenberg, Oliver; Orio, Patricio; Marmolejo-Ramos, Fernando
2015-10-01
Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum-Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum-Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data.
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
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.
Wientzek, Angelika; Floegel, Anna; Knüppel, Sven; Vigl, Matthaeus; Drogan, Dagmar; Adamski, Jerzy; Pischon, Tobias; Boeing, Heiner
2014-04-01
The aim of our study was to investigate the relationship between objectively measured physical activity (PA) and cardiorespiratory fitness (CRF) and serum metabolites measured by targeted metabolomics in a population- based study. A total of 100 subjects provided 2 fasting blood samples and engaged in a CRF and PA measurement at 2 visits 4 months apart. CRF was estimated from a step test, whereas physical activity energy expenditure (PAEE), time spent sedentary and time spend in vigorous activity were measured by a combined heart rate and movement sensor for a total of 8 days. Serum metabolite concentrations were determined by flow injection analysis tandem mass spectrometry (FIA-MS/MS). Linear mixed models were applied with multivariable adjustment and p-values were corrected for multiple testing. Furthermore, we explored the associations between CRF, PA and two metabolite factors that have previously been linked to risk of Type 2 diabetes. CRF was associated with two phosphatidylcholine clusters independently of all other exposures. Lysophosphatidylcholine C14:0 and methionine were significantly negatively associated with PAEE and sedentary time. CRF was positively associated with the Type 2 diabetes protective factor. Vigorous activity was positively associated with the Type 2 diabetes risk factor in the mutually adjusted model. Our results suggest that CRF and PA are associated with serum metabolites, especially CRF with phosphatidylcholines and with the Type 2 diabetes protective factor. PAEE and sedentary time were associated with methionine. The identified metabolites could be potential mediators of the protective effects of CRF and PA on chronic disease risk.
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
Activated partial thromboplastin time of owl monkey (Aotus trivirgatus) plasma.
Mrema, J E; Johnson, G S; Kelley, S T; Green, T J
1984-06-01
Owl monkey plasma samples produced short, reproducible activated partial thromboplastin times, similar to those obtained with samples from many other mammalian species. This was an apparent contradiction to an earlier report of long irreproducible activated partial thromboplastin times from owl monkey samples. The discrepant data could not be explained by differences in anticoagulants (citrate or oxalate), assay reagents (partial thromboplastin with either diatomaceous earth or ellagic acid), or activation incubation times (2, 5, or 10 minutes); nor could they be explained by differences in the monkeys' sex, age or previous experimental exposure to Plasmodium falciparum malaria.
Associations between Screen Time and Physical Activity among Spanish Adolescents
Serrano-Sanchez, Jose A.; Martí-Trujillo, Sara; Lera-Navarro, Angela; Dorado-García, Cecilia; González-Henríquez, Juan J.; Sanchís-Moysi, Joaquín
2011-01-01
Background Excessive time in front of a single or several screens could explain a displacement of physical activity. The present study aimed at determining whether screen-time is associated with a reduced level of moderate to vigorous physical activity (MVPA) in Spanish adolescents living in favorable environmental conditions. Methodology/Principal Findings A multi-stage stratified random sampling method was used to select 3503 adolescents (12–18 years old) from the school population of Gran Canaria, Spain. MVPA, screen-time in front of television, computer, video game console and portable console was assessed in the classroom by fulfilling a standardized questionnaire. Bivariate and multivariate logistic regression analyses adjusted by a set of social-environmental variables were carried out. Forty-six percent of girls (95% CI±2.3%) and 26% of boys (95% CI±2.1%) did not meet the MVPA recommendations for adolescents. Major gender differences were observed in the time devoted to vigorous PA, video games and the total time spent on screen-based activities. Boys who reported 4 hours•week−1 or more to total screen-time showed a 64% (OR = 0.61, 95% CI, 0.44–0.86) increased risk of failing to achieve the recommended adolescent MVPA level. Participation in organized physical activities and sports competitions were more strongly associated with MVPA than screen-related behaviors. Conclusions/Significance No single screen-related behavior explained the reduction of MVPA in adolescents. However, the total time accumulated through several screen-related behaviors was negatively associated with MVPA level in boys. This association could be due to lower availability of time for exercise as the time devoted to sedentary screen-time activities increases. Participation in organized physical activities seems to counteract the negative impact of excessive time in front of screens on physical activity. PMID:21909435
Modeling Coastal Vulnerability through Space and Time.
Hopper, Thomas; Meixler, Marcia S
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
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
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…
Automated time activity classification based on global positioning system (GPS) tracking data
2011-01-01
Background Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. Methods We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Results Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute
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
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…
Modeling of an Active Tablet Coating Process.
Toschkoff, Gregor; Just, Sarah; Knop, Klaus; Kleinebudde, Peter; Funke, Adrian; Djuric, Dejan; Scharrer, Georg; Khinast, Johannes G
2015-12-01
Tablet coating is a common unit operation in the pharmaceutical industry, during which a coating layer is applied to tablet cores. The coating uniformity of tablets in a batch is especially critical for active coating, that is, coating that contains an active pharmaceutical ingredient. In recent years, discrete element method (DEM) simulations became increasingly common for investigating tablet coating. In this work, DEM was applied to model an active coating process as closely as possible, using measured model parameters and non-spherical particles. We studied how operational conditions (rotation speed, fill level, number of nozzles, and spray rate) influence the coating uniformity. To this end, simulation runs were planned and interpreted according to a statistical design of (simulation) experiments. Our general goal was to achieve a deeper understanding of the process in terms of residence times and dimensionless scaling laws. With that regard, the results were interpreted in light of analytical models. The results were presented at various detail levels, ranging from an overview of all variations to in-depth considerations. It was determined that the biggest uniformity improvement in a realistic setting was achieved by increasing the number of spray nozzles, followed by increasing the rotation speed and decreasing the fill level.
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…
Activated Dynamics in Dense Model Nanocomposites
NASA Astrophysics Data System (ADS)
Xie, Shijie; Schweizer, Kenneth
The nonlinear Langevin equation approach is applied to investigate the ensemble-averaged activated dynamics of small molecule liquids (or disconnected segments in a polymer melt) in dense nanocomposites under model isobaric conditions where the spherical nanoparticles are dynamically fixed. Fully thermalized and quenched-replica integral equation theory methods are employed to investigate the influence on matrix dynamics of the equilibrium and nonequilibrium nanocomposite structure, respectively. In equilibrium, the miscibility window can be narrow due to depletion and bridging attraction induced phase separation which limits the study of activated dynamics to regimes where the barriers are relatively low. In contrast, by using replica integral equation theory, macroscopic demixing is suppressed, and the addition of nanoparticles can induce much slower activated matrix dynamics which can be studied over a wide range of pure liquid alpha relaxation times, interfacial attraction strengths and ranges, particle sizes and loadings, and mixture microstructures. Numerical results for the mean activated relaxation time, transient localization length, matrix elasticity and kinetic vitrification in the nanocomposite will be presented.
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.
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…
Modelling travel and residence times in the eastern Irish Sea.
Dabrowski, T; Hartnett, M
2008-01-01
The Irish Sea, which lies between 51 degrees N-56 degrees N and 2 degrees 50'W-7 degrees W, provides a sheltered environment to exploit valuable fisheries resource. Anthropogenic activity is a real threat to its water quality. The majority of freshwater input down rivers flows into the eastern Irish Sea. The structure of the water circulation was not well understood during the planning of Sellafield nuclear plant outfall site in the eastern Irish Sea. A three-dimensional primitive equation numerical model was applied to the Irish Sea to simulate both barotropic and baroclinic circulation within the region. High accuracy was achieved with regard to the prediction of both tidal circulation and surface and nearbed water temperatures across the region. The model properly represented the Western Irish Sea Gyre, induced by thermal stratification and not known during planning Sellafield. Passive tracer simulations based on the developed hydrodynamic model were used to deliver residence times of the eastern Irish Sea region for various times of the year as well as travel times from the Sellafield outfall site to various locations within the Irish Sea. The results indicate a strong seasonal variability of travel times from Sellafield to the examined locations. Travel time to the Clyde Sea is the shortest for the autumnal tracer release (90 days); it takes almost a year for the tracer to arrive at the same location if it is released in January. Travel times from Sellafield to Dublin Bay fall within the range of 180-360 days. The average residence time of the entire eastern Irish Sea is around 7 months. The areas surrounding the Isle of Man are initially flushed due to a predominant northward flow; a backwater is formed in Liverpool Bay. Thus, elevated tracer concentrations are predicted in Liverpool Bay in the case of accidental spills at the Sellafield outfall site.
Time of relaxation in dusty plasma model
NASA Astrophysics Data System (ADS)
Timofeev, A. V.
2015-11-01
Dust particles in plasma may have different values of average kinetic energy for vertical and horizontal motion. The partial equilibrium of the subsystems and the relaxation processes leading to this asymmetry are under consideration. A method for the relaxation time estimation in nonideal dusty plasma is suggested. The characteristic relaxation times of vertical and horizontal motion of dust particles in gas discharge are estimated by analytical approach and by analysis of simulation results. These relaxation times for vertical and horizontal subsystems appear to be different. A single hierarchy of relaxation times is proposed.
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…
Hierarchical Bayes Models for Response Time Data
ERIC Educational Resources Information Center
Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha
2010-01-01
Human response time (RT) data are widely used in experimental psychology to evaluate theories of mental processing. Typically, the data constitute the times taken by a subject to react to a succession of stimuli under varying experimental conditions. Because of the sequential nature of the experiments there are trends (due to learning, fatigue,…
Linear Relations in Time Series Models. I.
ERIC Educational Resources Information Center
Villegas, C.
1976-01-01
A multiple time series is defined as the sum of an autoregressive process on a line and independent Gaussian white noise or a hyperplane that goes through the origin and intersects the line at a single point. This process is a multiple autoregressive time series in which the regression matrices satisfy suitable conditions. For a related article…
"A waste of time": Hispanic women's attitudes toward physical activity.
Im, Eun-Ok; Lee, Bokim; Hwang, Hyenam; Yoo, Kyung Hee; Chee, Wonshik; Stuifbergen, Alexa; Walker, Lorraine; Brown, Adama; McPeek, Chelsea; Miro, Michelle; Chee, Eunice
2010-09-01
Despite a lack of studies on Hispanic midlife women's physical activity, the existing studies have indicated that Hispanics' ethnic-specific attitudes toward physical activity contributed to their lack of physical activity. However, little is still clearly known about Hispanic midlife women's attitudes toward physical activity. The purpose of this study was to explore Hispanic midlife women's attitudes toward physical activity using a feminist perspective. The study was a 6-month qualitative online forum among 23 Hispanic women who were recruited through Internet communities/groups. The data were collected using 17 online forum topics on attitudes toward physical activity and ethnic-specific contexts. The data were analyzed using thematic analysis. Three major themes emerged from the data analysis process: (a) "family first, no time for myself," (b) "little exercise, but naturally healthy," and (c) "dad died of a heart attack." Although some of the women perceived the importance of physical activity due to their family history of chronic diseases, the study participants thought that physical activity would be a waste of time in their busy daily schedules. These findings provided directions for future health care practice and research to increase physical activity among Hispanic midlife women.
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…
Quantitative modeling of multiscale neural activity
NASA Astrophysics Data System (ADS)
Robinson, Peter A.; Rennie, Christopher J.
2007-01-01
The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.
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
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.
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.
Predictive active disturbance rejection control for processes with time delay.
Zheng, Qinling; Gao, Zhiqiang
2014-07-01
Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems.
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."
Web access to tidal models for TIMED
NASA Astrophysics Data System (ADS)
Zhang, X.; Forbes, J.; Miyahara, S.; Hagan, M.
As part of the interdisciplinary investigation "Tides, Planetary Waves, and Eddy Forcing of the Mean MLT Circulation", we provide web-based access to global monthly mean tidal fields from two models: the Kyushu University General Circulation Model, and the NCAR/HAO Global Scale Wave Model. Interactive solutions (Hough functions) to Laplace's Tidal Equation and various animations are also available. Herein, we briefly describe the models and illustrate the various tabular and plot options available. This web site also illustrates web data sharing protocols relevant to wider applications: (1) Balance of public access vs. rights of the investigators - Data sharing agreements, appropriate uses and attribution of the data; (2) Levels of accessibility - Agreement, simple form, application and request for password; (3) Methods of data distribution - Data tables, data files, archived data files, plots; (4) Database management - data dictionary, data recovery, resource lock, security.
Time-Variant Least Squares Harmonic Modeling
2003-01-01
SNR situations. We show applicability to high accuracy speech pitch and heart sound beat epoch estimation. 1. INTRODUCTION Harmonic modeling...techniques have been successfully used for low bit-rate speech coding; however their performance degrades at low SNR . The LSH model is capable of...producing more accurate and robust harmonic analysis, even at very low SNR ; however, as will be shown, its performance degrades significantly with rapid
Adaptive Modeling and Real-Time Simulation
1984-01-01
34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in
Jáuregui, Alejandra; Salvo, Deborah; Lamadrid-Figueroa, Héctor; Hernández, Bernardo; Rivera, Juan A; Pratt, Michael
2016-12-07
Environmental factors have been associated with specific physical activity domains, including leisure-time and transport physical activity, in some high income countries. Few studies have examined the environmental correlates for domain-specific physical activity in low-and middle-income countries, and results are inconsistent. We aimed to estimate the associations between perceived environment and self-reported leisure-time walking, moderate-to-vigorous leisure-time physical activity and transport physical activity among adults living in Cuernavaca, Mexico. A population-based study of adults 20 to 64years old was conducted in Cuernavaca, Mexico in 2011 (n=677). Leisure and transport physical activity was measured using the International Physical Activity Questionnaire - Long Form. Perceptions of neighborhood environment were obtained by questionnaire. Hurdle regression models estimated the association between environmental perceptions and participation and time spent in each physical activity domain. High perceived aesthetics were positively correlated with participation and time spent in leisure-time walking and moderate-to-vigorous physical activity. SES differences existed for aesthetics in relation to participation in leisure-time walking. Participation in transport physical activity was positively associated with easy access to large parks, while closer distance to large parks was a negative correlate for participation and time-spent in this physical activity domain. Results suggest that perceived environmental characteristics related with physical activity are domain specific. High perceived aesthetics were an important correlate for leisure-time activities among Mexican adults, suggesting that policy strategies aimed at improving this environmental perception may be warranted. Patterns of associations between environmental correlates and transport physical activity differed from those reported in commonly studied high income countries.
PATTERNS OF ACTIVITY IN A GLOBAL MODEL OF A SOLAR ACTIVE REGION
Bradshaw, S. J.; Viall, N. M. E-mail: Nicholeen.M.Viall@nasa.gov
2016-04-10
In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (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 footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating 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.
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.
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...
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.
Timing of Cortico-Muscle Transmission During Active Movement.
Van Acker, Gustaf M; Luchies, Carl W; Cheney, Paul D
2016-08-01
Numerous studies have reported large disparities between short cortico-muscle conduction latencies and long recorded delays between cortical firing and evoked muscle activity. Using methods such as spike- and stimulus-triggered averaging of electromyographic (EMG) activity, previous studies have shown that the time delay between corticomotoneuronal (CM) cell firing and onset of facilitation of forelimb muscle activity ranges from 6.7 to 9.8 ms, depending on the muscle group tested. In contrast, numerous studies have reported delays of 60-122 ms between cortical cell firing onset and either EMG or movement onset during motor tasks. To further investigate this disparity, we simulated rapid active movement by applying frequency-modulated stimulus trains to M1 cortical sites in a rhesus macaque performing a movement task. This yielded corresponding EMG modulations, the latency of which could be measured relative to the stimulus modulations. The overall mean delay from stimulus frequency modulation to EMG modulation was 11.5 ± 5.6 ms, matching closely the conduction time through the cortico-muscle pathway (12.6 ± 2.0 ms) derived from poststimulus facilitation peaks computed at the same sites. We conclude that, during active movement, the delay between modulated M1 cortical output and its impact on muscle activity approaches the physical cortico-muscle conduction time.
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
Time-dependent Flare Models with MALI
NASA Astrophysics Data System (ADS)
Kašparová, J.; Heinzel, P.; Varady, M.; Karlický, M.
2003-01-01
Temporal variations of Hα line profile intensities related to electron beams are presented. We show first results of time dependent simulations of a chromospheric response to a 1 sec monoenergetic electron beam. 1-D hydrodynamic code together with particle representation of the beam have been used to calculate atmospheric evolution. Time dependent radiative transfer problem has been solved for the resulting atmosphere in the MALI approach, using the Crank-Nicholson implicit scheme. Non-thermal collisional rates were included in linearised equations of statistical equilibrium.
Active controllers and the time duration to learn a task
NASA Technical Reports Server (NTRS)
Repperger, D. W.; Goodyear, C.
1986-01-01
An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.
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…
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.
Dynamic Models of Insurgent Activity
2014-05-19
for repeat activity in security applications. The research team has made great strides in applying such ideas to urban domestic crime applications...developed new basic research to extend many of these ideas beyond domestic crime applications to problems abroad involving insurgents and also to other...for repeat activity in security applications. The research team has made great strides in applying such ideas to urban domestic crime applications
Exploring the Dynamics of Personality Change with Time Series Models
NASA Astrophysics Data System (ADS)
Keller, Ferdinand; Storch, Maja; Bigler, Susanne
This paper aims to show possible refinements in time series methods for evaluating the dynamics of personality change. For the study. 13 students attended a course of personality development based on Jungian theory. The course teaches how to contact one's personal self. For four months the students rated their mood, activity, tension, and feeling of inner control on visual analogue scales twice a day. Standard examination with ARIMA models yield that most subjects show a low to moderate correlation to the previous timepoint. About one third of the cases have an additional lag2-relation. Daytime effects are seldom and the residual tests for the ARIMA models suggest that these linear models are sufficient in describing most of the time series. To evalute the expected smooth transformations in personality the data from one subject is analysed and the following hypotheses are empirically tested by the time-variation of parameters in subsequent time windows: 1) Increasing stability in mood and in the feeling of inner control by decreasing standard deviations 2) higher innerpsychic coherence by increasing autocorrelation coefficients 3) dissociation between mood and feeling of inner control by decreasing cross-correlation coefficients between these two dimensions. Application of several statistical tests shows that hypothesis 1 can be accepted while the other two hypotheses cannot be confirmed. Some methodological difficulties emerge when applied to `real' data and some limitations are found in the statistical testing of time-varying parameters. Overall, though, the proposed methods for examining emotional variability have proven valuable and promising for further research.
The Association between Leisure-Time Physical Activity and Risk of Undetected Prediabetes
Wang, Jia; Wu, Yili; Ning, Feng; Zhang, Chaoying
2017-01-01
Aims. The purpose of the study was to assess the effects of leisure-time physical activity on undetected prediabetes. Methods. Data from the National Health and Nutrition Examination Survey 2007–2012 were used in our analyses. Logistic regression was conducted to estimate the odds ratios (ORs) with 95% confidence intervals (CIs) of prediabetes associated with leisure-time physical activity. Results. A total of 8204 subjects were eligible for our analyses. For all subjects, high level of total leisure-time physical activity (OR = 0.78, 95% CI: 0.66, 0.94) and low level of vigorous leisure-time physical activity (OR = 0.72, 95% CI: 0.58, 0.90) were inversely associated with the risk of prediabetes in multivariate-adjusted model. For subjects under 45 years of age, high level of total leisure-time physical activity (OR = 0.78, 95% CI: 0.61, 0.99) and low (OR = 0.61, 95% CI: 0.45, 0.83) and high (OR = 0.72, 95% CI: 0.53, 1.00) level of vigorous leisure-time physical activity were associated with a decreased risk of prediabetes. In the 45 to 65 age group, only high level of total leisure-time physical activity (OR = 0.73, 95% CI: 0.57, 0.95) had protective effect on prediabetes. Conclusions. Leisure-time physical activity may be associated with a decreased risk of prediabetes. PMID:28367452
A Real-Time Assimilative Model for IRI
NASA Astrophysics Data System (ADS)
Reinisch, B. W.; Huang, X.; Galkin, I.; Bilitza, D.
2012-04-01
Ionospheric models are mostly unable to correctly predict the effects of space weather events and atmospheric disturbances on the ionosphere. This is especially true for the International Reference Ionosphere (IRI) which by design is a monthly median (climatological) model [Bilitza et al., 2011]. We propose a Real-Time Assimilative Model "RTAM" for IRI that is ingesting, initially, the available real-time Digisonde GIRO [Reinisch and Galkin, 2011] data streams: foF2/hmF2, MUF3000F2, foF1/hmF1, and foE/hmF2 [Galkin et al., 2011]. Deviations of these characteristics, especially foF2, from the monthly median values are the main cause for errors in the IRI model prediction. The assimilative modeling will provide a high-resolution, global picture of the ionospheric response to various short-term events observed during periods of storm activity or the impact of gravity waves coupling the ionosphere to the lower atmosphere, including timelines of the vertical restructuring of the plasma distribution. GIRO currently provides reliable real-time data from 42 stations at a cadence of 15 min or 5 min. The number of stations is rapidly growing and is likely to soon be complemented by satellite borne topside sounders. IRI uses the characteristics predictions based on CCIR/URSI maps of coefficients. The diurnal variation of the foF2 characteristic, for example, is presented by the Fourier series Σ6 foF 2(T, φ,λ,χ) = a0(φ,λ,χ)+ (an(φ,λ,χ)cosnT + bn(φ,λ,χ)sin nT), n=1 where T is Universal Time in hours, and φ, λ, χ are the geographic latitude, longitude, and modified dip latitude, respectively. The coefficients an are in turn expanded as functions φ, λ, χ resulting in a set of 24 global maps of 988 coefficients each, one for each month of the year and for two levels of solar activity, R12=10 and 100, where R12 is the 12-month running-mean of the monthly sunspot number Rm (2*12*988 = 23,712 coefficients in all) [ITU-R, 2011]. For a given point in time, 988
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…
23 CFR 771.113 - Timing of Administration activities.
Code of Federal Regulations, 2010 CFR
2010-04-01
... related environmental laws and regulations to the maximum extent possible during the NEPA process. This work includes environmental studies, related engineering studies, agency coordination and public... ENVIRONMENTAL IMPACT AND RELATED PROCEDURES § 771.113 Timing of Administration activities. (a) The lead...
23 CFR 771.113 - Timing of Administration activities.
Code of Federal Regulations, 2012 CFR
2012-04-01
... related environmental laws and regulations to the maximum extent possible during the NEPA process. This work includes environmental studies, related engineering studies, agency coordination and public... ENVIRONMENTAL IMPACT AND RELATED PROCEDURES § 771.113 Timing of Administration activities. (a) The lead...
23 CFR 771.113 - Timing of Administration activities.
Code of Federal Regulations, 2011 CFR
2011-04-01
... related environmental laws and regulations to the maximum extent possible during the NEPA process. This work includes environmental studies, related engineering studies, agency coordination and public... ENVIRONMENTAL IMPACT AND RELATED PROCEDURES § 771.113 Timing of Administration activities. (a) The lead...
23 CFR 771.113 - Timing of Administration activities.
Code of Federal Regulations, 2014 CFR
2014-04-01
... related environmental laws and regulations to the maximum extent possible during the NEPA process. This work includes environmental studies, related engineering studies, agency coordination and public... ENVIRONMENTAL IMPACT AND RELATED PROCEDURES § 771.113 Timing of Administration activities. (a) The lead...
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.
Modelling road accidents: An approach using structural time series
NASA Astrophysics Data System (ADS)
Junus, Noor Wahida Md; Ismail, Mohd Tahir
2014-09-01
In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.
Modeling biological activities of nanoparticles.
Epa, V Chandana; Burden, Frank R; Tassa, Carlos; Weissleder, Ralph; Shaw, Stanley; Winkler, David A
2012-11-14
Products are increasingly incorporating nanomaterials, but we have a poor understanding of their adverse effects. To assess risk, regulatory authorities need more experimental testing of nanoparticles. Computational models play a complementary role in allowing rapid prediction of potential toxicities of new and modified nanomaterials. We generated quantitative, predictive models of cellular uptake and apoptosis induced by nanoparticles for several cell types. We illustrate the potential of computational methods to make a contribution to nanosafety.
Schneider, Cyril; Lavoie, Brigitte A; Barbeau, Hugues; Capaday, Charles
2004-12-01
Seated subjects were instructed to react to an auditory cue by simultaneously contracting the tibialis anterior (TA) muscle of each ankle isometrically. Focal transcranial magnetic stimulation of the leg area of the motor cortex (MCx) was used to determine the time course of changes in motor-evoked potential amplitude (MEP) during the reaction time (RT). In one condition the voluntary contraction was superimposed on tonic EMG activity maintained at 10% of maximal voluntary contraction. In the other condition the voluntary contraction was made starting from rest. MEPs in the TA contralateral to the stimulation coil were evoked at various times during the RT in each condition. These were compared to the control MEPs evoked during tonic voluntary activity or with the subject at rest. The RT was measured trial by trial from the EMG activity of the TA ipsilateral to the magnetic stimulus, taking into account the nearly constant time difference between the two sides. The MEPs became far greater than control MEPs during the RT (mean = 332%, SD = 44 %, of control MEPs, P < 0.001) without any measurable change in the background level of EMG activity. The onset of this facilitation occurred on average 12.80 ms (SD = 7.55 ms) before the RT. There was no difference in the onset of facilitation between the two conditions. Because MEPs were facilitated without a change in the background EMG activity, it is concluded that this facilitation is specifically due to an increase of MCx excitability just before voluntary muscle activation. This conclusion is further reinforced by the observation that MEPs evoked by near-threshold anodal stimuli to the MCx were not facilitated during the RT, in contrast to those evoked by near-threshold transcranial magnetic stimulation. However, several observations in the present and previous studies indicate that MEP amplitude may be more sensitive to alpha-motoneuron activity than to motor cortical neuron activity, an idea that has important
Kaolin-correctable prolongation of the activated partial thromboplastin time.
Briselli, M F; Ellman, L
1980-11-01
Seven patients who had normal prothrombin times but prolonged activated partial thromboplastin times (aPTT) are described. The prolonged aPTT, obtained with micronized silica as the contact activating agent in a semi-automated optical end-point system, a nonautomated optical end-point system, and a conductivity end-point system, corrected to normal when kaolin was used as the contact activating agent. Abnormal results were also obtained with celite and ellagic acid as contact activating agents. The activities of various clotting factors were within normal limits in all cases where they were assayed. The thromboplastin dilution test was uniformly negative, and mixtures of one patient's plasma with that of another patient failed to correct the abnormal aPTT. No patients had a personal or family history of bleeding, and all underwent surgery without bleeding difficulties. This pattern of a prolonged aPTT that corrects to normal when kaolin is used as the contact activator appears to represent a previously unrecognized laboratory phenomenon.
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…
CRAFFT: An Activity Prediction Model based on Bayesian Networks.
Nazerfard, Ehsan; Cook, Diane J
2015-04-01
Recent advances in the areas of pervasive computing, data mining, and machine learning offer unique opportunities to provide health monitoring and assistance for individuals facing difficulties to live independently in their homes. Several components have to work together to provide health monitoring for smart home residents including, but not limited to, activity recognition, activity discovery, activity prediction, and prompting system. Compared to the significant research done to discover and recognize activities, less attention has been given to predict the future activities that the resident is likely to perform. Activity prediction components can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-aware rules to prompt individuals to initiate important activities. In this paper, we propose an activity prediction model using Bayesian networks together with a novel two-step inference process to predict both the next activity features and the next activity label. We also propose an approach to predict the start time of the next activity which is based on modeling the relative start time of the predicted activity using the continuous normal distribution and outlier detection. To validate our proposed models, we used real data collected from physical smart environments.
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.
Gender differences in social support and leisure-time physical activity
Oliveira, Aldair J; Lopes, Claudia S; Rostila, Mikael; Werneck, Guilherme Loureiro; Griep, Rosane Härter; de Leon, Antônio Carlos Monteiro Ponce; Faerstein, Eduardo
2014-01-01
OBJECTIVE To identify gender differences in social support dimensions’ effect on adults’ leisure-time physical activity maintenance, type, and time. METHODS Longitudinal study of 1,278 non-faculty public employees at a university in Rio de Janeiro, RJ, Southeastern Brazil. Physical activity was evaluated using a dichotomous question with a two-week reference period, and further questions concerning leisure-time physical activity type (individual or group) and time spent on the activity. Social support was measured with the Medical Outcomes Study Social Support Scale. For the analysis, logistic regression models were adjusted separately by gender. RESULTS A multinomial logistic regression showed an association between material support and individual activities among women (OR = 2.76; 95%CI 1.2;6.5). Affective support was associated with time spent on leisure-time physical activity only among men (OR = 1.80; 95%CI 1.1;3.2). CONCLUSIONS All dimensions of social support that were examined influenced either the type of, or the time spent on, leisure-time physical activity. In some social support dimensions, the associations detected varied by gender. Future studies should attempt to elucidate the mechanisms involved in these gender differences. PMID:25210819
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.
Modelling Typical Online Language Learning Activity
ERIC Educational Resources Information Center
Montoro, Carlos; Hampel, Regine; Stickler, Ursula
2014-01-01
This article presents the methods and results of a four-year-long research project focusing on the language learning activity of individual learners using online tasks conducted at the University of Guanajuato (Mexico) in 2009-2013. An activity-theoretical model (Blin, 2010; Engeström, 1987) of the typical language learning activity was used to…
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…
Associative memory model with spontaneous neural activity
NASA Astrophysics Data System (ADS)
Kurikawa, Tomoki; Kaneko, Kunihiko
2012-05-01
We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.
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.
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
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.
Market volatility modeling for short time window
NASA Astrophysics Data System (ADS)
de Mattos Neto, Paulo S. G.; Silva, David A.; Ferreira, Tiago A. E.; Cavalcanti, George D. C.
2011-10-01
The gain or loss of an investment can be defined by the movement of the market. This movement can be estimated by the difference between the magnitudes of two stock prices in distinct periods and this difference can be used to calculate the volatility of the markets. The volatility characterizes the sensitivity of a market change in the world economy. Traditionally, the probability density function (pdf) of the movement of the markets is analyzed by using power laws. The contributions of this work is two-fold: (i) an analysis of the volatility dynamic of the world market indexes is performed by using a two-year window time data. In this case, the experiments show that the pdf of the volatility is better fitted by exponential function than power laws, in all range of pdf; (ii) after that, we investigate a relationship between the volatility of the markets and the coefficient of the exponential function based on the Maxwell-Boltzmann ideal gas theory. The results show an inverse relationship between the volatility and the coefficient of the exponential function. This information can be used, for example, to predict the future behavior of the markets or to cluster the markets in order to analyze economic patterns.
Continuous-time model of structural balance.
Marvel, Seth A; Kleinberg, Jon; Kleinberg, Robert D; Strogatz, Steven H
2011-02-01
It is not uncommon for certain social networks to divide into two opposing camps in response to stress. This happens, for example, in networks of political parties during winner-takes-all elections, in networks of companies competing to establish technical standards, and in networks of nations faced with mounting threats of war. A simple model for these two-sided separations is the dynamical system dX/dt = X(2), where X is a matrix of the friendliness or unfriendliness between pairs of nodes in the network. Previous simulations suggested that only two types of behavior were possible for this system: Either all relationships become friendly or two hostile factions emerge. Here we prove that for generic initial conditions, these are indeed the only possible outcomes. Our analysis yields a closed-form expression for faction membership as a function of the initial conditions and implies that the initial amount of friendliness in large social networks (started from random initial conditions) determines whether they will end up in intractable conflict or global harmony.
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.
Monitoring Heparin Therapy with the Activated Partial Thromboplastin Time
Stuart, R. K.; Michel, A.
1971-01-01
Difficulties associated with the whole blood clotting time (W.B.C.T.) as a method of monitoring heparin therapy have led to the investigation of the activated partial thromboplastin time (A.P.T.T.) as an alternative. The conclusion is reached that the latter procedure possesses several advantages. Using the method described and a citrate-preserved blood sample collected just prior to the administration of the next serial dose of heparin, the suggested therapeutic duration of the A.P.T.T. is 70 seconds or twice the mean control value. A practical range for this method is 60 to 70 seconds. PMID:5557913
Older Adults, Chronic Disease and Leisure-time Physical Activity
Ashe, Maureen C.; Miller, William C.; Eng, Janice J.; Noreau, Luc
2011-01-01
Background Participating in regular physical activity is an important part of healthy aging. There is an increased risk for inactivity associated with aging and the risk becomes greater for adults who have a chronic disease. However, there is limited information on current physical activity levels for older adults and even less for those with chronic diseases. Objective Our primary objective was to determine the proportion of older adults who achieved a recommended amount of weekly physical activity (≥1000 kcal/week). The secondary objectives were to identify variables associated with meeting guideline leisure-time physical activity (LTPA), and to describe the type of physical activities that respondents reported across different chronic diseases. Methods In this study we used the Canadian Community Health Survey Cycle 1.1 (2000/2001) to report LTPA for adults aged 65 years and older. This was a population-based self-report telephone survey. We used univariate logistic regression to provide odds ratios to determine differences in activity and the likelihood of meeting guideline recommendations. Results For adults over 65 years of age with no chronic diseases, 30% reported meeting guideline LTPA, while only 23% met the recommendations if they had one or more chronic diseases. Factors associated with achieving the guideline amount of physical activity included a higher level of education, higher income and moderate alcohol consumption. Likelihood for not achieving the recommended level of LTPA included low BMI, pain and the presence of mobility and dexterity problems. Walking, gardening and home exercises were the three most frequent types of reported physical activities. Conclusion This study provides the most recent evidence to suggest that older Canadians are not active enough and this is accentuated if a chronic disease is present. It is important to develop community-based programs to facilitate LTPA, in particular for older people with a chronic disease. PMID
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.
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
Just-in-time automated counseling for physical activity promotion.
Bickmore, Timothy; Gruber, Amanda; Intille, Stephen
2008-11-06
Preliminary results from a field study into the efficacy of automated health behavior counseling delivered at the moment of user decision-making compared to the same counseling delivered at the end of the day are reported. The study uses an animated PDA-based advisor with an integrated accelerometer that can engage users in dialogues about their physical activity throughout the day. Preliminary results indicate health counseling is more effective when delivered just-in-time than when delivered retrospectively.
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
Revisiting the Time Trade-Off Hypothesis: Work, Organized Activities, and Academics During College.
Greene, Kaylin M; Maggs, Jennifer L
2015-08-01
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, M age = 18.4) that was followed for 14 days within each of seven 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).
Emerging Models for the Molecular Basis of Mammalian Circadian Timing
2015-01-01
Mammalian circadian timekeeping arises from a transcription-based feedback loop driven by a set of dedicated clock proteins. At its core, the heterodimeric transcription factor CLOCK:BMAL1 activates expression of Period, Cryptochrome, and Rev-Erb genes, which feed back to repress transcription and create oscillations in gene expression that confer circadian timing cues to cellular processes. The formation of different clock protein complexes throughout this transcriptional cycle helps to establish the intrinsic ∼24 h periodicity of the clock; however, current models of circadian timekeeping lack the explanatory power to fully describe this process. Recent studies confirm the presence of at least three distinct regulatory complexes: a transcriptionally active state comprising the CLOCK:BMAL1 heterodimer with its coactivator CBP/p300, an early repressive state containing PER:CRY complexes, and a late repressive state marked by a poised but inactive, DNA-bound CLOCK:BMAL1:CRY1 complex. In this review, we analyze high-resolution structures of core circadian transcriptional regulators and integrate biochemical data to suggest how remodeling of clock protein complexes may be achieved throughout the 24 h cycle. Defining these detailed mechanisms will provide a foundation for understanding the molecular basis of circadian timing and help to establish new platforms for the discovery of therapeutics to manipulate the clock. PMID:25303119
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.
Can we understand time scales of solar activity?
NASA Astrophysics Data System (ADS)
Kremliovsky, M. N.
1994-05-01
The dynamo theory of the solar cycle faces numerous difficulties in regard to an explanation of the observed behavior of sunspot activity. In particular, there is an essential irregularity in the sequence of 11(22)-year cycles. In this paper we want to show how the complicated long-term evolution of solar activity can be understood within the framework of a simple model demonstrating low-dimensional chaotic behavior. According to this description we are able to give a definition for the periods of low activity (Global Minima), to describe how the transition to (from) a Global Minimum occurs and to show the role of the 11(22)-year cycle and its phase catastrophe. The explanations of the origin of the Gleissberg cycle and thousand-year variations of solar activity are given. In summary, the independence of the proposed scenario from the particular choice of model is shown. Thus one can formulate dynamics in the language of generalized instabilities which can aid the search for the underlying physical processes.
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
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.
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
Rethinking food anticipatory activity in the activity-based anorexia rat model.
Wu, Hemmings; van Kuyck, Kris; Tambuyzer, Tim; Luyten, Laura; Aerts, Jean-Marie; Nuttin, Bart
2014-01-29
When a rat is on a limited fixed-time food schedule with full access to a running wheel (activity-based anorexia model, ABA), its activity level will increase hours prior to the feeding period. This activity, called food-anticipatory activity (FAA), is a hypothesized parallel to the hyperactivity symptom in human anorexia nervosa. To investigate in depth the characteristics of FAA, we retrospectively analyzed the level of FAA and activities during other periods in ABA rats. To our surprise, rats with the most body weight loss have the lowest level of FAA, which contradicts the previously established link between FAA and the severity of ABA symptoms. On the contrary, our study shows that postprandial activities are more directly related to weight loss. We conclude that FAA alone may not be sufficient to reflect model severity, and activities during other periods may be of potential value in studies using ABA model.
Timing of mitogen-activated protein kinase (MAPK) activation in the rat pineal gland.
Ho, A K; Price, D M; Terriff, D; Chik, C L
2006-06-27
Activation of members of the mitogen-activated protein kinase (MAPK) family of signaling cascades is a tightly controlled event in rat pinealocytes. Cell culture studies indicate that whereas the NE-->cGMP activation of p42/44MAPK is rapid and transient, the NE-->cAMP activation of p38MAPK is slower and more sustained. The decline in the p42/44MAPK response is in part due to the induction of MAPK phosphatase-1 by NE. In comparison, p38MAPK activation is tightly coupled to the synthesis and degradation of an upstream element in its activation cascade. Whole animal studies confirm activation of p42/44MAPK occurring during the early part of night and precedes p38MAPK activation. Studies with selective MAPK inhibitors reveal a modulating effect of MAPKs on arylalkylamine-N-acetyltransferse (AA-NAT) activity, with involvement of p42/44MAPK in the induction of AA-NAT and p38MAPK participating in the amplitude and duration of the AA-NAT response. These effects of p42/44MAPK and p38MAPK on AA-NAT activity match their timing of activation. Taken together, our studies on the timing of MAPK activation and regulation of AA-NAT by MAPKs add to the importance of MAPKs in regulating the circadian biology of the pineal gland.
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.
Wanted: Active Role Models for Today's Kids | NIH MedlinePlus the Magazine
... this page please turn Javascript on. Feature: Reducing Childhood Obesity Wanted: Active Role Models for Today's Kids Past ... the active role models they can get. "With childhood obesity at an all-time high, we need to ...
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.
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
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
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.
Reducing Outpatient Waiting Time: A Simulation Modeling Approach
Aeenparast, Afsoon; Tabibi, Seyed Jamaleddin; Shahanaghi, Kamran; Aryanejhad, Mir Bahador
2013-01-01
Objectives The objective of this study was to provide a model for reducing outpatient waiting time by using simulation. Materials and Methods A simulation model was constructed by using the data of arrival time, service time and flow of 357 patients referred to orthopedic clinic of a general teaching hospital in Tehran. The simulation model was validated before constructing different scenarios. Results In this study 10 scenarios were presented for reducing outpatient waiting time. Patients waiting time was divided into three levels regarding their physicians. These waiting times for all scenarios were computed by simulation model. According to the final scores the 9th scenario was selected as the best way for reducing outpatient's waiting time. Conclusions Using the simulation as a decision making tool helps us to decide how we can reduce outpatient's waiting time. Comparison of outputs of this scenario and the based- case scenario in simulation model shows that combining physician's work time changing with patient's admission time changing (scenario 9) would reduce patient waiting time about 73.09%. Due to dynamic and complex nature of healthcare systems, the application of simulation for the planning, modeling and analysis of these systems has lagged behind traditional manufacturing practices. Rapid growth in health care system expenditures, technology and competition has increased the complexity of health care systems. Simulation is a useful tool for decision making in complex and probable systems. PMID:24616801
Discrete-time dynamic user-optimal departure time/route choice model
Chen, H.K.; Hsueh, C.F.
1998-05-01
This paper concerns a discrete-time, link-based, dynamic user-optimal departure time/route choice model using the variational inequality approach. The model complies with a dynamic user-optimal equilibrium condition in which for each origin-destination pair, the actual route travel times experienced by travelers, regardless the departure time, is equal and minimal. A nested diagonalization procedure is proposed to solve the model. Numerical examples are then provided for demonstration and detailed elaboration for multiple solutions and Braess`s paradox.
NASA Astrophysics Data System (ADS)
Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken
2015-04-01
We investigate the operational utility of fine time step hydro-climatic information using a large catchment data set. The originality of this data set lies in the availability of precipitation data from the 6-minute rain gauges of Météo-France, and in the size of the catchment set (217 French catchments in total). The rainfall-runoff model used (GR4) has been adapted to hourly and sub-hourly time steps (up to 6-minute) from the daily time step version (Perrin et al., 2003). The model is applied at different time steps ranging from 6-minute to 1 day (6-, 12-, 30-minute, 1-, 3-, 6-, 12-hour and 1 day) and the evolution of model performance for each catchment is evaluated at the daily time step by aggregation of model outputs. Three classes of behavior are found according to the trend of model performance as the time step becomes finer: (i) catchments presenting an improvement of model performance; (ii) catchments with a model performance insensitive to the time step; (iii) catchments for which the performance even deteriorates as the time step becomes finer. The reasons behind these different trends are investigated from a hydrological point of view, by relating the model sensitivity to data at finer time step to catchment descriptors. References: Perrin, C., C. Michel and V. Andréassian (2003), "Improvement of a parsimonious model for streamflow simulation", Journal of Hydrology, 279(1-4): 275-289.
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.
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.
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.
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
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).
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…
Detailed Analysis of the Interoccurrence Time Statistics in Seismic Activity
NASA Astrophysics Data System (ADS)
Tanaka, Hiroki; Aizawa, Yoji
2017-02-01
The interoccurrence time statistics of seismiciry is studied theoretically as well as numerically by taking into account the conditional probability and the correlations among many earthquakes in different magnitude levels. It is known so far that the interoccurrence time statistics is well approximated by the Weibull distribution, but the more detailed information about the interoccurrence times can be obtained from the analysis of the conditional probability. Firstly, we propose the Embedding Equation Theory (EET), where the conditional probability is described by two kinds of correlation coefficients; one is the magnitude correlation and the other is the inter-event time correlation. Furthermore, the scaling law of each correlation coefficient is clearly determined from the numerical data-analysis carrying out with the Preliminary Determination of Epicenter (PDE) Catalog and the Japan Meteorological Agency (JMA) Catalog. Secondly, the EET is examined to derive the magnitude dependence of the interoccurrence time statistics and the multi-fractal relation is successfully formulated. Theoretically we cannot prove the universality of the multi-fractal relation in seismic activity; nevertheless, the theoretical results well reproduce all numerical data in our analysis, where several common features or the invariant aspects are clearly observed. Especially in the case of stationary ensembles the multi-fractal relation seems to obey an invariant curve, furthermore in the case of non-stationary (moving time) ensembles for the aftershock regime the multi-fractal relation seems to satisfy a certain invariant curve at any moving times. It is emphasized that the multi-fractal relation plays an important role to unify the statistical laws of seismicity: actually the Gutenberg-Richter law and the Weibull distribution are unified in the multi-fractal relation, and some universality conjectures regarding the seismicity are briefly discussed.
A directed continuous time random walk model with jump length depending on waiting time.
Shi, Long; Yu, Zuguo; Mao, Zhi; Xiao, Aiguo
2014-01-01
In continuum one-dimensional space, a coupled directed continuous time random walk model is proposed, where the random walker jumps toward one direction and the waiting time between jumps affects the subsequent jump. In the proposed model, the Laplace-Laplace transform of the probability density function P(x, t) of finding the walker at position x at time t is completely determined by the Laplace transform of the probability density function φ(t) of the waiting time. In terms of the probability density function of the waiting time in the Laplace domain, the limit distribution of the random process and the corresponding evolving equations are derived.
Modeling Sexual Activity among Schoolgirls in Zambia.
ERIC Educational Resources Information Center
Pillai, Vijayan K.; Gupta, Rashmi
2000-01-01
Proposes a model of sexual activity among secondary school-going Zambian girls. Identifies the role of dating as an intervening variable in explaining the variation in sexual activity among teenagers. Schools are an important setting for the young to meet and initiate sexual relationships. Theoretical and policy implications are discussed.…
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…
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
Trend time-series modeling and forecasting with neural networks.
Qi, Min; Zhang, G Peter
2008-05-01
Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.
Space-time formulation for finite element modeling of superconductors
Ashworth, Stephen P; Grilli, Francesco; Sirois, Frederic; Laforest, Marc
2008-01-01
In this paper we present a new model for computing the current density and field distributions in superconductors by means of a periodic space-time formulation for finite elements (FE). By considering a space dimension as time, we can use a static model to solve a time dependent problem. This allows overcoming one of the major problems of FE modeling of superconductors: the length of simulations, even for relatively simple cases. We present our first results and compare them to those obtained with a 'standard' time-dependent method and with analytical solutions.
Studies in astronomical time series analysis. I - Modeling random processes in the time domain
NASA Technical Reports Server (NTRS)
Scargle, J. D.
1981-01-01
Several random process models in the time domain are defined and discussed. Attention is given to the moving average model, the autoregressive model, and relationships between and combinations of these models. Consideration is then given to methods for investigating pulse structure, procedures of model construction, computational methods, and numerical experiments. A FORTRAN algorithm of time series analysis has been developed which is relatively stable numerically. Results of test cases are given to study the effect of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the light curve of the quasar 3C 272 is considered as an example.
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.
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.
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.
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
A Time-Frequency Functional Model for Locally Stationary Time Series Data
Qin, Li; Guo, Wensheng; Litt, Brian
2009-01-01
Unlike traditional time series analysis that focuses on one long time series, in many biomedical experiments, it is common to collect multiple time series and focus on how the design covariates impact the patterns of stochastic variation over time. In this article, we propose a time-frequency functional model for a family of time series indexed by a set of covariates. This model can be used to compare groups of time series in terms of the patterns of stochastic variation and to estimate the covariate effects. We focus our development on locally stationary time series and propose the covariate-indexed locally stationary setting, which include stationary processes as special cases. We use smoothing spline ANOVA models for the time-frequency coefficients. A two-stage procedure is introduced for estimation. To reduce the computational demand, we develop an equivalent state space model to the proposed model with an efficient algorithm. We also propose a new simulation method to generate replicated time series from their design spectra. An epileptic intracranial electroencephalogram (IEEG) dataset is analyzed for illustration. PMID:20228961
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…
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…
Stochastic variance models in discrete time with feedforward neural networks.
Andoh, Charles
2009-07-01
The study overcomes the estimation difficulty in stochastic variance models for discrete financial time series with feedforward neural networks. The volatility function is estimated semiparametrically. The model is used to estimate market risk, taking into account not only the time series of interest but extra information on the market. As an application, some stock prices series are studied and compared with the nonlinear ARX-ARCHX model.
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.
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.
Nonlinear Maps for Design of Discrete Time Models of Neuronal Network Dynamics
2016-02-29
network activity. D· 1S. SUBJECT TERMS Map-based neuronal model , Discrete time spiking dynamics, Synapses, Neurons, Neurobiological Networks 16...N00014-16-1-2252 Report #1 Performance/Technical Monthly Report Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics...research of network dynamics utilizing the conductance-based models will be done in collaboration Dr. M. Bazhenov who will support the remaining 50% of
Choline chloride activates time-dependent and time-independent K+ currents in dog atrial myocytes.
Fermini, B; Nattel, S
1994-01-01
Using the whole cell configuration of the patch-clamp technique, we studied the effect of isotonic replacement of bath sodium chloride (NaCl) by choline chloride (ChCl) in dog atrial myocytes. Our results show that ChCl triggered 1) activation of a time-independent background current, characterized by a shift of the holding current in the outward direction at potentials positive to the K+ equilibrium potential (EK), and 2) activation of a time- and voltage-dependent outward current, following depolarizing voltage steps positive to EK. Because the choline-induced current obtained by depolarizing steps exhibited properties similar to the delayed rectifier K+ current (IK), we named it IKCh. The amplitude of IKCh was determined by extracellular ChCl concentration, and this current was generally undetectable in the absence of ChCl. IKCh was not activated by acetylcholine (0.001-1.0 mM) or carbachol (10 microM) and could not be recorded in the absence of ChCl or when external NaCl was replaced by sucrose or tetramethylammonium chloride. IKCh was inhibited by atropine (0.01-1.0 microM) but not by the M1 antagonist pirenzepine (up to 10 microM). This current was carried mainly by K+ and was inhibited by CsCl (120 mM, in the pipette) or barium (1 mM, in the bath). We conclude that in dog atrial myocytes, ChCl activates a background conductance comparable to ACh-dependent K+ current, together with a time-dependent K+ current showing properties similar to IK.
A multivariate heuristic model for fuzzy time-series forecasting.
Huarng, Kun-Huang; Yu, Tiffany Hui-Kuang; Hsu, Yu Wei
2007-08-01
Fuzzy time-series models have been widely applied due to their ability to handle nonlinear data directly and because no rigid assumptions for the data are needed. In addition, many such models have been shown to provide better forecasting results than their conventional counterparts. However, since most of these models require complicated matrix computations, this paper proposes the adoption of a multivariate heuristic function that can be integrated with univariate fuzzy time-series models into multivariate models. Such a multivariate heuristic function can easily be extended and integrated with various univariate models. Furthermore, the integrated model can handle multiple variables to improve forecasting results and, at the same time, avoid complicated computations due to the inclusion of multiple variables.
An Error Score Model for Time-Limit Tests
ERIC Educational Resources Information Center
Ven, A. H. G. S. van der
1976-01-01
A more generalized error model for time-limit tests is developed. Model estimates are derived for right-attempted and wrong-attempted correlations both within the same test and between different tests. A comparison is made between observed correlations and their model counterparts and a fair agreement is found between observed and expected…
Time-varying boundaries for diffusion models of decision making and response time
Zhang, Shunan; Lee, Michael D.; Vandekerckhove, Joachim; Maris, Gunter; Wagenmakers, Eric-Jan
2014-01-01
Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-varying boundaries. We then develop a computational method for finding time-varying boundaries from empirical data, and apply our new method to two problems. The first problem involves finding the time-varying boundaries that make diffusion models equivalent to the alternative sequential sampling class of accumulator models. The second problem involves finding the time-varying boundaries, at the individual level, that best fit empirical data for perceptual stimuli that provide equal evidence for both decision alternatives. We discuss the theoretical and modeling implications of using time-varying boundaries in diffusion models, as well as the limitations and potential of our approach to their inference. PMID:25538642
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.
2014-01-01
The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351
Hu, Wenfa; He, Xinhua
2014-01-01
The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.
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.
Multi-Wavelength Time Variability of Active Galactic Nuclei
NASA Astrophysics Data System (ADS)
Chatterjee, Ritaban
2009-01-01
Due to their large distances, AGNs are not spatially resolved with current and near-future technologies except by radio interferometry. However, we can use time variability, one of the defining properties of AGNs, to probe the location and physical processes related to the emission at resolutions even finer than provided by VLBI. I use extensive multi-frequency monitoring data of the blazars 3C 279 and PKS 1510-089 (over 10 years long) and the radio galaxy 3C 120 ( 5 years), including well-sampled light curves (radiative flux vs. time) at X-ray energies (2-10 keV), optical wavelengths (R band), and radio frequencies (14.5 GHz and 37 GHz), as well as monthly images obtained with the Very Long Baseline Array (VLBA) at 43 GHz that follow changes in the emission structure of the jet on parsec scales. I have developed and applied a set of statistical tools to characterize the time variability of AGNs. This includes the power spectral density (PSD) and its uncertainties, discrete cross-correlation functions and their significance using random light curves simulated from the previously calculated PSDs, and decomposition of light curves into individual flares. I also model the time variable emission spectrum of an AGN jet using a numerical code that includes conical geometry, turbulent magnetic field and density, and energization of electrons due to a moving shock front. Comparing the results of the model calculations and the application of the above-mentioned statistical procedures on the real data, I draw conclusions about the location of the emission regions of these objects. I also identify the ongoing emission mechanisms and implications regarding the physics of jets. This work is supported by NASA through grants NNX08AJ64G (ADP) and NNX08AV65G (Fermi).
Models of neural networks with fuzzy activation functions
NASA Astrophysics Data System (ADS)
Nguyen, A. T.; Korikov, A. M.
2017-02-01
This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.
Development of a real time activity monitoring Android application utilizing SmartStep.
Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward
2016-08-01
Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.
Path Flow Estimation Using Time Varying Coefficient State Space Model
NASA Astrophysics Data System (ADS)
Jou, Yow-Jen; Lan, Chien-Lun
2009-08-01
The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.
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
Modeling and Real-Time Simulation of UPFC
NASA Astrophysics Data System (ADS)
Kimura, Misao; Takahashi, Choei; Kishibe, Hideto; Miyazaki, Yasuyuki; Noro, Yasuhiro; Iio, Naotaka
We have developed a digital real time simulator of Power Electronics Controllers, so called FACTS (Flexible AC Transmission Systems) Controllers and/or Custom Power by using MATLABTM/SIMULINKTM and dSPACETM System. This paper describes the modeling and the calculation accuracy of a UPFC (Unified Power Flow Controller) model. Hence the developed simulator operates at a large time step, in order to improve simulation accuracy, a correction processing of the switching delay is implemented into the UPFC model. Calculation accuracy of the real time UPFC model is the same level as EMTDCTM results. We confirm stable operation of the developed UPFC model with connecting a commercial real time digital simulator (RTDSTM).
Time-dependent Hartree approximation and time-dependent harmonic oscillator model
NASA Astrophysics Data System (ADS)
Blaizot, J. P.; Schulz, H.
1982-03-01
We present an analytically soluble model for studying nuclear collective motion within the framework of the time-dependent Hartree (TDH) approximation. The model reduces the TDH equations to the Schrödinger equation of a time-dependent harmonic oscillator. Using canonical transformations and coherent states we derive a few properties of the time-dependent harmonic oscillator which are relevant for applications. We analyse the role of the normal modes in the time evolution of a system governed by TDH equations. We show how these modes couple together due to the anharmonic terms generated by the non-linearity of the theory.
[Model of active peristaltic transport in biosystems].
Klochkov, B N; Romanov, A S
2013-01-01
A nonlinear distributed mathematical model of soft vessel with the nonmonotonous static characteristic is proposed and considered. The model describes space-time dynamics of vessel clearance change. Wave phenomena in vessels of different nature and the possibility of peristaltic fluid pumping are discussed and analyzed. The model is rather common in character and represents a description of the whole class of transport phenomena. Lymphatic vessels are particularly considered.
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.
Mina, Ashraf; Favaloro, Emmanuel J; Koutts, Jerry
2012-04-01
Short activated partial thromboplastin times (APTTs) are associated with thrombosis. However, what short APTTs actually represent in terms of possible mechanistic pathways is not well characterized. We have assessed thrombin generation as compared with levels of procoagulant factor (fibrinogen, V, VIII, IX, XI and XII) activities, von Willebrand factor level and activity using collagen binding, as well as procoagulant phospholipid activity, in 113 consecutive samples exhibiting a short APTT compared with an equal number of age-matched and sex-matched samples yielding a normal APTT. We found a significant difference in peak thrombin generation, velocity index and area under the curve between the two groups, and that thrombin generation markers correlated with the APTT, procoagulant phospholipid activity and several procoagulant clotting factors. We conclude that short APTTs represent a procoagulant milieu, as represented by heightened thrombin generation and several other heightened procoagulant activities, which may help explain the association with thrombosis.
Earthquake Lights: Time-dependent Earth Surface - Ionosphere Coupling Model
NASA Astrophysics Data System (ADS)
Pasko, V. P.
2012-12-01
Co-seismic luminescence, commonly referred to as Earthquake lights (EQLs), is an atmospheric luminous phenomenon occurring during strong earthquakes and lasting from a fraction of a second to a few minutes [e.g., Derr, J. S., Bull. Seismol. Soc. Am., 63, 2177, 1973; St-Laurent, F., et al., Phys. Chem. Earth, 31, 305, 2006; Herauld and Lira, Nat. Hazards Earth Syst. Sci., 11, 1025, 2011]. Laboratory experiments of Freund, F. T., et al. [JGR, 105, 11001, 2000; JASTP, 71, 1824, 2009, and references therein] demonstrate that rocks subjected to stress force can generate electric currents. During earthquakes these currents can deliver significant amounts of net positive charge to the ground-air interface leading to enhancements in the electric field and corona discharges around ground objects [Freund et al., 2009]. The eyewitness reports [Herauld and Lira, 2011] indicate similarities of the blue glow observed during EQLs to St. Elmo's fire observed during thunderstorms around wing tips of airplanes or around the tall masts of sailing ships [e.g., Wescott, E.M., et al., GRL, 23, 3687, 1996]. Recent work indicates that the vertical currents induced in the stressed rock can map to ionospheric altitudes and create 10s of % variations in the total electron content in the Earth's ionosphere above the earthquake active region [Kuo, C. L., et al., JGR, 116, A10317, 2011]. The magnitudes of the vertical currents estimated by Kuo et al. [2011] based on work by Freund et al. [2009] range from 0.01 to 10 μA/m2. In this talk we report results from a new time-dependent model allowing to calculate currents induced in the ambient atmosphere and corona currents under application of vertical stressed rock currents with arbitrary time variation. We will report test results documenting the model performance under conditions: (1) relaxation toward the classic global electric circuit conditions in fair weather regions when ionosphere is maintained at 300 kV with respect to the ground; (2
Real-Time Statistical Modeling of Blood Sugar.
Otoom, Mwaffaq; Alshraideh, Hussam; Almasaeid, Hisham M; López-de-Ipiña, Diego; Bravo, José
2015-10-01
Diabetes is considered a chronic disease that incurs various types of cost to the world. One major challenge in the control of Diabetes is the real time determination of the proper insulin dose. In this paper, we develop a prototype for real time blood sugar control, integrated with the cloud. Our system controls blood sugar by observing the blood sugar level and accordingly determining the appropriate insulin dose based on patient's historical data, all in real time and automatically. To determine the appropriate insulin dose, we propose two statistical models for modeling blood sugar profiles, namely ARIMA and Markov-based model. Our experiment used to evaluate the performance of the two models shows that the ARIMA model outperforms the Markov-based model in terms of prediction accuracy.
Dark Energy Models with a Time-Dependent Gravitational Constant
NASA Astrophysics Data System (ADS)
Ray, Saibal; Mukhopadhyay, Utpal; Choudhury, S. B. Dutta
Two phenomenological models of Λ, viz. Λ ˜ (˙ a/a)2 and Λ ˜ ḋ a/a, are studied under the assumption that G is a time-variable parameter. Both models show that G is inversely proportional to time, as suggested earlier by others, including Dirac. The models considered here can be matched with observational results by properly tuning the parameters of the models. Our analysis shows that the Λ ˜ ḋ a/a model corresponds to a repulsive situation and hence correlates with the present status of the accelerating Universe. The other model, Λ ˜ (˙ a/a)2, is in general attractive in nature. Moreover, it is seen that due to the combined effect of time-variable Λ and G the Universe evolved with acceleration as well as deceleration. Deceleration indicates a "big crunch".
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.
Correcting transit time distributions in coarse MODFLOW-MODPATH models.
Abrams, Daniel
2013-01-01
In low to medium resolution MODFLOW models, the area occupied by sink cells often far exceeds the surface area of the streams they represent. As a result, MODPATH will calculate inaccurate particle traces and transit times. A frequency distribution of transit times for a watershed will also be in error. Such a distribution is used to assess the long-term impact of nonpoint source pollution on surface waters and wells. Although the inaccuracies for individual particles can only be avoided by increased model grid resolution or other advanced modeling techniques, the frequency distribution can be improved by scaling the particle transit times by an adjustment factor during post-processing.
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.
Sampling the NCAR TIEGCM, TIME-GCM, and GSWM models for CEDAR and TIMED related studies
NASA Astrophysics Data System (ADS)
Oberheide, J.; Hagan, M. E.; Roble, R. G.; Lu, G.
2003-04-01
The instruments on the TIMED satellite and a complement of ground based CEDAR instruments will provide invaluable diagnostics of mesosphere, lower thermosphere, and E-region ionosphere (MLTI, ca. 60-180 km) forcings, dynamics, and energetics. The interpretation of these diagnostics and elucidation of the impact of the associated processes on the MLTI requires complementary modeling initiatives. We make samples of the NCAR/HAO TIME-GCM, TIEGCM, and GSWM model outputs available to the community via the web. The model results are sampled in a way to provide winds, temperatures, and trace constituents that would be measured by the TIMED instruments if the satellite flew through the model atmosphere. We also provide an analogous product for the CEDAR ground-based component of TIMED.
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…
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.
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.
Semi-parametric estimation in failure time mixture models.
Taylor, J M
1995-09-01
A mixture model is an attractive approach for analyzing failure time data in which there are thought to be two groups of subjects, those who could eventually develop the endpoint and those who could not develop the endpoint. The proposed model is a semi-parametric generalization of the mixture model of Farewell (1982). A logistic regression model is proposed for the incidence part of the model, and a Kaplan-Meier type approach is used to estimate the latency part of the model. The estimator arises naturally out of the EM algorithm approach for fitting failure time mixture models as described by Larson and Dinse (1985). The procedure is applied to some experimental data from radiation biology and is evaluated in a Monte Carlo simulation study. The simulation study suggests the semi-parametric procedure is almost as efficient as the correct fully parametric procedure for estimating the regression coefficient in the incidence, but less efficient for estimating the latency distribution.
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.
Adaptive time-variant models for fuzzy-time-series forecasting.
Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching
2010-12-01
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.
Activity of a social dynamics model
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Neves, Ubiraci P. C.
2015-10-01
Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.
Residence time modeling of hot melt extrusion processes.
Reitz, Elena; Podhaisky, Helmut; Ely, David; Thommes, Markus
2013-11-01
The hot melt extrusion process is a widespread technique to mix viscous melts. The residence time of material in the process frequently determines the product properties. An experimental setup and a corresponding mathematical model were developed to evaluate residence time and residence time distribution in twin screw extrusion processes. The extrusion process was modeled as the convolution of a mass transport process described by a Gaussian probability function, and a mixing process represented by an exponential function. The residence time of the extrusion process was determined by introducing a tracer at the extruder inlet and measuring the tracer concentration at the die. These concentrations were fitted to the residence time model, and an adequate correlation was found. Different parameters were derived to characterize the extrusion process including the dead time, the apparent mixing volume, and a transport related axial mixing. A 2(3) design of experiments was performed to evaluate the effect of powder feed rate, screw speed, and melt viscosity of the material on the residence time. All three parameters affect the residence time of material in the extruder. In conclusion, a residence time model was developed to interpret experimental data and to get insights into the hot melt extrusion process.
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.
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
Generalized Dynamic Factor Models for Mixed-Measurement Time Series.
Cui, Kai; Dunson, David B
2014-02-12
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.
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
Timing of activity of two fault systems on Mercury
NASA Astrophysics Data System (ADS)
Galluzzi, V.; Guzzetta, L.; Giacomini, L.; Ferranti, L.; Massironi, M.; Palumbo, P.
2015-10-01
Here we discuss about two fault systems found in the Victoria and Shakespeare quadrangles of Mercury. The two fault sets intersect each other and show probable evidence for two stages of deformation. The most prominent system is N-S oriented and encompasses several tens to hundreds of kilometers long and easily recognizable fault segments. The other system strikes NE- SW and encompasses mostly degraded and short fault segments. The structural framework of the studied area and the morphological appearance of the faults suggest that the second system is older than the first one. We intend to apply the buffered crater counting technique on both systems to make a quantitative study of their timing of activity that could confirm the already clear morphological evidence.
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.
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 Persistence In Hydrological Time Series Using Fractional Differencing
NASA Astrophysics Data System (ADS)
Hosking, J. R. M.
1984-12-01
The class of autoregressive integrated moving average (ARIMA) time series models may be generalized by permitting the degree of differencing d to take fractional values. Models including fractional differencing are capable of representing persistent series (d > 0) or short-memory series (d = 0). The class of fractionally differenced ARIMA processes provides a more flexible way than has hitherto been available of simultaneously modeling the long-term and short-term behavior of a time series. In this paper some fundamental properties of fractionally differenced ARIMA processes are presented. Methods of simulating these processes are described. Estimation of the parameters of fractionally differenced ARIMA models is discussed, and an approximate maximum likelihood method is proposed. The methodology is illustrated by fitting fractionally differenced models to time series of streamflows and annual temperatures.
A noise model for InSAR time series
NASA Astrophysics Data System (ADS)
Agram, P. S.; Simons, M.
2015-04-01
Interferometric synthetic aperture radar (InSAR) time series methods estimate the spatiotemporal evolution of surface deformation by incorporating information from multiple SAR interferograms. While various models have been developed to describe the interferometric phase and correlation statistics in individual interferograms, efforts to model the generalized covariance matrix that is directly applicable to joint analysis of networks of interferograms have been limited in scope. In this work, we build on existing decorrelation and atmospheric phase screen models and develop a covariance model for interferometric phase noise over space and time. We present arguments to show that the exploitation of the full 3-D covariance structure within conventional time series inversion techniques is computationally challenging. However, the presented covariance model can aid in designing new inversion techniques that can at least mitigate the impact of spatial correlated nature of InSAR observations.
Distributed Time Delay Goodwin's Models of the Business Cycle
NASA Astrophysics Data System (ADS)
Antonova, A. O.; Reznik, S. N.; Todorov, M. D.
2011-11-01
We consider continuously distributed time delay Goodwin's model of the business cycle. We show that the delay induced sawtooth oscillations, similar to those detected by R. H. Strotz, J. C. McAnulty, J. B. Naines, Econometrica, 21, 390-411 (1953) for Goodwin's model with fixed investment time lag, exist only for very narrow delay distribution when the variance of the delay distribution much less than the average delay.
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...
Hick Samuelson Keynes Dynamic Economic Model with Discrete Time and Consumer Sentiment
NASA Astrophysics Data System (ADS)
Dobrescu, Loretti I.; Neamå#U, Mihaela; Opriş, Dumitru
The paper describes the Hick Samuelson Keynes dynamical economic model with discrete time and consumer sentiment. We seek to demonstrate that consumer sentiment may create fluctuations in the economical activities. The model possesses a flip bifurcation and a Neimark-Sacker bifurcation, after which the stable state is replaced by a (quasi-) periodic motion.
Real-time multi-model decadal climate predictions
NASA Astrophysics Data System (ADS)
Smith, Doug M.; Scaife, Adam A.; Boer, George J.; Caian, Mihaela; Doblas-Reyes, Francisco J.; Guemas, Virginie; Hawkins, Ed; Hazeleger, Wilco; Hermanson, Leon; Ho, Chun Kit; Ishii, Masayoshi; Kharin, Viatcheslav; Kimoto, Masahide; Kirtman, Ben; Lean, Judith; Matei, Daniela; Merryfield, William J.; Müller, Wolfgang A.; Pohlmann, Holger; Rosati, Anthony; Wouters, Bert; Wyser, Klaus
2013-12-01
We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the
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
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.
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.
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 hypocentral version of the space-time ETAS model
NASA Astrophysics Data System (ADS)
Guo, Yicun; Zhuang, Jiancang; Zhou, Shiyong
2015-10-01
The space-time Epidemic-Type Aftershock Sequence (ETAS) model is extended by incorporating the depth component of earthquake hypocentres. The depths of the direct offspring produced by an earthquake are assumed to be independent of the epicentre locations and to follow a beta distribution, whose shape parameter is determined by the depth of the parent event. This new model is verified by applying it to the Southern California earthquake catalogue. The results show that the new model fits data better than the original epicentre ETAS model and that it provides the potential for modelling and forecasting seismicity with higher resolutions.
Time-varying priority queuing models for human dynamics
NASA Astrophysics Data System (ADS)
Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo
2012-06-01
Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We theoretically study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's “state of mind.” However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario.
The burning fuse model of unbecoming in time
NASA Astrophysics Data System (ADS)
Norton, John D.
2015-11-01
In the burning fuse model of unbecoming in time, the future is real and the past is unreal. It is used to motivate the idea that there is something unbecoming in the present literature on the metaphysics of time: its focus is merely the assigning of a label "real."
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...
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…
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…
Model Identification in Time-Series Analysis: Some Empirical Results.
ERIC Educational Resources Information Center
Padia, William L.
Model identification of time-series data is essential to valid statistical tests of intervention effects. Model identification is, at best, inexact in the social and behavioral sciences where one is often confronted with small numbers of observations. These problems are discussed, and the results of independent identifications of 130 social and…
Relaxation-time measurement via a time-dependent helicity balance model
Wrobel, J. S.; Hansen, C. J.; Jarboe, T. R.; Smith, R. J.; Hossack, A. C.; Nelson, B. A.; Marklin, G. J.; Ennis, D. A.; Akcay, C.; Victor, B. S.
2013-01-15
A time-dependent helicity balance model applied to a spheromak helicity-injection experiment enables the measurement of the relaxation time during the sustainment phase of the spheromak. The experiment, the Helicity Injected Torus with Steady Inductive helicity injection (HIT-SI), studies spheromak formation and sustainment through inductive helicity injection. The model captures the dominant plasma behavior seen during helicity injection in HIT-SI by using an empirical helicity-decay rate, a time-dependent helicity-injection rate, and a composite Taylor state to model both the helicity content of the system and to calculate the resulting spheromak current. During single-injector operations, both the amplitude and the phase of the periodic rise and fall of the toroidal current are predicted by this model, with an exchange of helicity between the injector states and the spheromak state proposed as the causal mechanism. This phenomenon allows for the comparison of the delay between the current rises in the experiment and the numerical model, enabling a measurement of the relaxation time. The measured relaxation time of 4.8 {mu}s {+-} 2.8 {mu}s is shorter than the toroidal Alfven timescale. These results validate Hall MHD calculations of the Geospace Environmental Modeling challenge.
2001-11-01
33’’ Annual Precise Time and Time Interval (PTTI) Meeting Administrators Secretary Engineers and Technicians REPORT ON THE TIME AND FREQUENCY OF...THE U.S. NAVAL OBSERVATORY ACTIVITIES OF THE TIME SERVICE DEPARTMENT 2 1 4 Demetrios Matsakis and the staff of the Time Service Department U.S...requirements of many real- time users, the best known among them being GPS. 1 THE BASICS The most important part of the USNO Time Service Department is its
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.
Rodriguez-Perez, S; Fermoso, F G; Arnaiz, C
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.
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.
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.
Parametric time delay modeling for floating point units
NASA Astrophysics Data System (ADS)
Fahmy, Hossam A. H.; Liddicoat, Albert A.; Flynn, Michael J.
2002-12-01
A parametric time delay model to compare floating point unit implementations is proposed. This model is used to compare a previously proposed floating point adder using a redundant number representation with other high-performance implementations. The operand width, the fan-in of the logic gates and the radix of the redundant format are used as parameters to the model. The comparison is done over a range of operand widths, fan-in and radices to show the merits of each implementation.
Traffic model by braking capability and response time
NASA Astrophysics Data System (ADS)
Lee, Hyun Keun; Kim, Jeenu; Kim, Youngho; Lee, Choong-Ki
2015-06-01
We propose a microscopic traffic model where the update velocity is determined by the deceleration capacity and response time. It is found that there is a class of collisions that cannot be distinguished by simply comparing the stop positions. The model generates the safe, comfortable, and efficient traffic flow in numerical simulations with a reasonable values of the parameters, and this is analytically supported. Our approach provides a new perspective in modeling traffic-flow safety and worrying situations like lane changing.
Time Dependent Models of Grain Formation Around Carbon Stars
NASA Technical Reports Server (NTRS)
Egan, M. P.; Shipman, R. F.
1996-01-01
Carbon-rich Asymptotic Giant Branch stars are sites of dust formation and undergo mass loss at rates ranging from 10(exp -7) to 10(exp -4) solar mass/yr. The state-of-the-art in modeling these processes is time-dependent models which simultaneously solve the grain formation and gas dynamics problem. We present results from such a model, which also includes an exact solution of the radiative transfer within the system.
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.
Continuous-Time Discrete-Distribution Theory for Activity-Driven Networks
NASA Astrophysics Data System (ADS)
Zino, Lorenzo; Rizzo, Alessandro; Porfiri, Maurizio
2016-11-01
Activity-driven networks are a powerful paradigm to study epidemic spreading over time-varying networks. Despite significant advances, most of the current understanding relies on discrete-time computer simulations, in which each node is assigned an activity potential from a continuous distribution. Here, we establish a continuous-time discrete-distribution framework toward an analytical treatment of the epidemic spreading, from its onset to the endemic equilibrium. In the thermodynamic limit, we derive a nonlinear dynamical system to accurately model the epidemic spreading and leverage techniques from the fields of differential inclusions and adaptive estimation to inform short- and long-term predictions. We demonstrate our framework through the analysis of two real-world case studies, exemplifying different physical phenomena and time scales.
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.
Continuous-Time Discrete-Distribution Theory for Activity-Driven Networks.
Zino, Lorenzo; Rizzo, Alessandro; Porfiri, Maurizio
2016-11-25
Activity-driven networks are a powerful paradigm to study epidemic spreading over time-varying networks. Despite significant advances, most of the current understanding relies on discrete-time computer simulations, in which each node is assigned an activity potential from a continuous distribution. Here, we establish a continuous-time discrete-distribution framework toward an analytical treatment of the epidemic spreading, from its onset to the endemic equilibrium. In the thermodynamic limit, we derive a nonlinear dynamical system to accurately model the epidemic spreading and leverage techniques from the fields of differential inclusions and adaptive estimation to inform short- and long-term predictions. We demonstrate our framework through the analysis of two real-world case studies, exemplifying different physical phenomena and time scales.
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
Workflow Modeling Using Stochastic Activity Networks
NASA Astrophysics Data System (ADS)
Javadi Mottaghi, Fatemeh; Abdollahi Azgomi, Mohammad
The essence of workflow systems is workflow patterns. The aim is to use an existing powerful formal modeling language with workflow systems. Stochastic activity networks (SANs) are a powerful extension of Petri nets. Having the SAN model of a system, one can verify the functional aspects and evaluate the operational measures, both on a same model. SANs have already been used in a wide range of applications. As a new application area, we have used SANs for modeling workflow systems. The results show that the most important workflow patterns can be modeled in SANs. In addition, the resulting SAN models of workflow systems can be used for model checking and/or performance evaluation purposes using the existing tools. In this paper, we will present the results of this work. For this purpose, we will present the SAN submodels corresponding to the most important workflow patterns. Then, the proposed SAN submodels are used in a case study for workflow modeling, which will also be presented in this paper. Finally, we will present the results of the evaluation of the model using the Möbius modeling tool.
Automated model formulation for time-varying flexible structures
NASA Technical Reports Server (NTRS)
Glass, B. J.; Hanagud, S.
1989-01-01
Presented here is an identification technique that uses the sensor information to choose a new model out of a finite set of discrete model space, in order to follow the observed changes to the given time varying flexible structure. Boundary condition sets or other information on model variations are used to organize the set of possible models laterally into a search tree with levels of abstraction used to order the models vertically within branches. An object-oriented programming approach is used to represent the model set in the search tree. A modified A (asterisk) best first search algorithm finds the model where the model response best matches the current observations. Several extensions to this methodology are discussed. Methods of possible integration of rules with the current search algorithm are considered to give weight to interpreted trends that may be found in a series of observations. This capability might lead, for instance, to identifying a model that incorporates a progressive damage rather than with incorrect paramenters such as added mass. Another new direction is to consider the use of noisy time domain sensor feedback rather than frequency domain information in the search algorithm to improve the real-time capability of the developed procedure.
On reevaluation rate in discrete time Hogg-Huberman model
NASA Astrophysics Data System (ADS)
Tanaka, Toshijiro; Shibata, Junko; Inoue, Masayoshi
2002-06-01
The discrete time Hogg-Huberman model is extended to a case with time-dependent reevaluation rate at which agents using one resource decide to evaluate their resource choice. In this paper the time dependence of the reevaluation rate is determined by states of the system. The dynamical behavior of the extended Hogg-Huberman model is discussed. It is found that the change of fraction of agents using resource 1 is suppressed to be smaller than that in the case of constant reevaluation rate.
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.
Real-time Social Internet Data to Guide Forecasting Models
Del Valle, Sara Y.
2016-09-20
Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.
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.
Does an ‘Activity-Permissive’ Workplace Change Office Workers’ Sitting and Activity Time?
Gorman, Erin; Ashe, Maureen C.; Dunstan, David W.; Hanson, Heather M.; Madden, Ken; Winkler, Elisabeth A. H.; McKay, Heather A.; Healy, Genevieve N.
2013-01-01
Introduction To describe changes in workplace physical activity, and health-, and work-related outcomes, in workers who transitioned from a conventional to an ‘activity-permissive’ workplace. Methods A natural pre-post experiment conducted in Vancouver, Canada in 2011. A convenience sample of office-based workers (n=24, 75% women, mean [SD] age = 34.5 [8.1] years) were examined four months following relocation from a conventional workplace (pre) to a newly-constructed, purpose-built, movement-oriented physical environment (post). Workplace activity- (activPAL3-derived stepping, standing, and sitting time), health- (body composition and fasting cardio-metabolic blood profile), and work- (performance; job satisfaction) related outcomes were measured pre- and post-move and compared using paired t-tests. Results Pre-move, on average (mean [SD]) the majority of the day was spent sitting (364 [43.0] mins/8-hr workday), followed by standing (78.2 [32.1] mins/8-hr workday) and stepping (37.7 [15.6] mins/8-hr workday). The transition to the ‘activity-permissive’ workplace resulted in a significant increase in standing time (+18.5, 95% CI: 1.8, 35.2 mins/8-hr workday), likely driven by reduced sitting time (-19.7, 95% CI: -42.1, 2.8 mins/8-hr workday) rather than increased stepping time (+1.2, 95% CI: -6.2, 8.5 mins/8-hr workday). There were no statistically significant differences observed in health- or work-related outcomes. Discussion This novel, opportunistic study demonstrated that the broader workplace physical environment can beneficially impact on standing time in office workers. The long-term health and work-related benefits, and the influence of individual, organizational, and social factors on this change, requires further evaluation. PMID:24098555
Gu, Yiping; Patwardhan, Abhijit
2002-01-01
Activation sequences during ventricular fibrillation (VF) display complex pattern and fast rate. Recent evidence suggests that even during VF an excitable gap may exist. Existence of excitable gap lead us to hypothesize that it should be possible to entrain activation patterns during VF by using spatially distributed and temporally phased pacing strength stimuli. We describe here the electronics hardware and software that were developed to test our hypothesis. Eight biphasic stimulators were designed and fabricated, each addressable via a TTL input and thus independently triggered. To minimize electrical interference from stimulus pulses the stimulators were optically isolated. A program written in C was used to deliver TTL inputs to time the sequence of stimulation. The parameters that could be varied were, pulse intensity, polarity, and duration, inter pulse interval and activation pattern cycle length. Restitution's of action potential duration, conduction velocity, and complex activation patterns make the timing of stimulators complex. To aid in optimal timing of these stimulators, we used a Luo-Rudy ionic model of cellular activation to simulate VF in a matrix of 400 x 400 cells. Entrainment of activation was verified using animated displays of activation sequences. Using results of simulation we verified the function of our stimulators experimentally using electrically induced VF in canines and by using electrograms recorded from 121-electrode patch. Our results show that the developed hardware and software can be used to deliver distributed stimuli in a flexible and effective pattern, which may aid in development of approaches for treatment of VF.
Realistic Real World Contexts: Model Eliciting Activities
ERIC Educational Resources Information Center
Doruk, Bekir Kürsat
2016-01-01
Researchers have proposed a variety of methods to make a connection between real life and mathematics so that it can be learned in a practical way and enable people to utilise mathematics in their daily lives. Model-eliciting activities (MEAs) were developed to fulfil this need and are very capable of serving this purpose. The reason MEAs are so…
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...
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...
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 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.)
Spatio-temporal modeling for real-time ozone forecasting.
Paci, Lucia; Gelfand, Alan E; Holland, David M
2013-05-01
The accurate assessment of exposure to ambient ozone concentrations is important for informing the public and pollution monitoring agencies about ozone levels that may lead to adverse health effects. High-resolution air quality information can offer significant health benefits by leading to improved environmental decisions. A practical challenge facing the U.S. Environmental Protection Agency (USEPA) is to provide real-time forecasting of current 8-hour average ozone exposure over the entire conterminous United States. Such real-time forecasting is now provided as spatial forecast maps of current 8-hour average ozone defined as the average of the previous four hours, current hour, and predictions for the next three hours. Current 8-hour average patterns are updated hourly throughout the day on the EPA-AIRNow web site. The contribution here is to show how we can substantially improve upon current real-time forecasting systems. To enable such forecasting, we introduce a downscaler fusion model based on first differences of real-time monitoring data and numerical model output. The model has a flexible coefficient structure and uses an efficient computational strategy to fit model parameters. Our hybrid computational strategy blends continuous background updated model fitting with real-time predictions. Model validation analyses show that we are achieving very accurate and precise ozone forecasts.
Chromospheric extents predicted by time-dependent acoustic wave models
NASA Astrophysics Data System (ADS)
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.
Chromospheric extents predicted by time-dependent acoustic wave models
Cuntz, M. Heidelberg Universitaet )
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. 74 refs.
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…
Kamimura, Hidetaka; Ito, Satoshi; Chijiwa, Hiroyuki; Okuzono, Takeshi; Ishiguro, Tomohiro; Yamamoto, Yosuke; Nishinoaki, Sho; Ninomiya, Shin-Ichi; Mitsui, Marina; Kalgutkar, Amit S; Yamazaki, Hiroshi; Suemizu, Hiroshi
2016-07-07
1. The partial glucokinase activator N,N-dimethyl-5-((2-methyl-6-((5-methylpyrazin-2-yl)carbamoyl)benzofuran-4-yl)oxy)pyrimidine-2-carboxamide (PF-04937319) is biotransformed in humans to N-methyl-5-((2-methyl-6-((5-methylpyrazin-2-yl)carbamoyl)benzofuran-4-yl)oxy)pyrimidine-2-carboxamide (M1), accounting for ∼65% of total exposure at steady state. 2. As the disproportionately abundant nature of M1 could not be reliably predicted from in vitro metabolism studies, we evaluated a chimeric mouse model with humanized liver on TK-NOG background for its ability to retrospectively predict human disposition of PF-04937319. Since livers of chimeric mice were enlarged by hyperplasia and contained remnant mouse hepatocytes, hepatic intrinsic clearances normalized for liver weight, metabolite formation and liver to plasma concentration ratios were plotted against the replacement index by human hepatocytes and extrapolated to those in the virtual chimeric mouse with 100% humanized liver. 3. Semi-physiological pharmacokinetic analyses using the above parameters revealed that simulated concentration curves of PF-04937319 and M1 were approximately superimposed with the observed clinical data in humans. 4. Finally, qualitative profiling of circulating metabolites in humanized chimeric mice dosed with PF-04937319 or M1 also revealed the presence of a carbinolamide metabolite, identified in the clinical study as a human-specific metabolite. The case study demonstrates that humanized chimeric mice may be potentially useful in preclinical discovery towards studying disproportionate or human-specific metabolism of drug candidates.
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.
Characterization and modeling of compliant active materials
NASA Astrophysics Data System (ADS)
Marra, S. P.; Ramesh, K. T.; Douglas, A. S.
2003-09-01
Active materials respond mechanically to changes in environmental conditions. One example of a compliant active material is a polymer gel. Active polymer gels expand and contract in response to certain environmental stimuli, such as the application of an electric field or a change in the pH level of the surroundings. This ability to achieve large, reversible deformations with no external mechanical loading has generated much interest in the use of these gels as actuators and "artificial muscles". While much work has been done to study the behavior and properties of these gels, little information is available regarding the full constitutive description of the mechanical and actuation properties. This work focuses on developing a means of characterizing the mechanical properties of compliant active materials. A thermodynamically consistent finite-elastic constitutive model was developed to describe the mechanical and actuation behaviors of these kinds of materials. The mechanical properties of compliant active materials are characterized by a free-energy function, and the model utilizes an evolving internal variable to describe the actuation state. A biaxial testing system has been developed which can measure stresses and deformations of polymer gel films in a variety of liquid environments. This testing system is used to determine the form and parameters of the free-energy function for a specific active polymer gel, poly(vinyl alcohol)-poly(acrylic acid) gel.
Bacteriophage: A Model System for Active Learning
LUCIANO, CARL S.; YOUNG, MATTHEW W.; PATTERSON, ROBIN R.
2002-01-01
Although bacteriophage provided a useful model system for the development of molecular biology, its simplicity, accessibility, and familiarity have not been fully exploited in the classroom. We describe a student-centered laboratory course in which student teams selected phage from sewage samples and characterized the phage in a semester-long project that modeled real-life scientific research. The course used an instructional approach that included active learning, collaboration, and learning by inquiry. Cooperative student teams had primary responsibility for organizing the content of the course, writing to learn using a journal article format, involving the entire group in shared laboratory responsibilities, and applying knowledge to the choice of new experiments. The results of student evaluations indicated a high level of satisfaction with the course. Our positive experience with this course suggests that phage provides an attractive model system for an active-learning classroom. PMID:23653543
Cooper, Andrew J. M.; Simmons, Rebecca K.; Kuh, Diana; Brage, Soren; Cooper, Rachel
2015-01-01
Purpose To investigate the associations of time spent sedentary, in moderate-to-vigorous-intensity physical activity (MVPA) and physical activity energy expenditure (PAEE) with physical capability measures at age 60-64 years. Methods Time spent sedentary and in MVPA and, PAEE were assessed using individually calibrated combined heart rate and movement sensing among 1727 participants from the MRC National Survey of Health and Development in England, Scotland and Wales as part of a detailed clinical assessment undertaken in 2006-2010. Multivariable linear regression models were used to examine the cross-sectional associations between standardised measures of each of these behavioural variables with grip strength, chair rise and timed up-&-go (TUG) speed and standing balance time. Results Greater time spent in MVPA was associated with higher levels of physical capability; adjusted mean differences in each capability measure per 1standard deviation increase in MVPA time were: grip strength (0.477 kg, 95% confidence interval (CI): 0.015 to 0.939), chair rise speed (0.429 stands/min, 95% CI: 0.093 to 0.764), standing balance time (0.028 s, 95% CI: 0.003 to 0.053) and TUG speed (0.019 m/s, 95% CI: 0.011 to 0.026). In contrast, time spent sedentary was associated with lower grip strength (-0.540 kg, 95% CI: -1.013 to -0.066) and TUG speed (-0.011 m/s, 95% CI: -0.019 to -0.004). Associations for PAEE were similar to those for MVPA. Conclusion Higher levels of MVPA and overall physical activity (PAEE) are associated with greater levels of physical capability whereas time spent sedentary is associated with lower levels of capability. Future intervention studies in older adults should focus on both the promotion of physical activity and reduction in time spent sedentary. PMID:25961736
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.
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.
Kretschmer, Tina; Oliver, Bonamy R; Maughan, Barbara
2014-08-01
Extensive evidence supports associations between early pubertal timing and adolescent externalizing behavior, but how and under which conditions they are linked is not fully understood. In addition, pubertal development is also characterized by variations in the relative speed at which individuals mature, but studies linking pubertal 'tempo' and outcomes are scarce. This study examined the mediating and moderating roles of spare time activities in associations between pubertal development and later delinquency, using data from a large (4,327 girls, 4,250 boys) longitudinal UK cohort (Avon Longitudinal Study of Parents and Children). Self-reports of Tanner stage were available from ages 9 to 14, spare time activities at age 12 and delinquency at age 15. Pubertal development was examined using latent growth models. Spare time activities were categorized using factor analyses, yielding four types (hanging out at home, hanging out outside, consumerist behavior, and sports/games), which were examined as mediators and moderators. Earlier and faster maturation predicted delinquency in boys and girls. Spare time activities partially mediated these links such that early maturing girls more often engaged in hanging out outside, which placed them at greater risk for delinquency. In addition, compared to their later and slower maturing counterparts, boys who matured earlier and faster were less likely to engage in sports/games, a spare time activity type that is linked to lower delinquency risk. No moderation effects were found. The findings extend previous research on outcomes of early maturation and show how spare time activities act as proxies between pubertal development and delinquency.
The average rate of change for continuous time models.
Kelley, Ken
2009-05-01
The average rate of change (ARC) is a concept that has been misunderstood in the applied longitudinal data analysis literature, where the slope from the straight-line change model is often thought of as though it were the ARC. The present article clarifies the concept of ARC and shows unequivocally the mathematical definition and meaning of ARC when measurement is continuous across time. It is shown that the slope from the straight-line change model generally is not equal to the ARC. General equations are presented for two measures of discrepancy when the slope from the straight-line change model is used to estimate the ARC in the case of continuous time for any model linear in its parameters, and for three useful models nonlinear in their parameters.
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. PMID:22612543
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
Casualty modeling for real-time medical training.
Chi, D M; Clarke, J R; Webber, B L; Badler, N I
1996-01-01
We present a model for simulating casualties in virtual environments for real-time medical training. It allows a user to choose diagnostic and therapeutic actions to carry out on a simulated casualty who will manifest appropriate physiological, behavioral, and physical responses. Currently, the user or a "stealth instructor" can specify one or more injuries that the casualty has sustained. The model responds by continuously determining the state of the casualty, responding appropriately to medical assessment and treatment procedures. So far, we have modeled four medical conditions and over 20 procedures. The model has been designed to handle the addition of other injuries and medical procedures.
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.
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.
Challenges of Integrated Modeling Across Space and Time Scales
NASA Astrophysics Data System (ADS)
Jagers, B.; Donchyts, G.; Baart, F.; Schellekens, J.; Winsemius, H.
2015-12-01
New data collection methods combined with rapid advances in processing technologies enabled by increases in data processing and storage capabilities are causing an significant shift in our modeling capabilities. Freely available global data sets allow us to build more quickly models for bigger areas. By linking the right data, models, and tools we gain significant insight at scales that hadn't considered possible a few decades ago. However, by increasing the spatial extent of our models, we risk missing regionally important critical elements by limitations of model resolution, processes selected, or blind spots in our big data world. At the same time we are pushing the time scales of our models from events and seasonal scale out to decades, centuries, or millennia to simulate the dynamics of the earth surface under varying external conditions. Also here we simplify and ignore to gain performance to resolve bigger time and space domains; are we including all the relevant elements in our models? These elements are often easy to spot from the right perspective. However, what is that perspective when you try to comprehend the results of baffling integrated global models and the amount of data is overwhelming? At the same time we want to know results with an ever increasing accuracy and detail: Will my house flood? Can we reduce flood risk, increase shipping capacity here, and at the same time reduce the maintenance costs by optimizing our dredging strategy? Can we build a number of interoperable cyberinfrastructures that when combined address all these questions? This presentation gives an overview of our work in this field at Deltares, and the main challenges that we foresee.
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 dependent patient no-show predictive modelling development.
Huang, Yu-Li; Hanauer, David A
2016-05-09
Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows.
Audibility of time-varying signals in time-varying backgrounds: Model and data
NASA Astrophysics Data System (ADS)
Moore, Brian C. J.; Glasberg, Brian R.
2004-05-01
We have described a model for calculating the partial loudness of a steady signal in the presence of a steady background sound [Moore et al., J. Audio Eng. Soc. 45, 224-240 (1997)]. We have also described a model for calculating the loudness of time-varying signals [B. R. Glasberg and B. C. J. Moore, J. Audio Eng. Soc. 50, 331-342 (2002)]. These two models have been combined to allow calculation of the partial loudness of a time-varying signal in the presence of a time-varying background. To evaluate the model, psychometric functions for the detection of a variety of time-varying signals (e.g., telephone ring tones) have been measured in a variety of background sounds sampled from everyday listening situations, using a two-alternative forced-choice task. The different signals and backgrounds were interleaved, to create stimulus uncertainty, as would occur in everyday life. The data are used to relate the detectability index, d', to the calculated partial loudness. In this way, the model can be used to predict the detectability of any signal, based on its calculated partial loudness. [Work supported by MRC (UK) and by Nokia.
Kershaw, Geoffrey; Orellana, Daniel
2013-04-01
Mixing tests are a relatively simple procedure used in the hemostasis laboratory as a first-line investigation into the cause of an abnormal screening test, typically a prolonged activated partial thromboplastin time and/or a prolonged prothrombin time. The mixing test involves combining the test plasma with normal plasma, then repeating the screening test on the mixture to assess whether the clotting time becomes normal or remains prolonged. The primary purpose of a mixing test is to guide further investigations. When mixing test results "normalize," this suggests the test plasma is deficient in clotting factor(s) and thus specific factor assays can be performed to determine which are reduced. When the mixing test result does not "normalize," this suggests the presence of an inhibitor or other type of interference (e.g., the presence of an anticoagulant such as high-dose heparinoids), and so the laboratory needs to determine if this is a lupus anticoagulant or a specific coagulation factor inhibitor, or another type of inhibitor. Because these follow-up investigations are more costly and time-consuming than the basic screening tests, the appropriate performance and interpretation of mixing tests is advantageous for the laboratory. Moreover, the correct laboratory approach is also clinically relevant, as patient management is ultimately affected, and an incorrect interpretation may lead to inappropriate therapies being established. Components of a mixing test that can influence result interpretation include the sensitivity of the used screening reagents to various factor deficiencies and inhibitors, the source or composition of the normal plasma, and the setting of cutoffs for the formula used in expressing mixing test results. Numerous and differing criteria for mixing test interpretation have been suggested historically, which can lead to confusion as to which approach is the most appropriate. The use of differing criteria will also lead to differing
Static and Dynamic Modeling of a Solar Active Region
NASA Astrophysics Data System (ADS)
Warren, Harry P.; Winebarger, Amy R.
2007-09-01
Recent hydrostatic simulations of solar active regions have shown that it is possible to reproduce both the total intensity and the general morphology of the high-temperature emission observed at soft X-ray wavelengths using static heating models. These static models, however, cannot account for the lower temperature emission. In addition, there is ample observational evidence that the solar corona is highly variable, indicating a significant role for dynamical processes in coronal heating. Because they are computationally demanding, full hydrodynamic simulations of solar active regions have not been considered previously. In this paper we make first application of an impulsive heating model to the simulation of an entire active region, AR 8156 observed on 1998 February 16. We model this region by coupling potential field extrapolations to full solutions of the time-dependent hydrodynamic loop equations. To make the problem more tractable we begin with a static heating model that reproduces the emission observed in four different Yohkoh Soft X-Ray Telescope (SXT) filters and consider impulsive heating scenarios that yield time-averaged SXT intensities that are consistent with the static case. We find that it is possible to reproduce the total observed soft X-ray emission in all of the SXT filters with a dynamical heating model, indicating that nanoflare heating is consistent with the observational properties of the high-temperature solar corona. At EUV wavelengths the simulated emission shows more coronal loops, but the agreement between the simulation and the observation is still not acceptable.
A new physical model for earthquake time interval distribution
NASA Astrophysics Data System (ADS)
Liu, Guoliang
2017-01-01
This paper reports a new physical model for time interval distribution of earthquakes, which was obtained by borrowing the idea from the research in the time interval distribution of sand-dust storms. Of the model, it was hypothesized that the earthquakes were induced by the magma movement inside the earth, and if the speed of magma ≥ threshold value Ut, the earthquakes with magnitude ≥ M occurred. With this model, it was obtained that for the earthquakes with magnitude ≥ M there existed lg N(> t) = c - dt, where N was the number of time intervals longer than t; the value d decreased with M. This result was also verified by analyzing the earthquake data from the China Earthquake Networks Center (CENC).
Ground-based observations of time variability in multiple active volcanoes on Io
NASA Astrophysics Data System (ADS)
Rathbun, Julie A.; Spencer, John R.
2010-10-01
Since before the beginning of the Galileo spacecraft's Jupiter orbital tour, we have observed Io from the ground using NASA's Infrared Telescope Facility (IRTF). We obtained images of Io in reflected sunlight and in-eclipse at 2.3, 3.5, and 4.8 μm. In addition, we have measured the 3.5 μm brightness of an eclipsed Io as it is occulted by Jupiter. These lightcurves enable us to measure the brightness and one-dimensional location of active volcanoes on the surface. During the Galileo era, two volcanoes were observed to be regularly active: Loki and either Kanehekili and/or Janus. At least 12 other active volcanoes were observed for shorter periods of time, including one distinguishable in images that include reflected sunlight. These data can be used to compare volcano types and test volcano eruption models, such as the lava lake model for Loki.
Time domain analysis of the weighted distributed order rheological model
NASA Astrophysics Data System (ADS)
Cao, Lili; Pu, Hai; Li, Yan; Li, Ming
2016-11-01
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
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.
Model predictive control of P-time event graphs
NASA Astrophysics Data System (ADS)
Hamri, H.; Kara, R.; Amari, S.
2016-12-01
This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.
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.
Impact of Structured Movement Time on Preschoolers' Physical Activity Engagement
ERIC Educational Resources Information Center
Palmer, Kara K.; Matsuyama, Abigail L.; Robinson, Leah E.
2017-01-01
Preschool-aged children are not meeting national physical activity recommendations. This study compares preschoolers' physical activity engagement during two different physical activity opportunities: outdoor free play or a structured movement session. Eighty-seven children served as participants: 40 children participated in outdoor free play and…
Time-dependent buoyant puff model for explosive sources
Kansa, E.J.
1997-01-01
Several models exist to predict the time dependent behavior of bouyant puffs that result from explosions. This paper presents a new model that is derived from the strong conservative form of the conservation partial differential equations that are integrated over space to yield a coupled system of time dependent nonlinear ordinary differential equations. This model permits the cloud to evolve from an intial spherical shape not an ellipsoidal shape. It ignores the Boussinesq approximation, and treats the turbulence that is generated by the puff itself and the ambient atmospheric tubulence as separate mechanisms in determining the puff history. The puff cloud rise history was found to depend no only on the mass and initial temperature of the explosion, but also upon the stability conditions of the ambient atmosphere. This model was calibrated by comparison with the Roller Coaster experiments.
Time-delayed model of immune response in plants.
Neofytou, G; Kyrychko, Y N; Blyuss, K B
2016-01-21
In the studies of plant infections, the plant immune response is known to play an essential role. In this paper we derive and analyse a new mathematical model of plant immune response with particular account for post-transcriptional gene silencing (PTGS). Besides biologically accurate representation of the PTGS dynamics, the model explicitly includes two time delays to represent the maturation time of the growing plant tissue and the non-instantaneous nature of the PTGS. Through analytical and numerical analysis of stability of the steady states of the model we identify parameter regions associated with recovery and resistant phenotypes, as well as possible chronic infections. Dynamics of the system in these regimes is illustrated by numerical simulations of the model.
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.
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
Real-time model based electrical powered wheelchair control.
Wang, Hongwu; Salatin, Benjamin; Grindle, Garrett G; Ding, Dan; Cooper, Rory A
2009-12-01
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 3D 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.
Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles.
Lane, Kevin J; Levy, Jonathan I; Scammell, Madeleine Kangsen; Patton, Allison P; Durant, John L; Mwamburi, Mkaya; Zamore, Wig; Brugge, Doug
2015-01-01
Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time.
Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles
Lane, Kevin J; Levy, Jonathan I; Scammell, Madeleine Kangsen; Patton, Allison P; Durant, John L; Mwamburi, Mkaya; Zamore, Wig; Brugge, Doug
2015-01-01
Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time. PMID:25827314
Electromechanical Modelling of an Active Isolation System
1991-04-01
Department of Mechanical Engineering, Auburn University, Auburn , AL 36849, U.S.A. Active Control of Automobile Two-Stage Suspension System-Half Car Model...element model ..... one d.imensnional modelo -ilo0- S-120 1 L 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Frequency(f/fO) 6(b) Sensor Voltage S20 10 16
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.
Numerical modeling of microwave switchers with subpicosecond time delay
NASA Astrophysics Data System (ADS)
Konoplev, B.; Ryndin, E.
2016-12-01
In this article the layout and structure of the microwave switcher based on the managed electron density maximum rearrangement in multi-contacts functionally integrated active region are considered. The basis of the microwave switcher is a normally opened high electron mobility transistor structure (HEMT) with multiple Schottky gates and the corresponding number of switching ohmic contacts. In this research two-dimensional finite-difference physical and topological model of the considered microwave switchers is proposed. The distinctive features of the proposed model are combination of two different sets of variables and explicit first-order upwind discretization scheme for the normalized continuity equation. The obtained results of numerical modeling are discussed.
Verification of biological models with Timed Hybrid Petri Nets
NASA Astrophysics Data System (ADS)
Troncale, S.; Comet, J.-P.; Bernot, G.
2007-11-01
The formalism of Hybrid Functional Petri Nets (HFPN) has proved its convenience for simulating biological systems. The drawback of the noticeable expressiveness of HFPN is the difficulty to perform formal verifications of dynamical properties. In this article, we propose a model-checking procedure for Timed Hybrid Petri Nets (THPN), a sub-class of HFPN. This procedure is based on the translation of the THPN model and of the studied property into real-time automata. It is applied to a sub-network involved in amphibian metamorphosis.
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.
NASA Astrophysics Data System (ADS)
She, M.; Jiang, L. P.
2014-12-01
In this paper, an oscillating dark energy model is presented in an isotropic but inhomogeneous plane symmetric space-time by considering a time periodic varying deceleration parameter. We find three different types of new solutions which describe different scenarios of oscillating universe. The first two solutions show an oscillating universe with singularities. For the third one, the universe is singularity-free during the whole evolution. Moreover, the Hubble parameter oscillates and keeps positive which explores an interesting possibility to unify the early inflation and late time acceleration of the universe.
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.
Modeling of Time Varying Slag Flow in Coal Gasifiers
Pilli, Siva Prasad; Johnson, Kenneth I.; Williford, Ralph E.; Sundaram, S. K.; Korolev, Vladimir N.; Crum, Jarrod V.
2008-08-30
There is considerable interest within government agencies and the energy industries across the globe to further advance the clean and economical conversion of coal into liquid fuels to reduce our dependency on imported oil. To date, advances in these areas have been largely based on experimental work. Although there are some detailed systems level performance models, little work has been done on numerical modeling of the component level processes. If accurate models are developed, then significant R&D time might be saved, new insights into the process might be gained, and some good predictions of process or performance can be made. One such area is the characterization of slag deposition and flow on the gasifier walls. Understanding slag rheology and slag-refractory interactions is critical to design and operation of gasifiers with extended refractory lifetimes and also to better control of operating parameters so that the overall gasifier performance with extended service life can be optimized. In the present work, the literature on slag flow modeling was reviewed and a model similar to Seggiani’s was developed to simulate the time varying slag accumulation and flow on the walls of a Prenflo coal gasifier. This model was further extended and modified to simulate a refractory wall gasifier including heat transfer through the refractory wall with flowing slag in contact with the refractory. The model was used to simulate temperature dependent slag flow using rheology data from our experimental slag testing program. These modeling results as well as experimental validation are presented.
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.
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
Thermosphere-Ionosphere-Mesosphere Modeling Using the TIME-GCM
2014-09-30
Thermosphere-Ionosphere-Mesosphere Modeling Using the TIME-GCM Raymond G. Roble High Altitude Observatory National Center for Atmospheric...ORGANIZATION NAME(S) AND ADDRESS(ES) High Altitude Observatory,National Center for Atmospheric Research,,Box 3000,,Boulder,,CO, 80307 8. PERFORMING...climate model that extends from the ground, including oceans, to 500 km altitude to study global atmospheric variability and couplings. A project is
Finding a fractional model from frequency and time responses
NASA Astrophysics Data System (ADS)
Valério, Duarte; Sá da Costa, José
2010-04-01
An existing method for identifying an integer model from frequency data, developed to be used when synthesising second-generation Crone controllers, is adapted to identify fractional order plants. The modification only allows models with poles but no zeros or zeros but no poles. Two application examples are given, one of them showing how the method can also be used when a time response, rather than a frequency response, is available.
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.
Prediction limits of mobile phone activity modelling
Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo
2017-01-01
Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events. PMID:28386443
Patterns of leisure time and non-leisure time physical activity of Korean immigrant women.
Choi, Jiwon; Wilbur, Joellen; Kim, Mi Ja
2011-02-01
Our purpose in this study was to examine the patterns of physical activity and demographic characteristics associated with those patterns in Korean immigrants in the United States. Participants were 197 women, and the International Physical Activity Questionnaire was utilized. The inactive pattern was the most frequent pattern in all domains of physical activity except household physical activity. There were differences among the patterns of physical activity that were associated with variations in demographic characteristics. Health care providers who serve immigrants should assess physical activity level and demographic characteristics of the immigrants to enhance their physical activity.
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.
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.
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.
Time and Frequency Activities at the JHU Applied Physics Laboratory
2009-11-01
Resolution Offset Generator 2 GPS Time Transfer Receivers Time and Frequency Dissemination 1 MHz, 5 MHz, 10 MHz, 100 MHz 1 PPS IRIG ...B APL Local Time IRIG -B UTC Common View GPS Time Transfer •NIST, USNO, BIPM 41 st Annual Precise Time and Time Interval (PTTI) Meeting...MASER* CESIUM 3 MICROPHASE STEPPER 5 MHZ DISTRIBUTION APL TIMESCALE PROCESSOR PREDICTION ALGORITHM TIMECODE 1PPS & IRIG 8 CHANNEL GPS A
Integrated Sachs-Wolfe effect in time varying vacuum model
Wang, Y. T.; Gui, Y. X.; Xu, L. X.; Lu, J. B.
2010-04-15
The integrated Sachs-Wolfe (ISW) effect is an important implication for dark energy. In this paper, we have calculated the power spectrum of the ISW effect in the time varying vacuum cosmological model, where the model parameter {beta}=4.407 is obtained by the observational constraint of the growth rate. It is found that the source of the ISW effect is not only affected by the different evolutions of the Hubble function H(a) and the dimensionless matter density {Omega}{sub m}(a), but also by the different growth function D{sub +}(a), all of which are changed due to the presence of a matter production term in the time varying vacuum model. However, the difference of the ISW effect in the {Lambda}(t)CDM model and the {Lambda}CDM model is lessened to a certain extent because of the integration from the time of last scattering to the present. It is implied that the observations of the galaxies with high redshift are required to distinguish the two models.
LATEST: A model of saccadic decisions in space and time.
Tatler, Benjamin W; Brockmole, James R; Carpenter, R H S
2017-04-01
Many of our actions require visual information, and for this it is important to direct the eyes to the right place at the right time. Two or three times every second, we must decide both when and where to direct our gaze. Understanding these decisions can reveal the moment-to-moment information priorities of the visual system and the strategies for information sampling employed by the brain to serve ongoing behavior. Most theoretical frameworks and models of gaze control assume that the spatial and temporal aspects of fixation point selection depend on different mechanisms. We present a single model that can simultaneously account for both when and where we look. Underpinning this model is the theoretical assertion that each decision to move the eyes is an evaluation of the relative benefit expected from moving the eyes to a new location compared with that expected by continuing to fixate the current target. The eyes move when the evidence that favors moving to a new location outweighs that favoring staying at the present location. Our model provides not only an account of when the eyes move, but also what will be fixated. That is, an analysis of saccade timing alone enables us to predict where people look in a scene. Indeed our model accounts for fixation selection as well as (and often better than) current computational models of fixation selection in scene viewing. (PsycINFO Database Record
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.
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
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.
A field test of the TIME patient simulation model.
Harless, W G; Duncan, R C; Zier, M A; Ayers, W R; Berman, J R; Pohl, H S
1990-05-01
The Technological Innovations in Medical Education (TIME) Project has created an interactive videodisc patient-simulation model that provides faculty with a new method for patient-centered teaching in the medical school classroom. The TIME model is designed to be controlled by a professor in the classroom setting, and incorporates voice recognition technology and video dramatization to create a believable patient encounter. Under the auspices of the Lister Hill National Center for Biomedical Communications, National Library of Medicine, where the Project originated in 1983, three medical schools participated in a field test of this "high-tech" model. Six faculty members made ten classroom presentations of two TIME simulations to 306 second-year medical students. The principal finding was that, in a group setting, a large majority of the students at all three schools became individually committed to the care and management of the simulated patient. They acted as if the patient's problems were real and left the session feeling as though they had interacted with an actual person. Therefore, in terms of simulating a real patient, the TIME patient-simulation model was validated, providing the basis for the development of new patient-centered methods to teach and test medical students in the classroom setting. The Project has been at the Georgetown University School of Medicine, where the model is being introduced into the existing curriculum, since 1988. It is currently being used as a part of the final examination for second-year students and in discussion-group settings for fourth-year students in the internal medicine clerkship. A field test is also under way using the TIME model to assess the clinical performance of third-year students.
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.
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.
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.
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.
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.
A Stochastic-Dynamic Model for Real Time Flood Forecasting
NASA Astrophysics Data System (ADS)
Chow, K. C. A.; Watt, W. E.; Watts, D. G.
1983-06-01
A stochastic-dynamic model for real time flood forecasting was developed using Box-Jenkins modelling techniques. The purpose of the forecasting system is to forecast flood levels of the Saint John River at Fredericton, New Brunswick. The model consists of two submodels: an upstream model used to forecast the headpond level at the Mactaquac Dam and a downstream model to forecast the water level at Fredericton. Inputs to the system are recorded values of the water level at East Florenceville, the headpond level and gate position at Mactaquac, and the water level at Fredericton. The model was calibrated for the spring floods of 1973, 1974, 1977, and 1978, and its usefulness was verified for the 1979 flood. The forecasting results indicated that the stochastic-dynamic model produces reasonably accurate forecasts for lead times up to two days. These forecasts were then compared to those from the existing forecasting system and were found to be as reliable as those from the existing system.
Effect of time of day on bird activity
Robbins, C.S.; Ralph, C. John; Scott, J. Michael
1981-01-01
Breeding season activity, based on detections recorded on more than a million 3. minute Breeding Bird Survey stops, reaches a peak for most species during the hour centered at sunrise or in the following hour. Activity of most species then declines gradually as the morning progresses. When large samples are considered, activity patterns for a given species are quite constant from year to year; but each species has its own characteristic pattern and there is much similarity among members of the same genus. Activity reaches a low point in midday, and may almost cease in some habitats (e. g. deserts); but in deciduous forests, activity of many species continues at a reduced rate. By reducing walking rate or lengthening listening periods, productive censusing of many species could be extended into midday. Winter activity is even more strongly oriented toward the early morning.
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.
Simplified Modeling of Active Magnetic Regenerators
NASA Astrophysics Data System (ADS)
Burdyny, Thomas
Active magnetic regenerator (AMR) refrigeration is an alternative technology to conventional vapor-compression refrigerators that has the potential to operate at higher efficiencies. Based on the magnetocaloric effect, this technology uses the magnetization and demagnetization of environmentally neutral solid refrigerants to produce a cooling effect. To become competitive however, a large amount of research into the optimal device configurations, operating parameters and refrigerants is still needed. To aid in this research, a simplified model for predicting the general trends of AMR devices at a low computational cost is developed. The derivation and implementation of the model for an arbitrary AMR is presented. Simulations from the model are compared to experimental results from two different devices and show good agreement across a wide range of operating parameters. The simplified model is also used to study the impacts of Curie temperature spacing, material weighting and devices on the performance of multilayered regenerators. Future applications of the simplified AMR model include costing and optimization programs where the low computational demand of the model can be fully exploited.
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.
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.
Spatio-temporal modeling of Active Layer Thickness
NASA Astrophysics Data System (ADS)
Touyz, J.; Apanasovich, T. V.; Streletskiy, D. A.; Shiklomanov, N. I.
2015-12-01
Arctic Regions are experiencing an unprecedented rate of environmental and climate change. The active layer (the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climate and environmental changes and plays an important role in the functioning of Arctic ecosystems, planning, and economic activities. Knowledge about spatio-temporal variability of ALT is crucial for environmental and engineering applications. The objective of this study is to provide the methodology to model and estimate spatio-temporal variation in the active layer thickness (ALT) at several sites located in the Circumpolar region spanning the Alaska North Slope, and to demonstrate its use in spatio-temporal interpolation as well as time-forward prediction. In our data analysis we estimate a parametric trend and examine residuals for the presence of spatial and temporal dependence. We propose models that provide a description of residual space-time variability in ALT. Formulations that take into account interaction among spatial and temporal components are also developed. Moreover, we compare our models to naive models in which residual spatio-temporal and temporal correlations are not considered. The predicted root mean squared and absolute errors are significantly reduced when our approach is employed. While the methodology is developed in the context of ALT, it can also be applied to model and predict other environmental variables which use similar spatio-temporal sampling designs.
A Region of Proximal Learning Model of Study Time Allocation
ERIC Educational Resources Information Center
Metcalfe, J.; Kornell, N.
2005-01-01
A Region of Proximal Learning model is proposed emphasizing two components to people's study time allocation, controlled by different metacognitive indices. The first component is choice, which is further segmented into two stages: (1) a decision of whether to study or not and (2) the order of priority of items chosen. If the people's Judgments of…
Examining the role of finite reaction times in swarming models
NASA Astrophysics Data System (ADS)
Copenhagen, Katherine; Quint, David; Gopinathan, Ajay
2015-03-01
Modeling collective behavior in biological and artificial systems has had much success in recent years at predicting and mimicing real systems by utilizing techniques borrowed from modelling many particle systems interacting with physical forces. However unlike inert particles interacting with instantaneous forces, living organisms have finite reaction times, and behaviors that vary from individual to individual. What constraints do these physiological effects place on the interactions between individuals in order to sustain a robust ordered state? We use a self-propelled agent based model in continuous space based on previous models by Vicsek and Couzin including alignment and separation maintaining interactions to examine the behavior of a single cohesive group of organisms. We found that for very short reaction times the system is able to form an ordered state even in the presence of heterogeneities. However for larger more physiological reaction times organisms need a buffer zone with no cohesive interactions in order to maintain an ordered state. Finally swarms with finite reaction times and behavioral heterogeneities are able to dynamically sort out individuals with impaired function and sustain order.
A Field Test of the TIME Patient Simulation Model.
ERIC Educational Resources Information Center
Harless, William G.; And Others
1990-01-01
The Technological Innovations in Medical Education (TIME) model, designed to be controlled by a professor in the classroom, incorporates voice recognition technology and video dramatization to create a believable patient encounter. A field test finding was that the students became committed to the care and management of the simulated patient.…
Model for LMFBR core transient analysis in real-time
Tzanos, C.P.
1986-01-01
This paper discusses the modeling of LMFBR core transients. It is shown that with a proper choice of shape functions a nodal approximation of the coolant, cladding, and fuel temperature distributions leads to adequately accurate power and temperature predictions, as well as adequately short computation times.
Rapid Analysis Model: Reducing Analysis Time without Sacrificing Quality.
ERIC Educational Resources Information Center
Lee, William W.; Owens, Diana
2001-01-01
Discusses the performance technology design process and the fact that the analysis phase is often being eliminated to speed up the process. Proposes a rapid analysis model that reduces time needed for analysis and still ensures more successful value-added solutions that focus on customer satisfaction. (LRW)
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…
Comparison of residence time models for cascading rotary dryers
Cao, W.F.; Langrish, T.A.G.
1999-04-01
The predictions of the models of Matchett and Baker (1988), Saeman and Mitchell (1954) and Friedman and Marshall (1949) for the solids residence time in rotary dryers have been compared with both pilot-scale and industrial-scale data. A countercurrent pilot-scale dryer of 0.2m diameter and 2m long has been used with air velocities up to 1.5 m to measure the residence times of sorghum grain. The average discrepancy for the solids residence time between the predictions and the experiments that were carried out in the pilot-scale rotary dryer is {minus}10.4%. Compared with the models of Friedman and Marshall (1949) and Saeman and Mitchell (1954) for the pilot-scale data obtained here, the Matchett and Baker model is more satisfactory for predicting the solids residence time in this pilot-scale dryer. It has also been found that the model of Matchett and Baker describes the industrial data of Saeman and Mitchell (1954) than the correlation of Friedman and Marshall (1949).
A Novel Study: A Situation Model Analysis of Reading Times
ERIC Educational Resources Information Center
McNerney, M. Windy; Goodwin, Kerri A.; Radvansky, Gabriel A.
2011-01-01
One of the basic findings on situation models and language comprehension is that reading times are affected by the changing event structure in a text. However, many studies have traditionally used multiple, relatively short texts, in which there is little event consistency across the texts. It is unclear to what extent such changes will be…
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.
Park, Kyoung-Jin; Kwon, Eui-Hoon; Ma, Youngeun; Park, In-Ae; Kim, Seon-Woo; Kim, Sun-Hee; Kim, Hee-Jin
2012-01-01
The activated partial thromboplastin time (aPTT) is a widely used coagulation screening test in routine laboratories. The aPTT level in the control population varies and is reflected by the reference interval. However, there have been no studies to investigate the coagulation status determining the variability of the aPTT. The aim of this study was to investigate the coagulation factor activities underlying the variability of aPTT in the population. The study participants were reference individuals with prothrombin time and aPTT within reference intervals. The aPTT was determined using STA-PTT Automate (Diagnostica Stago, Asnieres, France; local reference interval, 29.1-41.9 s). Those with aPTT within the marginal ranges of reference interval were selected for factor assays. We defined the lower marginal group as the lowest 10 percentile of reference interval (29.1-30.9 s) and the upper marginal group as the highest 10 percentile (38.0-41.9 s). Activities of factor II, V, VIII, IX, X, XI, and XII were determined in both groups. The lower marginal and upper marginal groups consisted of 220 and 209 individuals, respectively. All coagulation factors were significantly higher in the lower marginal than in the upper marginal group (P = 0.0127 for factor II and P < 0.0001 for the others). Multiple logistic regression analyses revealed factor XII and VIII were two strongest contributors determining the aPTT level, whereas factor XI was not significantly different between the groups (P = 0.095). This study firstly demonstrated significantly different coagulation factor activities underlying the variability of aPTT in reference individuals. The results suggested the possibility of disease association or phenotypic contribution of variable coagulation activities in the population.
Modeling geomagnetic storms on prompt and diffusive time scales
NASA Astrophysics Data System (ADS)
Li, Zhao
The discovery of the Van Allen radiation belts in the 1958 was the first major discovery of the Space Age. There are two belts of energetic particles. The inner belt is very stable, but the outer belt is extremely variable, especially during geomagnetic storms. As the energetic particles are hazardous to spacecraft, understanding the source of these particles and their dynamic behavior driven by solar activity has great practical importance. In this thesis, the effects of magnetic storms on the evolution of the electron radiation belts, in particular the outer zone, is studied using two types of numerical simulation: radial diffusion and magnetohydrodynamics (MHD) test-particle simulation. A radial diffusion code has been developed at Dartmouth, applying satellite measurements to model flux as an outer boundary condition, exploring several options for the diffusion coefficient and electron loss time. Electron phase space density is analyzed for July 2004 coronal mass ejection (CME) driven storms and March-April 2008 co-rotating interaction region (CIR) driven storms, and compared with Global Positioning System (GPS) satellite measurements within 5 degrees of the magnetic equator at L=4.16. A case study of a month-long interval in the Van Allen Probes satellite era, March 2013, confirms that electron phase space density is well described by radial diffusion for the whole month at low first invariant <400~MeV/G, but peaks in phase space density observed by the ECT instrument suite at higher first invariant are not reproduced by radial transport from a source at higher L. A 3D guiding center code with plasmasheet injection is used to simulate particle motion in time-dependent MHD fields calculated from the Lyon-Fedder-Mobarry global MHD code, as an extension of the Hudson et al. (2012) study of the Whole Heliosphere Interval of CIR-driven storms in March-April 2008. Direct comparison with measured fluxes at GOES show improved comparison with observations relative to
A diagnostic process extended in time as a fuzzy model
NASA Astrophysics Data System (ADS)
Rakus-Andersson, Elisabeth; Gerstenkorn, Tadeusz
1999-03-01
The paper refers to earlier results obtained by the authors and constitutes their essential complement and extension by introducing to a diagnostic model the assumption that the decision concerning the diagnosis is based on observations of symptoms carried out repeatedly, by stages, which may have effect in a change of these symptoms in increasing time. The model concerns the observations of symptoms at an individual patient at a time interval. The changes of the symptoms give some additional information, sometimes very important in the diagnostic process when the clinical picture of a patient in a certain interval of time differs from that one which has been received from the beginning of the disease. It may occur that the change in the intensity of a symptom decides an acceptance of another diagnosis after some time when the patient does not feel better. The aim is to fix an optimal diagnosis on the basis of clinical symptoms typical of several morbid units with respect to the changes of these symptoms in time. In order to solve such a posed problem the authors apply the method of fuzzy relation equations which are modelled by means of logical rules of inference. Moreover, in the final decision concerning the choice of a proper diagnosis, a normed Euclidean distance is introduced as a measure between a real decision and an "ideal" decision. A simple example presents the practical action of the method to show its relevance to a possible user.
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
Improved jet noise modeling using a new time-scale.
Azarpeyvand, M; Self, R H
2009-09-01
To calculate the noise emanating from a turbulent flow using an acoustic analogy knowledge concerning the unsteady characteristics of the turbulence is required. Specifically, the form of the turbulent correlation tensor together with various time and length-scales are needed. However, if a Reynolds Averaged Navier-Stores calculation is used as the starting point then one can only obtain steady characteristics of the flow and it is necessary to model the unsteady behavior in some way. While there has been considerable attention given to the correct way to model the form of the correlation tensor less attention has been given to the underlying physics that dictate the proper choice of time-scale. In this paper the authors recognize that there are several time dependent processes occurring within a turbulent flow and propose a new way of obtaining the time-scale. Isothermal single-stream flow jets with Mach numbers 0.75 and 0.90 have been chosen for the present study. The Mani-Gliebe-Balsa-Khavaran method has been used for prediction of noise at different angles, and there is good agreement between the noise predictions and observations. Furthermore, the new time-scale has an inherent frequency dependency that arises naturally from the underlying physics, thus avoiding supplementary mathematical enhancements needed in previous modeling.
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)
Minimal model for short-time diffusion in periodic potentials.
Emary, Clive; Gernert, Robert; Klapp, Sabine H L
2012-12-01
We investigate the dynamics of a single, overdamped colloidal particle, which is driven by a constant force through a one-dimensional periodic potential. We focus on systems with large barrier heights where the lowest-order cumulants of the density field, that is, average position and the mean-squared displacement, show nontrivial (nondiffusive) short-time behavior characterized by the appearance of plateaus. We demonstrate that this "cage-like" dynamics can be well described by a discretized master equation model involving two states (related to two positions) within each potential valley. Nontrivial predictions of our approach include analytic expressions for the plateau heights and an estimate of the "de-caging time" obtained from the study of deviations from Gaussian behavior. The simplicity of our approach means that it offers a minimal model to describe the short-time behavior of systems with hindered dynamics.
Dose-time-response modeling using negative binomial distribution.
Roy, Munmun; Choudhury, Kanak; Islam, M M; Matin, M A
2013-01-01
People exposed to certain diseases are required to be treated with a safe and effective dose level of a drug. In epidemiological studies to find out an effective dose level, different dose levels are applied to the exposed and a certain number of cures is observed. Negative binomial distribution is considered to fit overdispersed Poisson count data. This study investigates the time effect on the response at different time points as well as at different dose levels. The point estimation and confidence bands for ED(100p)(t) and LT(100p)(d) are formulated in closed form for the proposed dose-time-response model with the negative binomial distribution. Numerical illustrations are carried out in order to check the performance level of the proposed model.
The Near Real Time Ionospheric Model of Latvia
NASA Astrophysics Data System (ADS)
Kaļinka, M.; Zvirgzds, J.; Dobelis, D.; Lazdāns, E.; Reiniks, M.
2015-11-01
A highly accurate ionosphere model is necessary to enable a fast and reliable coordinate determination with GNSS in real time. It is a partially ionized atmospheric region ranging up to 1,000 km height, affected by spatial variations, space weather, seasonal and solar cycle dependence. New approaches and algorithms of modelling techniques are sought to provide better solutions in the territory of Latvia. Ionospheric TEC value has large differences in Western Latvia and Eastern Latvia. Actual ionospheric map should be calculated and delivered to the surveyors near real time and published on the WEB. Delivering actual map to rover GNSS devices in a field will provide the surveyors with ionospheric conditions and allow choosing best time for surveying and making geodetic measurements with higher accuracy and reliability.
Hwang, Yaw-Huei; Chen, Yen-Ting; Yeh, Jao-Yu; Liang, Huey-Wen
2010-10-01
This study aimed to examine the effects of passive and non-computer work time on the estimation of computer use times by electronic activity monitoring. A total of 20 subjects with computers were monitored for 3 h. Average relative error for total computer use time estimation was about 4%, given that non-computer work time was 20% of the 3-h monitored period. No significant impact of passive computer use time was found in this study. Non-computer work time of 40% or less is suggested as criteria for the application of electronic activity monitoring to ensure reliability in the physical work loading assessment. Statement of Relevance: This research studied the criteria of non-computer work time for the appropriate use of electronic activity monitoring to ensure reliability in the assessment of physical work loading. It is suggested that it should be set to 40% or less of the 3-h monitoring period.
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.
Statistical modelling of agrometeorological time series by exponential smoothing
NASA Astrophysics Data System (ADS)
Murat, Małgorzata; Malinowska, Iwona; Hoffmann, Holger; Baranowski, Piotr
2016-01-01
Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, long-term meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.
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.
An Activation Threshold Model for Response Inhibition
MacDonald, Hayley J.; McMorland, Angus J. C.; Stinear, Cathy M.; Coxon, James P.; Byblow, Winston D.
2017-01-01
Reactive response inhibition (RI) is the cancellation of a prepared response when it is no longer appropriate. Selectivity of RI can be examined by cueing the cancellation of one component of a prepared multi-component response. This substantially delays execution of other components. There is debate regarding whether this response delay is due to a selective neural mechanism. Here we propose a computational activation threshold model (ATM) and test it against a classical “horse-race” model using behavioural and neurophysiological data from partial RI experiments. The models comprise both facilitatory and inhibitory processes that compete upstream of motor output regions. Summary statistics (means and standard deviations) of predicted muscular and neurophysiological data were fit in both models to equivalent experimental measures by minimizing a Pearson Chi-square statistic. The ATM best captured behavioural and neurophysiological dynamics of partial RI. The ATM demonstrated that the observed modulation of corticomotor excitability during partial RI can be explained by nonselective inhibition of the prepared response. The inhibition raised the activation threshold to a level that could not be reached by the original response. This was necessarily followed by an additional phase of facilitation representing a secondary activation process in order to reach the new inhibition threshold and initiate the executed component of the response. The ATM offers a mechanistic description of the neural events underlying RI, in which partial movement cancellation results from a nonselective inhibitory event followed by subsequent initiation of a new response. The ATM provides a framework for considering and exploring the neuroanatomical constraints that underlie RI. PMID:28085907
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.
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.
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.
Solvable time-dependent models in quantum mechanics
NASA Astrophysics Data System (ADS)
Cordero-Soto, Ricardo J.
In the traditional setting of quantum mechanics, the Hamiltonian operator does not depend on time. While some Schrodinger equations with time-dependent Hamiltonians have been solved, explicitly solvable cases are typically scarce. This thesis is a collection of papers in which this first author along with Suslov, Suazo, and Lopez, has worked on solving a series of Schrodinger equations with a time-dependent quadratic Hamiltonian that has applications in problems of quantum electrodynamics, lasers, quantum devices such as quantum dots, and external varying fields. In particular the author discusses a new completely integrable case of the time-dependent Schrodinger equation in Rn with variable coefficients for a modified oscillator, which is dual with respect to the time inversion to a model of the quantum oscillator considered by Meiler, Cordero-Soto, and Suslov. A second pair of dual Hamiltonians is found in the momentum representation. Our examples show that in mathematical physics and quantum mechanics a change in the direction of time may require a total change of the system dynamics in order to return the system back to its original quantum state. The author also considers several models of the damped oscillators in nonrelativistic quantum mechanics in a framework of a general approach to the dynamics of the time-dependent Schrodinger equation with variable quadratic Hamiltonians. The Green functions are explicitly found in terms of elementary functions and the corresponding gauge transformations are discussed. The factorization technique is applied to the case of a shifted harmonic oscillator. The time-evolution of the expectation values of the energy related operators is determined for two models of the quantum damped oscillators under consideration. The classical equations of motion for the damped oscillations are derived for the corresponding expectation values of the position operator. Finally, the author constructs integrals of motion for several models
Effect of Time Step On Atmospheric Model Systematic Errors
NASA Astrophysics Data System (ADS)
Williamson, D. L.
Semi-Lagrangian approximations are becoming more common in operational Numer- ical Weather Prediction models because of the efficiency allowed by their long time steps. The early work that demonstrated that semi-Lagrangian forecasts were compa- rable to Eulerian in accuracy were based on mid-latitude short-range forecasts which were dominated by dynamical processes. These indicated no significant loss of accu- racy with semi-Lagrangian approximations and long time steps. Today, subgrid-scale parameterizations play a larger role in even short range forecasts. While not ignored, the effect of a longer time step on the parameterizations has been less thoroughly stud- ied. We present results from the NCAR CCM3 that indicate that the systematic errors in tropical precipitation patterns can depend on the time step. The actual dependency depends on the parameterization suite of the model. We identify the dependency in aqua-planet integrations. With the CCM3 parameterization suite, longer time steps re- sult in double precipitation maxima straddling the SST maximum while shorter time steps result in a single precipitation maximum over the SST maximum. Other param- eterization suites behave differently. The cause of the dependency will be discussed.
Unsupervised Classification During Time-Series Model Building.
Gates, Kathleen M; Lane, Stephanie T; Varangis, E; Giovanello, K; Guiskewicz, K
2016-12-07
Researchers who collect multivariate time-series data across individuals must decide whether to model the dynamic processes at the individual level or at the group level. A recent innovation, group iterative multiple model estimation (GIMME), offers one solution to this dichotomy by identifying group-level time-series models in a data-driven manner while also reliably recovering individual-level patterns of dynamic effects. GIMME is unique in that it does not assume homogeneity in processes across individuals in terms of the patterns or weights of temporal effects. However, it can be difficult to make inferences from the nuances in varied individual-level patterns. The present article introduces an algorithm that arrives at subgroups of individuals that have similar dynamic models. Importantly, the researcher does not need to decide the number of subgroups. The final models contain reliable group-, subgroup-, and individual-level patterns that enable generalizable inferences, subgroups of individuals with shared model features, and individual-level patterns and estimates. We show that integrating community detection into the GIMME algorithm improves upon current standards in two important ways: (1) providing reliable classification and (2) increasing the reliability in the recovery of individual-level effects. We demonstrate this method on functional MRI from a sample of former American football players.
Comparison of statistical models for analyzing wheat yield time series.
Michel, Lucie; Makowski, David
2013-01-01
The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha⁻¹ year⁻¹ in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale.
Comparison of Statistical Models for Analyzing Wheat Yield Time Series
Michel, Lucie; Makowski, David
2013-01-01
The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha−1 year−1 in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale. PMID:24205280
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
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
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.
Extended risk-analysis model for activities of the project.
Kušar, Janez; Rihar, Lidija; Zargi, Urban; Starbek, Marko
2013-12-01
Project management of product/service orders has become a mode of operation in many companies. Although these are mostly cyclically recurring projects, risk management is very important for them. An extended risk-analysis model for new product/service projects is presented in this paper. Emphasis is on a solution developed in the Faculty of Mechanical Engineering in Ljubljana, Slovenia. The usual project activities risk analysis is based on evaluation of the probability that risk events occur and on evaluation of their consequences. A third parameter has been added in our model: an estimate of the incidence of risk events. On the basis of the calculated activity risk level, a project team prepares preventive and corrective measures that should be taken according to the status indicators. An important advantage of the proposed solution is that the project manager and his team members are timely warned of risk events and they can thus activate the envisaged preventive and corrective measures as necessary.
Accurate early-time and late-time modeling of countercurrent spontaneous imbibition
NASA Astrophysics Data System (ADS)
March, Rafael; Doster, Florian; Geiger, Sebastian
2016-08-01
Spontaneous countercurrent imbibition into a finite porous medium is an important physical mechanism for many applications, included but not limited to irrigation, CO2 storage, and oil recovery. Symmetry considerations that are often valid in fractured porous media allow us to study the process in a one-dimensional domain. In 1-D, for incompressible fluids and homogeneous rocks, the onset of imbibition can be captured by self-similar solutions and the imbibed volume scales with √t. At later times, the imbibition rate decreases and the finite size of the medium has to be taken into account. This requires numerical solutions. Here we present a new approach to approximate the whole imbibition process semianalytically. The onset is captured by a semianalytical solution. We also provide an a priori estimate of the time until which the imbibed volume scales with √t. This time is significantly longer than the time it takes until the imbibition front reaches the model boundary. The remainder of the imbibition process is obtained from a self-similarity solution. We test our approach against numerical solutions that employ parametrizations relevant for oil recovery and CO2 sequestration. We show that this concept improves common first-order approaches that heavily underestimate early-time behavior and note that it can be readily included into dual-porosity models.
Waddington, Amelia; Appleby, Peter A.; De Kamps, Marc; Cohen, Netta
2012-01-01
Synfire chains have long been proposed to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been argued that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure. PMID:23162457
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 operators' emergency response time for chemical processing operations.
Murray, Susan L; Harputlu, Emrah; Mentzer, Ray A; Mannan, M Sam
2014-01-01
Operators have a crucial role during emergencies at a variety of facilities such as chemical processing plants. When an abnormality occurs in the production process, the operator often has limited time to either take corrective actions or evacuate before the situation becomes deadly. It is crucial that system designers and safety professionals can estimate the time required for a response before procedures and facilities are designed and operations are initiated. There are existing industrial engineering techniques to establish time standards for tasks performed at a normal working pace. However, it is reasonable to expect the time required to take action in emergency situations will be different than working at a normal production pace. It is possible that in an emergency, operators will act faster compared to a normal pace. It would be useful for system designers to be able to establish a time range for operators' response times for emergency situations. This article develops a modeling approach to estimate the time standard range for operators taking corrective actions or following evacuation procedures in emergency situations. This will aid engineers and managers in establishing time requirements for operators in emergency situations. The methodology used for this study combines a well-established industrial engineering technique for determining time requirements (predetermined time standard system) and adjustment coefficients for emergency situations developed by the authors. Numerous videos of workers performing well-established tasks at a maximum pace were studied. As an example, one of the tasks analyzed was pit crew workers changing tires as quickly as they could during a race. The operations in these videos were decomposed into basic, fundamental motions (such as walking, reaching for a tool, and bending over) by studying the videos frame by frame. A comparison analysis was then performed between the emergency pace and the normal working pace operations
Dust Activity during Winter Time in East Asia and Snowfall Obervations and Simulations in Taiwan
NASA Astrophysics Data System (ADS)
Tsai, L.
2013-12-01
Taiwan has relatively frequent snowfall in mountain during winter among regions of the same latitude. The phenomenon is contributed by Taiwan's unique topography - high and steep mountains, and geographical location - sitting on the route the continental polar air mass travels from its birthplace to the ocean, contribute to this phenomenon. Snow occurence, in addition to the freezing-point temperature, when two requirements are met: sufficient vapor and the condensation nuclei in the air. This study pursues the causes of the snowfall activity in Taiwan, the relations between the East Asian dust aerosol and the snowfall activity in Taiwan, and the impacts the climate changes have on the snowfall activity in Taiwan. In this study, Yushan snowfall activity from 1995~2011 and related atmosphere circulations were examined using SYNOP data, NCEP/DOE reanalysis atmospheric data, the observations of the Central Weather Bureau's Yushan Weather Station and the Taiwan Air Quality Monitoring Network of the Environment Protect Administration, Executive Yuan. To provide a quantitative measure of snowfall events and dust activity, a snowfall activity index (SAI) and the DAI Index by Yu et al. (2010) were defined. The time series of yearly SAI and DAI show that East Asian dust storm activity and Taiwan snowfall marked interannual variations during 1995 ~ 2011. For active years such as 2008, 2010, and 2011, SAI was hundreds of times larger than that for inactive years such as 1996, 1999 and 2003; and DAI in active years such as 2001 and 2002 was several tens of times larger than that in inactive years such as 1997 and 2003. In active years when the EAT (East Asian Trough) was shifted eastward, the strength of WPH (West Pacific High) increased in the south and an anticyclone thus occurred. This anticyclone introduced anomalous southwesterly flows along the southeastern coast of mainland China and over Taiwan, resulting in a wetter-than-normal atmosphere in support of snowfall
An immunological model for detecting bot activities
NASA Astrophysics Data System (ADS)
Karim, Md E.; Phoha, Vir V.; Sultan, Md A.
2009-05-01
We develop a hierarchical immunological model to detect bot activities in a computer network. In the proposed model antibody (detector)-antigen (foreign object) reactions are defined using negative selection based approach and negative systems-properties are defined by various temporal as well as non-temporal systems features. Theory of sequential hypothesis testing has been used in the literature for identifying spatial-temporal correlations among malicious remote hosts and among the bots within a botnet. We use it for combining multiple immunocomputing based decisions too. Negative selection based approach defines a self and helps identifying non-selves. We define non-selves with respect to various systems characteristics and then use different combinations of non-selves to design bot detectors. Each detector operates at the client sites of the network under surveillance. A match with any of the detectors suggests presence of a bot. Preliminary results suggest that the proposed model based solutions can improve the identification of bot activities.
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…
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…