Preference as a Function of Active Interresponse Times: A Test of the Active Time Model
ERIC Educational Resources Information Center
Misak, Paul; Cleaveland, J. Mark
2011-01-01
In this article, we describe a test of the active time model for concurrent variable interval (VI) choice. The active time model (ATM) suggests that the time since the most recent response is one of the variables controlling choice in concurrent VI VI schedules of reinforcement. In our experiment, pigeons were trained in a multiple concurrent…
Patterns of Activity Revealed by a Time Lag Analysis of a Model Active Region
NASA Astrophysics Data System (ADS)
Bradshaw, Stephen; Viall, Nicholeen
2016-05-01
We investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of average frequencies. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine an extrapolated magnetic skeleton with hydrodynamic and forward modeling codes to create a model active region, and apply the time lag method to synthetic observations. Our aim is to recover some typical properties and patterns of activity observed in active regions. Our key findings are: 1. Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. 2. Shorter coronal loops in the core cool more quickly than longer loops at the periphery. 3. All channel pairs show zero time lag when the line-of-sight passes through coronal loop foot-points. 4. There is strong evidence that plasma must be re-energized on a time scale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies operates across active regions. 5. Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.
ERIC Educational Resources Information Center
Fazio, C.; Guastella, I.; Tarantino, G.
2007-01-01
In this paper, we describe a pedagogical approach to elastic body movement based on measurements of the contact times between a metallic rod and small bodies colliding with it and on modelling of the experimental results by using a microcomputer-based laboratory and simulation tools. The experiments and modelling activities have been built in the…
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
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.
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
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].
Convergence dynamics of the Bak Sneppen model: Activity rate and waiting time distribution
NASA Astrophysics Data System (ADS)
Tirnakli, Ugur; Lyra, Marcelo L.
2007-02-01
In this work, we study the convergence dynamics of two independent random configurations of the Bak-Sneppen model of self-organized criticality evolving under the same external noise. A recently proposed measure of the Hamming distance which considers the minimum difference between displaced configurations is used. The displacement evolves in time intermittently. We compute the jump activity rate and waiting time distribution and report on their asymptotic power-law scaling which characterizes the slow relaxation and the absence of typical length and time scales typical of critical dynamical systems.
Active open boundary forcing using dual relaxation time-scales in downscaled ocean models
NASA Astrophysics Data System (ADS)
Herzfeld, M.; Gillibrand, P. A.
2015-05-01
Regional models actively forced with data from larger scale models at their open boundaries often contain motion at different time-scales (e.g. tidal and low frequency). These motions are not always individually well specified in the forcing data, and one may require a more active boundary forcing while the other exert less influence on the model interior. If a single relaxation time-scale is used to relax toward these data in the boundary equation, then this may be difficult. The method of fractional steps is used to introduce dual relaxation time-scales in an open boundary local flux adjustment scheme. This allows tidal and low frequency oscillations to be relaxed independently, resulting in a better overall solution than if a single relaxation parameter is optimized for tidal (short relaxation) or low frequency (long relaxation) boundary forcing. The dual method is compared to the single relaxation method for an idealized test case where a tidal signal is superimposed on a steady state low frequency solution, and a real application where the low frequency boundary forcing component is derived from a global circulation model for a region extending over the whole Great Barrier Reef, and a tidal signal subsequently superimposed.
Modelling the Effects of Ageing Time of Starch on the Enzymatic Activity of Three Amylolytic Enzymes
Guerra, Nelson P.; Pastrana Castro, Lorenzo
2012-01-01
The effect of increasing ageing time (t) of starch on the activity of three amylolytic enzymes (Termamyl, San Super, and BAN) was investigated. Although all the enzymatic reactions follow michaelian kinetics, vmax decreased significantly (P < 0.05) and KM increased (although not always significantly) with the increase in t. The conformational changes produced in the starch chains as a consequence of the ageing seemed to affect negatively the diffusivity of the starch to the active site of the enzymes and the release of the reaction products to the medium. A similar effect was observed when the enzymatic reactions were carried out with unaged starches supplemented with different concentrations of gelatine [G]. The inhibition in the amylolytic activities was best mathematically described by using three modified forms of the Michaelis-Menten model, which included a term to consider, respectively, the linear, exponential, and hyperbolic inhibitory effects of t and [G]. PMID:22666116
Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J
2015-06-01
This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. PMID:25843359
Forecasting geomagnetic activity at monthly and annual horizons: Time series models
NASA Astrophysics Data System (ADS)
Reikard, Gordon
2015-10-01
Most of the existing work on forecasting geomagnetic activity has been over short intervals, on the order of hours or days. However, it is also of interest to predict over longer horizons, ranging from months to years. Forecasting tests are run for the Aa index, which begins in 1868 and provides the longest continuous records of geomagnetic activity. This series is challenging to forecast. While it exhibits cycles at 11-22 years, the amplitude and period of the cycles varies over time. There is also evidence of discontinuous trending: the slope and direction of the trend change repeatedly. Further, at the monthly resolution, the data exhibits nonlinear variability, with intermittent large outliers. Several types of models are tested: regressions, neural networks, a frequency domain algorithm, and combined models. Forecasting tests are run at horizons of 1-11 years using the annual data, and 1-12 months using the monthly data. At the 1-year horizon, the mean errors are in the range of 13-17 percent while the median errors are in the range of 10-14 percent. The accuracy of the models deteriorates at longer horizons. At 5 years, the mean errors lie in the range of 21-23 percent, and at 11 years, 23-25 percent. At the 1 year horizon, the most accurate forecast is achieved by a combined model, but over longer horizons (2-11 years), the neural net dominates. At the monthly resolution, the mean errors are in the range of 17-19 percent at 1 month, while the median errors lie in a range of 14-17 percent. The mean error increases to 23-24 percent at 5 months, and 25 percent at 12 months. A model combining frequency and time domain methods is marginally better than regressions and neural networks alone, up to 11 months. The main conclusion is that geomagnetic activity can only be predicted to within a limited threshold of accuracy, over a given range of horizons. This is consistent with the finding of irregular trends and cycles in the annual data and nonlinear variability in
Ma, Yinzhong; Li, Li; Niu, Ziran; Song, Junke; Lin, Yihuang; Zhang, Huifang; Du, Guanhua
2016-05-01
The treatment of acute ischemic stroke (AIS) using thrombolysis with recombinant tissue-plasminogen activator (rtPA, alteplase) is limited by its narrow time window and the risk of hemorrhage. Recombinant plasminogen activator (rPA, reteplase) has been used clinically on coronary artery thrombosis and acute myocardial infarction. It is necessary to induce strokes experimentally as a means of validating the rPA timing on patients with AIS. However, current embolic models cannot mimic clinical situations well due to the embolus's composition of dried blood clots or artificial materials. In this paper, we used two novel rat thromboembolic models to determine the dosage-effect relationship and therapeutic time window of r-PA. Male rats were administered rPA or rtPA intravenously at 2-12h postischemia. Cerebral blood flow, behavioral outcomes and infarct volume within the same animal group were determined. Our results demonstrated that rPA (0.2 and 0.4mg/kg) or rtPA (0.2mg/kg) restored focal perfusion, reduced cerebral infarction, and improved behavioral outcomes at 2-4h postischemia. rPA but not rtPA significantly restored focal perfusion at 6h postischemia. However, delayed rPA-treatment neither decreased infarct volume nor improved the neurological disorder. Cerebral hemorrhage occurred at 6h postischemia detected by Evan's blue leakage and tissue hemoglobin content. Collectively, Thrombolysis with rPA may be beneficial in revascularization at an acceptable dosage of 0.2-0.4mg/kg within 6h after the cerebral infarct onset. PMID:27038532
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…
Statistical modeling of time-dependent fMRI activation effects.
Kalus, Stefanie; Bothmann, Ludwig; Yassouridis, Christina; Czisch, Michael; Sämann, Philipp G; Fahrmeir, Ludwig
2015-02-01
Functional magnetic resonance imaging (fMRI) activation detection within stimulus-based experimental paradigms is conventionally based on the assumption that activation effects remain constant over time. This assumption neglects the fact that the strength of activation may vary, for example, due to habituation processes or changing attention. Neither the functional form of time variation can be retrieved nor short-lasting effects can be detected by conventional methods. In this work, a new dynamic approach is proposed that allows to estimate time-varying effect profiles and hemodynamic response functions in event-related fMRI paradigms. To this end, we incorporate the time-varying coefficient methodology into the fMRI general regression framework. Inference is based on a voxelwise penalized least squares procedure. We assess the strength of activation and corresponding time variation on the basis of pointwise confidence intervals on a voxel level. Additionally, spatial clusters of effect curves are presented. Results of the analysis of an active oddball experiment show that activation effects deviating from a constant trend coexist with time-varying effects that exhibit different types of shapes, such as linear, (inversely) U-shaped or fluctuating forms. In a comparison to conventional approaches, like classical SPM, we observe that time-constant methods are rather insensitive to detect temporary effects, because these do not emerge when aggregated across the entire experiment. Hence, it is recommended to base activation detection analyses not merely on time-constant procedures but to include flexible time-varying effects that harbour valuable information on individual response patterns. PMID:25339617
A new costing model in hospital management: time-driven activity-based costing system.
Öker, Figen; Özyapıcı, Hasan
2013-01-01
Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas. PMID:23364414
Müftüler, Mine; İnce, Mustafa Levent
2015-08-01
This study examined how a physical activity course based on the Trans-Contextual Model affected the variables of perceived autonomy support, autonomous motivation, determinants of leisure-time physical activity behavior, basic psychological needs satisfaction, and leisure-time physical activity behaviors. The participants were 70 Turkish university students (M age=23.3 yr., SD=3.2). A pre-test-post-test control group design was constructed. Initially, the participants were randomly assigned into an experimental (n=35) and a control (n=35) group. The experimental group followed a 12 wk. trans-contextual model-based intervention. The participants were pre- and post-tested in terms of Trans-Contextual Model constructs and of self-reported leisure-time physical activity behaviors. Multivariate analyses showed significant increases over the 12 wk. period for perceived autonomy support from instructor and peers, autonomous motivation in leisure-time physical activity setting, positive intention and perceived behavioral control over leisure-time physical activity behavior, more fulfillment of psychological needs, and more engagement in leisure-time physical activity behavior in the experimental group. These results indicated that the intervention was effective in developing leisure-time physical activity and indicated that the Trans-Contextual Model is a useful way to conceptualize these relationships. PMID:26226283
NASA Astrophysics Data System (ADS)
Baxevanis, Th.
2008-08-01
A coarse-grained mean-field model is proposed where the damage enhanced creep of heterogeneous materials is described by the theory of absolute reaction rates. The dynamics of the proposed model, below a critical load, is characterized by an intensive precursor activity in the form of avalanches of microscopic breaking events that leads to a final catastrophic cascade occurring at a finite strain. Above the critical load, failure is instantaneous. The critical load is the static (elastic) fracture strength; thus the model is consistent with its time-independent analogue. Finally, the proposed model reproduces the experimental observations on the time evolution of the creep rate.
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
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
Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M
2015-11-01
To develop and test time series single site and multi-site placement models, we used wrist, hip and ankle processed accelerometer data to estimate energy cost and type of physical activity in adults. Ninety-nine subjects in three age groups (18-39, 40-64, 65 + years) performed 11 activities while wearing three triaxial accelereometers: one each on the non-dominant wrist, hip, and ankle. During each activity net oxygen cost (METs) was assessed. The time series of accelerometer signals were represented in terms of uniformly discretized values called bins. Support Vector Machine was used for activity classification with bins and every pair of bins used as features. Bagged decision tree regression was used for net metabolic cost prediction. To evaluate model performance we employed the jackknife leave-one-out cross validation method. Single accelerometer and multi-accelerometer site model estimates across and within age group revealed similar accuracy, with a bias range of -0.03 to 0.01 METs, bias percent of -0.8 to 0.3%, and a rMSE range of 0.81-1.04 METs. Multi-site accelerometer location models improved activity type classification over single site location models from a low of 69.3% to a maximum of 92.8% accuracy. For each accelerometer site location model, or combined site location model, percent accuracy classification decreased as a function of age group, or when young age groups models were generalized to older age groups. Specific age group models on average performed better than when all age groups were combined. A time series computation show promising results for predicting energy cost and activity type. Differences in prediction across age group, a lack of generalizability across age groups, and that age group specific models perform better than when all ages are combined needs to be considered as analytic calibration procedures to detect energy cost and type are further developed. PMID:26449155
Tronstad, Christian; Staal, Odd M; Saelid, Steinar; Martinsen, Orjan G
2015-08-01
Measurement of electrodermal activity (EDA) has recently made a transition from the laboratory into daily life with the emergence of wearable devices. Movement and nongelled electrodes make these devices more susceptible to noise and artifacts. In addition, real-time interpretation of the measurement is needed for user feedback. The Kalman filter approach may conveniently deal with both these issues. This paper presents a biophysical model for EDA implemented in an extended Kalman filter. Employing the filter on data from Physionet along with simulated noise and artifacts demonstrates noise and artifact suppression while implicitly providing estimates of model states and parameters such as the sudomotor nerve activation. PMID:26736861
NASA Astrophysics Data System (ADS)
Mirmomeni, M.; Kamaliha, E.; Shafiee, M.; Lucas, C.
2009-09-01
Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and magnitude of such catastrophic events still remain. There are, however, descriptor systems that describe a wider class of systems, including physical models and non-dynamic constraints. It is well known that the descriptor system is much tighter than the state-space expression for representing real independent parametric perturbations. In addition, the fuzzy descriptor models as a generalization of the locally linear neurofuzzy models are general forms that can be trained by constructive intuitive learning algorithms. Here, we propose a combined model based on fuzzy descriptor models and singular spectrum analysis (SSA) (FD/SSA) to forecast a number of geomagnetic activity indices in a manner that optimizes a fuzzy descriptor model for each of the principal components obtained from singular spectrum analysis and recombines the predicted values so as to transform the geomagnetic activity time series into natural chaotic phenomena. The method has been applied to predict two solar and geomagnetic activity indices: geomagnetic aa and solar wind speed (SWS) of the solar wind index. The results demonstrate the higher power of the proposed method-- compared to other methods -- for predicting solar activity.
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
Fresiello, Libera; Khir, Ashraf William; Di Molfetta, Arianna; Kozarski, Maciej; Ferrari, Gianfranco
2013-03-01
Despite 50 years of research to assess the intra-aortic balloon pump (IABP) effects on patients' hemodynamics, some issues related to the effects of this therapy are still not fully understood. One of these issues is the effect of IABP, its inflation timing and duration on peripheral circulation autonomic controls. This work provides a systematic analysis of IABP effects on baroreflex using a cardiovascular hybrid model, which consists of computational and hydraulic submodels. The work also included a baroreflex computational model that was connected to a hydraulic model with a 40-cm(3) balloon. The IABP was operated at different inflation trigger timings (-0.14 to 0.31 s) and inflation durations (0.05-0.45 s), with time of the dicrotic notch being taken as t = 0. Baroreflex-dependent parameters-afferent and efferent pathway activity, heart rate, peripheral resistance, and venous tone-were evaluated at each of the inflation trigger times and durations considered. Balloon early inflation (0.09 s before the dicrotic notch) with inflation duration of 0.25 s generated a maximum net increment of afferent pathway activity of 10%, thus leading to a decrement of efferent sympathetic activity by 15.3% compared with baseline values. These times also resulted in a reduction in peripheral resistance and heart rate by 4 and 4.3% compared with baseline value. We conclude that optimum IABP triggering time results in positive effects on peripheral circulation autonomic controls. Conversely, if the balloon is not properly timed, peripheral resistance and heart rate may even increase, which could lead to detrimental outcomes. PMID:23121229
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
Miwa, Koji; Libben, Gary; Dijkstra, Ton; Baayen, Harald
2014-01-01
This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers' locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level. PMID:23713954
Kostylev, Maxim; Wilson, David
2014-01-01
Lignocellulosic biomass is a potential source of renewable, low-carbon-footprint liquid fuels. Biomass recalcitrance and enzyme cost are key challenges associated with the large-scale production of cellulosic fuel. Kinetic modeling of enzymatic cellulose digestion has been complicated by the heterogeneous nature of the substrate and by the fact that a true steady state cannot be attained. We present a two-parameter kinetic model based on the Michaelis-Menten scheme (Michaelis L and Menten ML. (1913) Biochem Z 49:333–369), but with a time-dependent activity coefficient analogous to fractal-like kinetics formulated by Kopelman (Kopelman R. (1988) Science 241:1620–1626). We provide a mathematical derivation and experimental support to show that one of the parameters is a total activity coefficient and the other is an intrinsic constant that reflects the ability of the cellulases to overcome substrate recalcitrance. The model is applicable to individual cellulases and their mixtures at low-to-medium enzyme loads. Using biomass degrading enzymes from a cellulolytic bacterium Thermobifida fusca we show that the model can be used for mechanistic studies of enzymatic cellulose digestion. We also demonstrate that it applies to the crude supernatant of the widely studied cellulolytic fungus Trichoderma reesei and can thus be used to compare cellulases from different organisms. The two parameters may serve a similar role to Vmax, KM, and kcat in classical kinetics. A similar approach may be applicable to other enzymes with heterogeneous substrates and where a steady state is not achievable. PMID:23837567
Neurocomputational models of time perception.
Hass, Joachim; Durstewitz, Daniel
2014-01-01
Mathematical modeling is a useful tool for understanding the neurodynamical and computational mechanisms of cognitive abilities like time perception, and for linking neurophysiology to psychology. In this chapter, we discuss several biophysical models of time perception and how they can be tested against experimental evidence. After a brief overview on the history of computational timing models, we list a number of central psychological and physiological findings that such a model should be able to account for, with a focus on the scaling of the variability of duration estimates with the length of the interval that needs to be estimated. The functional form of this scaling turns out to be predictive of the underlying computational mechanism for time perception. We then present four basic classes of timing models (ramping activity, sequential activation of neuron populations, state space trajectories and neural oscillators) and discuss two specific examples in more detail. Finally, we review to what extent existing theories of time perception adhere to the experimental constraints. PMID:25358705
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. PMID:25260856
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,…
Human activity pattern-exposure models require accurate submodels for the exposures in microenvironments that people occupy, including those containing environmental tobacco smoke (ETS). his paper describes the Sequential Cigarette Exposure Model (SCEM), a general-purpose mathema...
Sequential digital elevation models of active lava flows from ground-based stereo time-lapse imagery
NASA Astrophysics Data System (ADS)
James, M. R.; Robson, S.
2014-11-01
We describe a framework for deriving sequences of digital elevation models (DEMs) for the analysis of active lava flows using oblique stereo-pair time-lapse imagery. A photo-based technique was favoured over laser-based alternatives due to low equipment cost, high portability and capability for network expansion, with images of advancing flows captured by digital SLR cameras over durations of up to several hours. However, under typical field scale scenarios, relative camera orientations cannot be rigidly maintained (e.g. through the use of a stereo bar), preventing the use of standard stereo time-lapse processing software. Thus, we trial semi-automated DEM-sequence workflows capable of handling the small camera motions, variable image quality and restricted photogrammetric control that result from the practicalities of data collection at remote and hazardous sites. The image processing workflows implemented either link separate close-range photogrammetry and traditional stereo-matching software, or are integrated in a single software package based on structure-from-motion (SfM). We apply these techniques in contrasting case studies from Kilauea volcano, Hawaii and Mount Etna, Sicily, which differ in scale, duration and image texture. On Kilauea, the advance direction of thin fluid lava lobes was difficult to forecast, preventing good distribution of control. Consequently, volume changes calculated through the different workflows differed by ∼10% for DEMs (over ∼30 m2) that were captured once a minute for 37 min. On Mt. Etna, more predictable advance (∼3 m h-1 for ∼3 h) of a thicker, more viscous lava allowed robust control to be deployed and volumetric change results were generally within 5% (over ∼500 m2). Overall, the integrated SfM software was more straightforward to use and, under favourable conditions, produced results comparable to those from the close-range photogrammetry pipeline. However, under conditions with limited options for photogrammetric
Kössl, Manfred; Hechavarria, Julio; Voss, Cornelia; Schaefer, Markus; Vater, Marianne
2015-03-01
Audition in bats serves passive orientation, alerting functions and communication as it does in other vertebrates. In addition, bats have evolved echolocation for orientation and prey detection and capture. This put a selective pressure on the auditory system in regard to echolocation-relevant temporal computation and frequency analysis. The present review attempts to evaluate in which respect the processing modules of bat auditory cortex (AC) are a model for typical mammalian AC function or are designed for echolocation-unique purposes. We conclude that, while cortical area arrangement and cortical frequency processing does not deviate greatly from that of other mammals, the echo delay time-sensitive dorsal cortex regions contain special designs for very powerful time perception. Different bat species have either a unique chronotopic cortex topography or a distributed salt-and-pepper representation of echo delay. The two designs seem to enable similar behavioural performance. PMID:25728173
NASA Astrophysics Data System (ADS)
Kaiser, Andreas; Neugirg, Fabian; Hass, Erik; Jose, Steffen; Haas, Florian; Schmidt, Jürgen
2016-04-01
In erosional research a variety of processes are well understood and have been mimicked under laboratory conditions. In complex natural systems such as Alpine environments a multitude of influencing factors tend to superimpose single processes in a mixed signal which impedes a reliable interpretation. These mixed signals can already be captured by geoscientific research approaches such as sediment collectors, erosion pins or remote sensing surveys. Nevertheless, they fail to distinguish between single processes and their individual impact on slope morphology. Throughout the last two years a highly active slope of unsorted glacial deposits in the northern Alps has been monitored by repeated terrestrial laser scans roughly every three months. Resulting high resolution digital elevation models of difference were produced to identify possible seasonal patterns. By reproducing the TLS results with a physically based erosion model (EROSION 3D) ran with in situ input data from rainfall simulations and a climate station a better understanding of individual mechanism could be achieved. However, the already elaborate combination of soil science and close range remote sensing could not answer all questions concerning the slopes behaviour, especially not for freeze and thaw cycles and the winter period. Therefore, an array of three fully automatic synchronised cameras was setup to generate continuous 3D surface models. Among the main challenges faced for the system were the energy supply and durability, perspectives of the cameras to avoid shadowing and to guarantee sufficient overlap, a certain robustness to withstand rough alpine weather conditions, the scaling of each 3D model by tracked ground control points and the automatic data handling. First results show individual processes sculpting the slope's morphology but further work is required to improve automatic point cloud creation and change monitoring.
NASA Astrophysics Data System (ADS)
Sato, Takeshi; Ishikawa, Kenichi L.
2015-02-01
The time-dependent multiconfiguration self-consistent-field method based on the occupation-restricted multiple-active-space model is proposed (TD-ORMAS) for multielectron dynamics in intense laser fields. Extending the previously proposed time-dependent complete-active-space self-consistent-field method [TD-CASSCF; Phys. Rev. A 88, 023402 (2013), 10.1103/PhysRevA.88.023402], which divides the occupied orbitals into core and active orbitals, the TD-ORMAS method further subdivides the active orbitals into an arbitrary number of subgroups and poses the occupation restriction by giving the minimum and maximum number of electrons distributed in each subgroup. This enables highly flexible construction of the configuration-interaction (CI) space, allowing a large-active-space simulation of dynamics, e.g., the core excitation or ionization. The equations of motion for both CI coefficients and spatial orbitals are derived based on the time-dependent variational principle, and an efficient algorithm is proposed to solve for the orbital time derivatives. In-depth descriptions of the computational implementation are given in a readily programmable manner. The numerical application to the one-dimensional lithium hydride cluster models demonstrates that the high flexibility of the TD-ORMAS framework allows for the cost-effective simulations of multielectron dynamics by exploiting systematic series of approximations to the TD-CASSCF method.
Evrendilek, Gulsun Akdemir; Avsar, Yahya Kemal; Evrendilek, Fatih
2016-01-01
Effects of pulsed electric field (PEF) processing on 28 aroma active compounds, and four physical and eight sensory properties of peach nectar were explored using the best-fit multiple linear regression (MLR) models and Monte Carlo simulations as a function of the treatment times of 0, 66, 131, and 210 μs. The PEF treatment time of 131 μs on average led consistently to the least loss of most compounds. Significantly enhanced or no significant changes in the sensory properties were found as a function of the PEF treatment times. The most influential sensory predictor of the 28 MLR models was flavour, while the aroma compound most influential on the sensory properties of aftertaste, flavour, sweetness, and overall acceptance was octadecanoic acid. Monte Carlo simulations were used for the probabilistic assessments of stochastic variability and uncertainty associated with aroma active compounds of PEF-treated peach nectar. PMID:26213021
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. PMID:25407347
Hill, Yolanda R.; Child, Nick; Hanson, Ben; Wallman, Mikael; Coronel, Ruben; Plank, Gernot; Rinaldi, Christopher A.; Gill, Jaswinder; Smith, Nicolas P.; Taggart, Peter; Bishop, Martin J.
2016-01-01
Exit sites associated with scar-related reentrant arrhythmias represent important targets for catheter ablation therapy. However, their accurate location in a safe and robust manner remains a significant clinical challenge. We recently proposed a novel quantitative metric (termed the Reentry Vulnerability Index, RVI) to determine the difference between activation and repolarisation intervals measured from pairs of spatial locations during premature stimulation to accurately locate the critical site of reentry formation. In the clinic, the method showed potential to identify regions of low RVI corresponding to areas vulnerable to reentry, subsequently identified as ventricular tachycardia (VT) circuit exit sites. Here, we perform an in silico investigation of the RVI metric in order to aid the acquisition and interpretation of RVI maps and optimise its future usage within the clinic. Within idealised 2D sheet models we show that the RVI produces lower values under correspondingly more arrhythmogenic conditions, with even low resolution (8 mm electrode separation) recordings still able to locate vulnerable regions. When applied to models of infarct scars, the surface RVI maps successfully identified exit sites of the reentrant circuit, even in scenarios where the scar was wholly intramural. Within highly complex infarct scar anatomies with multiple reentrant pathways, the identified exit sites were dependent upon the specific pacing location used to compute the endocardial RVI maps. However, simulated ablation of these sites successfully prevented the reentry re-initiation. We conclude that endocardial surface RVI maps are able to successfully locate regions vulnerable to reentry corresponding to critical exit sites during sustained scar-related VT. The method is robust against highly complex and intramural scar anatomies and low resolution clinical data acquisition. Optimal location of all relevant sites requires RVI maps to be computed from multiple pacing
Hill, Yolanda R; Child, Nick; Hanson, Ben; Wallman, Mikael; Coronel, Ruben; Plank, Gernot; Rinaldi, Christopher A; Gill, Jaswinder; Smith, Nicolas P; Taggart, Peter; Bishop, Martin J
2016-01-01
Exit sites associated with scar-related reentrant arrhythmias represent important targets for catheter ablation therapy. However, their accurate location in a safe and robust manner remains a significant clinical challenge. We recently proposed a novel quantitative metric (termed the Reentry Vulnerability Index, RVI) to determine the difference between activation and repolarisation intervals measured from pairs of spatial locations during premature stimulation to accurately locate the critical site of reentry formation. In the clinic, the method showed potential to identify regions of low RVI corresponding to areas vulnerable to reentry, subsequently identified as ventricular tachycardia (VT) circuit exit sites. Here, we perform an in silico investigation of the RVI metric in order to aid the acquisition and interpretation of RVI maps and optimise its future usage within the clinic. Within idealised 2D sheet models we show that the RVI produces lower values under correspondingly more arrhythmogenic conditions, with even low resolution (8 mm electrode separation) recordings still able to locate vulnerable regions. When applied to models of infarct scars, the surface RVI maps successfully identified exit sites of the reentrant circuit, even in scenarios where the scar was wholly intramural. Within highly complex infarct scar anatomies with multiple reentrant pathways, the identified exit sites were dependent upon the specific pacing location used to compute the endocardial RVI maps. However, simulated ablation of these sites successfully prevented the reentry re-initiation. We conclude that endocardial surface RVI maps are able to successfully locate regions vulnerable to reentry corresponding to critical exit sites during sustained scar-related VT. The method is robust against highly complex and intramural scar anatomies and low resolution clinical data acquisition. Optimal location of all relevant sites requires RVI maps to be computed from multiple pacing
NASA Astrophysics Data System (ADS)
Semmar, Nadjib; Darif, Mohamed; Millon, Eric; Petit, Agnès; Etienne, Hasnaa; Delaporte, Philippe
2012-07-01
This work concerns the ALDIP (Laser Activation of Doping agents Implanted by Plasma immersion) project that was a successful collaboration with Ion Beam Services (IBS) corporation, the "Lasers, Plasmas and Photonic Processes" (LP3) laboratory and the GREMI laboratory. The aim of this work is to control the melted thickness (i.e. junction thickness in the range 10-100 nm) by the Real Time Reflectivity (TRR) monitoring during the Laser Thermal Processing (LTP). The LTP is achieved by using a KrF laser beam (248 nm, 27 ns) with a homogeneous 'Top-Hat' space distribution to induce a selective melting and the resolidification of the doped Si:B samples on few nanometers. This recrystallization is conducted here after the pre-amorphisation process resulting from the ionic implantation of Si (PIII IBS implanter). Thus, all the studied samples are partially amorphized and boron doped. TRR method allows the accurate evaluation of the melting threshold, the duration of the melting phase, and the maximum melted thickness. Obtained results versus laser fluence are shown in the new case of under vacuum treatment. In order to calibrate the TRR method (to determine the intensity and the profile of the TRR signal versus the melting depth), we have used the secondary ion mass spectrometry (TOF-SIMS) analysis. This technique gives the doping agents profile versus the depth before and after LTP and confirms also the melting kinetics from TRR results.
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…
Koral, Kenneth F.; Avram, Anca M.; Kaminski, Mark S.; Dewaraja, Yuni K.
2012-01-01
Abstract Background For individualized treatment planning in radioimmunotherapy (RIT), correlations must be established between tracer-predicted and therapy-delivered absorbed doses. The focus of this work was to investigate this correlation for tumors. Methods The study analyzed 57 tumors in 19 follicular lymphoma patients treated with I-131 tositumomab and imaged with SPECT/CT multiple times after tracer and therapy administrations. Instead of the typical least-squares fit to a single tumor's measured time-activity data, estimation was accomplished via a biexponential mixed model in which the curves from multiple subjects were jointly estimated. The tumor-absorbed dose estimates were determined by patient-specific Monte Carlo calculation. Results The mixed model gave realistic tumor time-activity fits that showed the expected uptake and clearance phases even with noisy data or missing time points. Correlation between tracer and therapy tumor-residence times (r=0.98; p<0.0001) and correlation between tracer-predicted and therapy-delivered mean tumor-absorbed doses (r=0.86; p<0.0001) were very high. The predicted and delivered absorbed doses were within±25% (or within±75 cGy) for 80% of tumors. Conclusions The mixed-model approach is feasible for fitting tumor time-activity data in RIT treatment planning when individual least-squares fitting is not possible due to inadequate sampling points. The good correlation between predicted and delivered tumor doses demonstrates the potential of using a pretherapy tracer study for tumor dosimetry-based treatment planning in RIT. PMID:22947086
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.
The Variance Reaction Time Model
ERIC Educational Resources Information Center
Sikstrom, Sverker
2004-01-01
The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…
Volcano Deformation and Modeling on Active Volcanoes in the Philippines from ALOS InSAR Time Series
NASA Astrophysics Data System (ADS)
Morales Rivera, Anieri M.; Amelung, Falk; Eco, Rodrigo
2015-05-01
Bulusan, Kanlaon, and Mayon volcanoes have erupted over the last decade, and Taal caldera showed signs of volcanic unrest within the same time range. Eruptions at these volcanoes are a threat to human life and infrastructure, having over 1,000,000 people living within 10 km from just these 4 volcanic centers. For this reason, volcano monitoring in the Philippines is of extreme importance. We use the ALOS-1 satellite from the Japanese Aerospace Exploration Agency (JAXA) to make an InSAR time series analysis over Bulusan, Kanlaon, Mayon, and Taal volcanoes for the 2007-2011 period. Time-dependent deformation was detected at all of the volcanoes. Deformation related to changes in pressurization of the volcanic systems was found on Taal caldera and Bulusan volcanoes, with best fitting Mogi sources located at half-space depths of 3.07 km and 0.5 km respectively.
Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen
2016-01-01
Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors. PMID:26943641
Yao, Min; Lu, Xin; Lei, Yingfeng; Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen
2016-01-01
Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors. PMID:26943641
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
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
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…
[Mathematical model of mental time].
Glasko, A V; Sadykhova, L G
2014-01-01
On the basis of Ernst Mach's ideas and developed before the mathematical theory of mental processes, mathematical definition of duration of an interval of mental time, all over again for perception (experience) of separate event, and then--generally, i.e. for perception (experience) of sequence of events is entered. Its dependence on duration of an appropriating interval of physical time is investigated. Communication of mental time with perception of time (for two cases: "greater" and "small" intervals) is investigated. Comparison of theoretical formulas with results of experimental measurements is spent. Is defined process time which can be used, in particular, as a measure of work. The effect of the inverse of the psychological time, described in works of the Mach is analyzed and modelled. PMID:25723024
Wanted: Active Role Models for Today's Kids
... 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 ...
Vocal Activity, Time Pressure and Interpersonal Judgments.
ERIC Educational Resources Information Center
Daly, John A.; Lashbrook, William B.
This study examined the effects of differential time pressures on small group members' rankings of one another based on vocal activity. Vocal activity was operationalized as observed frequency of interaction. Time pressure was manipulated by allowing either six minutes or no time limit on a group problem-solving task. Main effects were…
Analytic Time Depending Galaxy Models
NASA Astrophysics Data System (ADS)
Sala, F.
1990-11-01
RESUMEN. Considerando las hip6tesis de Chandrasekhar para el estudjo de la GalActicaq se han desarrollado varios modelos analiticos integrables con simetria axial y dependientes del . . By considering Chandrasekhar hypotheses +or the study o+ Galactic Dynamics, several integrable analytic axisymmetric time-depending galactic models have been developed. Ke ords; GALAXY-DYNAMICS - GALAXY-STRUCTURE
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. PMID:16725113
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.
Trost, A; Motloch, K; Bruckner, D; Schroedl, F; Bogner, B; Kaser-Eichberger, A; Runge, C; Strohmaier, C; Klein, B; Aigner, L; Reitsamer, H A
2015-07-01
Glaucoma is a group of neurodegenerative diseases characterized by the progressive loss of retinal ganglion cells (RGCs) and their axons, and is the second leading cause of blindness worldwide. Elevated intraocular pressure is a well known risk factor for the development of glaucomatous optic neuropathy and pharmacological or surgical lowering of intraocular pressure represents a standard procedure in glaucoma treatment. However, the treatment options are limited and although lowering of intraocular pressure impedes disease progression, glaucoma cannot be cured by the currently available therapy concepts. In an acute short-term ocular hypertension model in rat, we characterize RGC loss, but also microglial cell activation and vascular alterations of the retina at certain time points. The combination of these three parameters might facilitate a better evaluation of the disease progression, and could further serve as a new model to test novel treatment strategies at certain time points. Acute ocular hypertension (OHT) was induced by the injection of magnetic microbeads into the rat anterior chamber angle (n = 22) with magnetic position control, leading to constant elevation of IOP. At certain time points post injection (4d, 7d, 10d, 14d and 21d), RGC loss, microglial activation, and microvascular pericyte (PC) coverage was analyzed using immunohistochemistry with corresponding specific markers (Brn3a, Iba1, NG2). Additionally, the tightness of the retinal vasculature was determined via injections of Texas Red labeled dextran (10 kDa) and subsequently analyzed for vascular leakage. For documentation, confocal laser-scanning microscopy was used, followed by cell counts, capillary length measurements and morphological and statistical analysis. The injection of magnetic microbeads led to a progressive loss of RGCs at the five time points investigated (20.07%, 29.52%, 41.80%, 61.40% and 76.57%). Microglial cells increased in number and displayed an activated morphology
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.
Veltri, Alessandro; Chipouline, Arkadi; Aradian, Ashod
2016-01-01
The plasmonic response of a metal nanoparticle in the presence of surrounding gain elements is studied, using a space and time-dependent model, which integrates a quantum formalism to describe the gain and a classical treatment for the metal. Our model fully takes into account the influence of the system geometry (nanosphere) and offers for the first time, the possibility to describe the temporal evolution of the fields and the coupling among the multipolar modes of the particle. We calculate the lasing threshold value for all multipoles of the spaser, and demonstrate that the dipolar one is lowest. The onset of the lasing instability, in the linear regime, is then studied both with and without external field forcing. We also study the behaviour of the system below the lasing threshold, with the external field, demonstrating the existence of an amplification regime where the nanoparticle's plasmon is strongly enhanced as the threshold is approached. Finally, a qualitative discussion is provided on later, non-linear stages of the dynamics and the approach to the steady-state of the spaser; in particular, it is shown that, for the considered geometry, the spasing is necessarily multi-modal and multipolar modes are always activated. PMID:27625072
Timing analysis by model checking
NASA Technical Reports Server (NTRS)
Naydich, Dimitri; Guaspari, David
2000-01-01
The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.
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. PMID:26368669
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.
ERIC Educational Resources Information Center
Hagger, Martin S.; Chatzisarantis, Nikos L. D.; Barkoukis, Vassilis; Wang, C. K. John; Baranowski, Jaroslaw
2005-01-01
This study tested the replicability and cross-cultural invariance of a trans-contextual model of motivation across 4 samples from diverse cultures. The model proposes a motivational sequence in which perceived autonomy support (PAS) in physical education (PE) predicts autonomous motivation, intentions, and behavior in a leisure-time (LT) physical…
NASA Astrophysics Data System (ADS)
Ribárik, G.; Oláh, K.; Strassmeier, K. G.
We present and apply a new computer program named SpotModeL to analyze single and multiple bandpass photometric data of spotted stars. It is based on the standard analytical formulae from Budding and Dorren. The program determines the position, size, and temperature of up to three spots by minimizing the fit residuals with the help of the Marquardt-Levenberg non-linear least-squares algorithm. We also expand this procedure to full time-series analysis of differential data, just as real observations would deliver. If multi-bandpass data are available, all bandpasses can be treated simultaneously and thus the spot temperature is solved for implicitly. The program may be downloaded and used by anyone. In this paper, we apply our code to an ~23 year long photometric dataset of the spotted RS CVn giant IM Peg. We extracted and modelled 33 individual light curves, additionally, we fitted the entire V dataset in one run. The resulting spot parameters reflect the long term light variability and reveal two active longitudes on the substellar point and on the antipode. The radius and longitude of the dominant spot show variations with 29.8 and 10.4 years period, respectively. Our multicolour data suggests that the spot temperature is increasing with the brightening of the star. The average spot temperature from V,I_C is 3550+/- 150 K or approximately 900 K below the effective temperature of the star.
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.
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
Real-Time Monitoring of Active Landslides
Reid, Mark E.; LaHusen, Richard G.; Ellis, William L.
1999-01-01
Landslides threaten lives and property in every State in the Nation. To reduce the risk from active landslides, the U.S. Geological Survey (USGS) develops and uses real-time landslide monitoring systems. Monitoring can detect early indications of rapid, catastrophic movement. Up-to-the-minute or real-time monitoring provides immediate notification of landslide activity, potentially saving lives and property. Continuous information from real-time monitoring also provides a better understanding of landslide behavior, enabling engineers to create more effective designs for halting landslide movement.
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
Modeling flexible active nematics
NASA Astrophysics Data System (ADS)
Varga, Michael; Selinger, Robin
We study active nematic phases of self-propelled flexible chains in two dimensions using computer simulation, to investigate effects of chain flexibility. In a ``dry'' phase of self-propelled flexible chains, we find that increasing chain stiffness enhances orientational order and correlation length, narrows the distribution of turning angles, increases persistence length, and increases the magnitude of giant density fluctuations. We further adapt the simulation model to describe behavior of microtubules driven by kinesin molecular motors in two different environments: on a rigid substrate with kinesin immobilized on the surface; and on a lipid membrane where kinesin is bonded to lipid head groups and can diffuse. Results are compared to experiments by L. Hirst and J. Xu. Lastly, we consider active nematics of flexible particles enclosed in soft, deformable encapsulation in two dimensions, and demonstrate novel mechanisms of pattern formation that are fundamentally different from those observed in bulk. Supported by NSF-DMR 1409658.
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…
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
Seasonal variation in leisure time physical activity.
Uitenbroek, D G
1993-06-01
In this paper seasonal variation in leisure time physical activity for exercise is studied and quantified with regard to several popular exercise activities and taking the respondents gender, occupational status, and age into consideration. The analysis concerns data collected by telephone in Scotland between January 1989 and March 1992. Data from 7,202 male and 9,284 female respondents is used in the analysis; cosinor analysis using GLIM is applied. Considerable seasonal variation was found affecting both outdoor and indoor activities. During the peak phase in July, 32% of the respondents reported exercising for at least 20 min three or more times during the previous week, in the winter period this decreased to 23%. Older respondents were found to exercise more later in the year and also showed seasonal variation to a larger extent than younger respondents. This is particularly so for those respondents who exercise at a relatively high frequency. PMID:8321115
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)
On Modelling Minimal Disease Activity
Jackson, Christopher H.; Su, Li; Gladman, Dafna D.
2016-01-01
Objective To explore methods for statistical modelling of minimal disease activity (MDA) based on data from intermittent clinic visits. Methods The analysis was based on a 2‐state model. Comparisons were made between analyses based on “complete case” data from visits at which MDA status was known, and the use of hidden model methodology that incorporated information from visits at which only some MDA defining criteria could be established. Analyses were based on an observational psoriatic arthritis cohort. Results With data from 856 patients and 7,024 clinic visits, analysis was based on virtually all visits, although only 62.6% provided enough information to determine MDA status. Estimated mean times for an episode of MDA varied from 4.18 years to 3.10 years, with smaller estimates derived from the hidden 2‐state model analysis. Over a 10‐year period, the estimated expected times spent in MDA episodes of longer than 1 year was 3.90 to 4.22, and the probability of having such an MDA episode was estimated to be 0.85 to 0.91, with longer times and greater probabilities seen with the hidden 2‐state model analysis. Conclusion A 2‐state model provides a useful framework for the analysis of MDA. Use of data from visits at which MDA status can not be determined provide more precision, and notable differences are seen in estimated quantities related to MDA episodes based on complete case and hidden 2‐state model analyses. The possibility of bias, as well as loss of precision, should be recognized when complete case analyses are used. PMID:26315478
American Time Use Survey: Sleep Time and Its Relationship to Waking Activities
Basner, Mathias; Fomberstein, Kenneth M.; Razavi, Farid M.; Banks, Siobhan; William, Jeffrey H.; Rosa, Roger R.; Dinges, David F.
2007-01-01
Study Objectives: To gain some insight into how various behavioral (lifestyle) factors influence sleep duration, by investigation of the relationship of sleep time to waking activities using the American Time Use Survey (ATUS). Design: Cross-sectional data from ATUS, an annual telephone survey of a population sample of US citizens who are interviewed regarding how they spent their time during a 24-hour period between 04:00 on the previous day and 04:00 on the interview day. Participants: Data were pooled from the 2003, 2004, and 2005 ATUS databases involving N=47,731 respondents older than 14 years of age. Interventions: N/A Results: Adjusted multiple linear regression models showed that the largest reciprocal relationship to sleep was found for work time, followed by travel time, which included commute time. Only shorter than average sleepers (<7.5 h) spent more time socializing, relaxing, and engaging in leisure activities, while both short (<5.5 h) and long sleepers (≥8.5 h) watched more TV than the average sleeper. The extent to which sleep time was exchanged for waking activities was also shown to depend on age and gender. Sleep time was minimal while work time was maximal in the age group 45–54 yr, and sleep time increased both with lower and higher age. Conclusions: Work time, travel time, and time for socializing, relaxing, and leisure are the primary activities reciprocally related to sleep time among Americans. These activities may be confounding the frequently observed association between short and long sleep on one hand and morbidity and mortality on the other hand and should be controlled for in future studies. Citation: Basner M; Fomberstein KM; Razavi FM; Banks S; William JH; Rosa RR; Dinges DF. American time use survey: sleep time and its relationship to waking activities. SLEEP 2007;30(9):1085-1095. PMID:17910380
Models of Time Use in Paid and Unpaid Work
ERIC Educational Resources Information Center
Beaujot, Roderic; Liu, Jianye
2005-01-01
Models of time use need to consider especially the reproductive and productive activities of women and men. For husband-wife families, the breadwinner, one-earner, or complementary-roles model has advantages in terms of efficiency or specialization and stability; however, it is a high-risk model for women and children. The alternate model has been…
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.
Trajectory data analyses for pedestrian space-time activity study.
Qi, Feng; Du, Fei
2013-01-01
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission(1-3). An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data(4). Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an
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.
Bootstrapping a time series model
Son, M.S.
1984-01-01
The bootstrap is a methodology for estimating standard errors. The idea is to use a Monte Carlo simulation experiment based on a nonparametric estimate of the error distribution. The main objective of this dissertation was to demonstrate the use of the bootstrap to attach standard errors to coefficient estimates and multi-period forecasts in a second-order autoregressive model fitted by least squares and maximum likelihood estimation. A secondary objective of this article was to present the bootstrap in the context of two econometric equations describing the unemployment rate and individual income tax in the state of Oklahoma. As it turns out, the conventional asymptotic formulae (both the least squares and maximum likelihood estimates) for estimating standard errors appear to overestimate the true standard errors. But there are two problems: 1) the first two observations y/sub 1/ and y/sub 2/ have been fixed, and 2) the residuals have not been inflated. After these two factors are considered in the trial and bootstrap experiment, both the conventional maximum likelihood and bootstrap estimates of the standard errors appear to be performing quite well. At present, there does not seem to be a good rule of thumb for deciding when the conventional asymptotic formulae will give acceptable results.
Time Delay Evolution of Five Active Galactic Nuclei
NASA Astrophysics Data System (ADS)
Kovačević, A.; Popović, L. Č.; Shapovalova, A. I.; Ilić, D.; Burenkov, A. N.; Chavushyan, V. H.
2015-12-01
Here we investigate light curves of the continuum and emission lines of five type 1 active galactic nuclei (AGN) from our monitoring campaign, to test time-evolution of their time delays. Using both modeled and observed AGN light curves, we apply Gaussian kernel-based estimator to capture variation of local patterns of their time evolving delays. The largest variations of time delays of all objects occur in the period when continuum or emission lines luminosity is the highest. However, Gaussian kernel-based method shows instability in the case of NGC 5548, 3C 390.3, E1821 + 643 and NGC 4051 possibly due to numerical discrepancies between damped random walk (DRW) time scale of light curves and sliding time windows of the method. The temporal variations of time lags of Arp 102B can correspond to the real nature of the time lag evolution.
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.
Planning in time - Windows and durations for activities and goals
NASA Technical Reports Server (NTRS)
Vere, S. A.
1983-01-01
The present general purpose automated planner/scheduler generates parallel plans aimed at the achievement of goals having imposed time constraints, with both durations and start time windows being specifiable for sets of goal conditions. Deterministic durations of such parallel plan activities as actions, events triggered by circumstances, inferences, and scheduled events entirely outside the actor's control, are explicitly modeled and may be any computable function of the activity variables. The final plan network resembles a PERT chart. Examples are given from the traditional 'blocksworld', and from a realistic 'Spaceworld' in which an autonomous spacecraft photographs objects in deep space and transmits the information to earth.
REAL TIME DATA FOR REMEDIATION ACTIVITIES [11505
BROCK CT
2011-01-13
Health physicists from the CH2M HILL Plateau Remediation Company collaborated with Berkeley Nucleonics Corporation to modify the SAM 940 isotope identifier instrument to be used for nuclear waste remediation. These modifications coupled with existing capabilities of the SAM 940 have proven to be invaluable during remediation activities, reducing disposal costs by allowing swift remediation of targeted areas that have been identified as having isotopes of concern (IOC), and eliminating multiple visits to sites by declaring an excavation site clear of IOCs before demobilizing from the site. These advantages are enabled by accumulating spectral data for specific isotopes that is nearly 100 percent free of false positives, which are filtered out in 'real time.'
Physician Activities During Time Out of the Examination Room
Gilchrist, Valerie; McCord, Gary; Schrop, Susan Labuda; King, Bridget D.; McCormick, Kenelm F.; Oprandi, Allison M.; Selius, Brian A.; Cowher, Michael; Maheshwary, Rishi; Patel, Falguni; Shah, Ami; Tsai, Bonny; Zaharna, Mia
2005-01-01
PURPOSE Comprehensive medical care requires direct physician-patient contact, other office-based medical activities, and medical care outside of the office. This study was a systematic investigation of family physician office-based activities outside of the examination room. METHODS In the summer of 2000, 6 medical students directly observed and recorded the office-based activities of 27 northeastern Ohio community-based family physicians during 1 practice day. A checklist was used to record physician activity every 20 seconds outside of the examination room. Observation excluded medical care provided at other sites. Physicians were also asked to estimate how they spent their time on average and on the observed day. RESULTS The average office day was 8 hours 8 minutes. On average, 20.1 patients were seen and physicians spent 17.5 minutes per patient in direct contact time. Office-based time outside of the examination room averaged 3 hours 8 minutes or 39% of the office practice day; 61% of that time was spent in activities related to medical care. Charting (32.9 minutes per day) and dictating (23.4 minutes per day) were the most common medical activities. Physicians overestimated the time they spent in direct patient care and medical activities. None of the participating practices had electronic medical records. CONCLUSIONS If office-based, medically related activities were averaged over the number of patients seen in the office that day, the average office visit time per patient would increase by 7 minutes (40%). Care delivery extends beyond direct patient contact. Models of health care delivery need to recognize this component of care. PMID:16338912
Ionospheric Electron Density during Magnetically Active Times over Istanbul
NASA Astrophysics Data System (ADS)
Naz Erbaş, Bute; Kaymaz, Zerefsan; Ceren Moral, Aysegul; Emine Ceren Kalafatoglu Eyiguler, R. A..
2016-07-01
In this study, we analyze electron density variations over Istanbul using Dynasonde observations during the magnetically active times. In order to perform statistical analyses, we first determined magnetic storms and magnetospheric substorm intervals from October 2012 to October 2015 using Kyoto's magnetic index data. Corresponding ionospheric parameters, such as critical frequency of F2 region (foF2), maximum electron density height (hmF2), total electron density (TEC) etc. were retrieved from Dynasonde data base at Istanbul Technical University's Space Weather Laboratory. To understand the behavior of electron density during the magnetically active times, we remove the background quiet time variations first and then quantify the anomalies. In this presentation, we will report results from our preliminary analyses from the selected cases corresponding to the strong magnetic storms. Initial results show lower electron densities at noon times and higher electron densities in the late afternoon toward sunset times when compared to the electron densities of magnetically quiet times. We also compare the results with IRI and TIEGCM ionospheric models in order to understand the physical and dynamical causes of these variations. During the presentation we will also discuss the role of these changes during the magnetically active times on the GPS communications through ionosphere.
System-time entanglement in a discrete-time model
NASA Astrophysics Data System (ADS)
Boette, A.; Rossignoli, R.; Gigena, N.; Cerezo, M.
2016-06-01
We present a model of discrete quantum evolution based on quantum correlations between the evolving system and a reference quantum clock system. A quantum circuit for the model is provided, which in the case of a constant Hamiltonian is able to represent the evolution over 2n time steps in terms of just n time qubits and n control gates. We then introduce the concept of system-time entanglement as a measure of distinguishable quantum evolution, based on the entanglement between the system and the reference clock. This quantity vanishes for stationary states and is maximum for systems jumping onto a new orthogonal state at each time step. In the case of a constant Hamiltonian leading to a cyclic evolution it is a measure of the spread over distinct energy eigenstates and satisfies an entropic energy-time uncertainty relation. The evolution of mixed states is also examined. Analytical expressions for the basic case of a qubit clock, as well as for the continuous limit in the evolution between two states, are provided.
Time Domain Modelling of a Reciprocating Engine
NASA Astrophysics Data System (ADS)
Li, H.; Stone, B. J.
1999-01-01
This paper describes the application of a time domain systems approach to the modelling of a reciprocating engine. The engine model includes the varying inertia effects resulting from the motion of the piston and con-rod. The cylinder pressure measured under operating conditions is used to force the model and the resulting motion compared with the measured response. The results obtained indicate that the model is very good.
Global Modeling Activities and NAME
NASA Technical Reports Server (NTRS)
Schubert, Siegfried; Atlas, Robert (Technical Monitor)
2002-01-01
In this talk I will review global modeling activities in the United States that could contribute to and benefit from NAME activities. I will present some preliminary results from several global atmospheric general circulation model simulation experiments for the initial NAME model intercomparison project period of May-Oct 1990. These include an ensemble of medium resolution simulations, and a high resolution (one half degree) simulation. I will also discuss possible high resolution global data assimilation experiments that could be used to help validate the model simulations and assimilate planned NAME observations.
Building Chaotic Model From Incomplete Time Series
NASA Astrophysics Data System (ADS)
Siek, Michael; Solomatine, Dimitri
2010-05-01
This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual
Modeling approaches for active systems
NASA Astrophysics Data System (ADS)
Herold, Sven; Atzrodt, Heiko; Mayer, Dirk; Thomaier, Martin
2006-03-01
To solve a wide range of vibration problems with the active structures technology, different simulation approaches for several models are needed. The selection of an appropriate modeling strategy is depending, amongst others, on the frequency range, the modal density and the control target. An active system consists of several components: the mechanical structure, at least one sensor and actuator, signal conditioning electronics and the controller. For each individual part of the active system the simulation approaches can be different. To integrate the several modeling approaches into an active system simulation and to ensure a highly efficient and accurate calculation, all sub models must harmonize. For this purpose, structural models considered in this article are modal state-space formulations for the lower frequency range and transfer function based models for the higher frequency range. The modal state-space formulations are derived from finite element models and/or experimental modal analyses. Consequently, the structure models which are based on transfer functions are directly derived from measurements. The transfer functions are identified with the Steiglitz-McBride iteration method. To convert them from the z-domain to the s-domain a least squares solution is implemented. An analytical approach is used to derive models of active interfaces. These models are transferred into impedance formulations. To couple mechanical and electrical sub-systems with the active materials, the concept of impedance modeling was successfully tested. The impedance models are enhanced by adapting them to adequate measurements. The controller design strongly depends on the frequency range and the number of modes to be controlled. To control systems with a small number of modes, techniques such as active damping or independent modal space control may be used, whereas in the case of systems with a large number of modes or with modes that are not well separated, other control
Time prediction model of subway transfer.
Zhou, Yuyang; Yao, Lin; Gong, Yi; Chen, Yanyan
2016-01-01
Walking time prediction aims to deduce waiting time and travel time for passengers and provide a quantitative basis for the subway schedule management. This model is founded based on transfer passenger flow and type of pedestrian facilities. Chaoyangmen station in Beijing was taken as the learning set to obtain the relationship between transfer walking speed and passenger volume. The sectional passenger volume of different facilities was calculated related to the transfer passage classification. Model parameters were computed by curve fitting with respect to various pedestrian facilities. The testing set contained four transfer stations with large passenger volume. It is validated that the established model is effective and practical. The proposed model offers a real-time prediction method with good applicability. It can provide transfer scheme reference for passengers, meanwhile, improve the scheduling and management of the subway operation. PMID:26835224
A Home Production Activity Model.
ERIC Educational Resources Information Center
Beutler, Ivan F.; Owen, Alma J.
1980-01-01
The family is examined as a focal unit of production and a home production activity model is developed. An interdisciplinary approach is used which puts the broad range of family activities on a continuum from production to consumption. (Author/SK)
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. PMID:23945086
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…
Spatial Segmentation of Image Sequences Based on Their Time Activity
NASA Astrophysics Data System (ADS)
Galatsanos, N. P.
2006-04-01
There are many applications in medical imaging where one is interested in finding the areas of the image that exhibit the same time activity. Such applications occur in positron and single photon emission imaging as well as in perfusion studies with magnetic resonance imaging (MRI). In this talk we will present Bayesian methodology based on clustering to solve this problem. At first the dimensionality of the pixel observations is reduced using a probabilistic principle component model along the spatial dimension of the data. Then, a multidimensional Gaussian mixture model with spatial constraints is used for clustering. Examples from MRI perfusion studies of the heart and the brain will be shown.
Herkert, Nadja M; Lallement, Guy; Clarençon, Didier; Thiermann, Horst; Worek, Franz
2009-04-28
Recently, a dynamically working in vitro model with real-time determination of membrane-bound human acetylcholinesterase (AChE) activity was shown to be a versatile model to investigate oxime-induced reactivation kinetics of organophosphate- (OP) inhibited enzyme. In this assay, AChE was immobilized on particle filters which were perfused with acetylthiocholine, Ellman's reagent and phosphate buffer. Subsequently, AChE activity was continuously analyzed in a flow-through detector. Now, it was an intriguing question whether this model could be used with erythrocyte AChE from other species in order to investigate kinetic interactions in the absence of annoying side reactions. Rhesus monkey, swine and guinea pig erythrocytes were a stable and highly reproducible enzyme source. Then, the model was applied to the reactivation of sarin- and paraoxon-inhibited AChE by obidoxime or HI 6 and it could be shown that the derived reactivation rate constants were in good agreement to previous results obtained from experiments with a static model. Hence, this dynamic model offers the possibility to investigate highly reproducible interactions between AChE, OP and oximes with human and animal AChE. PMID:19428926
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.
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.
NASA Astrophysics Data System (ADS)
Smith, D. E.; Minson, S. E.; Langbein, J. O.; Murray, J. R.; Guillemot, C.
2014-12-01
Currently implemented Earthquake Early Warning (EEW) algorithms based on seismic data alone should provide the most robust warnings for most M<6 earthquakes, since real-time GPS positions are too noisy to aid in EEW. However, for larger events, which generate larger fault offsets, GPS data can provide a direct on-scale displacement measurements and has sufficient precision. In such situations, the GPS observations may enable more accurate estimation of magnitude and rupture extent than seismic data. The USGS Earthquake Science Center in Menlo Park currently obtains real-time data from approximately 100 GNSS stations in northern California. These stations, which span the San Andreas fault system from the Mendocino Triple Junction to San Juan Bautista, are operated by USGS-Menlo Park, UC Berkeley, and UNAVCO. We have developed software tools for monitoring and troubleshooting data acquisition and quality. We have evaluated the latency and precision of position estimates obtained through real-time processing and we have found these results satisfactory for EEW. We are now implementing the BEFORES algorithm (Minson et al., 2014) that uses Bayesian analysis to determine the best-fitting coseismic fault orientation and finite fault slip distribution (from which moment and rupture extent are obtained) in real-time. BEFORES has been tested extensively on both simulated and real data (retrospectively) for a variety of earthquakes. We are now focusing on three aspects of its implementation: 1) receiving real-time earthquake locations from independent seismic EEW algorithms, that are obtained through multiple TCP/IP connections, and 3) optimizing the computation of elastic Green's functions. Completion of these tasks plus additional tests using simulated waveforms of earthquakes displacements superimposed on actual data will prepare the algorithm for implementation in the West Coast EEW system.
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience. PMID:24808226
Computational models of epileptiform activity.
Wendling, Fabrice; Benquet, Pascal; Bartolomei, Fabrice; Jirsa, Viktor
2016-02-15
We reviewed computer models that have been developed to reproduce and explain epileptiform activity. Unlike other already-published reviews on computer models of epilepsy, the proposed overview starts from the various types of epileptiform activity encountered during both interictal and ictal periods. Computational models proposed so far in the context of partial and generalized epilepsies are classified according to the following taxonomy: neural mass, neural field, detailed network and formal mathematical models. Insights gained about interictal epileptic spikes and high-frequency oscillations, about fast oscillations at seizure onset, about seizure initiation and propagation, about spike-wave discharges and about status epilepticus are described. This review shows the richness and complementarity of the various modeling approaches as well as the fruitful contribution of the computational neuroscience community in the field of epilepsy research. It shows that models have progressively gained acceptance and are now considered as an efficient way of integrating structural, functional and pathophysiological data about neural systems into "coherent and interpretable views". The advantages, limitations and future of modeling approaches are discussed. Perspectives in epilepsy research and clinical epileptology indicate that very promising directions are foreseen, like model-guided experiments or model-guided therapeutic strategy, among others. PMID:25843066
Real-time visualization of neuronal activity during perception.
Muto, Akira; Ohkura, Masamichi; Abe, Gembu; Nakai, Junichi; Kawakami, Koichi
2013-02-18
To understand how the brain perceives the external world, it is desirable to observe neuronal activity in the brain in real time during perception. The zebrafish is a suitable model animal for fluorescence imaging studies to visualize neuronal activity because its body is transparent through the embryonic and larval stages. Imaging studies have been carried out to monitor neuronal activity in the larval spinal cord and brain using Ca(2+) indicator dyes and DNA-encoded Ca(2+) indicators, such as Cameleon, GFP-aequorin, and GCaMPs. However, temporal and spatial resolution and sensitivity of these tools are still limited, and imaging of brain activity during perception of a natural object has not yet been demonstrated. Here we demonstrate visualization of neuronal activity in the optic tectum of larval zebrafish by genetically expressing the new version of GCaMP. First, we demonstrate Ca(2+) transients in the tectum evoked by a moving spot on a display and identify direction-selective neurons. Second, we show tectal activity during perception of a natural object, a swimming paramecium, revealing a functional visuotopic map. Finally, we image the tectal responses of a free-swimming larval fish to a paramecium and thereby correlate neuronal activity in the brain with prey capture behavior. PMID:23375894
Modeling fibril fragmentation in real-time
NASA Astrophysics Data System (ADS)
Tan, Pengzhen; Hong, Liu
2013-08-01
During the application of the mass-action-equation models to the study of amyloid fiber formation, time-consuming numerical calculations constitute a major bottleneck. To conquer this difficulty, here an alternative efficient method is introduced for the fragmentation-only model. It includes two basic steps: (1) simulate close-formed time-evolutionary equations for the number concentration P(t) derived from the moment-closure method; (2) reconstruct the detailed fiber length distribution based on the knowledge of moments obtained in the first step. Compared to direct calculation, our method speeds up the performance by at least 10 000 times (from days to seconds). The accuracy is also satisfactory if suitable functions for the approximate fibril length distribution are taken. Further application to the sonication studies on PI264-b-PFS48 micelles performed by Guerin et al. confirms our method is very promising for the real-time analysis of the experiments on fibril fragmentation.
Diffraction in time: An exactly solvable model
NASA Astrophysics Data System (ADS)
Goussev, Arseni
2014-03-01
In optics, diffraction is typically portrayed as deflection of light incident upon an obstacle with sharp boundaries, that can not be accounted for by reflection or refraction. Interestingly, quantum mechanics allows for an additional, intrinsically time-dependent manifestation of the phenomenon: Owing to the dispersive nature of quantum matter waves, sudden changes in boundary conditions may cause the particle wave function to develop interference fringes akin to those in stationary (optical) diffraction problems. This phenomenon, pioneered in 1952 by Moshinsky [Phys. Rev. 88, 625 (1952)] and presently referred to as ``diffraction in time,'' is at the heart of a vibrant area of experimental and theoretical research concerned with quantum transients. In my talk, I will introduce a new versatile exactly-solvable model of diffraction in time. The model describes dynamics of a quantum particle in the presence of an absorbing time-dependent barrier, and enables a quantitative description of diffraction and interference patterns in a large variety of setups.
Using Online Lectures to Make Time for Active Learning
Prunuske, Amy J.; Batzli, Janet; Howell, Evelyn; Miller, Sarah
2012-01-01
To make time in class for group activities devoted to critical thinking, we integrated a series of short online lectures into the homework assignments of a large, introductory biology course at a research university. The majority of students viewed the online lectures before coming to class and reported that the online lectures helped them to complete the in-class activity and did not increase the amount of time they devoted to the course. In addition, students who viewed the online lecture performed better on clicker questions designed to test lower-order cognitive skills. The in-class activities then gave the students practice analyzing the information in groups and provided the instructor with feedback about the students’ understanding of the material. On the basis of the results of this study, we support creating hybrid course models that allow students to learn the fundamental information outside of class time, thereby creating time during the class period to be dedicated toward the conceptual understanding of the material. PMID:22714412
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.
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.
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…
Time series modelling of surface pressure data
NASA Astrophysics Data System (ADS)
Al-Awadhi, Shafeeqah; Jolliffe, Ian
1998-03-01
In this paper we examine time series modelling of surface pressure data, as measured by a barograph, at Herne Bay, England, during the years 1981-1989. Autoregressive moving average (ARMA) models have been popular in many fields over the past 20 years, although applications in climatology have been rather less widespread than in some disciplines. Some recent examples are Milionis and Davies (Int. J. Climatol., 14, 569-579) and Seleshi et al. (Int. J. Climatol., 14, 911-923). We fit standard ARMA models to the pressure data separately for each of six 2-month natural seasons. Differences between the best fitting models for different seasons are discussed. Barograph data are recorded continuously, whereas ARMA models are fitted to discretely recorded data. The effect of different spacings between the fitted data on the models chosen is discussed briefly.Often, ARMA models can give a parsimonious and interpretable representation of a time series, but for many series the assumptions underlying such models are not fully satisfied, and more complex models may be considered. A specific feature of surface pressure data in the UK is that its behaviour is different at high and at low pressures: day-to-day changes are typically larger at low pressure levels than at higher levels. This means that standard assumptions used in fitting ARMA models are not valid, and two ways of overcoming this problem are investigated. Transformation of the data to better satisfy the usual assumptions is considered, as is the use of non-linear, specifically threshold autoregressive (TAR), models.
Theory of Time beyond the standard model
Poliakov, Eugene S.
2008-05-29
A frame of non-uniform time is discussed. A concept of 'flow of time' is presented. The principle of time relativity in analogy with Galilean principle of relativity is set. Equivalence principle is set to state that the outcome of non-uniform time in an inertial frame of reference is equivalent to the outcome of a fictitious gravity force external to the frame of reference. Thus it is flow of time that causes gravity rather than mass. The latter is compared to experimental data achieving precision of up to 0.0003%. It is shown that the law of energy conservation is inapplicable to the frames of non-uniform time. A theoretical model of a physical entity (point mass, photon) travelling in the field of non-uniform time is considered. A generalized law that allows the flow of time to replace classical energy conservation is introduced on the basis of the experiment of Pound and Rebka. It is shown that linear dependence of flow of time on spatial coordinate conforms the inverse square law of universal gravitation and Keplerian mechanics. Momentum is shown to still be conserved.
SO2 EMISSIONS AND TIME SERIES MODELS
The paper describes a time series model that permits the estimation of the statistical properties of pounds of SO2 per million Btu in stack emissions. It uses measured values for this quantity provided by coal sampling and analysis (CSA), by a continuous emissions monitor (CEM), ...
A Ballistic Model of Choice Response Time
ERIC Educational Resources Information Center
Brown, Scott; Heathcote, Andrew
2005-01-01
Almost all models of response time (RT) use a stochastic accumulation process. To account for the benchmark RT phenomena, researchers have found it necessary to include between-trial variability in the starting point and/or the rate of accumulation, both in linear (R. Ratcliff & J. N. Rouder, 1998) and nonlinear (M. Usher & J. L. McClelland, 2001)…
Accelerated Failure-Time Models of Graduation
ERIC Educational Resources Information Center
Chimka, Justin R.; Wang, Qilu
2009-01-01
This third article in a series describing survival analysis of engineering student retention and graduation introduces accelerated failure-time as an alternative to the Cox proportional hazards model to the context of student data. The new survival analysis of graduation data presented here assumes different distributions including exponential,…
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.
Damte, Dereje; Lee, Seung-Jin; Yohannes, Sileshi B; Hossain, Md Akil; Suh, Joo-Won; Park, Seung-Chun
2013-12-01
The aim of the current study was to demonstrate and compare the impact of different pharmacokinetics of marbofloxacin, enrofloxacin and difloxacin on their antimicrobial effects, their killing and re-growth kinetics, and the population dynamics of Actinobacillus pleuropneumoniae clinical isolates in an in vitro dynamic model. Selected clinical isolates of A. pleuropneumoniae and three fluoroquinolones at a range of simulated AUC(24)/MIC ratios of multiple doses were investigated. At the same simulated AUC(24)/MIC ratios of the three fluoroquinolones, the killing re-growth profile and I(E) values (intensity of the antimicrobial effect) revealed strain- and fluoroquinolone-specific effects. For example, a 31% lower I(E) of difloxacin was observed in AppK5 (biofilm-former) than in AppK2 (biofilm-non-former) at the same AUC(24)/MIC ratio of 120 h. In addition, losses in A. pleuropneumoniae susceptibility of both strains by the three fluoroquinolones were observed. AUC(24)/MPC ratios of 20.89 and 39.81 for marbofloxacin, 17.32 and 19.49 for enrofloxacin and 31.62 and 60.25 for difloxacin were estimated to be protective against the selection of AppK2 and AppK5 strain mutants, respectively. Integration of these in vitro data with published pharmacokinetics revealed the inadequacy of the conventional clinical doses of the three drugs to attain the above protective values for minimum biofilm eradication concentration (MBEC) and concentration to prevent growth of 90% of the mutant subpopulation (MPC(90)). In conclusion, the results suggest optimising doses could suffice for resistant mutants control, while for biofilm-forming strains combination with biofilm-disrupting agents to reduce the MBEC to achieve AUC/MBEC ratios within the possible dosing regimens is desired. PMID:24139884
Time-resolved microrheology of actively remodeling actomyosin networks
NASA Astrophysics Data System (ADS)
Silva, Marina Soares e.; Stuhrmann, Björn; Betz, Timo; Koenderink, Gijsje H.
2014-07-01
Living cells constitute an extraordinary state of matter since they are inherently out of thermal equilibrium due to internal metabolic processes. Indeed, measurements of particle motion in the cytoplasm of animal cells have revealed clear signatures of nonthermal fluctuations superposed on passive thermal motion. However, it has been difficult to pinpoint the exact molecular origin of this activity. Here, we employ time-resolved microrheology based on particle tracking to measure nonequilibrium fluctuations produced by myosin motor proteins in a minimal model system composed of purified actin filaments and myosin motors. We show that the motors generate spatially heterogeneous contractile fluctuations, which become less frequent with time as a consequence of motor-driven network remodeling. We analyze the particle tracking data on different length scales, combining particle image velocimetry, an ensemble analysis of the particle trajectories, and finally a kymograph analysis of individual particle trajectories to quantify the length and time scales associated with active particle displacements. All analyses show clear signatures of nonequilibrium activity: the particles exhibit random motion with an enhanced amplitude compared to passive samples, and they exhibit sporadic contractile fluctuations with ballistic motion over large (up to 30 μm) distances. This nonequilibrium activity diminishes with sample age, even though the adenosine triphosphate level is held constant. We propose that network coarsening concentrates motors in large clusters and depletes them from the network, thus reducing the occurrence of contractile fluctuations. Our data provide valuable insight into the physical processes underlying stress generation within motor-driven actin networks and the analysis framework may prove useful for future microrheology studies in cells and model organisms.
Turnaround Time Modeling for Conceptual Rocket Engines
NASA Technical Reports Server (NTRS)
Nix, Michael; Staton, Eric J.
2004-01-01
Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.
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.
Multiharmonic model of seismic activity in Kamchatka
NASA Astrophysics Data System (ADS)
Sobolev, G. A.; Valeev, S. G.; Faskhutdinova, V. A.
2010-12-01
Based on the uniform catalogue of earthquakes of the minimum energy class 8.5 for 1962-2008, multiharmonic models of seismic activity in Kamchatka are developed. The main harmonic components with periods from a few days to 12 years are identified. Both the entire catalogue and its modified versions obtained by the elimination of aftershocks and clusters, as well as nonoverlapping time series were used to study the stability of the models. The forward-prediction testing showed that in the models with weekly averaged initial data, periods of increased and reduced seismic activity lasting for several weeks are predicted with high confidence on an interval of up to 1.8% of the education period. This testifies for the presence of deterministic components in the seismic activity.
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.
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. PMID:24576631
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…
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…
Real-time Models at the Community Coordinated Modeling Center and their Capabilities
NASA Technical Reports Server (NTRS)
Hesse, Michael
2006-01-01
Real-time models at the Community Coordinated Modeling Center and their capabilities The Community Coordinated Modeling Center serves both scientific research and space weather operations communities through access to and evaluation of modern space environment models. Critical to both objectives is an unbiased assessment of model capabilities, which includes scientific validity, performance verification, and model robustness. While all of these assessments are relevant to operational customers, the latter plays a particularly important role. For this reason, as well as for testing model validity, CCMC established a set of fully automated real-time execution systems, which are based on models provided by the research community. This presentation will provide a summary of these activities, and a report on experiences and model validity. Finally, this presentation will invite feedback from CCMC customers regarding future directions of real time modeling at CCMC.
Modeling activity rhythms in fiddler crabs.
Dugaw, Christopher J; Honeyfield, Rebecca; Taylor, Caz M; Verzi, Diana W
2009-10-01
Burrowing crabs of the genus Uca inhabit tidal mudflats and beaches. They feed actively during low tide and remain in their burrows when the tide is high. The timing of this activity has been shown to persist in the absence of external light and tidal cues, indicating the presence of an internal timing mechanism. Researchers report the persistence of several variations in locomotor activity under laboratory conditions that cannot be explained by a single circatidal clock. Previous studies supported two alternative hypotheses: the presence of either two circalunidian clocks, or a circadian and circatidal clock to regulate these activity rhythms. In this paper, we formulate mathematical models to describe and test these hypotheses. The models suggested by the literature contain some important differences beyond the frequency of proposed clocks, and these are reflected in the mathematical formulations and simulation results. One hypothesis suggests independent phase oscillators, while the other hypothesis suggests that they are coupled in anti-phase. Neither model is able to recover all of the variations in locomotor acitivity observed under laboratory conditions. However, we propose a new model that incorporates aspects of both existing hypotheses and is able to reproduce all laboratory observations. PMID:19916836
Modelling population change from time series data
Barker, R.J.; Sauer, J.R.
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, K.A.; Cherry, S.
2009-01-01
W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r - 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep {Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed. ?? 2009 by the Ecological Society of America.
Modeling atmospheric O 2 over Phanerozoic time
NASA Astrophysics Data System (ADS)
Berner, R. A.
2001-03-01
A carbon and sulfur isotope mass balance model has been constructed for calculating the variation of atmospheric O 2 over Phanerozoic time. In order to obtain realistic O 2 levels, rapid sediment recycling and O 2-dependent isotope fractionation have been employed by the modelling. The dependence of isotope fractionation on O 2 is based, for carbon, on the results of laboratory photosynthesis experiments and, for sulfur, on the observed relation between oxidation/reduction recycling and S-isotope fractionation during early diagenetic pyrite formation. The range of fractionations used in the modeling agree with measurements of Phanerozoic sediments by others. Results, derived from extensive sensitivity analysis, suggest that there was a positive excursion of O 2 to levels as high as 35% during the Permo-Carboniferous. High O 2 at this time agrees with independent modeling, based on the abundances of organic matter and pyrite in sediments, and with the occurrence of giant insects during this period. The cause of the excursion is believed to be the rise of vascular land plants and the consequent increased production of O 2 by the burial in sediments of lignin-rich organic matter that was resistant to biological decomposition.
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. PMID:19800708
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.
Optimal design of active and semi-active suspensions including time delays and preview
NASA Astrophysics Data System (ADS)
Hac', A.; Youn, I.
1993-10-01
Several control laws for active and semi-active suspension based on a linear half car model are derived and investigated. The strategies proposed take full advantage of the fact that the road input to the rear wheels is a delayed version of that to the front wheels, which in turn can be obtained either from the measurements of the front wheels and body motions or by direct preview of road irregularities if preview sensors are available. The suspension systems are optimized with respect to ride comfort, road holding and suspension rattle space as expressed by the mean-square-values of body acceleration (including effects of heave and pitch), tire deflections and front and rear suspension travels. The optimal control laws that minimize the given performance index and include passivity constraints in the semi-active case are derived using calculus of variation. The optimal semi-active suspension becomes piecewise linear, varying between passive and fully active systems and combinations of them. The performances of active and semi-active systems with and without preview were evaluated by numerical simulation in the time and frequency domains. The results show that incorporation of time delay between the front and rear axles in controller design improves the dynamic behavior of the rear axle and control of body pitch motion, while additional preview improves front wheel dynamics and body heave.
Paolone, Giovanna; Lee, Theresa M.; Sarter, Martin
2012-01-01
Although the impairments in cognitive performance that result from shifting or disrupting daily rhythms have been demonstrated, the neuronal mechanisms that optimize fixed time daily performance are poorly understood. We previously demonstrated that daily practice of a sustained attention task (SAT) evokes a diurnal activity pattern in rats. Here we report that SAT practice at a fixed time produced practice time-stamped increases in prefrontal cholinergic neurotransmission that persisted after SAT practice was terminated and in a different environment. SAT time-stamped cholinergic activation occurred irrespective of whether the SAT was practiced during the light or dark phase or in constant light conditions. In contrast, prior daily practice of an operant schedule of reinforcement, albeit generating more rewards and lever presses per session than the SAT, neither activated the cholinergic system nor affected the animals' nocturnal activity pattern. Likewise, food-restricted animals exhibited strong food anticipatory activity (FAA) and attenuated activity during the dark period but FAA was not associated with increases in prefrontal cholinergic activity. Removal of cholinergic neurons impaired SAT performance and facilitated the reemergence of nocturnality. Shifting SAT practice away from a fixed time resulted in significantly lower performance. In conclusion, these experiments demonstrated that fixed time, daily practice of a task assessing attention generates a precisely practice time-stamped activation of the cortical cholinergic input system. Time-stamped cholinergic activation benefits fixed time performance and, if practiced during the light phase, contributes to a diurnal activity pattern. PMID:22933795
Modelling and observing Jovian electron propagation times
NASA Astrophysics Data System (ADS)
Toit Strauss, Du; Potgieter, Marius; Kopp, Andreas; Heber, Bernd
2012-07-01
During the Pioneer 10 Jovian encounter, it was observed that the Jovian magnetosphere is a strong source of low energy electrons. These electrons are accelerated in the Jovian magnetosphere and then propagate through the interplanetary medium to reach Earth, sampling the heliospheric magnetic field (HMF) and its embedded turbulence. With the current constellation of near Earth spacecraft (STEREO, SOHO, ACE, ect.) various aspects of Jovian electron transport at/near Earth can be studied in 3D (spatially). During a CME, the plasma between the Earth and Jupiter becomes more disturbed, inhibiting the transport of these electrons to Earth. With the passage of the CME beyond Jupiter, quite-time transport conditions persist and increases of the electron flux at Earth are observed (so-called quite time increases). Using multi-spacecraft observation during such an event, we are able to infer the propagation time of these electrons from Jupiter to Earth. Using a state-of-the-art electron transport model, we study the transport of these electrons from Jupiter and Earth, focusing on their propagation times. These computed values are also compared with observations. We discuss the implications of these results from a particle transport point-of-view.
Modeling interdependent animal movement in continuous time.
Niu, Mu; Blackwell, Paul G; Skarin, Anna
2016-06-01
This article presents a new approach to modeling group animal movement in continuous time. The movement of a group of animals is modeled as a multivariate Ornstein Uhlenbeck diffusion process in a high-dimensional space. Each individual of the group is attracted to a leading point which is generally unobserved, and the movement of the leading point is also an Ornstein Uhlenbeck process attracted to an unknown attractor. The Ornstein Uhlenbeck bridge is applied to reconstruct the location of the leading point. All movement parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings algorithm. We apply the method to a small group of simultaneously tracked reindeer, Rangifer tarandus tarandus, showing that the method detects dependency in movement between individuals. PMID:26812666
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.
Using Active Modeling in Counterterrorism
NASA Astrophysics Data System (ADS)
Su, Yi-Jen; Jiau, Hewijin C.; Tsai, Shang-Rong
Terrorist organizations attain their goals by attacking various targets to jeopardize human lives and intimidate governments. As new terrorist attacks almost always aim to break the mold of old plots, tracing the dynamic behaviors of terrorists becomes crucial to national defense. This paper proposes using active modeling in analyzing unconventional attacks in the design of counterterrorism system. The intelligent terrorism detection system not only detects potential threats by monitoring terrorist networks with identified threat patterns, but also continually integrates new threat features in terrorist behaviors and the varying relationships among terrorists.
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 24 Housing and Urban Development 4 2012-04-01 2012-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 24 Housing and Urban Development 4 2013-04-01 2013-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 24 Housing and Urban Development 4 2011-04-01 2011-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
24 CFR 1006.225 - Model activities.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 24 Housing and Urban Development 4 2014-04-01 2014-04-01 false Model activities. 1006.225 Section... NATIVE HAWAIIAN HOUSING BLOCK GRANT PROGRAM Eligible Activities § 1006.225 Model activities. NHHBG funds may be used for housing activities under model programs that are: (a) Designed to carry out...
Timing Interactions in Social Simulations: The Voter Model
NASA Astrophysics Data System (ADS)
Fernández-Gracia, Juan; Eguíluz, Víctor M.; Miguel, Maxi San
The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.
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.
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.
Recurrence time distributions of large earthquakes in conceptual model studies
NASA Astrophysics Data System (ADS)
Zoeller, G.; Hainzl, S.
2007-12-01
The recurrence time distribution of large earthquakes in seismically active regions is a crucial ingredient for seismic hazard assessment. However, due to sparse observational data and a lack of knowledge on the precise mechanisms controlling seismicity, this distribution is unknown. In many practical applications of seismic hazard assessment, the Brownian passage time (BPT) distribution (or a different distribution) is fitted to a small number of observational recurrence times. Here, we study various aspects of recurrence time distributions in conceptual models of individual faults and fault networks: First, the dependence of the recurrence time distribution on the fault interaction is investigated by means of a network of Brownian relaxation oscillators. Second, the Brownian relaxation oscillator is modified towards a model for large earthquakes, taking into account also the statistics of intermediate events in a more appropriate way. This model simulates seismicity in a fault zone consisting of a major fault and some surrounding smaller faults with Gutenberg-Richter type seismicity. This model can be used for more realistic and robust estimations of the real recurrence time distribution in seismic hazard assessment.
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. PMID:25998210
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…
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
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.
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
Models of Impulsively Heated Solar Active Regions
NASA Astrophysics Data System (ADS)
Airapetian, Vladimir; Klimchuk, J.
2009-05-01
A number of attempts to model solar active regions with steady coronal heating have been modestly successful at reproducing the observed soft X-ray emission, but they fail dramatically at explaining EUV observations. Since impulsive heating (nanoflare) models can reproduce individual EUV loops, it seems reasonable to consider that entire active regions are impulsively heated. However, nanoflares are characterized by many parameters, such as magnitude, duration, and time delay between successive events, and these parameters may depend on the strength of the magnetic field or the length of field lines, for example, so a wide range of active region models must be examined. We have recently begun such a study. Each model begins with a magnetic "skeleton” obtained by extrapolating an observed photospheric magnetogram into the corona. Field lines are populated with plasma using our highly efficient hydro code called Enthalpy Based Thermal Evolution of Loops (EBTEL). We then produce synthetic images corresponding to emission line or broad-band observations. By determining which set of nanoflare parameters best reproduces actual observations, we hope to constrain the properties of the heating and ultimately to reveal the physical mechanism. We here report on the initial progress of our study.
A Real-Time Hybrid Heliospheric Modeling System
NASA Astrophysics Data System (ADS)
Detman, T.; Arge, C.; Fry, C.; Dryer, M.; Smith, Z.; Pizzo, V.
2001-12-01
The Hybrid Heliospheric Modeling System (HHMS) is a combination of existing models linked together to predict solar wind conditions at Earth and associated geomagnetic activity from solar observations. The HHMS consists of four models, two physics based and two empirical, hence the term hybrid. The primary input driving the system is daily magnetograms composed into global magnetic maps of the solar photosphere. These maps are used as input to the Potential Field Source Surface model of Wang and Sheeley. The output source surface maps are modified using the Current Sheet Model of Ken Shatten. The resulting Source Surface Current Sheet (SSCS) maps are used (via an intervening empirical translation model) to drive a time dependent 3D numerical MHD solar wind model. The solar wind model gives a predicted time series of solar wind and IMF (MHD parameters) at Earth and is verified using satellite measurements such as from Omni, Wind and ACE. Subsequent empirical (data based) models can use the predicted MHD time series at Earth to predict space weather effects such as the Ap and Dst indices, geosynchronous magnetopause crossings, and relativistic (killer) electron fluxes in geosynchronous orbit. Verification of HHMS predicted Ap indices against historical observations will be shown. The MHD time series at Earth could also be used as a driver for existing physics based magnetospheric models. The HHMS also has the potential to give a predicted solar wind time series at other locations such as Mercury or Mars. The HHMS has two modes of operation. The background mode uses only the SSCS maps as described above. This mode computes an evolving background state of the solar wind in the inner heliosphere (it could be extended outward). In the event mode, a second type of input is combined with the background mode to simulate the effect of solar transient events by perturbing the input boundary of the MHD solar wind model directly. At its current grid resolution of 5° x5° (to
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…
Time-space modeling of journey-time exposure to traffic-related air pollution using GIS.
Gulliver, John; Briggs, David J
2005-01-01
Journey-time exposures represent an important, though as yet little-studied, component of human exposure to traffic-related air pollution, potentially with important health effects. Methods for assessing journey-time exposures, either as part of epidemiological studies or for policy assessment, are, however, poorly developed. This paper describes the development and testing of a GIS-based system for modeling human journey-time exposures to traffic-related air pollution: STEMS (Space-Time Exposure Modeling System). The model integrates data on source activity, pollutant dispersion, and travel behavior to derive individual- or group-level exposure measures to atmospheric pollution. The model, which is designed to simulate exposures of people as they move through a changing air pollution field, was developed, validated, and trialed in Northampton, UK. The system currently uses ArcInfo to couple four separate submodels: a source activity/emission model (SATURN), a proprietary atmospheric dispersion model (ADMS-Urban), an empirically derived background air pollution model, and a purposely designed time-activity-based exposure model (TOTEM). This paper describes the structure of the modeling system; presents results of field calibration, validation, and sensitivity analysis; and illustrates the use of the model to analyze journey-time exposures of schoolchildren. PMID:15476729
High Resolution Space-Time Ozone Modeling for Assessing Trends
Sahu, Sujit K.; Gelfand, Alan E.; Holland, David M.
2008-01-01
The assessment of air pollution regulatory programs designed to improve ground level ozone concentrations is a topic of considerable interest to environmental managers. To aid this assessment, it is necessary to model the space-time behavior of ozone for predicting summaries of ozone across spatial domains of interest and for the detection of long-term trends at monitoring sites. These trends, adjusted for the effects of meteorological variables, are needed for determining the effectiveness of pollution control programs in terms of their magnitude and uncertainties across space. This paper proposes a space-time model for daily 8-hour maximum ozone levels to provide input to regulatory activities: detection, evaluation, and analysis of spatial patterns of ozone summaries and temporal trends. The model is applied to analyzing data from the state of Ohio which has been chosen because it contains a mix of urban, suburban, and rural ozone monitoring sites in several large cities separated by large rural areas. The proposed space-time model is auto-regressive and incorporates the most important meteorological variables observed at a collection of ozone monitoring sites as well as at several weather stations where ozone levels have not been observed. This problem of misalignment of ozone and meteorological data is overcome by spatial modeling of the latter. In so doing we adopt an approach based on the successive daily increments in meteorological variables. With regard to modeling, the increment (or change-in-meteorology) process proves more attractive than working directly with the meteorology process, without sacrificing any desired inference. The full model is specified within a Bayesian framework and is fitted using MCMC techniques. Hence, full inference with regard to model unknowns is available as well as for predictions in time and space, evaluation of annual summaries and assessment of trends. PMID:19759840
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…
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
Real-Time System for Water Modeling and Management
NASA Astrophysics Data System (ADS)
Lee, J.; Zhao, T.; David, C. H.; Minsker, B.
2012-12-01
Cyberintegrator workflow system provides RESTful web services for users to provide inputs, execute workflows, and retrieve outputs. Along with REST endpoints, PAW (Publishable Active Workflows) provides the web user interface toolkit for us to develop web applications with scientific workflows. The prototype web application is built on top of workflows with PAW, so that users will have a user-friendly web environment to provide input parameters, execute the model, and visualize/retrieve the results using geospatial mapping tools. In future work the optimization model will be developed and integrated into the workflow.; Real-Time System for Water Modeling and Management
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.
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. PMID:26344941
Stratospheric ozone time series analysis using dynamical linear models
NASA Astrophysics Data System (ADS)
Laine, Marko; Kyrölä, Erkki
2013-04-01
We describe a hierarchical statistical state space model for ozone profile time series. The time series are from satellite measurements by the SAGE II and GOMOS instruments spanning years 1984-2012. The original data sets are combined and gridded monthly using 10 degree latitude bands, and covering 20-60 km with 1 km vertical spacing. Model components include level, trend, seasonal effect with solar activity, and quasi biennial oscillations as proxy variables. A typical feature of an atmospheric time series is that they are not stationary but exhibit both slowly varying and abrupt changes in the distributional properties. These are caused by external forcing such as changes in the solar activity or volcanic eruptions. Further, the data sampling is often nonuniform, there are data gaps, and the uncertainty of the observations can vary. When observations are combined from various sources there will be instrument and retrieval method related biases. The differences in sampling lead also to uncertainties. Standard classical ARIMA type of statistical time series methods are mostly useless for atmospheric data. A more general approach makes use of dynamical linear models and Kalman filter type of sequential algorithms. These state space models assume a linear relationship between the unknown state of the system and the observations and for the process evolution of the hidden states. They are still flexible enough to model both smooth trends and sudden changes. The above mentioned methodological challenges are discussed, together with analysis of change points in trends related to recovery of stratospheric ozone. This work is part of the ESA SPIN and ozone CCI projects.
Thrombin time and anti-IIa dabigatran's activity: hypothesis of thrombin time's predictive value.
Le Guyader, Maïlys; Kaabar, Mohammed; Lemaire, Pierre; Pineau Vincent, Fabienne
2015-01-01
Dabigatran etexilate (Pradaxa®) is a new oral anticoagulant, competitive inhibitor, selective, fast, direct and reversible of thrombin. Dabigatran has an impact on a large panel of used coagulation tests. There is no relationship between thrombin time's lengthening and anti-IIa activity. This study defines thrombin time's predictive value, when its time is normal. The result of negative value is 97,6%. 255 patients were studied between January 2013 and July 2014. Thrombin time and anti-IIa activity were dosed for each patient. This study can be an assistant for therapeutic decision for laboratories without specialized test. PMID:26489812
Modeling in Real Time During the Ebola Response.
Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L
2016-01-01
To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in
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…
Nur, Nurhayati Mohd; Dawal, Siti Zawiah Md; Dahari, Mahidzal; Sanusi, Junedah
2015-01-01
[Purpose] This study investigated the variations in muscle fatigue, time to fatigue, and maximum task duration at different levels of production standard time. [Methods] Twenty subjects performed repetitive tasks at three different levels of production standard time corresponding to “normal”, “hard” and “very hard”. Surface electromyography was used to measure the muscle activity. [Results] The results showed that muscle activity was significantly affected by the production standard time level. Muscle activity increased twice in percentage as the production standard time shifted from hard to very hard (6.9% vs. 12.9%). The muscle activity increased over time, indicating muscle fatigue. The muscle fatigue rate increased for the harder production standard time (Hard: 0.105; Very hard: 0.115), which indicated the associated higher risk of work-related musculoskeletal disorders. Muscle fatigue was also found to occur earlier for hard and very hard production standard times. [Conclusion] It is recommended that the maximum task duration should not exceed 5.6, 2.9, and 2.2 hours for normal, hard, and very hard production standard times, respectively, in order to maintain work performance and minimize the risk of work-related musculoskeletal disorders. PMID:26311974
Influence of time and length size feature selections for human activity sequences recognition.
Fang, Hongqing; Chen, Long; Srinivasan, Raghavendiran
2014-01-01
In this paper, Viterbi algorithm based on a hidden Markov model is applied to recognize activity sequences from observed sensors events. Alternative features selections of time feature values of sensors events and activity length size feature values are tested, respectively, and then the results of activity sequences recognition performances of Viterbi algorithm are evaluated. The results show that the selection of larger time feature values of sensor events and/or smaller activity length size feature values will generate relatively better results on the activity sequences recognition performances. PMID:24075148
Strictosidine activation in Apocynaceae: towards a "nuclear time bomb"?
2010-01-01
Background The first two enzymatic steps of monoterpene indole alkaloid (MIA) biosynthetic pathway are catalysed by strictosidine synthase (STR) that condensates tryptamine and secologanin to form strictosidine and by strictosidine β-D-glucosidase (SGD) that subsequently hydrolyses the glucose moiety of strictosidine. The resulting unstable aglycon is rapidly converted into a highly reactive dialdehyde, from which more than 2,000 MIAs are derived. Many studies were conducted to elucidate the biosynthesis and regulation of pharmacologically valuable MIAs such as vinblastine and vincristine in Catharanthus roseus or ajmaline in Rauvolfia serpentina. However, very few reports focused on the MIA physiological functions. Results In this study we showed that a strictosidine pool existed in planta and that the strictosidine deglucosylation product(s) was (were) specifically responsible for in vitro protein cross-linking and precipitation suggesting a potential role for strictosidine activation in plant defence. The spatial feasibility of such an activation process was evaluated in planta. On the one hand, in situ hybridisation studies showed that CrSTR and CrSGD were coexpressed in the epidermal first barrier of C. roseus aerial organs. However, a combination of GFP-imaging, bimolecular fluorescence complementation and electromobility shift-zymogram experiments revealed that STR from both C. roseus and R. serpentina were localised to the vacuole whereas SGD from both species were shown to accumulate as highly stable supramolecular aggregates within the nucleus. Deletion and fusion studies allowed us to identify and to demonstrate the functionality of CrSTR and CrSGD targeting sequences. Conclusions A spatial model was drawn to explain the role of the subcellular sequestration of STR and SGD to control the MIA metabolic flux under normal physiological conditions. The model also illustrates the possible mechanism of massive activation of the strictosidine vacuolar pool
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…
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. PMID:15739850
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…
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.
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. PMID:24182516
Patterns of Activity in a Global Model of a Solar Active Region
NASA Astrophysics Data System (ADS)
Bradshaw, S. J.; Viall, N. M.
2016-04-01
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.
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…
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,…
ERIC Educational Resources Information Center
Cramp, Anita G.; Bray, Steven R.
2009-01-01
The purpose of this study was to examine women's leisure time physical activity (LTPA) before pregnancy, during pregnancy, and through the first 7 months postnatal. Pre- and postnatal women (n = 309) completed the 12-month Modifiable Activity Questionnaire and demographic information. Multilevel modeling was used to estimate a growth curve…
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.
Volatility modeling of rainfall time series
NASA Astrophysics Data System (ADS)
Yusof, Fadhilah; Kane, Ibrahim Lawal
2013-07-01
Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung-Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA-GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.
Time-dependent global modeling of the inner heliosphere
NASA Astrophysics Data System (ADS)
Merkin, V. G.; Lyon, J.; Arge, C. N.; Lario, D.; Linker, J.; Lionello, R.
2015-12-01
We present results of time-dependent modeling of the inner heliosphere using the Lyon-Fedder-Mobarry (LFM) magnetohydrodynamic (MHD). Two types of simulations are performed: one concentrates on the background solar wind specification, while the other deals with the propagation of coronal mass ejections (CMEs). For simulations of the first type we coupled the LFM-helio code with the ADAPT-driven WSA model. We present some details of the coupling machinery and then simulate selected periods characterized by very low solar activity with no significant energetic particle events or CMEs. The results of the model are compared with MESSENGER, ACE, STEREO A and B spacecraft to probe both radial and temporal evolution of solar wind structure. The results indicate, in particular, the importance of time-dependent modeling for more accurate prediction of high-speed streams and heliospheric current sheet structure when the spacecraft skim its surface. We will comment on the formation of magnetic field reversals in pseudostreamer regions, which is an intrinsically time-dependent phenomenon, and on the current sheet corrugation caused by solar wind momentum shears. For the second type of time-dependent inner heliosphere simulations we have coupled LFM-helio with the MAS MHD model of the corona. We first present results of idealized coupled MAS/LFM-helio simulations with symmetric solar wind background and no rotation intended to test the interface for seamless propagation of transients from the corona into the inner heliosphere domain. We then simulate an event with a CME propagating through a realistic heliosphere background including corotating interaction regions. We show details of propagation of flux-rope CMEs through the boundary between MAS and LFM-helio and compare the results between the two codes in the heliospheric domain. The results indicate that the coupling works well, although some differences in the solutions are observed probably due to differences in numerical
An immune system-tumour interactions model with discrete time delay: Model analysis and validation
NASA Astrophysics Data System (ADS)
Piotrowska, Monika Joanna
2016-05-01
In this article a generalised mathematical model describing the interactions between malignant tumour and immune system with discrete time delay incorporated into the system is considered. Time delay represents the time required to generate an immune response due to the immune system activation by cancer cells. The basic mathematical properties of the considered model, including the global existence, uniqueness, non-negativity of the solutions, the stability of steady sates and the possibility of the existence of the stability switches, are investigated when time delay is treated as a bifurcation parameter. The model is validated with the sets of the experimental data and additional numerical simulations are performed to illustrate, extend, interpret and discuss the analytical results in the context of the tumour progression.
Evaluation of Fast-Time Wake Vortex Prediction Models
NASA Technical Reports Server (NTRS)
Proctor, Fred H.; Hamilton, David W.
2009-01-01
Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.
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...
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."
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.
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.
Oscillatory phase modulates the timing of neuronal activations and resulting behavior.
Coon, W G; Gunduz, A; Brunner, P; Ritaccio, A L; Pesaran, B; Schalk, G
2016-06-01
Human behavioral response timing is highly variable from trial to trial. While it is generally understood that behavioral variability must be due to trial-by-trial variations in brain function, it is still largely unknown which physiological mechanisms govern the timing of neural activity as it travels through networks of neuronal populations, and how variations in the timing of neural activity relate to variations in the timing of behavior. In our study, we submitted recordings from the cortical surface to novel analytic techniques to chart the trajectory of neuronal population activity across the human cortex in single trials, and found joint modulation of the timing of this activity and of consequent behavior by neuronal oscillations in the alpha band (8-12Hz). Specifically, we established that the onset of population activity tends to occur during the trough of oscillatory activity, and that deviations from this preferred relationship are related to changes in the timing of population activity and the speed of the resulting behavioral response. These results indicate that neuronal activity incurs variable delays as it propagates across neuronal populations, and that the duration of each delay is a function of the instantaneous phase of oscillatory activity. We conclude that the results presented in this paper are supportive of a general model for variability in the effective speed of information transmission in the human brain and for variability in the timing of human behavior. PMID:26975551
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.
Evidence Against a Central Control Model of Timing in Typing.
ERIC Educational Resources Information Center
Gentner, Donald R.
The evidence for the Terzuolo and Viviani central control model of timing in typing was questioned, using data collected from skilled typists and data published by Terzuolo and Viviani. (In this model keystroke times are generated in parallel from centrally stored, word-specific timing patterns. Differences in overall time to type a given word are…
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.
Budman, S H; Cooley, S; Demby, A; Koppenaal, G; Koslof, J; Powers, T
1996-07-01
This article describes a model of time-limited psychotherapy for patients with personality disorders that emphasizes the group as a social microcosm. The patient population described is relatively high functioning, although the majority of the group members meet DSM-III-R (American Psychiatric Association, 1987) criteria for an Axis II diagnosis. The clinical model's key theoretical concepts, for example, interpersonal focus; active therapist stance; emphasis on group interaction and processes; use of time limits; primary care/intermittent treatment philosophy; and emphasis on patients' strengths, goals, and resources are described. The relationships between the phases of group therapy and the key theoretical concepts are delineated. PMID:8753151
Modeling Fan Effects on the Time Course of Associative Recognition
Schneider, Darryl W.; Anderson, John R.
2011-01-01
We investigated the time course of associative recognition using the response signal procedure, whereby a stimulus is presented and followed after a variable lag by a signal indicating that an immediate response is required. More specifically, we examined the effects of associative fan (the number of associations that an item has with other items in memory) on speed–accuracy tradeoff functions obtained in a previous response signal experiment involving briefly studied materials and in a new experiment involving well-learned materials. High fan lowered asymptotic accuracy or the rate of rise in accuracy across lags, or both. We developed an Adaptive Control of Thought–Rational (ACT-R) model for the response signal procedure to explain these effects. The model assumes that high fan results in weak associative activation that slows memory retrieval, thereby decreasing the probability that retrieval finishes in time and producing a speed–accuracy tradeoff function. The ACT-R model provided an excellent account of the data, yielding quantitative fits that were as good as those of the best descriptive model for response signal data. PMID:22197797
5 CFR 551.426 - Time spent in charitable activities.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Time spent in charitable activities. 551.426 Section 551.426 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Hours of Work Application of Principles...
Physical Activity in High School during "Free-Time" Periods
ERIC Educational Resources Information Center
Silva, Pedro; Sousa, Michael; Sá, Carla; Ribeiro, José; Mota, Jorge
2015-01-01
The purpose of this study was to examine youth physical activity (PA) in free-time periods during high school days and their contribution to total PA. Differences in terms of sex, age, body mass index and school level were assessed in a sample of Portuguese adolescents. Participants totalled 213 (135 girls), aged 14.6 ± 1.7, from two different…
Influence of computer work under time pressure on cardiac activity.
Shi, Ping; Hu, Sijung; Yu, Hongliu
2015-03-01
Computer users are often under stress when required to complete computer work within a required time. Work stress has repeatedly been associated with an increased risk for cardiovascular disease. The present study examined the effects of time pressure workload during computer tasks on cardiac activity in 20 healthy subjects. Heart rate, time domain and frequency domain indices of heart rate variability (HRV) and Poincaré plot parameters were compared among five computer tasks and two rest periods. Faster heart rate and decreased standard deviation of R-R interval were noted in response to computer tasks under time pressure. The Poincaré plot parameters showed significant differences between different levels of time pressure workload during computer tasks, and between computer tasks and the rest periods. In contrast, no significant differences were identified for the frequency domain indices of HRV. The results suggest that the quantitative Poincaré plot analysis used in this study was able to reveal the intrinsic nonlinear nature of the autonomically regulated cardiac rhythm. Specifically, heightened vagal tone occurred during the relaxation computer tasks without time pressure. In contrast, the stressful computer tasks with added time pressure stimulated cardiac sympathetic activity. PMID:25614130
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 corona models - Scaling laws
NASA Technical Reports Server (NTRS)
Korevaar, P.; Martens, P. C. H.
1989-01-01
Scaling laws are derived for the one-dimensional time-dependent Euler equations that describe the evolution of a spherically symmetric stellar atmosphere. With these scaling laws the results of the time-dependent calculations by Korevaar (1989) obtained for one star are applicable over the whole Hertzsprung-Russell diagram and even to elliptic galaxies. The scaling is exact for stars with the same M/R-ratio and a good approximation for stars with a different M/R-ratio. The global relaxation oscillation found by Korevaar (1989) is scaled to main sequence stars, a solar coronal hole, cool giants and elliptic galaxies.
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…
The Remapping of Time by Active Tool-Use
Anelli, Filomena; Candini, Michela; Cappelletti, Marinella; Oliveri, Massimiliano; Frassinetti, Francesca
2015-01-01
Multiple, action-based space representations are each based on the extent to which action is possible toward a specific sector of space, such as near/reachable and far/unreachable. Studies on tool-use revealed how the boundaries between these representations are dynamic. Space is not only multidimensional and dynamic, but it is also known for interacting with other dimensions of magnitude, such as time. However, whether time operates on similar action-driven multiple representations and whether it can be modulated by tool-use is yet unknown. To address these issues, healthy participants performed a time bisection task in two spatial positions (near and far space) before and after an active tool-use training, which consisted of performing goal-directed actions holding a tool with their right hand (Experiment 1). Before training, perceived stimuli duration was influenced by their spatial position defined by action. Hence, a dissociation emerged between near/reachable and far/unreachable space. Strikingly, this dissociation disappeared after the active tool-use training since temporal stimuli were now perceived as nearer. The remapping was not found when a passive tool-training was executed (Experiment 2) or when the active tool-training was performed with participants’ left hand (Experiment 3). Moreover, no time remapping was observed following an equivalent active hand-training but without a tool (Experiment 4). Taken together, our findings reveal that time processing is based on action-driven multiple representations. The dynamic nature of these representations is demonstrated by the remapping of time, which is action- and effector-dependent. PMID:26717521
Polynomial harmonic GMDH learning networks for time series modeling.
Nikolaev, Nikolay Y; Iba, Hitoshi
2003-12-01
This paper presents a constructive approach to neural network modeling of polynomial harmonic functions. This is an approach to growing higher-order networks like these build by the multilayer GMDH algorithm using activation polynomials. Two contributions for enhancement of the neural network learning are offered: (1) extending the expressive power of the network representation with another compositional scheme for combining polynomial terms and harmonics obtained analytically from the data; (2) space improving the higher-order network performance with a backpropagation algorithm for further gradient descent learning of the weights, initialized by least squares fitting during the growing phase. Empirical results show that the polynomial harmonic version phGMDH outperforms the previous GMDH, a Neurofuzzy GMDH and traditional MLP neural networks on time series modeling tasks. Applying next backpropagation training helps to achieve superior polynomial network performances. PMID:14622880
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
Developmental patterns and parental correlates of youth leisure-time physical activity.
Lam, Chun Bun; McHale, Susan M
2015-02-01
This study examined the developmental patterns and parental correlates of youth leisure-time physical activity from middle childhood through adolescence. On 5 occasions across 7 years, fathers, mothers, and children who were first- and second born from 201 European American, working- and middle-class families participated in home and multiple nightly phone interviews. Multilevel modeling revealed that, controlling for family socioeconomic status, neighborhood characteristics, and youth overweight status and physical health, leisure-time physical activity increased during middle childhood and declined across adolescence, and the decline was more pronounced for girls than for boys. Moreover, controlling for time-varying, parental work hours and youth interest in sports and outdoor activities, on occasions when fathers and mothers spent proportionally more time on these activities with youth than usual, youth also spent more total time on these activities than usual. The within-person association between mother-youth joint involvement and youth's total involvement in leisure-time physical activity reached statistical significance at the transition to adolescence, and became stronger over time. Findings highlight the importance of maintaining adolescents', especially girls', physical activity levels and targeting both fathers' and mothers' involvement to promote youth's physical activity. PMID:25485671
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.
2014-01-01
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. PMID:25937847
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.
Deterministic Modelling of BAK Activation Kinetics
NASA Astrophysics Data System (ADS)
Grills, C.; Chacko, A.; Crawford, N.; Johnston, P. G.; Fennell, D. A.; O'Rourke, S. F. C.
2009-08-01
The molecular mechanism underlying mitochondrial BAK activation during apoptosis remains highly controversial. Two seemingly conflicting models have been proposed. In the activation model, BAK requires so-called activating BH3 only proteins (aBH3) to initiate its conformation change. In the other, displacement from inhibitory pro-survival BCL-2 proteins (PBPs) and monomerization of BAK by PBP restricted dissociator BH3-only proteins (dBH3) is sufficient. To better understand the kinetic implications of these models and reconcile these conflicting but highly evidence-based models, we have employed dynamical systems analysis to explore the kinetics underlying BAK activation as a non-linear reaction system. Our findings accommodate both pure agonism and dissociation as mutually exclusive mechanisms capable of initiating BAK activation. In addition we find our work supports a modelling based approach for predicting resistance to therapeutically relevant small molecules BH3 mimetics.
A Unified Model of Time Perception Accounts for Duration-Based and Beat-Based Timing Mechanisms
Teki, Sundeep; Grube, Manon; Griffiths, Timothy D.
2011-01-01
Accurate timing is an integral aspect of sensory and motor processes such as the perception of speech and music and the execution of skilled movement. Neuropsychological studies of time perception in patient groups and functional neuroimaging studies of timing in normal participants suggest common neural substrates for perceptual and motor timing. A timing system is implicated in core regions of the motor network such as the cerebellum, inferior olive, basal ganglia, pre-supplementary, and supplementary motor area, pre-motor cortex as well as higher-level areas such as the prefrontal cortex. In this article, we assess how distinct parts of the timing system subserve different aspects of perceptual timing. We previously established brain bases for absolute, duration-based timing and relative, beat-based timing in the olivocerebellar and striato-thalamo-cortical circuits respectively (Teki et al., 2011). However, neurophysiological and neuroanatomical studies provide a basis to suggest that timing functions of these circuits may not be independent. Here, we propose a unified model of time perception based on coordinated activity in the core striatal and olivocerebellar networks that are interconnected with each other and the cerebral cortex through multiple synaptic pathways. Timing in this unified model is proposed to involve serial beat-based striatal activation followed by absolute olivocerebellar timing mechanisms. PMID:22319477
Assessment of toxicity using dehydrogenases activity and mathematical modeling.
Matyja, Konrad; Małachowska-Jutsz, Anna; Mazur, Anna K; Grabas, Kazimierz
2016-07-01
Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (TMDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and TMDTE are more appropriate than EC50 and IC50 for toxicity assessments, except for long exposure times. PMID:27021434
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
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.
Kim, Neil H; Lee, Gloria; Sherer, Nicholas A; Martini, K Michael; Goldenfeld, Nigel; Kuhlman, Thomas E
2016-06-28
The excision and reintegration of transposable elements (TEs) restructure their host genomes, generating cellular diversity involved in evolution, development, and the etiology of human diseases. Our current knowledge of TE behavior primarily results from bulk techniques that generate time and cell ensemble averages, but cannot capture cell-to-cell variation or local environmental and temporal variability. We have developed an experimental system based on the bacterial TE IS608 that uses fluorescent reporters to directly observe single TE excision events in individual cells in real time. We find that TE activity depends upon the TE's orientation in the genome and the amount of transposase protein in the cell. We also find that TE activity is highly variable throughout the lifetime of the cell. Upon entering stationary phase, TE activity increases in cells hereditarily predisposed to TE activity. These direct observations demonstrate that real-time live-cell imaging of evolution at the molecular and individual event level is a powerful tool for the exploration of genome plasticity in stressed cells. PMID:27298350
The timing of noise-sensitive activities in residential areas
NASA Astrophysics Data System (ADS)
Fields, J. M.
1985-07-01
Data from a nationally representative survey of time use was analyzed to provide estimates of the percentage of the population which is engaged in noise sensitive activities during each hour of the day on weekdays, Fridays, Saturdays and Sundays. Estimates are provided of the percentage engaged in aural communication activities at home, sleeping at home, or simply at home. The day can be roughly divided into four noise sensitivity periods consisting of two relatively steady state periods, night and day and the early morning and evening transition periods. Weekends differ from weekdays in that the morning transition period is one hour later and the numbers of people engaged in aural communication during the day at home are approximately one-half to three-quarters greater. The extent and timing of noise sensitive activities was found to be similiar for all parts of the United States, for different sizes of urban areas, and for the three seasons surveyed (September through May). The timing of activity periods does not differ greatly by sex or age even though women and people over 65 are much more likely to be at home during the daytime.
Quiet time particle fluxes and active phenomena on the Sun
NASA Astrophysics Data System (ADS)
Ishkov, Vitaly; Zeldovich, Mariya; Logachev, Yurii; Kecskemety, Karoly
Using ACE, SOHO and STEREO data the connection of quiet time particle fluxes with active processes on the Sun is examined in the 23rd SC. Investigation of the intervals selected in the conditions of low solar activity supports our assumption that the active structures on the Sun arising during minimum solar activity are mostly responsible for background particle fluxes. Sources on the Sun of charged particles with energies 0.3-8 MeV/nucleon have been determined during quiet time periods over all solar cycle by comparison with solar wind fluxes. It is shown that at the solar maximum a part of background fluxes with abundances of C and Fe corresponding to mean values in solar corona resulted from equatorial coronal holes. Bipolar structures arising in the hole area (bright X-ray points) were accompanied in most cases by the ejection of solar plasma according to HINOTORI satellite. The speed of a part of such emissions and open magnetic field lines above coronal holes can allow energetic particles to escape into the interplanetary space. During solar minimum abundances of C and Fe in majority of quiet time fluxes corresponded to solar wind values possibly indicating the common origin of energetic particle and solar wind fluxes.
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.
An ultrasound personal locator for time-activity assessment.
Allen-Piccolo, Gian; Rogers, Jamesine V; Edwards, Rufus; Clark, Michael C; Allen, T Tracy; Ruiz-Mercado, Ilse; Shields, Kyra N; Canuz, Eduardo; Smith, Kirk R
2009-01-01
The UC Berkeley Time-Activity Monitoring System (UCB-TAMS) was developed to measure time-activity in exposure studies. The system consists of small, light, inexpensive battery-operated 40-kHz ultrasound transmitters (tags) worn by participants and an ultrasound receiver (locator) attached to a datalogger fixed in an indoor location. Presence or absence of participants is monitored by distinguishing the unique ultrasound ID of each tag. Efficacy tests in rural households of highland Guatemala showed the system to be comparable to the gold-standard time-activity measure of direct observation by researchers, with an accuracy of predicting time-weighted averages of 90-95%, minute-by-minute accuracy of 80-85%, and sensitivity/specificity values of 86-89%/71-74% for one-minute readings on children 3-8 years-old. Additional controlled tests in modern buildings and in rural Guatemalan homes confirmed the performance of the system with the presence of other ultrasound sources, with multiple tags, covered by clothing, and in other non-ideal circumstances. PMID:19496478
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
Time dependent modeling at Mt. Etna volcano: an application to the 2005-2013 time interval
NASA Astrophysics Data System (ADS)
Cannavo', Flavio; McCaffrey, Robert; Palano, Mimmo
2015-04-01
Following the 2004-05 eruption, Mt. Etna activity has been characterized by the occurrence of a number of eruptive episodes (2006, 2008 and 2012) and more than 35 paroxysmal events (mainly during the 2011-2012 time interval). In addition, continuous downslope motion of its eastern flank has affected the volcano. This seaward motion has been characterized by some episodic phases combined with the occurrence of multiple slow slip events (SSEs). In order to obtain a comprehensive view of the time evolution of these observed features and thus provide new insight into the ground deformation pattern of Mt. Etna, here we use time-dependent modeling of the three-component daily time series of all GNSS continuous stations installed on the volcanic edifice. All GNSS data spanning the 2005-2013 time interval were processed using the GAMIT/GLOBK software (Herring et al. 2010) following the strategy described in Gonzalez and Palano (2014). Estimated GNSS daily time series were referred to the "Etn@ref" reference frame (a local reference frame computed to isolate the Mt. Etna volcanic deformation from the background tectonic pattern; Palano et al. 2010). Using these daily time series as input we performed a time-dependent, non-linear inversion using the TDEFNODE code (McCaffrey, 2009). We used TDEFNODE to invert the time series to model simultaneously the steady tectonic kinematics plus the transient volcanic and tectonic sources, thus obtaining a realistic model of the complex area. Preliminary results allow us to track, over the considered time interval, the volume changes associated to the activity of a magmatic reservoir located at a depth of about 5 km b.s.l. beneath the upper western flank of the volcano, as well as the location and associated magnitude of four SSEs below the eastern flank. In addition, we attempted a preliminary subdivision of the southern and eastern flanks of Mt. Etna into four tectonic blocks which provide a reasonable representation of the observed
Assimilation of LAI time-series in crop production models
NASA Astrophysics Data System (ADS)
Kooistra, Lammert; Rijk, Bert; Nannes, Louis
2014-05-01
Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor
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.
Active movement restores veridical event-timing after tactile adaptation.
Tomassini, Alice; Gori, Monica; Burr, David; Sandini, Giulio; Morrone, Maria Concetta
2012-10-01
Growing evidence suggests that time in the subsecond range is tightly linked to sensory processing. Event-time can be distorted by sensory adaptation, and many temporal illusions can accompany action execution. In this study, we show that adaptation to tactile motion causes a strong contraction of the apparent duration of tactile stimuli. However, when subjects make a voluntary motor act before judging the duration, it annuls the adaptation-induced temporal distortion, reestablishing veridical event-time. The movement needs to be performed actively by the subject: passive movement of similar magnitude and dynamics has no effect on adaptation, showing that it is the motor commands themselves, rather than reafferent signals from body movement, which reset the adaptation for tactile duration. No other concomitant perceptual changes were reported (such as apparent speed or enhanced temporal discrimination), ruling out a generalized effect of body movement on somatosensory processing. We suggest that active movement resets timing mechanisms in preparation for the new scenario that the movement will cause, eliminating inappropriate biases in perceived time. Our brain seems to utilize the intention-to-move signals to retune its perceptual machinery appropriately, to prepare to extract new temporal information. PMID:22832572
Mota, Jorge; Gomes, Helena; Almeida, Mariana; Ribeiro, José Carlos; Santos, Maria Paula
2007-08-01
This study analyzes the relationships between leisure time physical activity (LTPA), sedentary behaviors, socioeconomic status, and perceived environmental variables. The sample comprised 815 girls and 746 boys. In girls, non-LTPA participants reported significantly more screen time. Girls with safety concerns were more likely to be in the non-LTPA group (OR = 0.60) and those who agreed with the importance of aesthetics were more likely to be in the active-LTPA group (OR = 1.59). In girls, an increase of 1 hr of TV watching was a significant predictor of non-LTPA (OR = 0.38). LTPA for girls, but not for boys, seems to be influenced by certain modifiable factors of the built environment, as well as by time watching TV. PMID:18019587
Time-Driven Activity-Based Costing in Emergency Medicine.
Yun, Brian J; Prabhakar, Anand M; Warsh, Jonathan; Kaplan, Robert; Brennan, John; Dempsey, Kyle E; Raja, Ali S
2016-06-01
Value in emergency medicine is determined by both patient-important outcomes and the costs associated with achieving them. However, measuring true costs is challenging. Without an understanding of costs, emergency department (ED) leaders will be unable to determine which interventions might improve value for their patients. Although ongoing research may determine which outcomes are meaningful, an accurate costing system is also needed. This article reviews current costing mechanisms in the ED and their pitfalls. It then describes how time-driven activity-based costing may be superior to these current costing systems. Time-driven activity-based costing, in addition to being a more accurate costing system, can be used for process improvements in the ED. PMID:26365921
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
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…
Mischke, R; Wolling, H
2000-01-01
To investigate how thrombin time, activated partial thromboplastin time (APTT) and prothrombin time are influenced by fibrinogen degradation products (FDP), different concentrations (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8 and 1.0 mg/ml) of the purified FDP X, Y, D and E were added to the plasma of healthy dogs. If fragment Y was added to the plasma a considerable inhibitory effect could be demonstrated for all three test systems. A significant prolongation (p < 0.05) was found for concentrations of > or =0.1 mg/ml (thrombin time, APTT) and > or =0.2 mg/ml (prothrombin time). With FDP Y concentrations from >0.185 mg/ml (prothrombin time) to >0.24 mg/ml (APTT) coagulation time was prolonged beyond the respective reference range. As regards the other fragments, a comparable inhibitory effect could only be shown for fragment X added to the thrombin time test system. This effect can most probably be explained by the competition of the FDP X and fibrinogen for the fibrinogen binding sites of thrombin, rather than by a fibrin polymerization disorder. The results demonstrate that for plasma with normal fibrinogen concentration the group tests are only prolonged beyond the reference range at FDP concentrations very rarely found in spontaneous hyperfibrinolysis. PMID:11014962
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). PMID:25381597
Eaves, B.C.; Rothblum, U.G.
1990-08-01
A discounted-cost, continuous-time, infinite-horizon version of a flexible manufacturing and operator scheduling model is solved. The solution procedure is to convexify the discrete operator-assignment constraints to obtain a linear program, and then to regain the discreteness and obtain an approximate manufacturing schedule by deconvexification of the solution of the linear program over time. The strong features of the model are the accommodation of linear inequality relations among the manufacturing activities and the discrete manufacturing scheduling, whereas the weak features are intra-period relaxation of inventory availability constraints, and the absence of inventory costs, setup times, and setup charges.
Time series modeling of system self-assessment of survival
Lu, H.; Kolarik, W.J.
1999-06-01
Self-assessment of survival for a system, subsystem or component is implemented by assessing conditional performance reliability in real-time, which includes modeling and analysis of physical performance data. This paper proposes a time series analysis approach to system self-assessment (prediction) of survival. In the approach, physical performance data are modeled in a time series. The performance forecast is based on the model developed and is converted to the reliability of system survival. In contrast to a standard regression model, a time series model, using on-line data, is suitable for the real-time performance prediction. This paper illustrates an example of time series modeling and survival assessment, regarding an excessive tool edge wear failure mode for a twist drill operation.
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
Structural models for nickel electrode active mass
NASA Technical Reports Server (NTRS)
Cornilsen, B. C.; Karjala, P. J.; Loyselle, P. L.
1988-01-01
Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and X ray diffraction data are analyzed and shown to be consistent with this structural model.
Structural models for nickel electrode active mass
NASA Technical Reports Server (NTRS)
Cornilsen, Bahne C.; Karjala, P. J.; Loyselle, P. L.
1987-01-01
Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and x ray diffraction data are analyzed and shown to be consistent with this structural model.
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
2014-01-01
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. PMID:24473370
An Advanced Time Averaging Modelling Technique for Power Electronic Circuits
NASA Astrophysics Data System (ADS)
Jankuloski, Goce
For stable and efficient performance of power converters, a good mathematical model is needed. This thesis presents a new modelling technique for DC/DC and DC/AC Pulse Width Modulated (PWM) converters. The new model is more accurate than the existing modelling techniques such as State Space Averaging (SSA) and Discrete Time Modelling. Unlike the SSA model, the new modelling technique, the Advanced Time Averaging Model (ATAM) includes the averaging dynamics of the converter's output. In addition to offering enhanced model accuracy, application of linearization techniques to the ATAM enables the use of conventional linear control design tools. A controller design application demonstrates that a controller designed based on the ATAM outperforms one designed using the ubiquitous SSA model. Unlike the SSA model, ATAM for DC/AC augments the system's dynamics with the dynamics needed for subcycle fundamental contribution (SFC) calculation. This allows for controller design that is based on an exact model.
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.
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
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.
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.
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
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
Genetic and Environmental Influences on the Allocation of Adolescent Leisure Time Activities
Haberstick, Brett C.; Zeiger, Joanna S.; Corley, Robin P.
2014-01-01
There is a growing recognition of the importance of the out-of-school activities in which adolescents choose to participate. Youth activities vary widely in terms of specific activities and in time devoted to them but can generally be grouped by the type and total duration spent per type. We collected leisure time information using a 17-item leisure time questionnaire in a large sample of same- and opposite-sex adolescent twin pairs (N = 2847). Using both univariate and multivariate genetic models, we sought to determine the type and magnitude of genetic and environmental influences on the allocation of time toward different leisure times. Results indicated that both genetic and shared and nonshared environmental influences were important contributors to individual differences in physical, social, intellectual, family, and passive activities such as watching television. The magnitude of these influences differed between males and females. Environmental influences were the primary factors contributing to the covariation of different leisure time activities. Our results suggest the importance of heritable influences on the allocation of leisure time activity by adolescents and highlight the importance of environmental experiences in these choices. PMID:24967407
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…
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.
Frequency and time domain modeling of high speed amplifier
NASA Astrophysics Data System (ADS)
Opalska, Katarzyna
2015-09-01
The paper presents the lumped model of high speed amplifier useful for frequency and time domain (also large signal) simulation. Model is constructed on the basis of two-domain device measurements, namely small signal frequency parameters and time response to the input step of varying amplitude. Rational approximation of frequency domain data leads to small signal model composed of RLC subcircuits and controlled sources. Next, the model is complimented with the nonlinearities identified from time-domain measurements, including those taken for large input signals. Final amplifier model implemented in SPICE simulator is shown to correctly render the behavior of the device over the wide variety of operating conditions.
A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation
NASA Astrophysics Data System (ADS)
Pham, Cuong; Plötz, Thomas; Olivier, Patrick
We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.
Integrated active sensor system for real time vibration monitoring
NASA Astrophysics Data System (ADS)
Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue
2015-11-01
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.
Integrated active sensor system for real time vibration monitoring
Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue
2015-01-01
We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems. PMID:26538293
Integrated active sensor system for real time vibration monitoring.
Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue
2015-01-01
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
Model Assessment and Optimization Using a Flow Time Transformation
NASA Astrophysics Data System (ADS)
Smith, T. J.; Marshall, L. A.; McGlynn, B. L.
2012-12-01
Hydrologic modeling is a particularly complex problem that is commonly confronted with complications due to multiple dominant streamflow states, temporal switching of streamflow generation mechanisms, and dynamic responses to model inputs based on antecedent conditions. These complexities can inhibit the development of model structures and their fitting to observed data. As a result of these complexities and the heterogeneity that can exist within a catchment, optimization techniques are typically employed to obtain reasonable estimates of model parameters. However, when calibrating a model, the cost function itself plays a large role in determining the "optimal" model parameters. In this study, we introduce a transformation that allows for the estimation of model parameters in the "flow time" domain. The flow time transformation dynamically weights streamflows in the time domain, effectively stretching time during high streamflows and compressing time during low streamflows. Given the impact of cost functions on model optimization, such transformations focus on the hydrologic fluxes themselves rather than on equal time weighting common to traditional approaches. The utility of such a transform is of particular note to applications concerned with total hydrologic flux (water resources management, nutrient loading, etc.). The flow time approach can improve the predictive consistency of total fluxes in hydrologic models and provide insights into model performance by highlighting model strengths and deficiencies in an alternate modeling domain. Flow time transformations can also better remove positive skew from the streamflow time series, resulting in improved model fits, satisfaction of the normality assumption of model residuals, and enhanced uncertainty quantification. We illustrate the value of this transformation for two distinct sets of catchment conditions (snow-dominated and subtropical).
Comparison of several activated partial thromboplastin time methods.
Morin, R J; Willoughby, D
1975-08-01
Activated partial thromboplastin times (APTT's) performed with a semi-automated electrical-conductivity type of clot timer on plasmas from patients with hepatic disease and intravascular coagulation, and on warfarin or heparin therapy, were significantly lower than when done on the same plasmas with either a manual optical method or an automated optical-endpoint instrument. Results of APTT's done on normal plasmas by the three methods were not significantly different. Substitution of different activator-phospholipid reagents resulted in some variability in results, but these differences were less than those between the different done with both the electrical clot timer and the automated optical instrument on prepared plasmas containing 5.0 or 1.0% of factor II, V, VIII, IX, OR X revealed shorter times with the electrical clot timer only in the case of factor II- and factor V-deficient plasmas. APTT's done on normal plasmas to which 0.1 or 0.3 units per ml. of heparin had been added vitro also were shorter with the electrical clot itmer than the automatic optical instrument. Prothrombin times done on normal and abnormal control plasmas and on a series of plasmas from patients on warfarin therapy showed no significant difference between the two methods. PMID:239589
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.
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
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…
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.…
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.
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.
The timing of alluvial activity in Gale crater, Mars
NASA Astrophysics Data System (ADS)
Grant, John A.; Wilson, Sharon A.; Mangold, Nicolas; Calef, Fred; Grotzinger, John P.
2014-02-01
The Curiosity rover's discovery of rocks preserving evidence of past habitable conditions in Gale crater highlights the importance of constraining the timing of responsible depositional settings to understand the astrobiological implications for Mars. Crater statistics and mapping reveal the bulk of the alluvial deposits in Gale, including those interrogated by Curiosity, were likely emplaced during the Hesperian, thereby implying that habitable conditions persisted after the Noachian. Crater counting data sets and upper Peace Vallis fan morphology also suggest a possible younger period of fluvial activation that deposited ~10-20 m of sediments on the upper fan after emplacement of the main body of the fan. If validated, water associated with later alluvial activity may have contributed to secondary diagenetic features in Yellowknife Bay.
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.
Linear system identification via backward-time observer models
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh
1993-01-01
This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.
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.
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…
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…
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.
UASB reactor hydrodynamics: residence time distribution and proposed modelling tools.
López, I; Borzacconi, L
2010-05-01
The hydrodynamic behaviour of UASB (Up Flow Anaerobic Sludge Blanket) reactors based on residence time distribution curves allows the implementation of global models, including the kinetic aspects of biological reactions. The most relevant hydrodynamic models proposed in the literature are discussed and compared with the extended tanks in series (ETIS) model. Although derived from the tanks in series model, the ETIS model's parameter is not an integer. The ETIS model can be easily solved in the Laplace domain and applied to a two-stage anaerobic digestion linear model. Experimental data from a 250 m3 UASB reactor treating malting wastewater are used to calibrate and validate the proposed model. PMID:20540420
Performance modeling and measurement of real-time multiprocessors with time-shared buses
Woodbury, M.H.; Shin, K.G.
1988-02-01
A closed queueing network model is constructed to address workload effects on computer performance for a highly reliable unibus multiprocessor used in real-time control. The queueing model consists of multiserver nodes and a nonpreemptive priority queue. Use of this model requires partitioning the workload into task classes. The time average steady-state solution of the queuing model directly produces useful results that are necessary in performance evaluation. The model is experimentally justified with the Fault-Tolerant Multiprocessor (FTMP) located at the NASA AIRLAB. Extensive experiments are performed on FTMP with a synthetic workload generator (SWG) to directly measure performance parameters, such as processor idle time, system bus contention, and task processing times. These measurements determine values for parameters in the queueing model. Experimental and analytic results are then compared.
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.
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…
A Reparametrization Approach for Dynamic Space-Time Models
Lee, Hyeyoung; Ghosh, Sujit K.
2009-01-01
Researchers in diverse areas such as environmental and health sciences are increasingly working with data collected across space and time. The space-time processes that are generally used in practice are often complicated in the sense that the auto-dependence structure across space and time is non-trivial, often non-separable and non-stationary in space and time. Moreover, the dimension of such data sets across both space and time can be very large leading to computational difficulties due to numerical instabilities. Hence, space-time modeling is a challenging task and in particular parameter estimation based on complex models can be problematic due to the curse of dimensionality. We propose a novel reparametrization approach to fit dynamic space-time models which allows the use of a very general form for the spatial covariance function. Our modeling contribution is to present an unconstrained reparametrization method for a covariance function within dynamic space-time models. A major benefit of the proposed unconstrained reparametrization method is that we are able to implement the modeling of a very high dimensional covariance matrix that automatically maintains the positive definiteness constraint. We demonstrate the applicability of our proposed reparametrized dynamic space-time models for a large data set of total nitrate concentrations. PMID:21593998
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.
The Space-Time Model According to Dimensional Continuous Space-Time Theory
NASA Astrophysics Data System (ADS)
Martini, Luiz Cesar
2014-04-01
This article results from the Dimensional Continuous Space-Time Theory for which the introductory theoretician was presented in [1]. A theoretical model of the Continuous Space-Time is presented. The wave equation of time into absolutely stationary empty space referential will be described in detail. The complex time, that is the time fixed on the infinite phase time speed referential, is deduced from the New View of Relativity Theory that is being submitted simultaneously with this article in this congress. Finally considering the inseparable Space-Time is presented the duality equation wave-particle.
Bifurcation and oscillation in a time-delay neural mass model.
Geng, Shujuan; Zhou, Weidong; Zhao, Xiuhe; Yuan, Qi; Ma, Zhen; Wang, Jiwen
2014-12-01
The neural mass model developed by Lopes da Silva et al. simulates complex dynamics between cortical areas and is able to describe a limit cycle behavior for alpha rhythms in electroencephalography (EEG). In this work, we propose a modified neural mass model that incorporates a time delay. This time-delay model can be used to simulate several different types of EEG activity including alpha wave, interictal EEG, and ictal EEG. We present a detailed description of the model's behavior with bifurcation diagrams. Through simulation and an analysis of the influence of the time delay on the model's oscillatory behavior, we demonstrate that a time delay in neuronal signal transmission could cause seizure-like activity in the brain. Further study of the bifurcations in this new neural mass model could provide a theoretical reference for the understanding of the neurodynamics in epileptic seizures. PMID:25048203
ERIC Educational Resources Information Center
Blozis, Shelley A.; Cho, Young Il
2008-01-01
The coding of time in latent curve models has been shown to have important implications in the interpretation of growth parameters. Centering time is often done to improve interpretation but may have consequences for estimated parameters. This article studies the effects of coding and centering time when there is interindividual heterogeneity in…
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.
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.
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
Model for the Distribution of Aftershock Interoccurrence Times
Shcherbakov, Robert; Yakovlev, Gleb; Rundle, John B.; Turcotte, Donald L.
2005-11-18
In this work the distribution of interoccurrence times between earthquakes in aftershock sequences is analyzed and a model based on a nonhomogeneous Poisson (NHP) process is proposed to quantify the observed scaling. In this model the generalized Omori's law for the decay of aftershocks is used as a time-dependent rate in the NHP process. The analytically derived distribution of interoccurrence times is applied to several major aftershock sequences in California to confirm the validity of the proposed hypothesis.
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.
A Markov switching model for annual hydrologic time series
NASA Astrophysics Data System (ADS)
Akıntuǧ, B.; Rasmussen, P. F.
2005-09-01
This paper investigates the properties of Markov switching (MS) models (also known as hidden Markov models) for generating annual time series. This type of model has been used in a number of recent studies in the water resources literature. The model considered here assumes that climate is switching between M states and that the state sequence can be described by a Markov chain. Observations are assumed to be drawn from a normal distribution whose parameters depend on the state variable. We present the stochastic properties of this class of models along with procedures for model identification and parameter estimation. Although, at a first glance, MS models appear to be quite different from ARMA models, we show that it is possible to find an ARMA model that has the same autocorrelation function and the same marginal distribution as any given MS model. Hence, despite the difference in model structure, there are strong similarities between MS and ARMA models. MS and ARMA models are applied to the time series of mean annual discharge of the Niagara River. Although it is difficult to draw any general conclusion from a single case study, it appears that MS models (and ARMA models derived from MS models) generally have stronger autocorrelation at higher lags than ARMA models estimated by conventional maximum likelihood. This may be an important property if the purpose of the study is the analysis of multiyear droughts.
NASA Astrophysics Data System (ADS)
Mojtaba Tabatabaeipour, Seyed
2015-08-01
Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed. In set-membership approaches, instead of a point-wise estimation of the states, a set-valued estimation of them is computed. If this set becomes empty the given model of the system is not consistent with the measurements. Therefore, the model is falsified. When more than one model of the system remains un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved by a number of linear and quadratic programming problems, which result in a computationally efficient algorithm. The method is tested on a numerical example as well as on the pitch actuator of a benchmark wind turbine.
Time-delayed coupled logistic capacity model in population dynamics
NASA Astrophysics Data System (ADS)
Cáceres, Manuel O.
2014-08-01
This study proposes a delay-coupled system based on the logistic equation that models the interaction of a population with its varying environment. The integro-diferential equations of the model are presented in terms of a distributed time-delayed coupled logistic-capacity equation. The model eliminates the need for a prior knowledge of the maximum saturation environmental carrying capacity value. Therefore the dynamics toward the final attractor in a distributed time-delayed coupled logistic-capacity model is studied. Exact results are presented, and analytical conclusions have been done in terms of the two parameters of the model.
Intercept Centering and Time Coding in Latent Difference Score Models
ERIC Educational Resources Information Center
Grimm, Kevin J.
2012-01-01
Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…
A Formal Model for Real-Time Parallel Computation
Hui, Peter SY; Chikkagoudar, Satish
2012-12-29
The imposition of real-time constraints on a parallel computing environment--- specifically high-performance, cluster-computing systems--- introduces a variety of challenges with respect to the formal verification of the system's timing properties. In this paper, we briefly motivate the need for such a system, and we introduce an automaton-based method for performing such formal verification. We define the concept of a consistent parallel timing system: a hybrid system consisting of a set of timed automata (specifically, timed Buechi automata as well as a timed variant of standard finite automata), intended to model the timing properties of a well-behaved real-time parallel system. Finally, we give a brief case study to demonstrate the concepts in the paper: a parallel matrix multiplication kernel which operates within provable upper time bounds. We give the algorithm used, a corresponding consistent parallel timing system, and empirical results showing that the system operates under the specified timing constraints.
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
School playgrounds and physical activity policies as predictors of school and home time activity
2011-01-01
Background Previous work has suggested that the number of permanent play facilities in school playgrounds and school-based policies on physical activity can influence physical activity in children. However, few comparable studies have used objective measures of physical activity or have had little adjustment for multiple confounders. Methods Physical activity was measured by accelerometry over 5 recess periods and 3 full school days in 441 children from 16 primary schools in Dunedin, New Zealand. The number of permanent play facilities (swing, fort, slide, obstacle course, climbing wall etc) in each school playground was counted on three occasions by three researchers following a standardized protocol. Information on school policies pertaining to physical activity and participation in organized sport was collected by questionnaire. Results Measurement of school playgrounds proved to be reliable (ICC 0.89) and consistent over time. Boys were significantly more active than girls (P < 0.001), but little time overall was spent in moderate-vigorous physical activity (MVPA). Boys engaged in MVPA for 32 (SD 17) minutes each day of which 17 (10) took place at school compared with 23 (14) and 11 (7) minutes respectively in girls. Each additional 10-unit increase in play facilities was associated with 3.2% (95% CI 0.0-6.4%) more total activity and 8.3% (0.8-16.3%) more MVPA during recess. By contrast, school policy score was not associated with physical activity in children. Conclusion The number of permanent play facilities in school playgrounds is associated with higher physical activity in children, whereas no relationship was observed for school policies relating to physical activity. Increasing the number of permanent play facilities may offer a cost-effective long-term approach to increasing activity levels in children. PMID:21521530
Yang, Xiaobao; Abdel-Aty, Mohamed; Huan, Mei; Peng, Yichuan; Gao, Ziyou
2015-09-01
The waiting process is crucial to pedestrians in the street-crossing behavior. Once pedestrians terminate their waiting behavior during the red light period, they would cross against the red light and put themselves in danger. A joint hazard-based duration model is developed to investigate the effect of various covariates on pedestrian crossing behavior and to estimate pedestrian waiting times at signalized intersections. A total of 1181 pedestrians approaching the intersections during red light periods were observed in Beijing, China. Pedestrian crossing behaviors are classified into immediate crossing behavior and waiting behavior. The probability and effect of various covariates for pedestrians' immediate crossing behavior are identified by a logit model. Four accelerated failure time duration models based on the exponential, Weibull, lognormal and log-logistic distributions are proposed to examine the significant risk factors affecting duration times for pedestrians' waiting behavior. A joint duration model is developed to estimate pedestrian waiting times. Moreover, unobserved heterogeneity is considered in the proposed model. The results indicate that the Weibull AFT model with shared frailty is appropriate for modelling pedestrian waiting durations. Failure to account for heterogeneity would significantly underestimate the effects of covariates on waiting duration times. The proposed model provides a better understanding of pedestrian crossing behavior and more accurate estimation of pedestrian waiting times. It may be applicable in traffic system analysis in developing countries with high flow of mixed traffic. PMID:26072184
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.
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…
Modeling direct activation of corticospinal axons using transcranial electrical stimulation.
Suihko, V
1998-06-01
Corticospinal axons can be directly activated using anodal transcranial electrical stimulation. The purpose of this work was to find the location of the direct activation. The response to stimulation was modeled with a spherical head model and an active model of a corticospinal nerve. The nerve model had a deep bend at a location corresponding to a corticospinal fiber entering the midbrain. The threshold activation initiated close to brain surface; the exact location depended on whether the cell body located in the surface layers of the brain or in the bank of the central sulcus. The stimulation time constant was 44 micros. When the stimulus amplitude was increased, the site of activation shifted gradually to deeper level, until the activation initiated directly at the bend causing a half millisecond latency jump at spinal level. These results support the theory that the corticospinal axons can be directly activated at deep locations using anodal transcranial electrical stimulation. However, the high amplitude needed for the direct activation suggests that not only the bends on the fibers, but also the shape of surrounding volume conductor (intracranial cavity) favor activation at this location. PMID:9741790
Changes in screen time activity in Norwegian children from 2001 to 2008: two cross sectional studies
2013-01-01
Background There has been an increase in screen-based communication, leading to concerns about the negative health effects of screen-based activities in children and adolescents. The present study aimed to (1) analyze changes in screen time activity in Norwegian children from 2001 to 2008, and (2) to analyze associations between the changes in screen time activity over time and sex, grade level and parental educational level. Methods Within the project Fruits and Vegetables Make the Marks (FVMM), 1488 6th and 7th grade pupils from 27 Norwegian elementary schools completed a questionnaire including a question about time spent on television viewing and personal computer use in 2001 and 1339 pupils from the same schools completed the same questionnaire in 2008. Data were analyzed by multilevel linear mixed models. Results The proportions of 6th and 7th grade pupils at the 27 schools that reported screen time activity outside school of 2 hours/day or more decreased from 55% to 45% (p<0.001) from 2001 to 2008 when adjusting for sex, grade level and parental education. The decrease was most evident in 6th graders (51% to 37%) and in children with highly educated parents (54% to 39%). Conclusion The present study shows that there has been a marked reduction in screen time activity outside school in this group of Norwegian 10–12 year olds from 2001 to 2008. PMID:23356930
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
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.
Real-Time GNSS Positioning Along Canada's Active Coastal Margin
NASA Astrophysics Data System (ADS)
Henton, J. A.; Dragert, H.; Lu, Y.
2014-12-01
High-rate, low-latency Global Navigation Satellite System (GNSS) data are being refined for real-time applications to monitor and report motions related to large earthquakes in coastal British Columbia. Given the tectonic setting of Canada's west coast, specific goals for real-time regional geodetic monitoring are: (1) the collection of GNSS data with adequate station density to identify the deformation field for regional earthquakes with M>7.3; (2) the robust, continuous real-time analyses of GNSS data with a precision of 1-2 cm and a latency of less than 10s; and (3) the display of results with attending automated alarms and estimations of earthquake parameters. Megathrust earthquakes (M>8) are the primary targets for immediate identification, since the tsunamis they generate will strike the coast within 15 to 20 min. However, large (6.0
Functional and stochastic models estimation for GNSS coordinates time series
NASA Astrophysics Data System (ADS)
Galera Monico, J. F.; Silva, H. A.; Marques, H. A.
2014-12-01
GNSS has been largely used in Geodesy and correlated areas for positioning. The position and velocity of terrestrial stations have been estimated using GNSS data based on daily solutions. So, currently it is possible to analyse the GNSS coordinates time series aiming to improve the functional and stochastic models what can help to understand geodynamic phenomena. Several sources of errors are mathematically modelled or estimated in the GNSS data processing to obtain precise coordinates what in general is carried out by using scientific software. However, due to impossibility to model all errors some kind of noises can remain contaminating the coordinate time series, especially those related with seasonal effects. The noise affecting GNSS coordinate time series can be composed by white and coloured noises what can be characterized from Variance Component Estimation technique through Least Square Method. The methodology to characterize noise in GNSS coordinates time series will be presented in this paper so that the estimated variance can be used to reconstruct stochastic and functional models of the times series providing a more realistic and reliable modeling of time series. Experiments were carried out by using GNSS time series for few Brazilian stations considering almost ten years of daily solutions. The noises components were characterized as white, flicker and random walk noise and applied to estimate the times series functional model considering semiannual and annual effects. The results show that the adoption of an adequate stochastic model considering the noises variances of time series can produce more realistic and reliable functional model for GNSS coordinate time series. Such results may be applied in the context of the realization of the Brazilian Geodetic System.
Finite difference time domain grid generation from AMC helicopter models
NASA Technical Reports Server (NTRS)
Cravey, Robin L.
1992-01-01
A simple technique is presented which forms a cubic grid model of a helicopter from an Aircraft Modeling Code (AMC) input file. The AMC input file defines the helicopter fuselage as a series of polygonal cross sections. The cubic grid model is used as an input to a Finite Difference Time Domain (FDTD) code to obtain predictions of antenna performance on a generic helicopter model. The predictions compare reasonably well with measured data.
NASA AVOSS Fast-Time Wake Prediction Models: User's Guide
NASA Technical Reports Server (NTRS)
Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew
2014-01-01
The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.
Continuous-time discrete-space models for animal movement
Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.
2015-01-01
The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.
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. PMID:26303151
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.
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.
Modeling and optimum time performance for concurrent processing
NASA Astrophysics Data System (ADS)
Mielke, Roland R.; Stoughton, John W.; Som, Sukhamoy
1988-08-01
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.
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.
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. PMID:22974377
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.
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
Eckert, Saskia; Eyer, Peter; Herkert, Nadja; Bumm, Rudolf; Weber, Georg; Thiermann, Horst; Worek, Franz
2008-02-01
The purpose of these experiments was to compare oxime-induced reactivation rate constants of acetylcholinesterase from different human tissue sources inhibited by organophosphorus compounds. To this end, preliminary testing was necessary to generate a stable system both for working with erythrocytes and musculature. We established a dynamically working in vitro model with a fixed enzyme source in a bioreactor that was perfused with acetylthiocholine, Ellman's reagent and any agent of interest (e.g. nerve agents, oximes) and analyzed in a common HPLC flow-through detector. The enzyme reactor was composed of a particle filter (Millex-GS, 0.22 microm) containing a thin layer of membrane-bound acetylcholinesterase and was kept at constant temperature in a water bath. At constant flow the height of absorbance was directly proportional to the enzyme activity. To start with, we applied this system to human red cell membranes and then adapted the system to acetylcholinesterase of muscle tissue. Homogenate (Ultra-Turrax and Potter-Elvehjem homogenizer) of human muscle tissue (intercostal musculature) was applied to the same particle filter and perfused in a slightly modified way, as done with human red cell membranes. We detected no decrease of acetylcholinesterase activity within 2.5h and we reproducibly determined reactivation rate constants for reactivation with obidoxime (10 microM) or HI 6 (30 microM) of sarin-inhibited human muscle acetylcholinesterase (0.142+/-0.004 min(-1) and 0.166+/-0.008 min(-1), respectively). The reactivation rate constants of erythrocyte and muscular acetylcholinesterase differed only slightly, highlighting erythrocyte acetylcholinesterase as a proper surrogate marker. PMID:17977518
Modeling heterogeneous processor scheduling for real time systems
NASA Technical Reports Server (NTRS)
Leathrum, J. F.; Mielke, R. R.; Stoughton, J. W.
1994-01-01
A new model is presented to describe dataflow algorithms implemented in a multiprocessing system. Called the resource/data flow graph (RDFG), the model explicitly represents cyclo-static processor schedules as circuits of processor arcs which reflect the order that processors execute graph nodes. The model also allows the guarantee of meeting hard real-time deadlines. When unfolded, the model identifies statically the processor schedule. The model therefore is useful for determining the throughput and latency of systems with heterogeneous processors. The applicability of the model is demonstrated using a space surveillance algorithm.
Influence of viscosity on myocardium mechanical activity: a mathematical model.
Katsnelson, Leonid B; Nikitina, Larissa V; Chemla, Denis; Solovyova, Olga; Coirault, Catherine; Lecarpentier, Yves; Markhasin, Vladimir S
2004-10-01
We have previously proposed and validated a mathematical model of myocardium contraction-relaxation cycle based on current knowledge of regulatory role of Ca2+ and cross-bridge kinetics in cardiac cell. That model did not include viscous elements. Here we propose a modification of the model, in which two viscous elements are added, one in parallel to the contractile element, and one more in parallel to the series elastic element. The modified model allowed us to simulate and explain some subtle experimental data on relaxation velocity in isotonic twitches and on a mismatch between the time course of sarcomere shortening/lengthening and the time course of active force generation in isometric twitches. Model results were compared with experimental data obtained from 28 rat LV papillary muscles contracting and relaxing against various loads. Additional model analysis suggested contribution of viscosity to main inotropic and lusitropic characteristics of myocardium performance. PMID:15302547
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.
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.
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.
ERIC Educational Resources Information Center
Sinclair, Christina D.; Stellino, Megan Babkes; Partidge, Julie A.
2008-01-01
Childhood obesity and inactivity levels among young Americans have risen steadily over the last few decades, and has become a major concern. Participation in regular physical activity helps prevent excess adiposity in children and youth. Recess is a regularly occurring period of time in school children's days which is an opportunity to help them…
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.
Rodriguez-Perez, S; Fermoso, F G; Arnaiz, C
2016-01-01
Medium-sized wastewater treatment plants are considered too small to implement anaerobic digestion technologies and too large for extensive treatments. A promising option as a sewage sludge reduction method is the inclusion of anoxic time exposures. In the present study, three different anoxic time exposures of 12, 6 and 4 hours have been studied to reduce sewage sludge production. The best anoxic time exposure was observed under anoxic/oxic cycles of 6 hours, which reduced 29.63% of the biomass production compared with the oxic control conditions. The sludge under different anoxic time exposures, even with a lower active biomass concentration than the oxic control conditions, showed a much higher metabolic activity than the oxic control conditions. Microbiological results suggested that both protozoa density and abundance of filamentous bacteria decrease under anoxic time exposures compared to oxic control conditions. The anoxic time exposures 6/6 showed the highest reduction in both protozoa density, 37.5%, and abundance of filamentous bacteria, 41.1%, in comparison to the oxic control conditions. The groups of crawling ciliates, carnivorous ciliates and filamentous bacteria were highly influenced by the anoxic time exposures. Protozoa density and abundance of filamentous bacteria have been shown as promising bioindicators of biomass production reduction. PMID:27508364
Time dependent turbulence modeling and analytical theories of turbulence
NASA Technical Reports Server (NTRS)
Rubinstein, R.
1993-01-01
By simplifying the direct interaction approximation (DIA) for turbulent shear flow, time dependent formulas are derived for the Reynolds stresses which can be included in two equation models. The Green's function is treated phenomenologically, however, following Smith and Yakhot, we insist on the short and long time limits required by DIA. For small strain rates, perturbative evaluation of the correlation function yields a time dependent theory which includes normal stress effects in simple shear flows. From this standpoint, the phenomenological Launder-Reece-Rodi model is obtained by replacing the Green's function by its long time limit. Eddy damping corrections to short time behavior initiate too quickly in this model; in contrast, the present theory exhibits strong suppression of eddy damping at short times. A time dependent theory for large strain rates is proposed in which large scales are governed by rapid distortion theory while small scales are governed by Kolmogorov inertial range dynamics. At short times and large strain rates, the theory closely matches rapid distortion theory, but at long times it relaxes to an eddy damping model.
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.
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
Distributed real-time model-based diagnosis
NASA Technical Reports Server (NTRS)
Barrett, A. C.; Chung, S. H.
2003-01-01
This paper presents an approach to onboard anomaly diagnosis that combines the simplicity and real-time guarantee of a rule-based diagnosis system with the specification ease and coverage guarantees of a model-based diagnosis system.
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. PMID:24791133
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.
Linear Time Invariant Models for Integrated Flight and Rotor Control
NASA Astrophysics Data System (ADS)
Olcer, Fahri Ersel
2011-12-01
Recent developments on individual blade control (IBC) and physics based reduced order models of various on-blade control (OBC) actuation concepts are opening up opportunities to explore innovative rotor control strategies for improved rotor aerodynamic performance, reduced vibration and BVI noise, and improved rotor stability, etc. Further, recent developments in computationally efficient algorithms for the extraction of Linear Time Invariant (LTI) models are providing a convenient framework for exploring integrated flight and rotor control, while accounting for the important couplings that exist between body and low frequency rotor response and high frequency rotor response. Formulation of linear time invariant (LTI) models of a nonlinear system about a periodic equilibrium using the harmonic domain representation of LTI model states has been studied in the literature. This thesis presents an alternative method and a computationally efficient scheme for implementation of the developed method for extraction of linear time invariant (LTI) models from a helicopter nonlinear model in forward flight. The fidelity of the extracted LTI models is evaluated using response comparisons between the extracted LTI models and the nonlinear model in both time and frequency domains. Moreover, the fidelity of stability properties is studied through the eigenvalue and eigenvector comparisons between LTI and LTP models by making use of the Floquet Transition Matrix. For time domain evaluations, individual blade control (IBC) and On-Blade Control (OBC) inputs that have been tried in the literature for vibration and noise control studies are used. For frequency domain evaluations, frequency sweep inputs are used to obtain frequency responses of fixed system hub loads to a single blade IBC input. The evaluation results demonstrate the fidelity of the extracted LTI models, and thus, establish the validity of the LTI model extraction process for use in integrated flight and rotor control
Modeling past, current, and future time in medical databases.
Kouramajian, V.; Fowler, J.
1994-01-01
Recent research has focused on increasing the power of medical information systems by incorporating time into the database system. A problem with much of this research is that it fails to differentiate between historical time and future time. The concept of bitemporal lifespan presented in this paper overcomes this deficiency. Bitemporal lifespan supports the concepts of valid time and transaction time and allows the integration of past, current, and future information in a unified model. The concept of bitemporal lifespan is presented within the framework of the Extended Entity-Relationship model. This model permits the characterization of temporal properties of entities, relationships, and attributes. Bitemporal constraints are defined that must hold between entities forming "isa" hierarchies and between entities and relationships. Finally, bitemporal extensions are presented for database query languages in order to provide natural high-level operators for bitemporal query expressions. PMID:7949941
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.
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...
Melandri, A.; Mundell, C. G.; Kobayashi, S.; Bersier, D.; Steele, I. A.; Smith, R. J.; Carter, D.; Bode, M. F.; Guidorzi, C.; Gomboc, A.
2009-05-25
Using a new, comprehensive multiwavelength survey of 63 Gamma Ray Bursts (GRBs) with unprecedented temporal coverage, we classify the observed afterglows into four main classes and discuss the underlying physics that can explain them. The presence or absence of temporal breaks in X-ray and optical bands is used to examine the emission in the context of the standard model; a number of GRBs are shown to deviate from the forward shock model even with the inclusion of energy injection or ambient density gradients. We show that additional emission in the early-time X-ray afterglow due to late-time central engine activity is key and may explain both GRBs whose afterglows do not fit the standard model and those GRBs that appear to be optically dark even at early times.
Spots and Flares: Stellar Activity in the Time Domain Era
NASA Astrophysics Data System (ADS)
Davenport, James R. A.
Time domain photometric surveys for large numbers of stars have ushered in a new era of statistical studies of astrophysics. This new parameter space allows us to observe how stars behave and change on a human timescale, and facilitates ensemble studies to understand how stars change over cosmic timescales. With current and planned time domain stellar surveys, we will be able to put the Sun in a Galactic context, and discover how typical or unique our parent star truly is. The goal of this thesis is to develop techniques for detecting and analyzing the most prominent forms of magnetic activity from low-mass stars in modern time domain surveys: starspots and flares. Magnetic field strength is a fundamental property that decays over a star's life. As a result, flux modulations from both flares and starspots become smaller amplitude and more infrequent in light curves. Methods for detecting these forms of magnetic activity will be extensible to future time domain surveys, and helpful in characterizing the properties of stars as they age. Flares can be detected in sparsely sampled wide field surveys by searching for bright single-point outliers in light curves. Using both red optical and near infrared data from ground-based surveys over many years, I have constrained the rate of flares in multiple wavelengths for an ensemble of M dwarfs. Studying flares in these existing ground-based datasets will enable predictions for future survey yields. Space-based photometry enables continuous and precise monitoring of stars for many years, which is crucial for obtaining a complete census of flares from a single star. Using 11 months of 1-minute photometry for the M dwarf GJ 1243, I have amassed over 6100 flare events, the largest sample of white light flares for any low-mass star. I have also created the first high fidelity empirical white light flare template, which shows three distinct phases in typical flare light curves. With this template, I demonstrate that complex multi
Spots and Flares: Stellar Activity in the Time Domain Era
NASA Astrophysics Data System (ADS)
Davenport, James
2015-08-01
Time domain photometric surveys for large numbers of stars have ushered in a new era of statistical studies of astrophysics. This new parameter space allows us to observe how stars behave and change on a human timescale, and facilitates ensemble studies to understand how stars change over cosmic timescales. With current and planned time domain stellar surveys, we will be able to put the Sun in a Galactic context, and discover how typical or unique our parent star truly is. The goal of this thesis is to develop techniques for detecting and analyzing the most prominent forms of magnetic activity from low-mass stars in modern time domain surveys: starspots and flares. Magnetic field strength is a fundamental property that decays over a star's life. As a result, flux modulations from both flares and starspots become smaller amplitude and more infrequent in light curves. Methods for detecting these forms of magnetic activity will be extensible to future time domain surveys, and helpful in characterizing the properties of stars as they age. Flares can be detected in sparsely sampled wide field surveys by searching for bright single-point outliers in light curves. Using both red optical and near infrared data from ground-based surveys over many years, I have constrained the rate of flares in multiple wavelengths for an ensemble of M dwarfs. Studying flares in these existing ground-based datasets will enable predictions for future survey yields. Space-based photometry enables continuous and precise monitoring of stars for many years, which is crucial for obtaining a complete census of flares from a single star. Using 11 months of 1-minute photometry for the M dwarf GJ 1243, I have amassed over 6100 flare events, the largest sample of white light flares for any low-mass star. I have also created the first high fidelity empirical white light flare template, which shows three distinct phases in typical flare light curves. With this template, I demonstrate that complex multi
Ontogenic timing mechanism initiates the expression of rat intestinal sucrase activity
Yeh, K.Y.; Holt, P.R.
1986-03-01
Morphologic and enzymic differentiation occurs in rat small intestinal epithelium during 16-20 days of postnatal life. This change is considered to be initiated by an ontogenic timing mechanism and is modulated by extrinsic systemic and luminal factors. The importance of the ontogenic timing was tested directly using a transplantation technique in which jejunal isografts from newborn (day 0) and 5-day-old (day 5) rats were implanted under the skin of newborn (day 0) hosts. Isografts showing cryptvillus architecture were obtained in 44% and 21% of transplants, respectively. Day 0 isografts and host intestine expressed sucrase activity at about 16-18 days of age and showed similar crypt cell labeling and epithelial migration after (3H)thymidine injection. Day 5 isografts expressed sucrase activity when the hosts were 13 days of age, whereas host intestine showed no detectable sucrase activity. Isograft lactase activities in both experimental transplant models were significantly higher than host intestinal lactase up to 28 days of age, suggesting that luminal factors are important in modulating lactase activity during the first 4 wk of postnatal life. It is concluded that (a) no systemic factors at day 13 inhibit the expression of sucrase activity and (b) an ontogenic timing mechanism in the jejunum initiates the expression of sucrase activity.
Time Outdoors, Visual Activity, and Myopia Progression in Juvenile-Onset Myopes
Jones-Jordan, Lisa A.; Sinnott, Loraine T.; Cotter, Susan A.; Kleinstein, Robert N.; Manny, Ruth E.; Mutti, Donald O.; Twelker, J. Daniel; Zadnik,, Karla
2012-01-01
Purpose. To investigate the association between myopia progression and time spent outdoors and in various visual activities. Methods. Subjects were 835 myopes (both principal meridians −0.75 diopters [D] or more myopia by cycloplegic autorefraction) in the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) Study with both progression data and at least one measure of activity associated with a progression interval. Activity data were collected by parental survey. Average activity level (mean of the activity at the beginning and the end of a 1-year progression interval) was the primary predictor in a repeated-measures mixed model. The model controlled for age, sex, ethnicity, refractive error at the beginning of the progression interval, clinic site, and type of autorefractor used. Effects were scaled based on performing an additional 10 hours per week of an activity. Results. In the multivariate model, the number of hours of reading for pleasure per week was not significantly associated with annual myopia progression at an a priori level of P ≤ 0.01, nor were the other near activities, the near-work composite variable diopter-hours, or outdoor/sports activity. The magnitude of effects was clinically small. For example, the largest multivariate effect was that each additional 10 hours of reading for pleasure per week at the end of a progression interval was associated with an increase in average annual progression by −0.08 D. Conclusions. Despite protective associations previously reported for time outdoors reducing the risk of myopia onset, outdoor/sports activity was not associated with less myopia progression following onset. Near work also had little meaningful effect on the rate of myopia progression. PMID:22977132
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...
The Seasons Explained by Refutational Modeling Activities
ERIC Educational Resources Information Center
Frede, Valerie
2008-01-01
This article describes the principles and investigation of a small-group laboratory activity based on refutational modeling to teach the concept of seasons to preservice elementary teachers. The results show that these teachers improved significantly when they had to refute their initial misconceptions practically. (Contains 8 figures and 1 table.)
Using Hybrid Modeling to Develop Innovative Activities
ERIC Educational Resources Information Center
Lichtman, Brenda; Avans, Diana
2005-01-01
This article describes a hybrid activities model that physical educators can use with students in grades four and above to create virtually a limitless array of novel games. A brief introduction to the basic theory is followed by descriptions of some hybrid games. Hybrid games are typically the result of merging two traditional sports or other…
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-varying priority queuing models for human dynamics.
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. PMID:23005156
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.
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…
A model of interval timing by neural integration
Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip
2011-01-01
We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374
MSW Time to Tumor Model and Supporting Documentation
The multistage Weibull (MSW) time-to-tumor model and related documentation were developed principally (but not exclusively) for conducting time-to-tumor analyses to support risk assessments under the IRIS program. These programs and related docum...
Stability of a general SEIV epidemic model with time delay
NASA Astrophysics Data System (ADS)
Hikal, M. M.; El-Sheikh, M. M. A.
2013-10-01
An SEIV epidemic model with a general nonlinear incidence rate, vaccination and time delay in treatment is considered. Sufficient conditions for the time delay to keep the stability of the endemic equilibria are given. A numerical simulations is given to illustrate our results.
Thermally activated breakdown in a simple polymer model.
Fugmann, S; Sokolov, I M
2010-03-01
We consider the thermally activated fragmentation of a homopolymer chain. In our simple model the dynamics of the intact chain is a Rouse one until a bond breaks and bond breakdown is considered as a first passage problem over a barrier to an absorbing boundary. Using the framework of the Wilemski-Fixman approximation we calculate activation times of individual bonds for free and grafted chains. We show that these times crucially depend on the length of the chain and the location of the bond yielding a minimum at the free chain ends. Theoretical findings are qualitatively confirmed by Brownian dynamics simulations. PMID:20365762
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.
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.
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…
Snyder-de Sitter model from two-time physics
Carrisi, M. C.; Mignemi, S.
2010-11-15
We show that the symplectic structure of the Snyder model on a de Sitter background can be derived from two-time physics in seven dimensions and propose a Hamiltonian for a free particle consistent with the symmetries of the model.
Separability of Item and Person Parameters in Response Time Models.
ERIC Educational Resources Information Center
Van Breukelen, Gerard J. P.
1997-01-01
Discusses two forms of separability of item and person parameters in the context of response time models. The first is "separate sufficiency," and the second is "ranking independence." For each form a theorem stating sufficient conditions is proved. The two forms are shown to include several cases of models from psychometric and biometric…
Identification of human operator performance models utilizing time series analysis
NASA Technical Reports Server (NTRS)
Holden, F. M.; Shinners, S. M.
1973-01-01
The results of an effort performed by Sperry Systems Management Division for AMRL in applying time series analysis as a tool for modeling the human operator are presented. This technique is utilized for determining the variation of the human transfer function under various levels of stress. The human operator's model is determined based on actual input and output data from a tracking experiment.
Kālī: Time series data modeler
NASA Astrophysics Data System (ADS)
Kasliwal, Vishal P.
2016-07-01
The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālimacr; is written in c++ with Python language bindings for ease of use. K¯lī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.
Studies in astronomical time series analysis: Modeling random processes in the time domain
NASA Technical Reports Server (NTRS)
Scargle, J. D.
1979-01-01
Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.
U.S.-MEXICO BORDER PROGRAM ARIZONA BORDER STUDY--TIME AND ACTIVITY DIARY QUESTIONNAIRE DATA
The Time and Activity Diary Questionnaire data set provides information about the daily activities of the respondents during the sampling week. The information is from 260 Time and Activity Diary Questionnaires for 91 households. Supplemental pages were provided. The informati...
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. PMID:24323040
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.
Double time lag combustion instability model for bipropellant rocket engines
NASA Technical Reports Server (NTRS)
Liu, C. K.
1973-01-01
A bipropellant stability model is presented in which feed system inertance and capacitance are treated along with injection pressure drop and distinctly different propellant time lags. The model is essentially an extension of Crocco's and Cheng's monopropellant model to the bipropellant case assuming that the feed system inertance and capacitance along with the resistance are located at the injector. The neutral stability boundaries are computed in terms of these parameters to demonstrate the interaction among them.
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
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.
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.
Spatio-temporal modeling for real-time ozone forecasting
Paci, Lucia; Gelfand, Alan E.; Holland, David M.
2013-01-01
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. PMID:24010052
Modeling Real-Time Applications with Reusable Design Patterns
NASA Astrophysics Data System (ADS)
Rekhis, Saoussen; Bouassida, Nadia; Bouaziz, Rafik
Real-Time (RT) applications, which manipulate important volumes of data, need to be managed with RT databases that deal with time-constrained data and time-constrained transactions. In spite of their numerous advantages, RT databases development remains a complex task, since developers must study many design issues related to the RT domain. In this paper, we tackle this problem by proposing RT design patterns that allow the modeling of structural and behavioral aspects of RT databases. We show how RT design patterns can provide design assistance through architecture reuse of reoccurring design problems. In addition, we present an UML profile that represents patterns and facilitates further their reuse. This profile proposes, on one hand, UML extensions allowing to model the variability of patterns in the RT context and, on another hand, extensions inspired from the MARTE (Modeling and Analysis of Real-Time Embedded systems) profile.
Two relaxation time lattice Boltzmann model for rarefied gas flows
NASA Astrophysics Data System (ADS)
Esfahani, Javad Abolfazli; Norouzi, Ali
2014-01-01
In this paper, the lattice Boltzmann equation (LBE) with two relaxation times (TRT) is implemented in order to study gaseous flow through a long micro/nano-channel. A new relation is introduced for the reflection factor in the bounce-back/specular reflection (BSR) boundary condition based on the analytical solution of the Navier-Stokes equations. The focus of the present study is on comparing TRT with the other LBE models called multiple relaxation times (MRT) and single relaxation time (SRT) in simulation of rarefied gas flows. After a stability analysis for the TRT and SRT models, the numerical results are presented and validated by the analytical solution of the Navier-Stokes equations with slip boundary condition, direct simulation of Monte Carlo (DSMC) and information preservation (IP) method. The effect of various gases on flow behavior is also investigated by using the variable hard sphere (VHS) model through the symmetrical relaxation time.
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.
Chromospheric extents predicted by time-dependent acoustic wave models
NASA Technical Reports Server (NTRS)
Cuntz, Manfred
1990-01-01
Theoretical models for chromospheric structures of late-type giant stars are computed, including the time-dependent propagation of acoustic waves. Models with short-period monochromatic shock waves as well as a spectrum of acoustic waves are discussed, and the method is applied to the stars Arcturus, Aldebaran, and Betelgeuse. Chromospheric extent, defined as the monotonic decrease with height of the time-averaged electron densities, are found to be 1.12, 1.13, and 1.22 stellar radii for the three stars, respectively; this corresponds to a time-averaged electron density of 10 to the 7th/cu cm. Predictions of the extended chromospheric obtained using a simple scaling law agree well with those obtained by the time-dependent wave models; thus, the chromospheres of all stars for which the scaling law is valid consist of the same number of pressure scale heights.
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.
Logic Model Checking of Time-Periodic Real-Time Systems
NASA Technical Reports Server (NTRS)
Florian, Mihai; Gamble, Ed; Holzmann, Gerard
2012-01-01
In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.
Multi-scale gravity field modeling in space and time
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2016-04-01
The Earth constantly deforms as it undergoes dynamic phenomena, such as earthquakes, post-glacial rebound and water displacement in its fluid envelopes. These processes have different spatial and temporal scales and are accompanied by mass displacements, which create temporal variations of the gravity field. Since 2002, the GRACE satellite missions provide an unprecedented view of the gravity field spatial and temporal variations. Gravity models built from these satellite data are essential to study the Earth's dynamic processes (Tapley et al., 2004). Up to present, time variations of the gravity field are often modelled using spatial spherical harmonics functions averaged over a fixed period, as 10 days or 1 month. This approach is well suited for modeling global phenomena. To better estimate gravity related to local and/or transient processes, such as earthquakes or floods, and adapt the temporal resolution of the model to its spatial resolution, we propose to model the gravity field using localized functions in space and time. For that, we build a model of the gravity field in space and time with a four-dimensional wavelet basis, well localized in space and time. First we design the 4D basis, then, we study the inverse problem to model the gravity field from the potential differences between the twin GRACE satellites, and its regularization using prior knowledge on the water cycle. Our demonstration of surface water mass signals decomposition in time and space is based on the use of synthetic along-track gravitational potential data. We test the developed approach on one year of 4D gravity modeling and compare the reconstructed water heights to those of the input hydrological model. Perspectives of this work is to apply the approach on real GRACE data, addressing the challenge of a realistic noise, to better describe and understand physical processus with high temporal resolution/low spatial resolution or the contrary.
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
A continuous-time neural model for sequential action.
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard
2014-11-01
Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. 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.
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
GOCE gravity field models following the time-wise approach
NASA Astrophysics Data System (ADS)
Brockmann, Jan Martin; Höck, Eduard; Loth, Ina; Mayer-Gürr, Torsten; Pail, Roland; Schuh, Wolf-Dieter; Zehentner, Norbert
2015-04-01
Since the launch of the European Space Agency's (ESA) Gravity field and Ocean Circulation Explorer (GOCE) satellite in 2009 and its end in 2013, a sequence of official GOCE gravity field models was released. One of the series of models follows the so called time-wise approach (EGM_TIM). They are purely based on GOCE observations such that they are independent of any other gravity field information available and describe the Earth's gravity field as seen by GOCE. Recently, the fifth release, EGM_TIM_RL05, was computed and made available to users. The models of the time-wise series were computed within the ESA funded High-level Processing Facility (HPF) and are part of the official ESA GOCE products. Calibrated gravity gradients in the gradiometer reference frame and the satellites position as derived by GPS measurements entered the solutions as observations. Together with the spherical harmonic coefficients, a realistic the full covariance matrix is provided reflecting the model quality. This contribution summarizes the gravity field models derived with the time-wise approach. The method is summarized and the progress along the five releases is highlighted. Special focus is put on the final release 5, the gravity field model which includes all data collected during the entire GOCE mission. This model, parametrized as 78,957 spherical harmonic coefficients (spatial resolution of 71 km), was determined from 4*109,799,264 gravity gradient measurements and 108,754,709 three dimensional positions within a joint least squares adjustment procedure. As this gravity field models only depend on GOCE observations, the gain of GOCE compared to other missions and other gravity field products can be clearly demonstrated. With release 5 of the time-wise model, a pure GOCE based model with a mean global accuracy of 2.4 cm at a spatial resolution of 100 km for the geoid is available (0.7 mGal for gravity anomalies).
A model for discriminating reinforcers in time and space.
Cowie, Sarah; Davison, Michael; Elliffe, Douglas
2016-06-01
Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a
Time series ARIMA models for daily price of palm oil
NASA Astrophysics Data System (ADS)
Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu
2015-02-01
Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.
A 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. PMID:24828770
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
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
Bifurcation and chaotic in a model for activated sludge reactors
NASA Astrophysics Data System (ADS)
El-Marouf, S. A. A.; Bahaa, G. M.
2015-04-01
A dynamical model of an activated sludge process system is considered and analyzed. Numerical techniques are used to show when the system exhibits chaos. Three choices of bifurcation parameters produce different pictures of solution behavior in the form of limit cycles, two-torus and chaotic behavior. For some range of the reactor residence time the model exhibits chaotic behavior as well. Practical criteria are also derived for the effects of feed conditions and purge fraction on the dynamic characteristics of the bioreactor model.
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…
Staiano, Amanda E; Broyles, Stephanie T; Katzmarzyk, Peter T
2015-08-01
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. PMID:26264005
Motl, Robert W; McAuley, Edward; Birnbaum, Amanda S; Lytle, Leslie A
2006-02-01
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 an increase in frequency of leisure-time physical activity. That relationship was strong in magnitude and independent of sex, socioeconomic status, smoking, and the value participants placed on health, appearance, and achievement. Our results encourage the design of interventions that reduce television watching as a possible means of increasing adolescent physical activity. PMID:16338428
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.
van der Vinne, V; Akkerman, J; Lanting, G D; Riede, S J; Hut, R A
2015-09-24
Circadian clocks drive daily rhythms in physiology and behavior which allow organisms to anticipate predictable daily changes in the environment. In most mammals, circadian rhythms result in nocturnal activity patterns although plasticity of the circadian system allows activity patterns to shift to different times of day. Such plasticity is seen when food access is restricted to a few hours during the resting (light) phase resulting in food anticipatory activity (FAA) in the hours preceding food availability. The mechanisms underlying FAA are unknown but data suggest the involvement of the reward system and homeostatic regulation of metabolism. We previously demonstrated the isolated effect of metabolism by inducing diurnality in response to energetic challenges. Here the importance of reward timing in inducing daytime activity is assessed. The daily activity distribution of mice earning palatable chocolate at their preferred time by working in a running wheel was compared with that of mice receiving a timed palatable meal at noon. Mice working for chocolate (WFC) without being energetically challenged increased their total daily activity but this did not result in a shift to diurnality. Providing a chocolate meal at noon each day increased daytime activity, identifying food timing as a factor capable of altering the daily distribution of activity and rest. These results show that timing of food reward and energetic challenges are both independently sufficient to induce diurnality in nocturnal mammals. FAA observed following timed food restriction is likely the result of an additive effect of distinct regulatory pathways activated by energetic challenges and food reward. PMID:26215921
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
The activity-based anorexia mouse model.
Klenotich, Stephanie J; Dulawa, Stephanie C
2012-01-01
Animals housed with running wheels and subjected to daily food restriction show paradoxical reductions in food intake and increases in running wheel activity. This phenomenon, known as activity-based anorexia (ABA), leads to marked reductions in body weight that can ultimately lead to death. Recently, ABA has been proposed as a model of anorexia nervosa (AN). AN affects about 8 per 100,000 females and has the highest mortality rate among all psychiatric illnesses. Given the reductions in quality of life, high mortality rate, and the lack of pharmacological treatments for AN, a better understanding of the mechanisms underlying AN-like behavior is greatly needed. This chapter provides basic guidelines for conducting ABA experiments using mice. The ABA mouse model provides an important tool for investigating the neurobiological underpinnings of AN-like behavior and identifying novel treatments. PMID:22231828
Audibility of time-varying signals in time-varying backgrounds: Model and data
NASA Astrophysics Data System (ADS)
Moore, Brian C. J.; Glasberg, Brian R.
2001-05-01
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.
Time dependent patient no-show predictive modelling development.
Huang, Yu-Li; Hanauer, David A
2016-05-01
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. PMID:27142954
NHEXAS PHASE I REGION 5 STUDY--TIME-ACTIVITY DIARY QUESTIONNAIRE DATA (MONITORING PERIOD 1)
This data set includes responses for 249 time-activity diary questionnaires. The Time Diary and Activity Questionnaire was used for collecting data on detailed (daily) time and location information and activity patterns (for relatively frequent activities when recalling events ov...
Hamilton, Kyra; Thomson, Courtney E; White, Katherine M
2013-07-01
Given increasing trends of obesity being noted from early in life and that active lifestyles track across time, it is important that children at a very young age be active to combat a foundation of unhealthy behaviours forming. This study investigated, within a theory of planned behaviour (TPB) framework, factors which influence mothers' decisions about their child's (1) adequate physical activity (PA) and (2) limited screen time behaviours. Mothers (N = 162) completed a main questionnaire, via on-line or paper-based administration, which comprised standard TPB items in addition to measures of planning and background demographic variables. One week later, consenting mothers completed a follow-up telephone questionnaire which assessed the decisions they had made regarding their child's PA and screen time behaviours during the previous week. Hierarchical multiple regression analyses revealed support for the predictive model, explaining an overall 73 and 78 % of the variance in mothers' intention and 38 and 53 % of the variance in mothers' decisions to ensure their child engages in adequate PA and limited screen time, respectively. Attitude and subjective norms predicted intention in both target behaviours, as did intentions with behaviour. Contrary to predictions, perceived behavioural control (PBC) in PA behaviour and planning in screen time behaviour were not significant predictors of intention, neither was PBC a predictor of either behaviour. The findings illustrate the various roles that psycho-social factors play in mothers' decisions to ensure their child engages in active lifestyle behaviours which can help to inform future intervention programs aimed at combating very young children's inactivity. PMID:22833334
Active walker models: tracks and landscapes
NASA Astrophysics Data System (ADS)
Kayser, D. R.; Aberle, L. K.; Pochy, R. D.; Lam, L.
1992-12-01
The track patterns from the active walker models (AWMs) are compared with experimental retinal neuron and dielectric breakdown of liquid patterns, respectively. Excellent qualitative and quantitative agreements are obtained. The landscapes from the Boltzmann AWM in 1 + 1 dimensions form rough surfaces, with a first-order phase transition as the height of the landscaping function W0 is varied. Landscapes and statistics of the tracks from the probabilistic AWM in 2 + 1 dimensions are presented.
Time series segmentation with shifting means hidden markov models
NASA Astrophysics Data System (ADS)
Kehagias, Ath.; Fortin, V.
2006-08-01
We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means models introduced by Chernoff and Zacks and by Salas and Boes. An estimation method inspired from the EM algorithm is proposed, and we show that it can accurately identify multiple change-points in a time series. We also show that the solution obtained using this algorithm can serve as a starting point for a Monte-Carlo Markov chain Bayesian estimation method, thus reducing the computing time needed for the Markov chain to converge to a stationary distribution.
Reaction times to weak test lights. [psychophysics biological model
NASA Technical Reports Server (NTRS)
Wandell, B. A.; Ahumada, P.; Welsh, D.
1984-01-01
Maloney and Wandell (1984) describe a model of the response of a single visual channel to weak test lights. The initial channel response is a linearly filtered version of the stimulus. The filter output is randomly sampled over time. Each time a sample occurs there is some probability increasing with the magnitude of the sampled response - that a discrete detection event is generated. Maloney and Wandell derive the statistics of the detection events. In this paper a test is conducted of the hypothesis that the reaction time responses to the presence of a weak test light are initiated at the first detection event. This makes it possible to extend the application of the model to lights that are slightly above threshold, but still within the linear operating range of the visual system. A parameter-free prediction of the model proposed by Maloney and Wandell for lights detected by this statistic is tested. The data are in agreement with the prediction.
Positive outcomes increase over time with the implementation of a semiflipped teaching model.
Gorres-Martens, Brittany K; Segovia, Angela R; Pfefer, Mark T
2016-03-01
The flipped teaching model can engage students in the learning process and improve learning outcomes. The purpose of the present study was to assess the outcomes of a semiflipped teaching model over time. Neurophysiology students spent the majority of class time listening to traditional didactic lectures, but they also listened to 5 online lectures and spent 8-10 class periods completing an active learning assignment. At the end of the term, students completed a survey to assess the outcomes of the active learning assignments. The positive outcomes were greater the second time the course was taught in a semiflipped manner. While completely flipping a course takes a tremendous amount of time, instructors can still obtain positive outcomes by implementing a semiflipped teaching model. PMID:26847255
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.
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.
Time domain analysis of the weighted distributed order rheological model
NASA Astrophysics Data System (ADS)
Cao, Lili; Pu, Hai; Li, Yan; Li, Ming
2016-05-01
This paper presents the fundamental solution and relevant properties of the weighted distributed order rheological model in the time domain. Based on the construction of distributed order damper and the idea of distributed order element networks, this paper studies the weighted distributed order operator of the rheological model, a generalization of distributed order linear rheological model. The inverse Laplace transform on weighted distributed order operators of rheological model has been obtained by cutting the complex plane and computing the complex path integral along the Hankel path, which leads to the asymptotic property and boundary discussions. The relaxation response to weighted distributed order rheological model is analyzed, and it is closely related to many physical phenomena. A number of novel characteristics of weighted distributed order rheological model, such as power-law decay and intermediate phenomenon, have been discovered as well. And meanwhile several illustrated examples play important role in validating these results.
Three real-time architectures - A study using reward models
NASA Technical Reports Server (NTRS)
Sjogren, J. A.; Smith, R. M.
1990-01-01
Numerous applications in the area of computer system analysis can be effectively studied with Markov reward models. These models describe the evolutionary behavior of the computer system by a continuous-time Markov chain, and a reward rate is associated with each state. In reliability/availability models, upstates have reward rate 1, and down states have reward rate zero associated with them. In a combined model of performance and reliability, the reward rate of a state may be the computational capacity, or a related performance measure. Steady-state expected reward rate and expected instantaneous reward rate are clearly useful measures which can be extracted from the Markov reward model. The diversity of areas where Markov reward models may be used is illustrated with a comparative study of three examples of interest to the fault tolerant computing community.
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.
Clark, L A; Denby, L; Pregibon, D; Harshfield, G A; Pickering, T G; Blank, S; Laragh, J H
1987-01-01
The effects of activity and time of day on blood pressure (BP) were analyzed in 461 patients with untreated hypertension who wore a noninvasive portable BP recorder which took readings every 15 minutes for 24 hours. Patients recorded activity and location in a diary. The data were analyzed separately for two groups of patients: the 190 who stayed at home and the 271 who went to work. The effects of 16 different activities on BP were estimated by relating the BP to the associated activity and to the individual's clinic BP. Blood pressure was higher at work than at home, but the increment of BP for individual activities was similar in the two locations. The overall effect of activities on BP variability was computed using a one-way analysis of covariance model. For the patients who went to work this model accounted for 40% of the observed variation (R2) for systolic and 39% for diastolic BP. A similar model using time of day instead of activity accounted for 33% of variability in both systolic and diastolic BP. Combining activity and time of day was little better than activity alone (41% for both). After allowing for the effects of activity on BP, where sleep is one of the activities, there was no significant diurnal variation of BP. We conclude that there is no important circadian rhythm of BP which is independent of activity. PMID:3597670
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.
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.
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.
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
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.
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.
Empirical modeling of the quiet time nightside magnetosphere
NASA Technical Reports Server (NTRS)
Lui, A. T. Y.; Spence, H. E.; Stern, D. P.
1993-01-01
Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko (1989) but is modified by the addition of an inner eastward ring current at a radial distance of approximately 3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko (1987) such that the former dominates the magnetic field in the inner magnetosphere while the latter prevails in the distant tail. The distribution of plasma pressure which is required to balance the magnetic force for each of these two field models is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This represents the first effort to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of approximately 3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between approximately 2 and approximately 35 RE.
A real-time groundwater management model using data assimilation
NASA Astrophysics Data System (ADS)
Cheng, Wei-Chen; Putti, Mario; Kendall, Donald R.; Yeh, William W.-G.
2011-06-01
This study develops a groundwater management model for real-time operation of an aquifer system. A groundwater flow model is allied with a nudging data assimilation algorithm that reduces the forecast error, minimizes the risk of system failure, and improves management strategies. The nudging algorithm treats the unknown private pumping as an additional sink term in the groundwater flow equation and provides a consistently physical interpretation for the identification of pumping rates. The system response due to pumping and injection is represented by a response matrix that is generated by the influence coefficient method. The response matrix (with a much smaller dimension) is used as a reduced model and is embedded directly in the management model as a part of the constraint set. Additionally, the influence coefficient method is utilized to include the nudging effect in the reduced model. The management model optimizes the monthly operation for 12 months into the future and determines the optimal strategy using the information provided by nudging. The management model is updated at the beginning of each month when new head observations and pumping data become available. We also discuss the utility, accuracy, and efficiency of the proposed management model for real-time operation.
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.
Empirical modeling of the quiet time nightside magnetosphere
Lui, A.T.Y. ); Spence, H.E. ); Stern, D.P. )
1994-01-01
Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko but is modified by the addition of an inner eastward ring current at a radial distance of [approximately]3 R[sub E] as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko such that the former dominates the magnetic field in the inner magnetosphere, whereas the latter prevails in the distant tail. The distribution of plasma pressure, which is required to balance the magnetic force for each of these two field models, is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This effort is the first attempt to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of [approximately]3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between [approximately]2 and [approximately]35 R[sub E]. 40 refs., 5 figs.
Empirical modeling of the quiet time nightside magnetosphere
Lui, A.T.Y.; Spence, H.E.; Stern, D.P.
1993-12-31
Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko but is modified by the addition of an inner eastward ring current at a radial distance of approximately 3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko such that the former dominates the magnetic field in the inner magnetosphere while the latter prevails in the distant tail. The distribution of plasma pressure which is required to balance the magnetic force for each of these two field models is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This represents the first effort to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of approximately 3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between approximately 2 and approximately 35 RE.
Modeling Pubertal Timing and Tempo and Examining Links to Behavior Problems
Beltz, Adriene M.; Corley, Robin P.; Bricker, Josh B.; Wadsworth, Sally J.; Berenbaum, Sheri A.
2014-01-01
Research on the role of puberty in adolescent psychological development requires attention to the meaning and measurement of pubertal development. Particular questions concern the utility of self report, the need for complex models to describe pubertal development, the psychological significance of pubertal timing versus tempo, and sex differences in the nature and psychological significance of pubertal development. We used longitudinal self-report data to model linear and logistic trajectories of pubertal development, and used timing and tempo estimates from these models, and from traditional approaches (age at menarche and time from onset of breast development to menarche), to predict psychological outcomes of internalizing and externalizing behavior problems, and early sexual activity. Participants (738 girls, 781 boys) reported annually from ages 9 through 15 on their pubertal development, and they and their parents reported on their behavior in mid-to-late adolescence and early adulthood. Self reports of pubertal development provided meaningful data for both boys and girls, producing good trajectories, and estimates of individuals’ pubertal timing and tempo. A logistic model best fit the group data. Pubertal timing was estimated to be earlier in the logistic compared to linear model, but linear, logistic, and traditional estimates of pubertal timing correlated highly with each other and similarly with psychological outcomes. Pubertal tempo was not consistently estimated, and associations of tempo with timing and with behavior were model dependent. Advances in modeling facilitate the study of some questions about pubertal development, but assumptions of the models affect their utility in psychological studies. PMID:25437757
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
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.
a Spatio-Temporal Framework for Modeling Active Layer Thickness
NASA Astrophysics Data System (ADS)
Touyz, J.; Streletskiy, D. A.; Nelson, F. E.; Apanasovich, T. V.
2015-07-01
The Arctic is 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 climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness (ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model's stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naïve model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naïve model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.
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.
Models of Emergency Departments for Reducing Patient Waiting Times
Laskowski, Marek; McLeod, Robert D.; Friesen, Marcia R.; Podaima, Blake W.; Alfa, Attahiru S.
2009-01-01
In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial–topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed. PMID:19572015
TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information
Kim, Yongsoo; Jang, Jin-Hyeok; Choi, Seungjin; Hwang, Daehee
2014-01-01
Motivation: Time-evolving differential protein–protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time. Results: Here, we present a probabilistic model for estimating Time-Evolving differential PPI networks with MultiPle Information (TEMPI). This model describes probabilistic relationships among network structures, time-course gene expression data and Gene Ontology biological processes (GOBPs). By maximizing the likelihood of the probabilistic model, TEMPI estimates jointly the time-evolving differential PPI networks (TDNs) describing temporal transition of PPI network structures together with serial activation of DRPs associated with transiting networks. This joint estimation enables us to interpret the TDNs in terms of temporal transition of the DRPs. To demonstrate the utility of TEMPI, we applied it to two time-course datasets. TEMPI identified the TDNs that correctly delineated temporal transition of DRPs and time-dependent associations between the DRPs. These TDNs provide hypotheses for mechanisms underlying serial activation of key DRPs and their temporal associations. Availability and implementation: Source code and sample data files are available at http://sbm.postech.ac.kr/tempi/sources.zip. Contact: seungjin@postech.ac.kr or dhwang@dgist.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161233
Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.
2014-01-01
Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256
Trends, time-varying and nonlinear time series models for NGRIP and VOSTOK paleoclimate data
NASA Astrophysics Data System (ADS)
Matyasovszky, István
2010-08-01
In order to gain further insights into stochastic behaviour of paleoclimate data, including timescales at and below Milankovitch forcing, three specific questions are discussed using δ 18O NGRIP and Vostok Deuterium content data. A comparison of ordinary and time-varying coefficients autoregressive (AR) models shows that both data sets are distinguishable from data generated by suitable low-order AR processes in contrast to earlier conclusions. A harmonic regression analysis clearly distinguishing between discrete and continuous spectra detects cycles corresponding to variations of eccentricity, obliquity and precession. Contribution of eccentricity to the total variance in the last 422,766-year Vostok data is close to, while the variance reduction delivered jointly by obliquity and precession is substantially smaller than a previous recent finding. A harmonic regression analysis with time-varying frequencies and amplitudes is also performed. This approach delivers a gain over the constant frequency model at any reasonable significance level. It is demonstrated that variations of frequencies are at least partly due to real variations and not merely to timescale uncertainties. In order to consider nonlinearity in paleoclimate data, threshold autoregressive (TAR) models are applied to time series examined. A bivariate TAR model describing simultaneous NGRIP and Vostok data exhibits three fix points and one limit cycle related to a part of Dansgaard-Oeschger events. The model selected suggests that Greenland has a primary role in the Greenland-Antarctica climate variation relationship.
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.
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.
Dynamic regimes of local homogeneous population model with time lag
NASA Astrophysics Data System (ADS)
Neverova, Galina; Frisman, Efim
2016-06-01
We investigated Moran - Ricker model with time lag 1. It is made analytical and numerical study of the model. It is shown there is co-existence of various dynamic regimes under the same values of parameters. The model simultaneously possesses several different limit regimes: stable state, periodic fluctuations, and chaotic attractor. The research results show if present population size substantially depends on population number of previous year then it is observed quasi-periodic oscillations. Fluctuations with period 2 occur when the growth of population size is regulated by density dependence in the current year.
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.
Analytical model of coincidence resolving time in TOF-PET.
Wieczorek, H; Thon, A; Dey, T; Khanin, V; Rodnyi, P
2016-06-21
The coincidence resolving time (CRT) of scintillation detectors is the parameter determining noise reduction in time-of-flight PET. We derive an analytical CRT model based on the statistical distribution of photons for two different prototype scintillators. For the first one, characterized by single exponential decay, CRT is proportional to the decay time and inversely proportional to the number of photons, with a square root dependence on the trigger level. For the second scintillator prototype, characterized by exponential rise and decay, CRT is proportional to the square root of the product of rise time and decay time divided by the doubled number of photons, and it is nearly independent of the trigger level. This theory is verified by measurements of scintillation time constants, light yield and CRT on scintillator sticks. Trapping effects are taken into account by defining an effective decay time. We show that in terms of signal-to-noise ratio, CRT is as important as patient dose, imaging time or PET system sensitivity. The noise reduction effect of better timing resolution is verified and visualized by Monte Carlo simulation of a NEMA image quality phantom. PMID:27245232
Analytical model of coincidence resolving time in TOF-PET
NASA Astrophysics Data System (ADS)
Wieczorek, H.; Thon, A.; Dey, T.; Khanin, V.; Rodnyi, P.
2016-06-01
The coincidence resolving time (CRT) of scintillation detectors is the parameter determining noise reduction in time-of-flight PET. We derive an analytical CRT model based on the statistical distribution of photons for two different prototype scintillators. For the first one, characterized by single exponential decay, CRT is proportional to the decay time and inversely proportional to the number of photons, with a square root dependence on the trigger level. For the second scintillator prototype, characterized by exponential rise and decay, CRT is proportional to the square root of the product of rise time and decay time divided by the doubled number of photons, and it is nearly independent of the trigger level. This theory is verified by measurements of scintillation time constants, light yield and CRT on scintillator sticks. Trapping effects are taken into account by defining an effective decay time. We show that in terms of signal-to-noise ratio, CRT is as important as patient dose, imaging time or PET system sensitivity. The noise reduction effect of better timing resolution is verified and visualized by Monte Carlo simulation of a NEMA image quality phantom.
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.
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
Short-term Time Step Convergence in a Climate Model
Wan, Hui; Rasch, Philip J.; Taylor, Mark; Jablonowski, Christiane
2015-02-11
A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to the expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.
Time Ordering in Frontal Lobe Patients: A Stochastic Model Approach
ERIC Educational Resources Information Center
Magherini, Anna; Saetti, Maria Cristina; Berta, Emilia; Botti, Claudio; Faglioni, Pietro
2005-01-01
Frontal lobe patients reproduced a sequence of capital letters or abstract shapes. Immediate and delayed reproduction trials allowed the analysis of short- and long-term memory for time order by means of suitable Markov chain stochastic models. Patients were as proficient as healthy subjects on the immediate reproduction trial, thus showing spared…
Time-to-Compromise Model for Cyber Risk Reduction Estimation
Miles A. McQueen; Wayne F. Boyer; Mark A. Flynn; George A. Beitel
2005-09-01
We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.
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.
Short-term Time Step Convergence in a Climate Model
Wan, Hui; Rasch, Philip J.; Taylor, Mark; Jablonowski, Christiane
2015-02-11
A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore » expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less
Toward a Wellness Model of Time-Effective Family Psychotherapy.
ERIC Educational Resources Information Center
Friedman, Steven
1991-01-01
Contends that psychologists need to appreciate the client's resources and strengths and avoid being coopted into a medical framework which skews one's thinking toward pathology and deficits. Describes a time-effective model of family psychotherapy which emphasizes possibilities, strengths, and resources. (Author/NB)
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.
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
Real-time Control and Modeling of Plasma Etching
NASA Astrophysics Data System (ADS)
Sarfaty, M.; Baum, C.; Harper, M.; Hershkowitz, N.; Shohet, J. L.
1997-10-01
The relatively high process rates in high density plasma tools as well as the shrinking thickness of the films, require fast estimate of the process state in order to implement real-time advanced process control. The fast etch rate estimate, within one second, in a single spot size of 1-2 mm and the time averaged rates across the wafer are obtained by a combined use of an in-situ two-color laser interferometer and a full wafer image interferometer, respectively. The gas phase state is monitored by optical emission spectroscopy and a residual gas analyzer. The magnetically confined ICP tool state, including gas flow, pressure, and RF power to the antenna and the electrostatic chuck, is computer controlled and monitored. The absolute thickness of the film is determined during the process, thus providing an end-point prediction. The advantages of two-color laser interferometry for real-time process monitoring, development and control will be described. Langmuir kinetics modeling of the measured etch rates of polysilicon and SiO2 films in Cl2 and CF4 discharges using tool state parameters will be described. The etch rate model enabled us to develop a model-based real-time control algorithm. The achieved real-time control of plasma etch rates of un-patterned SiO2 and polysilicon films will be described. This work is funded by NSF grant No. EEC-8721545.
Time-variant clustering model for understanding cell fate decisions.
Huang, Wei; Cao, Xiaoyi; Biase, Fernando H; Yu, Pengfei; Zhong, Sheng
2014-11-01
Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development. PMID:25339442
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
A discrete time random walk model for anomalous diffusion
NASA Astrophysics Data System (ADS)
Angstmann, C. N.; Donnelly, I. C.; Henry, B. I.; Nichols, J. A.
2015-07-01
The continuous time random walk, introduced in the physics literature by Montroll and Weiss, has been widely used to model anomalous diffusion in external force fields. One of the features of this model is that the governing equations for the evolution of the probability density function, in the diffusion limit, can generally be simplified using fractional calculus. This has in turn led to intensive research efforts over the past decade to develop robust numerical methods for the governing equations, represented as fractional partial differential equations. Here we introduce a discrete time random walk that can also be used to model anomalous diffusion in an external force field. The governing evolution equations for the probability density function share the continuous time random walk diffusion limit. Thus the discrete time random walk provides a novel numerical method for solving anomalous diffusion equations in the diffusion limit, including the fractional Fokker-Planck equation. This method has the clear advantage that the discretisation of the diffusion limit equation, which is necessary for numerical analysis, is itself a well defined physical process. Some examples using the discrete time random walk to provide numerical solutions of the probability density function for anomalous subdiffusion, including forcing, are provided.
Age-space-time CAR models in Bayesian disease mapping.
Goicoa, T; Ugarte, M D; Etxeberria, J; Militino, A F
2016-06-30
Mortality counts are usually aggregated over age groups assuming similar effects of both time and region, yet the spatio-temporal evolution of cancer mortality rates may depend on changing age structures. In this paper, mortality rates are analyzed by region, time period and age group, and models including space-time, space-age, and age-time interactions are considered. The integrated nested Laplace approximation method, known as INLA, is adopted for model fitting and inference in order to reduce computing time in comparison with Markov chain Monte Carlo (McMC) methods. The methodology provides full posterior distributions of the quantities of interest while avoiding complex simulation techniques. The proposed models are used to analyze prostate cancer mortality data in 50 Spanish provinces over the period 1986-2010. The results reveal a decline in mortality since the late 1990s, particularly in the age group [65,70), probably because of the inclusion of the PSA (prostate-specific antigen) test and better treatment of early-stage disease. The decline is not clearly observed in the oldest age groups. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26814019
Analytic Modeling of Collector Current and Delay Time in Hbts
NASA Astrophysics Data System (ADS)
Jung, Hee-Bum
1992-01-01
Collector current in abrupt Al_ {0.48}In_{0.52} As/In_{0.53}Ga _{0.47}As HBTs is investigated. Because tunneling plays an important role for abrupt heterojunctions, thermionic field emission (TF) mechanism is included, as a part of the model, in addition to thermionic emission (TE) theory. To model the modulation of the effective barrier height correctly, non-ideal doping profile across the heterojunction is considered. Calculations showed that under nominal operating conditions, TF is dominant over TE in determining the collector current. Furthermore, modulation of the effective barrier height manifests itself in the collector ideality factor that is greater than unity. It is shown that, by calculating the above mentioned transport mechanisms and including the barrier height modulation, the collector current and its temperature dependence in abrupt AlInAs/InGaAs HBTs can be predicted correctly. The detailed calculation is reduced to an analytical closed -form model by assuming a Gaussian energy spectrum for TF current. The model is determined to be accurate over a wide range of bias and temperatures. A simple TE/TF Ebers -Moll model for abrupt HBTs is derived. The classical expression for collector small signal delay time is inadequate for vertically scaled transistors where transient velocity effects can no longer be ignored. Analytical expressions for collector transit time and small signal delay time are proposed for circuit simulation. These models use a general non-uniform velocity profile described entirely in terms of five physical parameters: momentum and energy relaxation times, and initial, peak, and saturated velocities. A C_infty-continuous function approximation for the transit time is used to obtain analytical closed-form expressions for collector small signal delay time in terms of physically meaningful transport parameters. An accurate empirical two-piece model is also proposed. As the collector thickness is scaled down, the ratio of small signal
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
Modeling the Quiet Time Outflow Solution in the Polar Cap
NASA Technical Reports Server (NTRS)
Glocer, Alex
2011-01-01
We use the Polar Wind Outflow Model (PWOM) to study the geomagnetically quiet conditions in the polar cap during solar maximum, The PWOM solves the gyrotropic transport equations for O(+), H(+), and He(+) along several magnetic field lines in the polar region in order to reconstruct the full 3D solution. We directly compare our simulation results to the data based empirical model of Kitamura et al. [2011] of electron density, which is based on 63 months of Akebono satellite observations. The modeled ion and electron temperatures are also compared with a statistical compilation of quiet time data obtained by the EISCAT Svalbard Radar (ESR) and Intercosmos Satellites (Kitamura et al. [2011]). The data and model agree reasonably well. This study shows that photoelectrons play an important role in explaining the differences between sunlit and dark results, ion composition, as well as ion and electron temperatures of the quiet time polar wind solution. Moreover, these results provide validation of the PWOM's ability to model the quiet time ((background" solution.
Modeling a Transient Pressurization with Active Cooling Sizing Tool
NASA Technical Reports Server (NTRS)
Guzik, Monica C.; Plachta, David W.; Elchert, Justin P.
2011-01-01
As interest in the area of in-space zero boil-off cryogenic propellant storage develops, the need to visualize and quantify cryogen behavior during ventless tank self-pressurization and subsequent cool-down with active thermal control has become apparent. During the course of a mission, such as the launch ascent phase, there are periods that power to the active cooling system will be unavailable. In addition, because it is not feasible to install vacuum jackets on large propellant tanks, as is typically done for in-space cryogenic applications for science payloads, instances like the launch ascent heating phase are important to study. Numerous efforts have been made to characterize cryogenic tank pressurization during ventless cryogen storage without active cooling, but few tools exist to model this behavior in a user-friendly environment for general use, and none exist that quantify the marginal active cooling system size needed for power down periods to manage tank pressure response once active cooling is resumed. This paper describes the Transient pressurization with Active Cooling Tool (TACT), which is based on a ventless three-lump homogeneous thermodynamic self-pressurization model1 coupled with an active cooling system estimator. TACT has been designed to estimate the pressurization of a heated but unvented cryogenic tank, assuming an unavailable power period followed by a given cryocooler heat removal rate. By receiving input data on the tank material and geometry, propellant initial conditions, and passive and transient heating rates, a pressurization and recovery profile can be found, which establishes the time needed to return to a designated pressure. This provides the ability to understand the effect that launch ascent and unpowered mission segments have on the size of an active cooling system. A sample of the trends found show that an active cooling system sized for twice the steady state heating rate would results in a reasonable time for tank
Intrinsically Motivated, Free-Time Physical Activity: Considerations for Recess
ERIC Educational Resources Information Center
Stellino, Megan Babkes; Sinclair, Christina D.
2008-01-01
The current childhood obesity rates raise concern about youths' health and the role that a sedentary lifestyle plays in this growing trend. Focusing on how children choose to spend their free time is one approach that may yield ideas for reducing childhood obesity. Recess is a regularly occurring "free time" period in elementary schools. It is,…
Active versus Passive Screen Time for Young Children
ERIC Educational Resources Information Center
Sweetser, Penelope; Johnson, Daniel; Ozdowska, Anne; Wyeth, Peta
2012-01-01
In this paper we report some initial findings from our investigations into the Australian Government's Longitudinal Study of Australian Children dataset. It is revealed that the majority of Australian children are exceeding the government's Screen Time recommendations and that most of their screen time is spent as TV viewing, as opposed to video…
Family Time Activities and Adolescents' Emotional Well-Being
ERIC Educational Resources Information Center
Offer, Shira
2013-01-01
The literature is divided on the issue of what matters for adolescents' well-being, with one approach focusing on quality and the other on routine family time. Using the experience sampling method, a unique form of time diary, and survey data drawn from the 500 Family Study ("N" = 237 adolescents with 8,122 observations), this study examined the…
Modeling Finite-Time Failure Probabilities in Risk Analysis Applications.
Dimitrova, Dimitrina S; Kaishev, Vladimir K; Zhao, Shouqi
2015-10-01
In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time-dependent critical risk level within a finite-time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented. PMID:26010201
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)
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.
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 multiscale statistical model for time series forecasting
NASA Astrophysics Data System (ADS)
Wang, W.; Pollak, I.
2007-02-01
We propose a stochastic grammar model for random-walk-like time series that has features at several temporal scales. We use a tree structure to model these multiscale features. The inside-outside algorithm is used to estimate the model parameters. We develop an algorithm to forecast the sign of the first difference of a time series. We illustrate the algorithm using log-price series of several stocks and compare with linear prediction and a neural network approach. We furthermore illustrate our algorithm using synthetic data and show that it significantly outperforms both the linear predictor and the neural network. The construction of our synthetic data indicates what types of signals our algorithm is well suited for.
A channel dynamics model for real-time flood forecasting
Hoos, A.B.; Koussis, A.D.; Beale, G.O.
1989-01-01
A new channel dynamics scheme ASPIRE (alternative system predictor in real time), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio. -Authors
Time to Absorption for a Heterogeneous Neutral Competition Model
NASA Astrophysics Data System (ADS)
Borile, Claudio; Pra, Paolo Dai; Fischer, Markus; Formentin, Marco; Maritan, Amos
2014-07-01
Neutral models aspire to explain biodiversity patterns in ecosystems where species difference can be neglected and perfect symmetry is assumed between species. Voter-like models capture the essential ingredients of the neutral hypothesis and represent a paradigm for other disciplines like social studies and chemical reactions. In a system where each individual can interact with all the other members of the community, the typical time to reach an absorbing state with a single species scales linearly with the community size. Here we show, by using a rigorous approach based on a large deviation principle and confirming previous approximate and numerical results, that in a mean-field heterogeneous voter model the typical time to reach an absorbing state scales exponentially with the system size.
Instrumented Shoes for Real-Time Activity Monitoring Applications.
Moufawad El Achkar, Christopher; Lenoble-Hoskovec, Constanze; Major, Kristof; Paraschiv-Ionescu, Anisoara; Büla, Christophe; Aminian, Kamiar
2016-01-01
Activity monitoring in daily life is gaining momentum as a health assessment tool, especially in older adults and at-risk populations. Several research-based and commercial systems have been proposed with varying performances in classification accuracy. Configurations with many sensors are generally accurate but cumbersome, whereas single sensors tend to have lower accuracies. To this end, we propose an instrumented shoes system capable of accurate activity classification and gait analysis that contains sensors located entirely at the level of the shoes. One challenge in daily activity monitoring is providing punctual and subject-tailored feedback to improve mobility. Therefore, the instrumented shoe system was equipped with a Bluetooth® module to transmit data to a smartphone and perform detailed activity profiling of the monitored subjects. The potential applications of such a system are numerous in mobility and fall risk-assessment as well as in fall prevention. PMID:27332298
Activities. Mathematics as Communication: Graphing Information Collected Over Time.
ERIC Educational Resources Information Center
Moody, Marian
1990-01-01
Described is a learning activity that requires students to observe, read, and interpret graphs and organize and describe data. Included are the grade level, materials, objectives, prerequisites, directions, answers to questions, and copies of handouts. (KR)
A Circuit Model of Real Time Human Body Hydration.
Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H
2016-06-01
Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration. PMID:26485354
Labrou, Maria; Michail, George; Ntokou, Eleni; Pittaras, Theodore E; Pournaras, Spyros; Tsakris, Athanassios
2012-06-01
We compared the activity of dicloxacillin with that of vancomycin against 15 oxacillin-susceptible, methicillin-resistant Staphylococcus aureus (OS-MRSA) clinical isolates. By population analyses, we found that 6 OS-MRSA isolates were able to grow in the presence of up to 8 μg/ml dicloxacillin and 9 isolates were able to grow in 12 to >32 μg/ml dicloxacillin; all isolates grew in up to 2 μg/ml vancomycin. Both drugs exhibited similar bactericidal activities. In experimental infections, the therapeutic efficacy of dicloxacillin was significant (P < 0.05 versus untreated controls) in 10 OS-MRSA isolates and vancomycin was effective (P < 0.05) against 12 isolates; dicloxacillin had an efficacy that was comparable to that of vancomycin (P > 0.05) in 8 isolates. The favorable response to dicloxacillin treatment might suggest that antistaphylococcal penicillins could be used against OS-MRSA infections. PMID:22430957
Walton, Richard D.; Smith, Rebecca M.; Mitrea, Bogdan G.; White, Edward; Bernus, Olivier; Pertsov, Arkady M.
2012-01-01
Optical mapping has become an indispensible tool for studying cardiac electrical activity. However, due to the three-dimensional nature of the optical signal, the optical upstroke is significantly longer than the electrical upstroke. This raises the issue of how to accurately determine the activation time on the epicardial surface. The purpose of this study was to establish a link between the optical upstroke and exact surface activation time using computer simulations, with subsequent validation by a combination of microelectrode recordings and optical mapping experiments. To simulate wave propagation and associated optical signals, we used a hybrid electro-optical model. We found that the time of the surface electrical activation (tE) within the accuracy of our simulations coincided with the maximal slope of the optical upstroke (tF∗) for a broad range of optical attenuation lengths. This was not the case when the activation time was determined at 50% amplitude (tF50) of the optical upstroke. The validation experiments were conducted in isolated Langendorff-perfused rat hearts and coronary-perfused pig left ventricles stained with either di-4-ANEPPS or the near-infrared dye di-4-ANBDQBS. We found that tF∗ was a more accurate measure of tE than was tF50 in all experimental settings tested (P = 0.0002). Using tF∗ instead of tF50 produced the most significant improvement in measurements of the conduction anisotropy and the transmural conduction time in pig ventricles. PMID:22225795
Where Has the Time Gone? Faculty Activities and Time Commitments in the Online Classroom
ERIC Educational Resources Information Center
Mandernach, B. Jean; Hudson, Swinton; Wise, Shanna
2013-01-01
While research has examined the comparative time commitment required for online versus face-to-face teaching, little is known about the distribution of faculty time investment into the various aspects of online course facilitation. The purpose of this study is to examine the proportion of time faculty devote to each of the pedagogical components…
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.
Identification of neutral biochemical network models from time series data
Vilela, Marco; Vinga, Susana; Maia, Marco A Grivet Mattoso; Voit, Eberhard O; Almeida, Jonas S
2009-01-01
Background The major difficulty in modeling biological systems from multivariate time series is the identification of parameter sets that endow a model with dynamical behaviors sufficiently similar to the experimental data. Directly related to this parameter estimation issue is the task of identifying the structure and regulation of ill-characterized systems. Both tasks are simplified if the mathematical model is canonical, i.e., if it is constructed according to strict guidelines. Results In this report, we propose a method for the identification of admissible parameter sets of canonical S-systems from biological time series. The method is based on a Monte Carlo process that is combined with an improved version of our previous parameter optimization algorithm. The method maps the parameter space into the network space, which characterizes the connectivity among components, by creating an ensemble of decoupled S-system models that imitate the dynamical behavior of the time series with sufficient accuracy. The concept of sloppiness is revisited in the context of these S-system models with an exploration not only of different parameter sets that produce similar dynamical behaviors but also different network topologies that yield dynamical similarity. Conclusion The proposed parameter estimation methodology was applied to actual time series data from the glycolytic pathway of the bacterium Lactococcus lactis and led to ensembles of models with different network topologies. In parallel, the parameter optimization algorithm was applied to the same dynamical data upon imposing a pre-specified network topology derived from prior biological knowledge, and the results from both strategies were compared. The results suggest that the proposed method may serve as a powerful exploration tool for testing hypotheses and the design of new experiments. PMID:19416537
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. PMID:26188633
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.
Unsteady aerodynamic modeling and active aeroelastic control
NASA Technical Reports Server (NTRS)
Edwards, J. W.
1977-01-01
Unsteady aerodynamic modeling techniques are developed and applied to the study of active control of elastic vehicles. The problem of active control of a supercritical flutter mode poses a definite design goal stability, and is treated in detail. The transfer functions relating the arbitrary airfoil motions to the airloads are derived from the Laplace transforms of the linearized airload expressions for incompressible two dimensional flow. The transfer function relating the motions to the circulatory part of these loads is recognized as the Theodorsen function extended to complex values of reduced frequency, and is termed the generalized Theodorsen function. Inversion of the Laplace transforms yields exact transient airloads and airfoil motions. Exact root loci of aeroelastic modes are calculated, providing quantitative information regarding subcritical and supercritical flutter conditions.
CFD Modeling for Active Flow Control
NASA Technical Reports Server (NTRS)
Buning, Pieter G.
2001-01-01
This presentation describes current work under UEET Active Flow Control CFD Research Tool Development. The goal of this work is to develop computational tools for inlet active flow control design. This year s objectives were to perform CFD simulations of fully gridded vane vortex generators, micro-vortex genera- tors, and synthetic jets, and to compare flowfield results with wind tunnel tests of simple geometries with flow control devices. Comparisons are shown for a single micro-vortex generator on a flat plate, and for flow over an expansion ramp with sidewall effects. Vortex core location, pressure gradient and oil flow patterns are compared between experiment and computation. This work lays the groundwork for evaluating simplified modeling of arrays of devices, and provides the opportunity to test simple flow control device/sensor/ control loop interaction.
Active shape models with optimised texture features for radiotherapy
NASA Astrophysics Data System (ADS)
Cheng, K.; Montgomery, D.; Yang, F.; McLaren, D. B.; McLaughlin, S.; Nailon, W. H.
2014-03-01
There is now considerable interest in radiation oncology on the use of shape models of anatomy to improve target delineation and assess anatomical disparity at time of radiotherapy. In this paper a texture based active shape model (ASM) is presented for automatic delineation of the gross tumor volume (GTV), containing the prostate, on computed tomography (CT) images of prostate cancer patients. The model was trained on two-dimensional (2D) contours identified by a radiation oncologist on sequential CT image slices. A three-dimensional (3D) GTV shape was constructed from these and iteratively aligned using Procrustes analysis. To train the model the shape deformation variance was learnt using the Active Shape Model (ASM) approach. In a novel development to this approach a profile feature was selected from pre-computed texture features by minimizing the Mahalanobis distance to obtain the most distinct feature for each landmark. The interior of the GTV was modelled using quantile histograms to initialize the shape model on new cases. From the archive of 42 cases of contoured CT scans, 32 cases were randomly selected for training the model and 10 cases for evaluating performance. The gold standard was defined by the radiation oncologist. The shape model achieved an overall Dice coefficient of 0.81 for all test cases. Performance was found to increase, mean Dice coefficient of 0.87, when the volume size of the new case was similar to the mean shape of the model. With further work the approach has the potential to be used in real-time delineation of target volumes and improve segmentation accuracy.
Predicting aquifer response time for application in catchment modeling.
Walker, Glen R; Gilfedder, Mat; Dawes, Warrick R; Rassam, David W
2015-01-01
It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments. PMID:24842053
Time-series models for border inspection data.
Decrouez, Geoffrey; Robinson, Andrew
2013-12-01
We propose a new modeling approach for inspection data that provides a more useful interpretation of the patterns of detections of invasive pests, using cargo inspection as a motivating example. Methods that are currently in use generally classify shipments according to their likelihood of carrying biosecurity risk material, given available historical and contextual data. Ideally, decisions regarding which cargo containers to inspect should be made in real time, and the models used should be able to focus efforts when the risk is higher. In this study, we propose a dynamic approach that treats the data as a time series in order to detect periods of high risk. A regulatory organization will respond differently to evidence of systematic problems than evidence of random problems, so testing for serial correlation is of major interest. We compare three models that account for various degrees of serial dependence within the data. First is the independence model where the prediction of the arrival of a risky shipment is made solely on the basis of contextual information. We also consider a Markov chain that allows dependence between successive observations, and a hidden Markov model that allows further dependence on past data. The predictive performance of the models is then evaluated using ROC and leakage curves. We illustrate this methodology on two sets of real inspection data. PMID:23682814
Travel-time curves for a simple sea floor model
NASA Astrophysics Data System (ADS)
Stephen, R. A.
1982-09-01
This paper reviews a simple technique for interpreting the velocity structure of upper oceanic crust from travel-time data of sonobuoy and ocean bottom receiver refraction experiments. The technique does not involve sophisticated digital processing or synthetic seismogram analysis. Interpretations can be carried out with a pencil, paper and slide rule. Travel-time inversion procedures based on the τ- p transformation require the assumption of the shallowmost velocity. In some cases, however, such as oceanic crustal studies, the shallowmost velocity is one tf the critical parameters for which one wishes to invert. An inversion method for the shallowmost velocity is discussed which assumes a constant velocity gradient. The time, range and ray parameter of a point on the travel-time curve are sufficient to obtain the velocity at the top of the gradient zone and the gradient. The method can be used to interpolate the velocity-depth function into regions from which no seismic energy is returned as a first arrival. Once an estimate of the upper crustal velocity is obtained the traditional τ- p procedures can be applied. The model considered consists of a homogeneous layer over a layer in which velocity increases linearly with depth. For such a geometry there are three classes of behaviour of the travel-time curve based on the number of cusps: zero, one or two. The number of cusps depends on the uppermost velocity in the crust, the velocity gradient of the upper crust and the depth of the sources and receivers. It has not been previously recognized that two cusps in the travel time curve may be observed for this simple model. Since estimating the ray parameter from first arrival times is less ambiguous when there are no cusps, understanding the relations involved with the three classes aids in the design of experiments. It is reasonable to apply the model to shallow sea floor structure because of the high quality of marine refraction data which has recently been
Travel Time Distribution Modeling in the Valles Caldera, New Mexico
NASA Astrophysics Data System (ADS)
Broxton, P. D.; Troch, P. A.; Brooks, P. D.; Lyon, S. W.; Gustafson, J. R.; Veatch, W. C.
2007-12-01
Modeling the transit times of catchment waters is of paramount importance in hydrology. The distribution of the time it takes for individual water molecules to move through a hydrologic system (a.k.a., the travel time distribution) is a fundamental characterization of a catchment. Travel time distributions are affected by a variety of physical characteristics of catchments (e.g., vegetation type, degree of soil development) that depend on the amount of solar energy the catchment receives. These characteristics, therefore, can be considered a function of aspect. The goal of this research is to constrain travel time distributions on a series of eight radial mountain streams having different slope aspects on Redondo Peak, a resurgent dome in the center of the Valles Caldera, near Los Alamos, New Mexico. Redondo Peak is an excellent natural laboratory for this type of experiment because all aspects are represented on different sides of the mountain while the internal geology and climate are relatively consistent. To model the transit time distributions of each catchment, variations of chemical load of the snowpack, isotopic compositions of meltwater samples, and snowcover distribution data from closely related studies are coupled with periodic stream and precipitation samples that are analyzed for stable water isotopes content. Additional information comes from a network of temperature sensors to monitor the distribution of snowmelt and headwater stream discharge as well as a series of flumes to capture the flows from the streams. The travel time distributions determined in this project provide a bottom up approach to verify catchment-scale models.
Relationship between the peak time of hamstring stretch and activation during sprinting.
Higashihara, Ayako; Nagano, Yasuharu; Ono, Takashi; Fukubayashi, Toru
2016-01-01
The purpose of this study was to investigate the time series relationships between the peak musculotendon length and electromyography (EMG) activation during overground sprinting to clarify the risk of muscle strain injury incidence in each hamstring muscle. Full-body kinematics and EMG of the right biceps femoris long head (BFlh) and semitendinosus (ST) muscles were recorded in 13 male sprinters during overground sprinting at maximum effort. The hamstring musculotendon lengths during sprinting were computed using a three-dimensional musculoskeletal model. The time of the peak musculotendon length, in terms of the percentage of the running gait cycle, was measured and compared with that of the peak EMG activity. The maximum length of the hamstring muscles was noted during the late swing phase of sprinting. The peak musculotendon length was synchronous with the peak EMG activation in the BFlh muscle, while the time of peak musculotendon length in the ST muscle occurred significantly later than the peak level of EMG activation (p < 0.05). These results suggest that the BFlh muscle is exposed to an instantaneous high tensile force during the late swing phase of sprinting, indicating a higher risk for muscle strain injury. PMID:25360992
A nonlinear dynamical analogue model of geomagnetic activity
NASA Technical Reports Server (NTRS)
Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Buechner, J.
1992-01-01
Consideration is given to the solar wind-magnetosphere interaction within the framework of deterministic nonlinear dynamics. An earlier dripping faucet analog model of the low-dimensional solar wind-magnetosphere system is reviewed, and a plasma physical counterpart to that model is constructed. A Faraday loop in the magnetotail is considered, and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. The model is characterized as an elementary time-dependent global convection model. The convection evolves within a magnetotail shape that varies in a prescribed manner in response to the dynamical evolution of the convection. The result is a nonlinear model capable of exhibiting a transition from regular to chaotic loading and unloading. The model's behavior under steady loading and also some elementary forms of time-dependent loading is discussed.
Lau, Erica Y; Barr-Anderson, Daheia J; Dowda, Marsha; Forthofer, Melinda; Saunders, Ruth P; Pate, Russell R
2015-05-01
This study examined associations of various elements of the home environment with after-school physical activity and sedentary time in 671 6th-grade children (Mage = 11.49 ± 0.5 years). Children's after-school total physical activity, moderate-to-vigorous physical activity, and sedentary time were measured by accelerometry. Parents completed surveys assessing elements of the home social and physical environment. Mixed-model regression analyses were used to examine the associations between each element of the home environment and children's after-school physical activity and sedentary time. Availability of home physical activity resources was associated positively with after-school total physical activity and negatively with after-school sedentary time in boys. Parental support was associated positively with after-school total physical activity and MVPA and negatively with after-school sedentary time in girls. The home physical environment was associated with boys' after-school physical activity and sedentary time, whereas the home social environment was associated with girls' after-school physical activity and sedentary time. PMID:25386734
Bitew, Menberu; Jackson, Rhett
2015-02-01
The objective of this report is to document the methodology used to calculate the three hydro-geomorphic indices: C Index, Nhot spot, and Interflow Contributing Area (IFC Area). These indices were applied in the Upper Four Mile Creek Watershed in order to better understand the potential mechanisms controlling retention time, path lengths, and potential for nutrient and solute metabolism and exchange associated with the geomorphic configurations of the upland contributing areas, groundwater, the riparian zone, and stream channels.
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.
2016-01-01
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
Gomersall, Sjaan; Maher, Carol; English, Coralie; Rowlands, Alex; Olds, Tim
2015-01-01
The aim of this study was to investigate how previously inactive adults who had participated in a structured, partly supervised 6-week exercise program restructured their time budgets when the program ended. Using a randomised controlled trial design, 129 previously inactive adults were recruited and randomly allocated to one of three groups: a Moderate or Extensive six-week physical activity intervention (150 and 300 additional minutes of exercise per week, respectively) or a Control group. Additional physical activity was accumulated through both group and individual exercise sessions with a wide range of activities. Use of time and time spent in energy expenditure zones was measured using a computerised 24-h self-report recall instrument, the Multimedia Activity Recall for Children and Adults, and accelerometry at baseline, mid- and end-program and at 3- and 6-months follow up. At final follow up, all significant changes in time use domains had returned to within 20 minutes of baseline levels (Physical Activity 1-2 min/d, Active Transport 3-9 min/d, Self-Care 0-2 min/d, Television/Videogames 13-18 min/d in the Moderate and Extensive group, relative to Controls, respectively, p>0.05). Similarly, all significant changes in time spent in the moderate energy expenditure zone had returned to within 1-3 min/d baseline levels (p>0.05), however time spent in vigorous physical activity according to accelerometry estimates remained elevated, although the changes were small in magnitude (1 min/d in the Moderate and Extensive groups, relative to Controls, p=0.01). The results of this study demonstrate strong recidivist patterns in physical activity, but also in other aspects of time use. In designing and determining the effectiveness of exercise interventions, future studies would benefit from considering the whole profile of time use, rather than focusing on individual activities. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12610000248066 PMID
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
Stochastic Modeling Approach to the Incubation Time of Prionic Diseases
NASA Astrophysics Data System (ADS)
Ferreira, A. S.; da Silva, M. A.; Cressoni, J. C.
2003-05-01
Transmissible spongiform encephalopathies are neurodegenerative diseases for which prions are the attributed pathogenic agents. A widely accepted theory assumes that prion replication is due to a direct interaction between the pathologic (PrPSc) form and the host-encoded (PrPC) conformation, in a kind of autocatalytic process. Here we show that the overall features of the incubation time of prion diseases are readily obtained if the prion reaction is described by a simple mean-field model. An analytical expression for the incubation time distribution then follows by associating the rate constant to a stochastic variable log normally distributed. The incubation time distribution is then also shown to be log normal and fits the observed BSE (bovine spongiform encephalopathy) data very well. Computer simulation results also yield the correct BSE incubation time distribution at low PrPC densities.
A refined fuzzy time series model for stock market forecasting
NASA Astrophysics Data System (ADS)
Jilani, Tahseen Ahmed; Burney, Syed Muhammad Aqil
2008-05-01
Time series models have been used to make predictions of stock prices, academic enrollments, weather, road accident casualties, etc. In this paper we present a simple time-variant fuzzy time series forecasting method. The proposed method uses heuristic approach to define frequency-density-based partitions of the universe of discourse. We have proposed a fuzzy metric to use the frequency-density-based partitioning. The proposed fuzzy metric also uses a trend predictor to calculate the forecast. The new method is applied for forecasting TAIEX and enrollments’ forecasting of the University of Alabama. It is shown that the proposed method work with higher accuracy as compared to other fuzzy time series methods developed for forecasting TAIEX and enrollments of the University of Alabama.
Gunnell, Katie E; Flament, Martine F; Buchholz, Annick; Henderson, Katherine A; Obeid, Nicole; Schubert, Nicholas; Goldfield, Gary S
2016-07-01
More physical activity (PA) and less screen time (ST) are positively associated with mental health in adolescents; however, research is limited by short-term designs and the exclusion of ST when examining PA. We examined: (a) changes in PA, ST, symptoms of depression, and symptoms of anxiety over four assessments spanning 11years, and (b) bidirectional relationships between initial PA, ST, and symptoms of depression and anxiety as predictors of change in each other during adolescence. Between 2006 and 2010, participants from Ottawa Canada (Time1; N=1160, Mean age=13.54years) completed questionnaires at four points covering the ages from 10 to 21years. Latent growth modeling was used. PA decreased over time whereas ST and symptoms of depression and anxiety increased over time. Controlling for sex, ethnicity, school location, zBMI, birth year, and parents' education, initially higher anxiety was associated with initially higher ST (covariance=.88, p<.05) and initially lower PA (covariance=-6.84, p=.07) independent of initial symptoms of depression. Higher initial depression was associated with higher initial ST (covariance=2.55, p<.05). Increases in anxiety were associated with increases in ST (covariance=.07, p=.06) and increases in depression (covariance=.41, p<.05). Examining bidirectional relationships, higher initial symptoms of depression predicted greater decreases in PA (b=-.28, p<.05). No other significant findings between initial PA, ST, anxiety, or depression were found as predictors of change in each other. Interventions targeting depression around age 13 may be useful to prevent further declines in PA. Similarly, interventions to reduce ST may be beneficial for concurrent reductions in symptoms of depression and anxiety, irrespective of PA. PMID:27090920
21 CFR 864.7140 - Activated whole blood clotting time tests.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Activated whole blood clotting time tests. 864....7140 Activated whole blood clotting time tests. (a) Identification. An activated whole blood clotting... pulmonary embolism by measuring the coagulation time of whole blood. (b) Classification. Class...