An Innovative Time-Cost-Quality Tradeoff Modeling of Building Construction Project Based on Resource Allocation

PubMed Central

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

Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model

PubMed Central

Abdelnour, A. Farras; Huppert, Theodore

2009-01-01

Near-infrared spectroscopy is a non-invasive neuroimaging method which uses light to measure changes in cerebral blood oxygenation associated with brain activity. In this work, we demonstrate the ability to record and analyze images of brain activity in real-time using a 16-channel continuous wave optical NIRS system. We propose a novel real-time analysis framework using an adaptive Kalman filter and a state–space model based on a canonical general linear model of brain activity. We show that our adaptive model has the ability to estimate single-trial brain activity events as we apply this method to track and classify experimental data acquired during an alternating bilateral self-paced finger tapping task. PMID:19457389

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

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

The Elastic Body Model: A Pedagogical Approach Integrating Real Time Measurements and Modelling Activities

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…

Accelerometer-measured dose-response for physical activity, sedentary time, and mortality in US adults.

PubMed

Matthews, Charles E; Keadle, Sarah Kozey; Troiano, Richard P; Kahle, Lisa; Koster, Annemarie; Brychta, Robert; Van Domelen, Dane; Caserotti, Paolo; Chen, Kong Y; Harris, Tamara B; Berrigan, David

2016-11-01

Moderate-to-vigorous-intensity physical activity is recommended to maintain and improve health, but the mortality benefits of light activity and risk for sedentary time remain uncertain. Using accelerometer-based measures, we 1) described the mortality dose-response for sedentary time and light- and moderate-to-vigorous-intensity activity using restricted cubic splines, and 2) estimated the mortality benefits associated with replacing sedentary time with physical activity, accounting for total activity. US adults (n = 4840) from NHANES (2003-2006) wore an accelerometer for ≤7 d and were followed prospectively for mortality. Proportional hazards models were used to estimate adjusted HRs and 95% CIs for mortality associations with time spent sedentary and in light- and moderate-to-vigorous-intensity physical activity. Splines were used to graphically present behavior-mortality relation. Isotemporal models estimated replacement associations for sedentary time, and separate models were fit for low- (<5.8 h total activity/d) and high-active participants to account for nonlinear associations. Over a mean of 6.6 y, 700 deaths occurred. Compared with less-sedentary adults (6 sedentary h/d), those who spent 10 sedentary h/d had 29% greater risk (HR: 1.29; 95% CI: 1.1, 1.5). Compared with those who did less light activity (3 h/d), those who did 5 h of light activity/d had 23% lower risk (HR: 0.77; 95% CI: 0.6, 1.0). There was no association with mortality for sedentary time or light or moderate-to-vigorous activity in highly active adults. In less-active adults, replacing 1 h of sedentary time with either light- or moderate-to-vigorous-intensity activity was associated with 18% and 42% lower mortality, respectively. Health promotion efforts for physical activity have mostly focused on moderate-to-vigorous activity. However, our findings derived from accelerometer-based measurements suggest that increasing light-intensity activity and reducing sedentary time are also important, particularly for inactive adults. © 2016 American Society for Nutrition.

An active monitoring method for flood events

NASA Astrophysics Data System (ADS)

Chen, Zeqiang; Chen, Nengcheng; Du, Wenying; Gong, Jianya

2018-07-01

Timely and active detecting and monitoring of a flood event are critical for a quick response, effective decision-making and disaster reduction. To achieve the purpose, this paper proposes an active service framework for flood monitoring based on Sensor Web services and an active model for the concrete implementation of the active service framework. The framework consists of two core components-active warning and active planning. The active warning component is based on a publish-subscribe mechanism implemented by the Sensor Event Service. The active planning component employs the Sensor Planning Service to control the execution of the schemes and models and plans the model input data. The active model, called SMDSA, defines the quantitative calculation method for five elements, scheme, model, data, sensor, and auxiliary information, as well as their associations. Experimental monitoring of the Liangzi Lake flood in the summer of 2010 is conducted to test the proposed framework and model. The results show that 1) the proposed active service framework is efficient for timely and automated flood monitoring. 2) The active model, SMDSA, is a quantitative calculation method used to monitor floods from manual intervention to automatic computation. 3) As much preliminary work as possible should be done to take full advantage of the active service framework and the active model.

An Application of the Trans-Contextual Model of Motivation in Elementary School Physical Education

ERIC Educational Resources Information Center

Ntovolis, Yannis; Barkoukis, Vassilis; Michelinakis, Evaggelos; Tsorbatzoudis, Haralambos

2015-01-01

Elementary school physical education can play a prominent role in promoting children's leisure-time physical activity. The trans-contextual model of motivation has been proven effective in describing the process through which school physical education can affect students' leisure-time physical activity. This model has been tested in secondary…

Stochastic modeling of neurobiological time series: Power, coherence, Granger causality, and separation of evoked responses from ongoing activity

NASA Astrophysics Data System (ADS)

Chen, Yonghong; Bressler, Steven L.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Mingzhou

2006-06-01

In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.

Operations Assessment of Launch Vehicle Architectures using Activity Based Cost Models

NASA Technical Reports Server (NTRS)

Ruiz-Torres, Alex J.; McCleskey, Carey

2000-01-01

The growing emphasis on affordability for space transportation systems requires the assessment of new space vehicles for all life cycle activities, from design and development, through manufacturing and operations. This paper addresses the operational assessment of launch vehicles, focusing on modeling the ground support requirements of a vehicle architecture, and estimating the resulting costs and flight rate. This paper proposes the use of Activity Based Costing (ABC) modeling for this assessment. The model uses expert knowledge to determine the activities, the activity times and the activity costs based on vehicle design characteristics. The approach provides several advantages to current approaches to vehicle architecture assessment including easier validation and allowing vehicle designers to understand the cost and cycle time drivers.

HOW DO IMMIGRANTS SPEND THEIR TIME?

PubMed Central

Hamermesh, Daniel S.

2012-01-01

Sharp differences in time use by nativity emerge when activities are distinguished by incidence and intensity in recent U.S. data. A model with daily fixed costs for assimilating activities predicts immigrants are less likely than natives to undertake such activities on a given day; but those who do will spend relatively more time on them. Activities such as purchasing, education, and market work conform to the model. Other results suggest that fixed costs for assimilating activities are higher for immigrants with poor English proficiency or who originate in less developed countries. An analysis of comparable Australian data yields similar results. PMID:24443631

Teacher, peer and parent autonomy support in physical education and leisure-time physical activity: A trans-contextual model of motivation in four nations.

PubMed

Hagger, Martin; Chatzisarantis, Nikos L D; Hein, Vello; Soós, István; Karsai, István; Lintunen, Taru; Leemans, Sofie

2009-07-01

An extended trans-contextual model of motivation for health-related physical activity was tested in samples from four nations. The model proposes a motivational sequence in which perceived autonomy support from teachers in a physical education (PE) context and from peers and parents in a leisure-time physical activity context predict autonomous motivation, intentions and physical activity behaviour in a leisure-time context. A three-wave prospective correlational design was employed. High-school pupils from Britain, Estonia, Finland and Hungary completed measures of perceived autonomy support from PE teachers, autonomous motivation in both contexts, perceived autonomy support from peers and parents, attitudes, subjective norms, perceived behavioural control and intentions from the Theory of Planned Behaviour (TPB), and measures of behaviour and past behaviour in a leisure-time context. Path-analyses controlling for past behaviour supported trans-contextual model hypotheses across all samples. Effects of perceived autonomy support from peers and parents on leisure-time autonomous motivation were small and inconsistent, while effects on TPB variables were stronger. There was a unique effect of perceived autonomy support from PE teachers on leisure-time autonomous motivation. Findings support the model, which provides an explanation of the processes by which perceived autonomy support from different sources affects health-related physical activity motivation across these contexts.

A NEW METHOD OF LONGITUDINAL DIARY ASSEMBLY FOR EXPOSURE MODELING

EPA Science Inventory

Many stochastic human exposure models require the construction of longitudinal time-activity diaries to evaluate the time sequence of concentrations encountered, and hence, the pollutant exposure for the simulated individuals. However, most of the available data on human activiti...

The Active Fault Parameters for Time-Dependent Earthquake Hazard Assessment in Taiwan

NASA Astrophysics Data System (ADS)

Lee, Y.; Cheng, C.; Lin, P.; Shao, K.; Wu, Y.; Shih, C.

2011-12-01

Taiwan is located at the boundary between the Philippine Sea Plate and the Eurasian Plate, with a convergence rate of ~ 80 mm/yr in a ~N118E direction. The plate motion is so active that earthquake is very frequent. In the Taiwan area, disaster-inducing earthquakes often result from active faults. For this reason, it's an important subject to understand the activity and hazard of active faults. The active faults in Taiwan are mainly located in the Western Foothills and the Eastern longitudinal valley. Active fault distribution map published by the Central Geological Survey (CGS) in 2010 shows that there are 31 active faults in the island of Taiwan and some of which are related to earthquake. Many researchers have investigated these active faults and continuously update new data and results, but few people have integrated them for time-dependent earthquake hazard assessment. In this study, we want to gather previous researches and field work results and then integrate these data as an active fault parameters table for time-dependent earthquake hazard assessment. We are going to gather the seismic profiles or earthquake relocation of a fault and then combine the fault trace on land to establish the 3D fault geometry model in GIS system. We collect the researches of fault source scaling in Taiwan and estimate the maximum magnitude from fault length or fault area. We use the characteristic earthquake model to evaluate the active fault earthquake recurrence interval. In the other parameters, we will collect previous studies or historical references and complete our parameter table of active faults in Taiwan. The WG08 have done the time-dependent earthquake hazard assessment of active faults in California. They established the fault models, deformation models, earthquake rate models, and probability models and then compute the probability of faults in California. Following these steps, we have the preliminary evaluated probability of earthquake-related hazards in certain faults in Taiwan. By accomplishing active fault parameters table in Taiwan, we would apply it in time-dependent earthquake hazard assessment. The result can also give engineers a reference for design. Furthermore, it can be applied in the seismic hazard map to mitigate disasters.

A NEW METHOD OF LONGITUDINAL DIARY ASSEMBLY FOR HUMAN EXPOSURE MODELING

EPA Science Inventory

Human exposure time-series modeling requires longitudinal time-activity diaries to evaluate the sequence of concentrations encountered, and hence, pollutant exposure for the simulated individuals. However, most of the available data on human activities are from cross-sectional su...

Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

PubMed

Garcia, Leandro M T; Diez Roux, Ana V; Martins, André C R; Yang, Yong; Florindo, Alex A

2017-08-22

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults.

Wanted: Active Role Models for Today's Kids | NIH MedlinePlus the Magazine

MedlinePlus

... 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 ...

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

PubMed

Hardy, N F; Buonomano, Dean V

2018-02-01

Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

Dual Sticky Hierarchical Dirichlet Process Hidden Markov Model and Its Application to Natural Language Description of Motions.

PubMed

Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen

2017-09-25

In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.

Applying cost accounting to operating room staffing in otolaryngology: time-driven activity-based costing and outpatient adenotonsillectomy.

PubMed

Balakrishnan, Karthik; Goico, Brian; Arjmand, Ellis M

2015-04-01

(1) To describe the application of a detailed cost-accounting method (time-driven activity-cased costing) to operating room personnel costs, avoiding the proxy use of hospital and provider charges. (2) To model potential cost efficiencies using different staffing models with the case study of outpatient adenotonsillectomy. Prospective cost analysis case study. Tertiary pediatric hospital. All otolaryngology providers and otolaryngology operating room staff at our institution. Time-driven activity-based costing demonstrated precise per-case and per-minute calculation of personnel costs. We identified several areas of unused personnel capacity in a basic staffing model. Per-case personnel costs decreased by 23.2% by allowing a surgeon to run 2 operating rooms, despite doubling all other staff. Further cost reductions up to a total of 26.4% were predicted with additional staffing rearrangements. Time-driven activity-based costing allows detailed understanding of not only personnel costs but also how personnel time is used. This in turn allows testing of alternative staffing models to decrease unused personnel capacity and increase efficiency. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

The Effect of the Activities Enhanced Concerning Time Concept on Time Concept Acquisition of Children

ERIC Educational Resources Information Center

Birgül, Arzu Ergisi; Zeteroglu, Elvan Sahin; Derman, Meral Taner

2017-01-01

The aim of this study is to examine the effect of the activities enhanced concerning time concept on time concept acquisition of children. The research is a quantitative study in experimental model with pretest-posttest control group aiming to examine the effect of the activities enhanced concerning time concept on time concept acquisition of…

Social capital, desire to increase physical activity and leisure-time physical activity: a population-based study.

PubMed

Lindström, M

2011-07-01

To investigate the associations between social capital (trust) and leisure-time physical activity. The 2004 Public Health Survey in Skåne is a cross-sectional study. In total, 27,757 individuals aged 18-80 years answered a postal questionnaire (59% participation). Logistic regression models were used to investigate the associations between trust, desire to increase physical activity and leisure-time physical activity. The prevalence of low leisure-time physical activity was 15.3% among men and 13.2% among women. Middle-aged men and older women, respondents born abroad, those with medium/low education, those with the desire to increase physical activity but needing support, and those reporting low trust had significantly higher odds ratios of low leisure-time physical activity than their respective reference groups. The associations between low trust and desire to increase physical activity and between low trust and low leisure-time physical activity remained in the multiple models. The positive association between low trust and low leisure-time physical activity remained after multiple adjustments. There is a concentration of men and women with low leisure-time physical activity who report the desire to increase their physical activity but think that they need support to do so. This group also has a significantly higher prevalence of low trust. Copyright © 2011 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age

PubMed Central

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

Earthquake precursors: activation or quiescence?

NASA Astrophysics Data System (ADS)

Rundle, John B.; Holliday, James R.; Yoder, Mark; Sachs, Michael K.; Donnellan, Andrea; Turcotte, Donald L.; Tiampo, Kristy F.; Klein, William; Kellogg, Louise H.

2011-10-01

We discuss the long-standing question of whether the probability for large earthquake occurrence (magnitudes m > 6.0) is highest during time periods of smaller event activation, or highest during time periods of smaller event quiescence. The physics of the activation model are based on an idea from the theory of nucleation, that a small magnitude earthquake has a finite probability of growing into a large earthquake. The physics of the quiescence model is based on the idea that the occurrence of smaller earthquakes (here considered as magnitudes m > 3.5) may be due to a mechanism such as critical slowing down, in which fluctuations in systems with long-range interactions tend to be suppressed prior to large nucleation events. To illuminate this question, we construct two end-member forecast models illustrating, respectively, activation and quiescence. The activation model assumes only that activation can occur, either via aftershock nucleation or triggering, but expresses no choice as to which mechanism is preferred. Both of these models are in fact a means of filtering the seismicity time-series to compute probabilities. Using 25 yr of data from the California-Nevada catalogue of earthquakes, we show that of the two models, activation and quiescence, the latter appears to be the better model, as judged by backtesting (by a slight but not significant margin). We then examine simulation data from a topologically realistic earthquake model for California seismicity, Virtual California. This model includes not only earthquakes produced from increases in stress on the fault system, but also background and off-fault seismicity produced by a BASS-ETAS driving mechanism. Applying the activation and quiescence forecast models to the simulated data, we come to the opposite conclusion. Here, the activation forecast model is preferred to the quiescence model, presumably due to the fact that the BASS component of the model is essentially a model for activated seismicity. These results lead to the (weak) conclusion that California seismicity may be characterized more by quiescence than by activation, and that BASS-ETAS models may not be robustly applicable to the real data.

The Processes by which Perceived Autonomy Support in Physical Education Promotes Leisure-Time Physical Activity Intentions and Behavior: A Trans-Contextual Model.

ERIC Educational Resources Information Center

Hagger, Martin S.; Chatzisarantis, Nikos L. D.; Culverhouse, Trudi; Biddle, Stuart J. H.

2003-01-01

Model proposes that young people's perceived autonomy support in physical education will affect their perceived locus of causality, intentions, and physical activity behavior in leisure time. Results support the trans-contextual model indicating that perceived autonomy support in an educational context influences motivation in a leisure-time…

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…

Empirical Model of the Location of the Main Ionospheric Trough

NASA Astrophysics Data System (ADS)

Deminov, M. G.; Shubin, V. N.

2018-05-01

The empirical model of the location of the main ionospheric trough (MIT) is developed based on an analysis of data from CHAMP satellite measured at the altitudes of 350-450 km during 2000-2007; the model is presented in the form of the analytical dependence of the invariant latitude of the trough minimum Φm on the magnetic local time (MLT), the geomagnetic activity, and the geographical longitude for the Northern and Southern Hemispheres. The time-weighted average index Kp(τ), the coefficient of which τ = 0.6 is determined by the requirement of the model minimum deviation from experimental data, is used as an indicator of geomagnetic activity. The model has no limitations, either in local time or geomagnetic activity. However, the initial set of MIT minima mainly contains data dealing with an interval of 16-08 MLT for Kp(τ) < 6; therefore, the model is rather qualitative outside this interval. It is also established that (a) the use of solar local time (SLT) instead of MLT increases the model error no more than by 5-10%; (b) the amplitude of the longitudinal effect at the latitude of MIT minimum in geomagnetic (invariant) coordinates is ten times lower than that in geographical coordinates.

Change in physical education motivation and physical activity behavior during middle school.

PubMed

Cox, Anne E; Smith, Alan L; Williams, Lavon

2008-11-01

To test a mediational model of the relationships among motivation-related variables in middle-school physical education and leisure-time physical activity behavior. Sixth- and seventh-grade physical education students from five middle schools in the midwest United States completed a survey containing measures of study variables on two occasions, 1 year apart. Motivation-related constructs positively predicted leisure-time physical activity behavior. Enjoyment of activities in physical education and physical activity during class mediated the relationship between self-determined motivation in physical education and leisure-time physical activity. Perceived competence, autonomy, and relatedness were important antecedent variables in the model, with autonomy and relatedness showing less stability over time and positively predicting self-determined motivation. Students' leisure-time physical activity is linked to motivation-related experiences in physical education. Perceptions of competence, autonomy, and relatedness, self-determined motivation, enjoyment, and physical activity in the physical education setting directly or indirectly predict leisure-time physical activity. The associations suggest that more adaptive motivation corresponds to transfer of behavior across contexts. Also, the findings suggest that the efficacy of school-based physical activity interventions, within and outside of school, is linked to the degree of support for students' self-determined motivation.

Modeling long-term human activeness using recurrent neural networks for biometric data.

PubMed

Kim, Zae Myung; Oh, Hyungrai; Kim, Han-Gyu; Lim, Chae-Gyun; Oh, Kyo-Joong; Choi, Ho-Jin

2017-05-18

With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user's "activeness", and investigates the feasibility in modeling and predicting the long-term activeness of the user. The dataset used in this study consisted of several months of biometric time-series data gathered by seven users independently. Four recurrent neural network (RNN) architectures-as well as a deep neural network and a simple regression model-were proposed to investigate the performance on predicting the activeness of the user under various length-related hyper-parameter settings. In addition, the learned model was tested to predict the time period when the user's activeness falls below a certain threshold. A preliminary experimental result shows that each type of activeness data exhibited a short-term autocorrelation; and among the three types of data, the consumed calories and the number of footsteps were positively correlated, while the heart rate data showed almost no correlation with neither of them. It is probably due to this characteristic of the dataset that although the RNN models produced the best results on modeling the user's activeness, the difference was marginal; and other baseline models, especially the linear regression model, performed quite admirably as well. Further experimental results show that it is feasible to predict a user's future activeness with precision, for example, a trained RNN model could predict-with the precision of 84%-when the user would be less active within the next hour given the latest 15 min of his activeness data. This paper defines and investigates the notion of a user's "activeness", and shows that forecasting the long-term activeness of the user is indeed possible. Such information can be utilized by a health-related application to proactively recommend suitable events or services to the user.

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

The dorsal medial frontal cortex is sensitive to time on task, not response conflict or error likelihood.

PubMed

Grinband, Jack; Savitskaya, Judith; Wager, Tor D; Teichert, Tobias; Ferrera, Vincent P; Hirsch, Joy

2011-07-15

The dorsal medial frontal cortex (dMFC) is highly active during choice behavior. Though many models have been proposed to explain dMFC function, the conflict monitoring model is the most influential. It posits that dMFC is primarily involved in detecting interference between competing responses thus signaling the need for control. It accurately predicts increased neural activity and response time (RT) for incompatible (high-interference) vs. compatible (low-interference) decisions. However, it has been shown that neural activity can increase with time on task, even when no decisions are made. Thus, the greater dMFC activity on incompatible trials may stem from longer RTs rather than response conflict. This study shows that (1) the conflict monitoring model fails to predict the relationship between error likelihood and RT, and (2) the dMFC activity is not sensitive to congruency, error likelihood, or response conflict, but is monotonically related to time on task. Copyright © 2010 Elsevier Inc. All rights reserved.

Coping, stress, and the psychological symptoms of children of divorce: a cross-sectional and longitudinal study.

PubMed

Sandler, I N; Tein, J Y; West, S G

1994-12-01

The authors conducted a cross-sectional and prospective longitudinal study of stress, coping, and psychological symptoms in children of divorce. The sample consisted of 258 children (mean age = 10.1; SD = 1.2), of whom 196 were successfully followed 5.5 months later. A 4-dimensional model of coping was found using confirmatory factor analysis, with the factors being active coping, avoidance, distraction, and support. In the cross-sectional model avoidance coping partially mediated the relations between negative events and symptoms while active coping moderated the relations between negative events and conduct problems. In the longitudinal model significant negative paths were found from active coping and distraction Time 1 to internalizing symptoms Time 2, while Time 1 support coping had a positive path coefficient to Time 2 depression. Positive paths were found between negative events at Time 1 and anxiety at Time 2, and between all symptoms at Time 1 and negative events at Time 2.

Modelling the Surface Distribution of Magnetic Activity on Sun-Like Stars

NASA Astrophysics Data System (ADS)

Isik, Emre

2018-04-01

With the advent of high-precision space-borne stellar photometry and prospects for direct imaging, it is timely and essential to improve our understanding of stellar magnetic activity in rotational time scales. We present models for 'younger suns' with rotation and flux emergence rates between 1 and 16 times the solar rate. The models provide latitudinal distributions and tilt angles of bipolar magnetic regions, using flux tube rise simulations. Using these emergence patterns, we model the subsequent surface flux transport, to predict surface distributions of star-spots. Based on these models, we present preliminary results from our further modelling of the observed azimuthal magnetic fields, which strengthen for more rapidly rotating Sun-like stars.

Statistical Properties of Longitudinal Time-Activity Data for Use in Human Exposure Modeling

EPA Science Inventory

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 ...

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Activity-based costing: a practical model for cost calculation in radiotherapy.

PubMed

Lievens, Yolande; van den Bogaert, Walter; Kesteloot, Katrien

2003-10-01

The activity-based costing method was used to compute radiotherapy costs. This report describes the model developed, the calculated costs, and possible applications for the Leuven radiotherapy department. Activity-based costing is an advanced cost calculation technique that allocates resource costs to products based on activity consumption. In the Leuven model, a complex allocation principle with a large diversity of cost drivers was avoided by introducing an extra allocation step between activity groups and activities. A straightforward principle of time consumption, weighed by some factors of treatment complexity, was used. The model was developed in an iterative way, progressively defining the constituting components (costs, activities, products, and cost drivers). Radiotherapy costs are predominantly determined by personnel and equipment cost. Treatment-related activities consume the greatest proportion of the resource costs, with treatment delivery the most important component. This translates into products that have a prolonged total or daily treatment time being the most costly. The model was also used to illustrate the impact of changes in resource costs and in practice patterns. The presented activity-based costing model is a practical tool to evaluate the actual cost structure of a radiotherapy department and to evaluate possible resource or practice changes.

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…

The Developmental Pathway From Pubertal Timing to Delinquency and Sexual Activity From Early to Late Adolescence

PubMed Central

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

The developmental pathway from pubertal timing to delinquency and sexual activity from early to late adolescence.

PubMed

Negriff, Sonya; Susman, Elizabeth J; Trickett, Penelope K

2011-10-01

There is strong evidence that early pubertal timing is associated with adolescent problem behaviors. However, there has been limited investigation of the mechanisms or developmental relationships. The present study examined longitudinal models incorporating pubertal timing, delinquency, and sexual activity in a sample of 454 adolescents (9-13 years old at enrollment; 47% females). Participants were seen for three assessments approximately 1 year apart. Characteristics of friendship networks (older friends, male friends, older male friends) were examined as mediators. Structural equation modeling was used to test these associations as well as temporal relationships between sexual activity and delinquency. Results showed that early pubertal timing at Time 1 was related to more sexual activity at Time 2, which was related to higher delinquency at Time 3, a trend mediation effect. None of the friendship variables mediated these associations. Gender or maltreatment status did not moderate the meditational pathways. The results also supported the temporal sequence of sexual activity preceding increases in delinquency. These findings reveal that early maturing adolescents may actively seek out opportunities to engage in sexual activity which appears to be risk for subsequent delinquency.

Space Weather Models at the CCMC And Their Capabilities

NASA Technical Reports Server (NTRS)

Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

2007-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. In this presentation, we will provide an overview of the community-provided, space weather-relevant, model suite, which resides at CCMC. We will discuss current capabilities, and analyze expected future developments of space weather related modeling.

Coping efficacy and psychological problems of children of divorce.

PubMed

Sandler, I N; Tein, J Y; Mehta, P; Wolchik, S; Ayers, T

2000-01-01

Three models of the relations of coping efficacy, coping, and psychological problems of children of divorce were investigated. A structural equation model using cross-sectional data of 356 nine- to twelve-year-old children of divorce yielded results that supported coping efficacy as a mediator of the relations between both active coping and avoiding coping and psychological problems. In a prospective longitudinal model with a subsample of 162 of these children, support was found for Time 2 coping efficacy as a mediator of the relations between Time 1 active coping and Time 2 internalizing of problems. Individual growth curve models over four waves also found support for coping efficacy as a mediator of the relations between active coping and psychological problems. No support was found for alternative models of coping as a mediator of the relations between efficacy and symptoms or for coping efficacy as a moderator of the relations between coping and symptoms.

Understanding human activity patterns based on space-time-semantics

NASA Astrophysics Data System (ADS)

Huang, Wei; Li, Songnian

2016-11-01

Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis

PubMed Central

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents’ time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the ‘success breeds success’ hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined. PMID:27055121

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis.

PubMed

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents' time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the 'success breeds success' hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation

NASA Astrophysics Data System (ADS)

Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe

2017-08-01

Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus  <54% in two-choice classification accuracy. Significance. We believe GMMAC will be useful for clinical fNIRS-based brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

PubMed

Wu, Jun; Tjoa, Thomas; Li, Lianfa; Jaimes, Guillermo; Delfino, Ralph J

2012-07-11

Exposure to polycyclic aromatic hydrocarbon (PAH) has been linked to various adverse health outcomes. Personal PAH exposures are usually measured by personal monitoring or biomarkers, which are costly and impractical for a large population. Modeling is a cost-effective alternative to characterize personal PAH exposure although challenges exist because the PAH exposure can be highly variable between locations and individuals in non-occupational settings. In this study we developed models to estimate personal inhalation exposures to particle-bound PAH (PB-PAH) using data from global positioning system (GPS) time-activity tracking data, traffic activity, and questionnaire information. We conducted real-time (1-min interval) personal PB-PAH exposure sampling coupled with GPS tracking in 28 non-smoking women for one to three sessions and one to nine days each session from August 2009 to November 2010 in Los Angeles and Orange Counties, California. Each subject filled out a baseline questionnaire and environmental and behavior questionnaires on their typical activities in the previous three months. A validated model was used to classify major time-activity patterns (indoor, in-vehicle, and other) based on the raw GPS data. Multiple-linear regression and mixed effect models were developed to estimate averaged daily and subject-level PB-PAH exposures. The covariates we examined included day of week and time of day, GPS-based time-activity and GPS speed, traffic- and roadway-related parameters, meteorological variables (i.e. temperature, wind speed, relative humidity), and socio-demographic variables and occupational exposures from the questionnaire. We measured personal PB-PAH exposures for 180 days with more than 6 h of valid data on each day. The adjusted R2 of the model was 0.58 for personal daily exposures, 0.61 for subject-level personal exposures, and 0.75 for subject-level micro-environmental exposures. The amount of time in vehicle (averaging 4.5% of total sampling time) explained 48% of the variance in daily personal PB-PAH exposure and 39% of the variance in subject-level exposure. The other major predictors of PB-PAH exposures included length-weighted traffic count, work-related exposures, and percent of weekday time. We successfully developed regression models to estimate PB-PAH exposures based on GPS-tracking data, traffic data, and simple questionnaire information. Time in vehicle was the most important determinant of personal PB-PAH exposure in this population. We demonstrated the importance of coupling real-time exposure measures with GPS time-activity tracking in personal air pollution exposure assessment.

A tracer kinetic model for 18F-FHBG for quantitating herpes simplex virus type 1 thymidine kinase reporter gene expression in living animals using PET.

PubMed

Green, Leeta Alison; Nguyen, Khoi; Berenji, Bijan; Iyer, Meera; Bauer, Eileen; Barrio, Jorge R; Namavari, Mohammad; Satyamurthy, Nagichettiar; Gambhir, Sanjiv S

2004-09-01

Reporter probe 9-(4-18F-fluoro-3-[hydroxymethyl]butyl)guanine (18F-FHBG) and reporter gene mutant herpes simplex virus type 1 thymidine kinase (HSV1-sr39tk) have been used for imaging reporter gene expression with PET. Current methods for quantitating the images using the percentage injected dose per gram of tissue do not distinguish between the effects of probe transport and subsequent phosphorylation. We therefore investigated tracer kinetic models for 18F-FHBG dynamic microPET data and noninvasive methods for determining blood time-activity curves in an adenoviral gene delivery model in mice. 18F-FHBG (approximately 7.4 MBq [approximately 200 microCi]) was injected into 4 mice; 18F-FHBG concentrations in plasma and whole blood were measured from mouse heart left ventricle (LV) direct sampling. Replication-incompetent adenovirus (0-2 x 10(9) plaque-forming units) with the E1 region deleted (n = 8) or replaced by HSV1-sr39tk (n = 18) was tail-vein injected into mice. Mice were dynamically scanned using microPET (approximately 7.4 MBq [approximately 200 microCi] 18F-FHBG) over 1 h; regions of interest were drawn on images of the heart and liver. Serial whole blood 18F-FHBG concentrations were measured in 6 of the mice by LV sampling, and 1 least-squares ratio of the heart image to the LV time-activity curve was calculated for all 6 mice. For 2 control mice and 9 mice expressing HSV1-sr39tk, heart image (input function) and liver image time-activity curves (tissue curves) were fit to 2- and 3-compartment models using Levenberg-Marquardt nonlinear regression. The models were compared using an F statistic. HSV1-sr39TK enzyme activity was determined from liver samples and compared with model parameter estimates. For another 3 control mice and 6 HSV1-sr39TK-positive mice, the model-predicted relative percentage of metabolites was compared with high-performance liquid chromatography analysis. The ratio of 18F-FHBG in plasma to whole blood was 0.84 +/- 0.05 (mean +/- SE) by 30 s after injection. The least-squares ratio of the heart image time-activity curve to the LV time-activity curve was 0.83 +/- 0.02, consistent with the recovery coefficient for the partial-volume effect (0.81) based on independent measures of heart geometry. A 3-compartment model best described 18F-FHBG kinetics in mice expressing HSV1-sr39tk in the liver; a 2-compartment model best described the kinetics in control mice. The 3-compartment model parameter, k3, correlated well with the HSV1-sr39TK enzyme activity (r2 = 0.88). 18F-FHBG equilibrates rapidly between plasma and whole blood in mice. Heart image time-activity curves corrected for partial-volume effects well approximate LV time-activity curves and can be used as input functions for 2- and 3-compartment models. The model parameter k3 from the 3-compartment model can be used as a noninvasive estimate for HSV1-sr39TK reporter protein activity and can predict the relative percentage of metabolites.

A framework for the use of agent based modeling to simulate inter- and intraindividual variation in human behaviors

EPA Science Inventory

Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an ag...

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…

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time & space model (sSoTS).

PubMed

Mavritsaki, Eirini; Heinke, Dietmar; Humphreys, Glyn W; Deco, Gustavo

2006-01-01

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.

Self-determined motivation in physical education and its links to motivation for leisure-time physical activity, physical activity, and well-being in general.

PubMed

Bagøien, Tor Egil; Halvari, Hallgeir; Nesheim, Hallgeir

2010-10-01

The present study tested a trans-contextual model based on self-determination theory of the relations between motivation in physical education, motivation in leisure-time physical activity, physical activity, and psychological well-being. Participants were 329 Norwegian upper secondary school students (M age = 16.5 yr., SD = 0.7). Students' perceptions of autonomy-supportive teachers in physical education were expected to be positively associated with students' psychological needs satisfaction in physical education, which was expected to be positively related to autonomous motivation for physical education participation. In turn, autonomous motivation for physical education was expected to be positively associated with perceived competence and autonomous motivation for leisure-time physical activity, which both were expected to be positively associated with leisure-time physical activity and psychological well-being in general. Structural equation models and bootstrapping supported the hypotheses and the indirect links between variables. Sex differences indicate that more research is needed on how to motivate girls to be more physically active in leisure time.

Leisure-Time Physical Activity and Academic Performance: Cross-Lagged Associations from Adolescence to Young Adulthood

PubMed Central

Aaltonen, Sari; Latvala, Antti; Rose, Richard J.; Kujala, Urho M.; Kaprio, Jaakko; Silventoinen, Karri

2016-01-01

Physical activity and academic performance are positively associated, but the direction of the association is poorly understood. This longitudinal study examined the direction and magnitude of the associations between leisure-time physical activity and academic performance throughout adolescence and young adulthood. The participants were Finnish twins (from 2,859 to 4,190 individuals/study wave) and their families. In a cross-lagged path model, higher academic performance at ages 12, 14 and 17 predicted higher leisure-time physical activity at subsequent time-points (standardized path coefficient at age 14: 0.07 (p < 0.001), age 17: 0.12 (p < 0.001) and age 24: 0.06 (p < 0.05)), whereas physical activity did not predict future academic performance. A cross-lagged model of co-twin differences suggested that academic performance and subsequent physical activity were not associated due to the environmental factors shared by co-twins. Our findings suggest that better academic performance in adolescence modestly predicts more frequent leisure-time physical activity in late adolescence and young adulthood. PMID:27976699

Leisure-Time Physical Activity and Academic Performance: Cross-Lagged Associations from Adolescence to Young Adulthood.

PubMed

Aaltonen, Sari; Latvala, Antti; Rose, Richard J; Kujala, Urho M; Kaprio, Jaakko; Silventoinen, Karri

2016-12-15

Physical activity and academic performance are positively associated, but the direction of the association is poorly understood. This longitudinal study examined the direction and magnitude of the associations between leisure-time physical activity and academic performance throughout adolescence and young adulthood. The participants were Finnish twins (from 2,859 to 4,190 individuals/study wave) and their families. In a cross-lagged path model, higher academic performance at ages 12, 14 and 17 predicted higher leisure-time physical activity at subsequent time-points (standardized path coefficient at age 14: 0.07 (p < 0.001), age 17: 0.12 (p < 0.001) and age 24: 0.06 (p < 0.05)), whereas physical activity did not predict future academic performance. A cross-lagged model of co-twin differences suggested that academic performance and subsequent physical activity were not associated due to the environmental factors shared by co-twins. Our findings suggest that better academic performance in adolescence modestly predicts more frequent leisure-time physical activity in late adolescence and young adulthood.

Simulating wildfire spread behavior between two NASA Active Fire data timeframes

NASA Astrophysics Data System (ADS)

Adhikari, B.; Hodza, P.; Xu, C.; Minckley, T. A.

2017-12-01

Although NASA's Active Fire dataset is considered valuable in mapping the spatial distribution and extent of wildfires across the world, the data is only available at approximately 12-hour time intervals, creating uncertainties and risks associated with fire spread and behavior between the two Visible Infrared Imaging Radiometer Satellite (VIIRS) data collection timeframes. Our study seeks to close the information gap for the United States by using the latest Active Fire data collected for instance around 0130 hours as an ignition source and critical inputs to a wildfire model by uniquely incorporating forecasted and real-time weather conditions for predicting fire perimeter at the next 12 hour reporting time (i.e. around 1330 hours). The model ingests highly dynamic variables such as fuel moisture, temperature, relative humidity, wind among others, and prompts a Monte Carlo simulation exercise that uses a varying range of possible values for evaluating all possible wildfire behaviors. The Monte Carlo simulation implemented in this model provides a measure of the relative wildfire risk levels at various locations based on the number of times those sites are intersected by simulated fire perimeters. Model calibration is achieved using data at next reporting time (i.e. after 12 hours) to enhance the predictive quality at further time steps. While initial results indicate that the calibrated model can predict the overall geometry and direction of wildland fire spread, the model seems to over-predict the sizes of most fire perimeters possibly due to unaccounted fire suppression activities. Nonetheless, the results of this study show great promise in aiding wildland fire tracking, fighting and risk management.

The role of the time-kill kinetics assay as part of a preclinical modeling framework for assessing the activity of anti-tuberculosis drugs.

PubMed

Bax, Hannelore I; Bakker-Woudenberg, Irma A J M; de Vogel, Corné P; van der Meijden, Aart; Verbon, Annelies; de Steenwinkel, Jurriaan E M

2017-07-01

Novel treatment strategies for tuberculosis are urgently needed. Many different preclinical models assessing anti-tuberculosis drug activity are available, but it is yet unclear which combination of models is most predictive of clinical treatment efficacy. The aim of this study was to determine the role of our in vitro time kill-kinetics assay as an asset to a predictive preclinical modeling framework assessing anti-tuberculosis drug activity. The concentration- and time-dependent mycobacterial killing capacities of six anti-tuberculosis drugs were determined during exposure as single drugs or in dual, triple and quadruple combinations towards a Mycobacterium tuberculosis Beijing genotype strain and drug resistance was assessed. Streptomycin, rifampicin and isoniazid were most active against fast-growing M. tuberculosis. Isoniazid with rifampicin or high dose ethambutol were the only synergistic drug combinations. The addition of rifampicin or streptomycin to isoniazid prevented isoniazid resistance. In vitro ranking showed agreement with early bactericidal activity in tuberculosis patients for some but not all anti-tuberculosis drugs. The time-kill kinetics assay provides important information on the mycobacterial killing dynamics of anti-tuberculosis drugs during the early phase of drug exposure. As such, this assay is a valuable component of the preclinical modeling framework. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mathematical Modelling of Liner Piston Maintenance Activity using Field Data to Minimize Overhauling Time and Human Energy Consumption

NASA Astrophysics Data System (ADS)

Belkhode, Pramod Namdeorao

2017-06-01

Field data based model is proposed to reduce the overhauling time and human energy consumed in liner piston maintenance activity so as to increase the productivity of liner piston maintenance activity. The independent variables affecting the phenomenon such as anthropometric parameters of workers (Eastman Kodak Co. Ltd in Section VIA Appendix-A: Anthropometric Data. Ergonomic Design for People at Work, Van Nostrans Reinhold, New York, 1), workers parameters, specification of liner piston data, specification of tools used in liner piston maintenance activity, specification of solvents, axial clearance of big end bearing and bolt elongation, workstation data (Eastman Kodak Co. Ltd in Work Place Ergonomic Design for People at Work, Van Nostrans Reinhold, New York, 2) and extraneous variables, namely, temperature, humidity at workplace, illumination at workplace and noise at workplace (Eastman Kodak Co. Ltd in Chapter V Environment Ergonomic Design for People at Work, Van Nostrans Reinhold, New York, 3) are taken into account. The model is formulated for dependent variables of liner piston maintenance activity to minimize the overhauling time and human energy consumption so as to improve the productivity of liner piston maintenance activity. The developed model can predict the performance of liner piston maintenance activity which involves man and machine system (Schenck in Theories of Engineering Experimentation, Mc-Graw Hill, New York 4). The model is then optimized by optimization technique and the sensitivity analysis of the model has also been estimated.

Forecasting Geomagnetic Activity Using Kalman Filters

NASA Astrophysics Data System (ADS)

Veeramani, T.; Sharma, A.

2006-05-01

The coupling of energy from the solar wind to the magnetosphere leads to the geomagnetic activity in the form of storms and substorms and are characterized by indices such as AL, Dst and Kp. The geomagnetic activity has been predicted near-real time using local linear filter models of the system dynamics wherein the time series of the input solar wind and the output magnetospheric response were used to reconstruct the phase space of the system by a time-delay embedding technique. Recently, the radiation belt dynamics have been studied using a adaptive linear state space model [Rigler et al. 2004]. This was achieved by assuming a linear autoregressive equation for the underlying process and an adaptive identification of the model parameters using a Kalman filter approach. We use such a model for predicting the geomagnetic activity. In the case of substorms, the Bargatze et al [1985] data set yields persistence like behaviour when a time resolution of 2.5 minutes was used to test the model for the prediction of the AL index. Unlike the local linear filters, which are driven by the solar wind input without feedback from the observations, the Kalman filter makes use of the observations as and when available to optimally update the model parameters. The update procedure requires the prediction intervals to be long enough so that the forecasts can be used in practice. The time resolution of the data suitable for such forecasting is studied by taking averages over different durations.

Funding models for outreach ophthalmology services.

PubMed

Turner, Angus W; Mulholland, Will; Taylor, Hugh R

2011-01-01

This paper aims to describe funding models used and compare the effects of funding models for remuneration on clinical activity and cost-effectiveness in outreach eye services in Australia. Cross-sectional case study based in remote outreach ophthalmology services in Australia. Key stake-holders from eye services in nine outreach regions participated in the study. Semistructured interviews were conducted to perform a qualitative assessment of outreach eye services' funding mechanisms. Records of clinical activity were used to statistically compare funding models. Workforce availability (supply of ophthalmologists), costs of services, clinical activity (surgery and clinic consultation rates) and waiting times. The supply of ophthalmologists (full-time equivalence) to all remote regions was below the national average (up to 19 times lower). Cataract surgery rates were also below national averages (up to 10 times lower). Fee-for-service funding significantly increased clinical activity. There were also trends to shorter waiting times and lower costs per attendance. For outreach ophthalmology services, the funding model used for clinician reimbursement may influence the efficiency and costs of the services. Fee-for-service funding models, safety-net funding options or differential funding/incentives need further exploration to ensure isolated disadvantaged areas prone to poor patient attendance are not neglected. In order for outreach eye health services to be sustainable, remuneration rates need to be comparable to those for urban practice. © 2011 The Authors. Clinical and Experimental Ophthalmology © 2011 Royal Australian and New Zealand College of Ophthalmologists.

Broadening the trans-contextual model of motivation: A study with Spanish adolescents.

PubMed

González-Cutre, D; Sicilia, Á; Beas-Jiménez, M; Hagger, M S

2014-08-01

The original trans-contextual model of motivation proposed that autonomy support from teachers develops students' autonomous motivation in physical education (PE), and that autonomous motivation is transferred from PE contexts to physical activity leisure-time contexts, and predicts attitudes, perceived behavioral control and subjective norms, and forming intentions to participate in future physical activity behavior. The purpose of this study was to test an extended trans-contextual model of motivation including autonomy support from peers and parents and basic psychological needs in a Spanish sample. School students (n = 400) aged between 12 and 18 years completed measures of perceived autonomy support from three sources, autonomous motivation and constructs from the theory of planned behavior at three different points in time and in two contexts, PE and leisure-time. A path analysis controlling for past physical activity behavior supported the main postulates of the model. Autonomous motivation in a PE context predicted autonomous motivation in a leisure-time physical activity context, perceived autonomy support from teachers predicted satisfaction of basic psychological needs in PE, and perceived autonomy support from peers and parents predicted need satisfaction in leisure-time. This study provides a cross-cultural replication of the trans-contextual model of motivation and broadens it to encompass basic psychological needs. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Nowcasting influenza outbreaks using open-source media report.

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

Ray, Jaideep; Brownstein, John S.

We construct and verify a statistical method to nowcast influenza activity from a time-series of the frequency of reports concerning influenza related topics. Such reports are published electronically by both public health organizations as well as newspapers/media sources, and thus can be harvested easily via web crawlers. Since media reports are timely, whereas reports from public health organization are delayed by at least two weeks, using timely, open-source data to compensate for the lag in %E2%80%9Cofficial%E2%80%9D reports can be useful. We use morbidity data from networks of sentinel physicians (both the Center of Disease Control's ILINet and France's Sentinelles network)more » as the gold standard of influenza-like illness (ILI) activity. The time-series of media reports is obtained from HealthMap (http://healthmap.org). We find that the time-series of media reports shows some correlation ( 0.5) with ILI activity; further, this can be leveraged into an autoregressive moving average model with exogenous inputs (ARMAX model) to nowcast ILI activity. We find that the ARMAX models have more predictive skill compared to autoregressive (AR) models fitted to ILI data i.e., it is possible to exploit the information content in the open-source data. We also find that when the open-source data are non-informative, the ARMAX models reproduce the performance of AR models. The statistical models are tested on data from the 2009 swine-flu outbreak as well as the mild 2011-2012 influenza season in the U.S.A.« less

Time-driven activity-based costing.

PubMed

Kaplan, Robert S; Anderson, Steven R

2004-11-01

In the classroom, activity-based costing (ABC) looks like a great way to manage a company's limited resources. But executives who have tried to implement ABC in their organizations on any significant scale have often abandoned the attempt in the face of rising costs and employee irritation. They should try again, because a new approach sidesteps the difficulties associated with large-scale ABC implementation. In the revised model, managers estimate the resource demands imposed by each transaction, product, or customer, rather than relying on time-consuming and costly employee surveys. This method is simpler since it requires, for each group of resources, estimates of only two parameters: how much it costs per time unit to supply resources to the business's activities (the total overhead expenditure of a department divided by the total number of minutes of employee time available) and how much time it takes to carry out one unit of each kind of activity (as estimated or observed by the manager). This approach also overcomes a serious technical problem associated with employee surveys: the fact that, when asked to estimate time spent on activities, employees invariably report percentages that add up to 100. Under the new system, managers take into account time that is idle or unused. Armed with the data, managers then construct time equations, a new feature that enables the model to reflect the complexity of real-world operations by showing how specific order, customer, and activity characteristics cause processing times to vary. This Tool Kit uses concrete examples to demonstrate how managers can obtain meaningful cost and profitability information, quickly and inexpensively. Rather than endlessly updating and maintaining ABC data,they can now spend their time addressing the deficiencies the model reveals: inefficient processes, unprofitable products and customers, and excess capacity.

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

PubMed Central

Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

2013-01-01

Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

Longitudinal Relationships Between Productive Activities and Functional Health in Later Years: A Multivariate Latent Growth Curve Modeling Approach.

PubMed

Choi, Eunhee; Tang, Fengyan; Kim, Sung-Geun; Turk, Phillip

2016-10-01

This study examined the longitudinal relationships between functional health in later years and three types of productive activities: volunteering, full-time, and part-time work. Using the data from five waves (2000-2008) of the Health and Retirement Study, we applied multivariate latent growth curve modeling to examine the longitudinal relationships among individuals 50 or over. Functional health was measured by limitations in activities of daily living. Individuals who volunteered, worked either full time or part time exhibited a slower decline in functional health than nonparticipants. Significant associations were also found between initial functional health and longitudinal changes in productive activity participation. This study provides additional support for the benefits of productive activities later in life; engagement in volunteering and employment are indeed associated with better functional health in middle and old age. © The Author(s) 2016.

Mean first passage time of active Brownian particle in one dimension

NASA Astrophysics Data System (ADS)

Scacchi, A.; Sharma, A.

2018-02-01

We investigate the mean first passage time of an active Brownian particle in one dimension using numerical simulations. The activity in one dimension is modelled as a two state model; the particle moves with a constant propulsion strength but its orientation switches from one state to other as in a random telegraphic process. We study the influence of a finite resetting rate r on the mean first passage time to a fixed target of a single free active Brownian particle and map this result using an effective diffusion process. As in the case of a passive Brownian particle, we can find an optimal resetting rate r* for an active Brownian particle for which the target is found with the minimum average time. In the case of the presence of an external potential, we find good agreement between the theory and numerical simulations using an effective potential approach.

Estimation of exposure to atmospheric pollutants during pregnancy integrating space-time activity and indoor air levels: does it make a difference?

PubMed Central

Marion, OUIDIR; Lise, GIORGIS-ALLEMAND; Sarah, LYON-CAEN; Xavier, MORELLI; Claire, CRACOWSKI; Sabrina, PONTET; Isabelle, PIN; Johanna, LEPEULE; Valérie, SIROUX; Rémy, SLAMA

2016-01-01

Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity and indoor air pollution levels. We recruited 40 pregnant women in the Grenoble urban area, France, who carried a Global Positioning System (GPS) during up to 3 weeks; in a subgroup, indoor measurements of fine particles (PM2.5) were conducted at home (n=9) and personal exposure to nitrogen dioxide (NO2) was assessed using passive air samplers (n=10). Outdoor concentrations of NO2, and PM2.5 were estimated from a dispersion model with a fine spatial resolution. Women spent on average 16 h per day at home. Considering only outdoor levels, for estimates at the home address, the correlation between the estimate using the nearest background air monitoring station and the estimate from the dispersion model was high (r=0.93) for PM2.5 and moderate (r=0.67) for NO2. The model incorporating clean GPS data was less correlated with the estimate relying on raw GPS data (r=0.77) than the model ignoring space-time activity (r=0.93). PM2.5 outdoor levels were not to moderately correlated with estimates from the model incorporating indoor measurements and space-time activity (r=−0.10 to 0.47), while NO2 personal levels were not correlated with outdoor levels (r=−0.42 to 0.03). In this urban area, accounting for space-time activity little influenced exposure estimates; in a subgroup of subjects (n=9), incorporating indoor pollution levels seemed to strongly modify them. PMID:26300245

Issues and Challenges in Situation Assessment (Level 2 Fusion)

DTIC Science & Technology

2006-12-01

2 SAW–Comprehension of the current situa- tion ² Level 3 SAW–Projection of future states Operators of dynamic systems use their SAW in de - termining...1) build a model by either editing an existing template/model or create a new one; (2) activate/ de -activate existing models; or (3) view active models...and any evidence that has been associated with the model over time. Different political, military, economic, social , infrastructure, and informa

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…

Trajectory data analyses for pedestrian space-time activity study.

PubMed

Qi, Feng; Du, Fei

2013-02-25

It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission(1-3). An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data(4). Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation(5) involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping(6) and density volume rendering(7). We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry.

PubMed

Durrieu, Gilles; Pham, Quang-Khoai; Foltête, Anne-Sophie; Maxime, Valérie; Grama, Ion; Tilly, Véronique Le; Duval, Hélène; Tricot, Jean-Marie; Naceur, Chiraz Ben; Sire, Olivier

2016-07-01

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter t,τ , beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.

Unsupervised daily routine and activity discovery in smart homes.

PubMed

Jie Yin; Qing Zhang; Karunanithi, Mohan

2015-08-01

The ability to accurately recognize daily activities of residents is a core premise of smart homes to assist with remote health monitoring. Most of the existing methods rely on a supervised model trained from a preselected and manually labeled set of activities, which are often time-consuming and costly to obtain in practice. In contrast, this paper presents an unsupervised method for discovering daily routines and activities for smart home residents. Our proposed method first uses a Markov chain to model a resident's locomotion patterns at different times of day and discover clusters of daily routines at the macro level. For each routine cluster, it then drills down to further discover room-level activities at the micro level. The automatic identification of daily routines and activities is useful for understanding indicators of functional decline of elderly people and suggesting timely interventions.

Motor Competence and its Effect on Positive Developmental Trajectories of Health.

PubMed

Robinson, Leah E; Stodden, David F; Barnett, Lisa M; Lopes, Vitor P; Logan, Samuel W; Rodrigues, Luis Paulo; D'Hondt, Eva

2015-09-01

In 2008, Stodden and colleagues took a unique developmental approach toward addressing the potential role of motor competence in promoting positive or negative trajectories of physical activity, health-related fitness, and weight status. The conceptual model proposed synergistic relationships among physical activity, motor competence, perceived motor competence, health-related physical fitness, and obesity with associations hypothesized to strengthen over time. At the time the model was proposed, limited evidence was available to support or refute the model hypotheses. Over the past 6 years, the number of investigations exploring these relationships has increased significantly. Thus, it is an appropriate time to examine published data that directly or indirectly relate to specific pathways noted in the conceptual model. Evidence indicates that motor competence is positively associated with perceived competence and multiple aspects of health (i.e., physical activity, cardiorespiratory fitness, muscular strength, muscular endurance, and a healthy weight status). However, questions related to the increased strength of associations across time and antecedent/consequent mechanisms remain. An individual's physical and psychological development is a complex and multifaceted process that synergistically evolves across time. Understanding the most salient factors that influence health and well-being and how relationships among these factors change across time is a critical need for future research in this area. This knowledge could aid in addressing the declining levels of physical activity and fitness along with the increasing rates of obesity across childhood and adolescence.

Multi-spacecraft testing of time-dependent interplanetary MHD models for operational forecasting of geomagnetic storms

NASA Technical Reports Server (NTRS)

Dryer, M.; Smith, Z. K.

1989-01-01

An MHD 2-1/2D, time-dependent model is used, together with observations of six solar flares during February 3-7, 1986, to demonstrate global, large-scale, compound disturbances in the solar wind over a wide range of heliolongitudes. This scenario is one that is likely to occur many times during the cruise, possibly even encounter, phases of the Multi-Comet Mission. It is suggested that a model such as this one should be tested with multi-spacecraft data (such as the MCM and earth-based probes) with several goals in view: (1) utility of the model for operational real-time forecasting of geomagnetic storms, and (2) scientific interpretation of certain forms of cometary activities and their possible association with solar-generated activity.

Mortality Risk Reductions from Substituting Screen Time by Discretionary Activities.

PubMed

Wijndaele, Katrien; Sharp, Stephen J; Wareham, Nicholas J; Brage, Søren

2017-06-01

Leisure screen time, including TV viewing, is associated with increased mortality risk. We estimated the all-cause mortality risk reductions associated with substituting leisure screen time with different discretionary physical activity types, and the change in mortality incidence associated with different substitution scenarios. A total of 423,659 UK Biobank participants, without stroke, myocardial infarction, or cancer history, were followed for 7.6 (1.4) yr, median (interquartile range [IQR]). They reported leisure screen time (TV watching and home computer use) and leisure/home activities, categorized as daily life activities (walking for pleasure, light do-it-yourself [DIY], and heavy DIY) and structured exercise (strenuous sports and other exercises). Isotemporal substitution modeling in Cox regression provided hazard ratios (95% confidence intervals) for all-cause mortality when substituting screen time (30 min·d) with different discretionary activity types of the same duration. Potential impact fractions estimated the proportional change in mortality incidence associated with different substitution scenarios. During 3,202,105 person-years of follow-up, 8928 participants died. Each 30-min·d difference in screen time was associated with lower mortality hazard when modeling substitution of screen time by an equal amount of daily life activities (0.95, 0.94-0.97), as well as structured exercise (0.87, 0.84-0.90). Reallocations from screen time into specific activity subtypes suggested different reductions in mortality hazard: walking for pleasure (0.95, 0.92-0.98), light DIY (0.97, 0.94-1.00), heavy DIY (0.93, 0.90-0.96), strenuous sports (0.87, 0.79-0.95), and other exercises (0.88, 0.84-0.91). The lowest hazard estimates were found when modeling replacement of TV viewing. Potential impact fractions ranged from 4.3% (30-min·d substitution of screen time into light DIY) to 14.9% (TV viewing into strenuous sports). Substantial public health benefits could be gained by replacing small amounts of screen time with daily life activities and structured exercise. Daily life activities may provide feasible screen time alternatives, if structured exercise is initially too ambitious.

Mortality Risk Reductions from Substituting Screen-Time by Discretionary Activities

PubMed Central

Wijndaele, Katrien; Sharp, Stephen J; Wareham, Nicholas J; Brage, Søren

2017-01-01

Purpose Leisure-screen-time, including TV viewing, is associated with increased mortality risk. We estimated the all-cause mortality risk reductions associated with substituting leisure-screen-time with different discretionary physical activity types, and the change in mortality incidence associated with different substitution scenarios. Methods 423,659 UK Biobank participants, without stroke, myocardial infarction or cancer history, were followed for 7.6 (1.4) (median (IQR)) years. They reported leisure-screen-time (TV watching and home computer use) and leisure/home activities, categorised as daily-life activities (walking for pleasure; light DIY; heavy DIY) and structured exercise (strenuous sports; other exercises). Iso-temporal substitution modelling in Cox regression provided hazard ratios (95% confidence intervals) for all-cause mortality when substituting screen-time (30 minutes/day) with different discretionary activity types of the same duration. Potential impact fractions (PIFs) estimated the proportional change in mortality incidence associated with different substitution scenarios. Results During 3,202,105 person-years of follow-up, 8,928 participants died. Each 30 minute/day difference in screen-time was associated with lower mortality hazard when modelling substitution of screen-time by an equal amount of daily-life activities (0.95 (0.94-0.97)), as well as structured exercise (0.87 (0.84-0.90)). Re-allocations from screen-time into specific activity subtypes suggested different reductions in mortality hazard (walking for pleasure (0.95 (0.92-0.98)), light DIY (0.97 (0.94-1.00)), heavy DIY (0.93 (0.90-0.96)), strenuous sports (0.87 (0.79-0.95)), other exercises (0.88 (0.84-0.91))). The lowest hazard estimates were found when modelling replacement of TV viewing. PIFs ranged from 4.3% (30 minute/day substitution of screen-time into light DIY) to 14.9% (TV viewing into strenuous sports). Conclusion Substantial public health benefits could be gained by replacing small amounts of screen-time with daily-life activities and structured exercise. Daily-life activities may provide feasible screen-time alternatives, if structured exercise is initially too ambitious. PMID:28106621

Leisure-Time Physical Activity and Sedentary Behavior and Their Cross-Sectional Associations with Excessive Daytime Sleepiness in the French SU.VI.MAX-2 Study.

PubMed

Andrianasolo, Roland M; Menai, Mehdi; Galan, Pilar; Hercberg, Serge; Oppert, Jean-Michel; Kesse-Guyot, Emmanuelle; Andreeva, Valentina A

2016-04-01

The potential benefit of physical activity in terms of decreasing excessive daytime sleepiness (EDS) prevalence is unclear, especially in aging adults. We aimed to elucidate the associations among physical activity, sedentariness, and EDS in middle-aged and older adults. We conducted a cross-sectional analysis using data from a subsample of participants in the SU.VI.MAX-2 observational study (2007-2009; N = 4179; mean age = 61.9 years). EDS was defined as a score >10 on the Epworth Sleepiness Scale. Leisure-time physical activity and different types of sedentary behavior were assessed with the Modifiable Activity Questionnaire. The associations were examined with multivariable logistic regression models. In the adjusted multivariable model, total leisure-time physical activity (modeled in quartiles, Q) was significantly, inversely associated with EDS (odds ratios (OR)Q4 vs Q1 = 0.70, 95 % confidence interval (CI) = 0.54-0.89). The association persisted in analyses restricted to individuals not taking sleep medication (ORQ4 vs Q1 = 0.72, 95 % CI = 0.54-0.95). In turn, time spent watching television and time spent reading appeared protective against EDS (ORQ4 vs Q1 = 0.73, 95 % CI = 0.57-0.94; ORQ4 vs Q1 = 0.76, 95 % CI = 0.60-0.97, respectively), whereas time spent on a computer appeared to confer an increased risk for EDS (ORQ4 vs Q1 = 1.30, 95 % CI = 1.05-1.62). When physical activity and sedentariness were modeled jointly, using WHO recommendation-based cutoffs for high/low levels, no significant associations were observed in the fully adjusted models. The findings reinforce public health recommendations promoting behavior modification and specifically moderate-intensity exercise in middle-aged and older adults. The association of high physical activity/low sedentariness with EDS, which was not supported by the data, merits further investigation before firm conclusions could be drawn.

Stochastic modeling of a serial killer

PubMed Central

Simkin, M.V.; Roychowdhury, V.P.

2014-01-01

We analyze the time pattern of the activity of a serial killer, who during twelve years had murdered 53 people. The plot of the cumulative number of murders as a function of time is of “Devil’s staircase” type. The distribution of the intervals between murders (step length) follows a power law with the exponent of 1.4. We propose a model according to which the serial killer commits murders when neuronal excitation in his brain exceeds certain threshold. We model this neural activity as a branching process, which in turn is approximated by a random walk. As the distribution of the random walk return times is a power law with the exponent 1.5, the distribution of the inter-murder intervals is thus explained. We illustrate analytical results by numerical simulation. Time pattern activity data from two other serial killers further substantiate our analysis. PMID:24721476

Stochastic modeling of a serial killer.

PubMed

Simkin, M V; Roychowdhury, V P

2014-08-21

We analyze the time pattern of the activity of a serial killer, who during 12 years had murdered 53 people. The plot of the cumulative number of murders as a function of time is of "Devil's staircase" type. The distribution of the intervals between murders (step length) follows a power law with the exponent of 1.4. We propose a model according to which the serial killer commits murders when neuronal excitation in his brain exceeds certain threshold. We model this neural activity as a branching process, which in turn is approximated by a random walk. As the distribution of the random walk return times is a power law with the exponent 1.5, the distribution of the inter-murder intervals is thus explained. We illustrate analytical results by numerical simulation. Time pattern activity data from two other serial killers further substantiate our analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a real time activity monitoring Android application utilizing SmartStep.

PubMed

Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward

2016-08-01

Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.

Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community

PubMed Central

Taylor, Sarah L.; Curry, Whitney B.; Knowles, Zoe R.; Noonan, Robert J.; McGrane, Bronagh; Fairclough, Stuart J.

2017-01-01

Background: Schools have been identified as important settings for health promotion through physical activity participation, particularly as children are insufficiently active for health. The aim of this study was to investigate the child and school-level influences on children′s physical activity levels and sedentary time during school hours in a sample of children from a low-income community; Methods: One hundred and eighty-six children (110 boys) aged 9–10 years wore accelerometers for 7 days, with 169 meeting the inclusion criteria of 16 h∙day−1 for a minimum of three week days. Multilevel prediction models were constructed to identify significant predictors of sedentary time, light, and moderate to vigorous physical activity during school hour segments. Child-level predictors (sex, weight status, maturity offset, cardiorespiratory fitness, physical activity self-efficacy, physical activity enjoyment) and school-level predictors (number on roll, playground area, provision score) were entered into the models; Results: Maturity offset, fitness, weight status, waist circumference-to-height ratio, sedentary time, moderate to vigorous physical activity, number of children on roll and playground area significantly predicted physical activity and sedentary time; Conclusions: Research should move towards considering context-specific physical activity and its correlates to better inform intervention strategies. PMID:28509887

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

PubMed

Qi, Jin; Yang, Zhiyong

2014-01-01

Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

System modeling of the Thirty Meter Telescope alignment and phasing system

NASA Astrophysics Data System (ADS)

Dekens, Frank G.; Seo, Byoung-Joon; Troy, Mitchell

2014-08-01

We have developed a system model using the System Modeling Language (SysML) for the Alignment and Phasing System (APS) on the Thirty Meter Telescope (TMT). APS is a Shack-Hartmann wave-front sensor that will be used to measure the alignment and phasing of the primary mirror segments, and the alignment of the secondary and tertiary mirrors. The APS system model contains the ow-down of the Level 1 TMT requirements to APS (Level 2) requirements, and from there to the APS sub-systems (Level 3) requirements. The model also contains the operating modes and scenarios for various activities, such as maintenance alignment, post-segment exchange alignment, and calibration activities. The requirements ow-down is captured in SysML requirements diagrams, and we describe the process of maintaining the DOORS database as the single-source-of-truth for requirements, while using the SysML model to capture the logic and notes associated with the ow-down. We also use the system model to capture any needed communications from APS to other TMT systems, and between the APS sub-systems. The operations are modeled using SysML activity diagrams, and will be used to specify the APS interface documents. The modeling tool can simulate the top level activities to produce sequence diagrams, which contain all the communications between the system and subsystem needed for that activity. By adding time estimates for the lowest level APS activities, a robust estimate for the total time on-sky that APS requires to align and phase the telescope can be obtained. This estimate will be used to verify that the time APS requires on-sky meets the Level 1 TMT requirements.

Dynamic Transcription Factor Networks in Epithelial-Mesenchymal Transition in Breast Cancer Models

PubMed Central

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J.; Shin, Seungjin; Jeruss, Jacqueline S.; Shea, Lonnie D.

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy. PMID:23593114

Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

PubMed

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

CRAFFT: An Activity Prediction Model based on Bayesian Networks

PubMed Central

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

CRAFFT: An Activity Prediction Model based on Bayesian Networks.

PubMed

Nazerfard, Ehsan; Cook, Diane J

2015-04-01

Recent advances in the areas of pervasive computing, data mining, and machine learning offer unique opportunities to provide health monitoring and assistance for individuals facing difficulties to live independently in their homes. Several components have to work together to provide health monitoring for smart home residents including, but not limited to, activity recognition, activity discovery, activity prediction, and prompting system. Compared to the significant research done to discover and recognize activities, less attention has been given to predict the future activities that the resident is likely to perform. Activity prediction components can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-aware rules to prompt individuals to initiate important activities. In this paper, we propose an activity prediction model using Bayesian networks together with a novel two-step inference process to predict both the next activity features and the next activity label. We also propose an approach to predict the start time of the next activity which is based on modeling the relative start time of the predicted activity using the continuous normal distribution and outlier detection. To validate our proposed models, we used real data collected from physical smart environments.

Using avian radar to examine relationships among avian activity, bird strikes, and meteorological factors

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Halstead, Brian J.; Fleskes, Joseph P.; Laughlin, James A.

2011-01-01

Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24-hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fit. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.

Task allocation model for minimization of completion time in distributed computer systems

NASA Astrophysics Data System (ADS)

Wang, Jai-Ping; Steidley, Carl W.

1993-08-01

A task in a distributed computing system consists of a set of related modules. Each of the modules will execute on one of the processors of the system and communicate with some other modules. In addition, precedence relationships may exist among the modules. Task allocation is an essential activity in distributed-software design. This activity is of importance to all phases of the development of a distributed system. This paper establishes task completion-time models and task allocation models for minimizing task completion time. Current work in this area is either at the experimental level or without the consideration of precedence relationships among modules. The development of mathematical models for the computation of task completion time and task allocation will benefit many real-time computer applications such as radar systems, navigation systems, industrial process control systems, image processing systems, and artificial intelligence oriented systems.

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

Active learning reduces annotation time for clinical concept extraction.

PubMed

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2017-10-01

To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

Parametric models to relate spike train and LFP dynamics with neural information processing.

PubMed

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

Using a Time-Driven Activity-Based Costing Model To Determine the Actual Cost of Services Provided by a Transgenic Core.

PubMed

Gerwin, Philip M; Norinsky, Rada M; Tolwani, Ravi J

2018-03-01

Laboratory animal programs and core laboratories often set service rates based on cost estimates. However, actual costs may be unknown, and service rates may not reflect the actual cost of services. Accurately evaluating the actual costs of services can be challenging and time-consuming. We used a time-driven activity-based costing (ABC) model to determine the cost of services provided by a resource laboratory at our institution. The time-driven approach is a more efficient approach to calculating costs than using a traditional ABC model. We calculated only 2 parameters: the time required to perform an activity and the unit cost of the activity based on employee cost. This method allowed us to rapidly and accurately calculate the actual cost of services provided, including microinjection of a DNA construct, microinjection of embryonic stem cells, embryo transfer, and in vitro fertilization. We successfully implemented a time-driven ABC model to evaluate the cost of these services and the capacity of labor used to deliver them. We determined how actual costs compared with current service rates. In addition, we determined that the labor supplied to conduct all services (10,645 min/wk) exceeded the practical labor capacity (8400 min/wk), indicating that the laboratory team was highly efficient and that additional labor capacity was needed to prevent overloading of the current team. Importantly, this time-driven ABC approach allowed us to establish a baseline model that can easily be updated to reflect operational changes or changes in labor costs. We demonstrated that a time-driven ABC model is a powerful management tool that can be applied to other core facilities as well as to entire animal programs, providing valuable information that can be used to set rates based on the actual cost of services and to improve operating efficiency.

Hands On Earth Science.

ERIC Educational Resources Information Center

Weisgarber, Sherry L.; Van Doren, Lisa; Hackathorn, Merrianne; Hannibal, Joseph T.; Hansgen, Richard

This publication is a collection of 13 hands-on activities that focus on earth science-related activities and involve students in learning about growing crystals, tectonics, fossils, rock and minerals, modeling Ohio geology, geologic time, determining true north, and constructing scale-models of the Earth-moon system. Each activity contains…

Generation of skeletal mechanism by means of projected entropy participation indices

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Valorani, Mauro; Ciottoli, Pietro Paolo; Galassi, Riccardo Malpica

2017-11-01

When the dynamics of reactive systems develop very-slow and very-fast time scales separated by a range of active time scales, with gaps in the fast/active and slow/active time scales, then it is possible to achieve multi-scale adaptive model reduction along-with the integration of the ODEs using the G-Scheme. The scheme assumes that the dynamics is decomposed into active, slow, fast, and invariant subspaces. We derive expressions that establish a direct link between time scales and entropy production by using estimates provided by the G-Scheme. To calculate the contribution to entropy production, we resort to a standard model of a constant pressure, adiabatic, batch reactor, where the mixture temperature of the reactants is initially set above the auto-ignition temperature. Numerical experiments show that the contribution to entropy production of the fast subspace is of the same magnitude as the error threshold chosen for the identification of the decomposition of the tangent space, and the contribution of the slow subspace is generally much smaller than that of the active subspace. The information on entropy production associated with reactions within each subspace is used to define an entropy participation index that is subsequently utilized for model reduction.

Should precipitation influence dust emission in global dust models?

NASA Astrophysics Data System (ADS)

Okin, Gregory

2016-04-01

Soil moisture modulates the threshold shear stress required to initiate aeolian transport and dust emission. Most of the theoretical and laboratory work that has confirmed the impact of soil moisture has appropriately acknowledged that it is the soil moisture of a surface layer a few grain diameters thick that truly controls threshold shear velocity. Global and regional models of dust emission include the effect of soil moisture on transport threshold, but most ignore the fact that only the moisture of the very topmost "active layer" matters. The soil moisture in the active layer can differ greatly from that integrated through the top 2, 5, 10, or 100 cm (surface layers used by various global models) because the top 2 mm of heavy texture soils dries within ~1/2 day while sandy soils dry within less than 2 hours. Thus, in drylands where dust emission occurs, it is likely that this top layer is drier than the underlying soil in the days and weeks after rain. This paper explores, globally, the time between rain events in relation to the time for the active layer to dry and the timing of high wind events. This analysis is carried out using the same coarse reanalyses used in global dust models and is intended to inform the soil moisture controls in these models. The results of this analysis indicate that the timing between events is, in almost all dust-producing areas, significantly longer than the drying time of the active layer, even when considering soil texture differences. Further, the analysis shows that the probability of a high wind event during the period after a rain where the surface is wet is small. Therefore, in coarse global models, there is little reason to include rain-derived soil moisture in the modeling scheme.

A biophysical model examining the role of low-voltage-activated potassium currents in shaping the responses of vestibular ganglion neurons.

PubMed

Hight, Ariel E; Kalluri, Radha

2016-08-01

The vestibular nerve is characterized by two broad groups of neurons that differ in the timing of their interspike intervals; some fire at highly regular intervals, whereas others fire at highly irregular intervals. Heterogeneity in ion channel properties has been proposed as shaping these firing patterns (Highstein SM, Politoff AL. Brain Res 150: 182-187, 1978; Smith CE, Goldberg JM. Biol Cybern 54: 41-51, 1986). Kalluri et al. (J Neurophysiol 104: 2034-2051, 2010) proposed that regularity is controlled by the density of low-voltage-activated potassium currents (IKL). To examine the impact of IKL on spike timing regularity, we implemented a single-compartment model with three conductances known to be present in the vestibular ganglion: transient sodium (gNa), low-voltage-activated potassium (gKL), and high-voltage-activated potassium (gKH). Consistent with in vitro observations, removing gKL depolarized resting potential, increased input resistance and membrane time constant, and converted current step-evoked firing patterns from transient (1 spike at current onset) to sustained (many spikes). Modeled neurons were driven with a time-varying synaptic conductance that captured the random arrival times and amplitudes of glutamate-driven synaptic events. In the presence of gKL, spiking occurred only in response to large events with fast onsets. Models without gKL exhibited greater integration by responding to the superposition of rapidly arriving events. Three synaptic conductance were modeled, each with different kinetics to represent a variety of different synaptic processes. In response to all three types of synaptic conductance, models containing gKL produced spike trains with irregular interspike intervals. Only models lacking gKL when driven by rapidly arriving small excitatory postsynaptic currents were capable of generating regular spiking. Copyright © 2016 the American Physiological Society.

The examination of headache activity using time-series research designs.

PubMed

Houle, Timothy T; Remble, Thomas A; Houle, Thomas A

2005-05-01

The majority of research conducted on headache has utilized cross-sectional designs which preclude the examination of dynamic factors and principally rely on group-level effects. The present article describes the application of an individual-oriented process model using time-series analytical techniques. The blending of a time-series approach with an interactive process model allows consideration of the relationships of intra-individual dynamic processes, while not precluding the researcher to examine inter-individual differences. The authors explore the nature of time-series data and present two necessary assumptions underlying the time-series approach. The concept of shock and its contribution to headache activity is also presented. The time-series approach is not without its problems and two such problems are specifically reported: autocorrelation and the distribution of daily observations. The article concludes with the presentation of several analytical techniques suited to examine the time-series interactive process model.

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…

Self-expansion and flow in couples' momentary experiences: an experience sampling study.

PubMed

Graham, James M

2008-09-01

The self-expansion model of close relationships posits that when couples engage in exciting and activating conjoint activities, they feel connected with their partners and more satisfied with their relationships. In the present study, the experience sampling method was used to examine the predictions of the self-expansion model in couples' momentary experiences. In addition, the author generated several new hypotheses by integrating the self-expansion model with existing research on flow. Over the course of 1 week, 20 couples were signaled at quasi-random intervals to provide data on 1,265 unique experiences. The results suggest that the level of activation experienced during an activity was positively related to experience-level relationship quality. This relationship was consistent across free-time and nonfree-time contexts and was mediated by positive affect. Activation was not found to predict later affect unless the level of activation exceeded what was typical for the individual. Also examined was the influence of interpersonal context and activity type on self-expansion. The results support the self-expansion model and suggest that it could be considered under the broader umbrella of flow.

Investigating the American Time Use Survey from an exposure modeling perspective.

PubMed

George, Barbara Jane; McCurdy, Thomas

2011-01-01

This paper describes an evaluation of the US 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 activities they undertake in those locations. The data are reported as a series of sequential activities over a 24-h time period--a "diary day"--starting at 0400 hours. Between 12,000 and 13,000 surveys are obtained each year and the Bureau has plans to continue ATUS for the foreseeable future. The ATUS already has about 73,000 diary days of data, more than twice as many as that which currently exists in the US Environmental Protection Agency's (EPA) "Consolidated Human Activity Database" (CHAD) that the Agency uses for exposure modeling purposes. There are limitations for using ATUS in modeling human exposures to environmental pollutants. The ATUS does not report the location for a number of activities regarded as "personal." For 2006, personal activities with missing location information totaled 572 min/day, on average, for survey participants: about 40% of their day. Another limitation is that ATUS does not distinguish between indoor and outdoor activities at home, two of the traditional locational demarcations used in human exposure modeling. This lack of information affects exposure estimates to both indoor and outdoor air pollutants and potentially affects non-dietary ingestion estimates for children, which can vary widely depending on whether or not a child is indoors. Finally, a detailed analysis of the work travel activity in a subsample from ATUS 2006 indicates that the coding scheme is not fully consistent with a CHAD-based exposure modeling approach. For ATUS respondents in this subsample who reported work as an activity, roughly 48% of their days were missing work travel at one or both ends of the work shift or reported within work-shift travel inconsistently. An extensive effort would be needed to recode work travel data from ATUS for EPA's exposure modeling purposes.

Reading Time as Evidence for Mental Models in Understanding Physics

NASA Astrophysics Data System (ADS)

Brookes, David T.; Mestre, José; Stine-Morrow, Elizabeth A. L.

2007-11-01

We present results of a reading study that show the usefulness of probing physics students' cognitive processing by measuring reading time. According to contemporary discourse theory, when people read a text, a network of associated inferences is activated to create a mental model. If the reader encounters an idea in the text that conflicts with existing knowledge, the construction of a coherent mental model is disrupted and reading times are prolonged, as measured using a simple self-paced reading paradigm. We used this effect to study how "non-Newtonian" and "Newtonian" students create mental models of conceptual systems in physics as they read texts related to the ideas of Newton's third law, energy, and momentum. We found significant effects of prior knowledge state on patterns of reading time, suggesting that students attempt to actively integrate physics texts with their existing knowledge.

Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data

PubMed Central

Wu, Lun; Zhi, Ye; Sui, Zhengwei; Liu, Yu

2014-01-01

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. PMID:24824892

Maximum height and minimum time vertical jumping.

PubMed

Domire, Zachary J; Challis, John H

2015-08-20

The performance criterion in maximum vertical jumping has typically been assumed to simply raise the center of mass as high as possible. In many sporting activities minimizing movement time during the jump is likely also critical to successful performance. The purpose of this study was to examine maximum height jumps performed while minimizing jump time. A direct dynamics model was used to examine squat jump performance, with dual performance criteria: maximize jump height and minimize jump time. The muscle model had activation dynamics, force-length, force-velocity properties, and a series of elastic component representing the tendon. The simulations were run in two modes. In Mode 1 the model was placed in a fixed initial position. In Mode 2 the simulation model selected the initial squat configuration as well as the sequence of muscle activations. The inclusion of time as a factor in Mode 1 simulations resulted in a small decrease in jump height and moderate time savings. The improvement in time was mostly accomplished by taking off from a less extended position. In Mode 2 simulations, more substantial time savings could be achieved by beginning the jump in a more upright posture. However, when time was weighted more heavily in these simulations, there was a more substantial reduction in jump height. Future work is needed to examine the implications for countermovement jumping and to examine the possibility of minimizing movement time as part of the control scheme even when the task is to jump maximally. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of queueing models to multiprogrammed computer systems operating in a time-critical environment

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.

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.

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

PubMed

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Simultaneous determination of interfacial energy and growth activation energy from induction time measurements

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.

Effects of tour boats on dolphin activity examined with sensitivity analysis of Markov chains.

PubMed

Dans, Silvana Laura; Degrati, Mariana; Pedraza, Susana Noemí; Crespo, Enrique Alberto

2012-08-01

In Patagonia, Argentina, watching dolphins, especially dusky dolphins (Lagenorhynchus obscurus), is a new tourist activity. Feeding time decreases and time to return to feeding after feeding is abandoned and time it takes a group of dolphins to feed increase in the presence of boats. Such effects on feeding behavior may exert energetic costs on dolphins and thus reduce an individual's survival and reproductive capacity or maybe associated with shifts in distribution. We sought to predict which behavioral changes modify the activity pattern of dolphins the most. We modeled behavioral sequences of dusky dolphins with Markov chains. We calculated transition probabilities from one activity to another and arranged them in a stochastic matrix model. The proportion of time dolphins dedicated to a given activity (activity budget) and the time it took a dolphin to resume that activity after it had been abandoned (recurrence time) were calculated. We used a sensitivity analysis of Markov chains to calculate the sensitivity of the time budget and the activity-resumption time to changes in behavioral transition probabilities. Feeding-time budget was most sensitive to changes in the probability of dolphins switching from traveling to feeding behavior and of maintaining feeding behavior. Thus, an increase in these probabilities would be associated with the largest reduction in the time dedicated to feeding. A reduction in the probability of changing from traveling to feeding would also be associated with the largest increases in the time it takes dolphins to resume feeding. To approach dolphins when they are traveling would not affect behavior less because presence of the boat may keep dolphins from returning to feeding. Our results may help operators of dolphin-watching vessels minimize negative effects on dolphins. ©2012 Society for Conservation Biology.

INTEGRATED PROBABILISTIC AND DETERMINISTIC MODELING TECHNIQUES IN ESTIMATING EXPOSURE TO WATER-BORNE CONTAMINANTS: PART 2 PHARMACOKINETIC MODELING

EPA Science Inventory

The Total Exposure Model (TEM) uses deterministic and stochastic methods to estimate the exposure of a person performing daily activities of eating, drinking, showering, and bathing. There were 250 time histories generated, by subject with activities, for the three exposure ro...

Carbon transfer dynamics from bomb- 14C and δ 13C time series of a laminated stalagmite from SW France - modelling and comparison with other stalagmite records

NASA Astrophysics Data System (ADS)

Genty, Dominique; Massault, Marc

1999-05-01

Twenty-two AMS 14C measurements have been made on a modern stalagmite from SW France in order to reconstruct the 14C activity history of the calcite deposit. Annual growth laminae provides a chronology up to 1919 A.D. Results show that the stalagmite 14C activity time series is sensitive to modern atmosphere 14C activity changes such as those produced by the nuclear weapon tests. The comparison between the two 14C time series shows that the stalagmite time series is damped: its amplitude variation between pre-bomb and post-bomb values is 75% less and the time delay between the two time series peaks is 16 years ±3. A model is developed using atmosphere 14C and 13C data, fractionation processes and three soil organic matter components whose mean turnover rates are different. The linear correlation coefficient between modeled and measured activities is 0.99. These results, combined with two other stalagmite 14C time series already published and compared with local vegetation and climate, demonstrate that most of the carbon transfer dynamics are controlled in the soil by soil organic matter degradation rates. Where vegetation produces debris whose degradation is slow, the fraction of old carbon injected in the system increases, the observed 14C time series is much more damped and lag time longer than that observed under grassland sites. The same mixing model applied on the 13C shows a good agreement ( R2 = 0.78) between modeled and measured stalagmite δ 13C and demonstrates that the Suess Effect due to fossil fuel combustion in the atmosphere is recorded in the stalagmite but with a damped effect due to SOM degradation rate. The different sources of dead carbon in the seepage water are calculated and discussed.

Life span in online communities

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kosiński, R. A.

2010-12-01

Recently online communities have attracted great interest and have become an important medium of information exchange between users. The aim of this work is to introduce a simple model of the evolution of online communities. This model describes (a) the time evolution of users’ activity in a web service, e.g., the time evolution of the number of online friends or written posts, (b) the time evolution of the degree distribution of a social network, and (c) the time evolution of the number of active users of a web service. In the second part of the paper we investigate the influence of the users’ lifespan (i.e., the total time in which they are active in an online community) on the process of rumor propagation in evolving social networks. Viral marketing is an important application of such method of information propagation.

Life span in online communities.

PubMed

Grabowski, A; Kosiński, R A

2010-12-01

Recently online communities have attracted great interest and have become an important medium of information exchange between users. The aim of this work is to introduce a simple model of the evolution of online communities. This model describes (a) the time evolution of users' activity in a web service, e.g., the time evolution of the number of online friends or written posts, (b) the time evolution of the degree distribution of a social network, and (c) the time evolution of the number of active users of a web service. In the second part of the paper we investigate the influence of the users' lifespan (i.e., the total time in which they are active in an online community) on the process of rumor propagation in evolving social networks. Viral marketing is an important application of such method of information propagation.

A Scalable Heuristic for Viral Marketing Under the Tipping Model

DTIC Science & Technology

2013-09-01

removal of high-degree nodes. The rest of the paper is organized as follows. In Section 2, we provide formal definitions of the tipping model. This is...that must be activated for it to become activate as well. A Scalable Heuristic for Viral Marketing Under the Tipping Model 3 Definition 1 (Threshold...returns a set of active nodes after one time step. Definition 2 (Activation Function) Given a threshold function, θ, an ac- tivation function Aθ maps

Surrogate screening models for the low physical activity criterion of frailty.

PubMed

Eckel, Sandrah P; Bandeen-Roche, Karen; Chaves, Paulo H M; Fried, Linda P; Louis, Thomas A

2011-06-01

Low physical activity, one of five criteria in a validated clinical phenotype of frailty, is assessed by a standardized, semiquantitative questionnaire on up to 20 leisure time activities. Because of the time demanded to collect the interview data, it has been challenging to translate to studies other than the Cardiovascular Health Study (CHS), for which it was developed. Considering subsets of activities, we identified and evaluated streamlined surrogate assessment methods and compared them to one implemented in the Women's Health and Aging Study (WHAS). Using data on men and women ages 65 and older from the CHS, we applied logistic regression models to rank activities by "relative influence" in predicting low physical activity.We considered subsets of the most influential activities as inputs to potential surrogate models (logistic regressions). We evaluated predictive accuracy and predictive validity using the area under receiver operating characteristic curves and assessed criterion validity using proportional hazards models relating frailty status (defined using the surrogate) to mortality. Walking for exercise and moderately strenuous household chores were highly influential for both genders. Women required fewer activities than men for accurate classification. The WHAS model (8 CHS activities) was an effective surrogate, but a surrogate using 6 activities (walking, chores, gardening, general exercise, mowing and golfing) was also highly predictive. We recommend a 6 activity questionnaire to assess physical activity for men and women. If efficiency is essential and the study involves only women, fewer activities can be included.

Global empirical model of TEC response to geomagnetic activity

NASA Astrophysics Data System (ADS)

Mukhtarov, P.; Andonov, B.; Pancheva, D.

2013-10-01

global total electron content (TEC) model response to geomagnetic activity described by the Kp index is built by using the Center for Orbit Determination of Europe (CODE) TEC data for a full 13 years, January 1999 to December 2011. The model describes the most probable spatial distribution and temporal variability of the geomagnetically forced TEC anomalies assuming that these anomalies at a given modified dip latitude depend mainly on the Kp index, local time (LT), and longitude. The geomagnetic anomalies are expressed by the relative deviation of TEC from its 15 day median and are denoted as rTEC. The rTEC response to the geomagnetic activity is presented by a sum of two responses with different time delay constants and different signs of the cross-correlation function. It has been found that the mean dependence of rTEC on Kp index can be expressed by a cubic function. The LT dependence of rTEC is described by Fourier time series which includes the contribution of four diurnal components with periods 24, 12, 8, and 6 h. The rTEC dependence on longitude is presented by Fourier series which includes the contribution of zonal waves with zonal wave numbers up to 6. In order to demonstrate how the model is able to reproduce the rTEC response to geomagnetic activity, three geomagnetic storms at different seasons and solar activity conditions are presented. The model residuals clearly reveal two types of the model deviation from the data: some underestimation of the largest TEC response to the geomagnetic activity and randomly distributed errors which are the data noise or anomalies generated by other sources. The presented TEC model fits to the CODE TEC input data with small negative bias of -0.204, root mean squares error RMSE = 4.592, and standard deviation error STDE = 4.588. The model offers TEC maps which depend on geographic coordinates (5° × 5° in latitude and longitude) and universal time (UT) at given geomagnetic activity and day of the year. It could be used for both science and possible service (nowcasting and short-term prediction); for the latter, a detailed validation of the model at different geophysical conditions has to be performed in order to clarify the model predicting quality.

Prediction of Therapy Tumor-Absorbed Dose Estimates in I-131 Radioimmunotherapy Using Tracer Data Via a Mixed-Model Fit to Time Activity

PubMed Central

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

Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models

NASA Astrophysics Data System (ADS)

Beckx, Carolien; Int Panis, Luc; Uljee, Inge; Arentze, Theo; Janssens, Davy; Wets, Geert

Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated model chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport model) and about ambient pollutant concentrations (obtained from a dispersion model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all models under consideration. The evaluation of population level exposure in The Netherlands to NO 2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO 2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification.

The biomechanics of an overarm throwing task: a simulation model examination of optimal timing of muscle activations.

PubMed

Chowdhary, A G; Challis, J H

2001-07-07

A series of overarm throws, constrained to the parasagittal plane, were simulated using a muscle model actuated two-segment model representing the forearm and hand plus projectile. The parameters defining the modeled muscles and the anthropometry of the two-segment models were specific to the two young male subjects. All simulations commenced from a position of full elbow flexion and full wrist extension. The study was designed to elucidate the optimal inter-muscular coordination strategies for throwing projectiles to achieve maximum range, as well as maximum projectile kinetic energy for a variety of projectile masses. A proximal to distal (PD) sequence of muscle activations was seen in many of the simulated throws but not all. Under certain conditions moment reversal produced a longer throw and greater projectile energy, and deactivation of the muscles resulted in increased projectile energy. Therefore, simple timing of muscle activation does not fully describe the patterns of muscle recruitment which can produce optimal throws. The models of the two subjects required different timings of muscle activations, and for some of the tasks used different coordination patterns. Optimal strategies were found to vary with the mass of the projectile, the anthropometry and the muscle characteristics of the subjects modeled. The tasks examined were relatively simple, but basic rules for coordinating these tasks were not evident. Copyright 2001 Academic Press.

Psychosocial work conditions, unemployment, and leisure-time physical activity: a population-based study.

PubMed

Ali, Sadiq Mohammad; Lindström, Martin

2006-01-01

To investigate the association between psychosocial work conditions and unemployment, and low leisure-time physical activity. The 2000 public health survey in Scania is a cross-sectional postal questionnaire study with a 59% participation rate. A total of 5,180 persons aged 18-64 years who belonged to the workforce and the unemployed were included in this study. Logistic regression models were used to investigate the associations between psychosocial factors at work and unemployment, and low leisure-time physical activity. Psychosocial conditions at work were defined according to the Karasek-Theorell demand-control/decision latitudes into relaxed, active, passive, and job strain categories. The multivariate analyses included age, country of birth, education, economic stress, and social participation. In total, 16.1% of men and 14.8% of women had low leisure-time physical activity. The job strain (high demands/low control) and unemployed categories had significantly higher odds ratios of low leisure-time physical activity among both men and women compared with the relaxed (low demands/high control) reference category. However, the significant differences between the job strain, the unemployed, and the relaxed categories disappeared in the multivariate models. Respondents with job strain or unemployment have significantly higher odds ratios of low leisure-time physical activity than the relaxed category. However, after adjustments for education in particular the differences disappear. Nevertheless, the results suggest that the association between psychosocial work conditions, which are often dependent on education, and leisure-time physical activity may be interesting to study in more detail.

Role of hepsin in factor VII activation in zebrafish.

PubMed

Khandekar, Gauri; Jagadeeswaran, Pudur

2014-01-01

Factor VII, the initiator of the extrinsic coagulation cascade, circulates in human plasma mainly in its zymogen form, factor VII and in small amounts in its activated form, factor VIIa. However, the mechanism of initial generation of factor VIIa is not known despite intensive research using currently available model systems. Earlier findings suggested serine proteases factor VII activating protease and hepsin play a role in activating factor VII, however, it has remained controversial. In this paper we estimated the levels of factor VIIa and factor VII for the first time in zebrafish adult population and also reevaluated the role of the above two serine proteases in activating factor VII in vivo using zebrafish as a model system. Knockdown of factor VII activating protease and hepsin was performed followed by assaying for their effect on factor VIIa concentration and extrinsic coagulation as measured by the kinetic prothrombin time. Factor VII activating protease knockdown showed no change in kinetic prothrombin time and no effect on factor VIIa levels while hepsin knockdown increased the kinetic prothrombin time and significantly reduced the factor VIIa plasma levels. Our results thus indicate that hepsin plays a physiologically important role in factor VII activation and hemostasis in zebrafish. © 2013.

Relationship of sitting time and physical activity with non-alcoholic fatty liver disease.

PubMed

Ryu, Seungho; Chang, Yoosoo; Jung, Hyun-Suk; Yun, Kyung Eun; Kwon, Min-Jung; Choi, Yuni; Kim, Chan-Won; Cho, Juhee; Suh, Byung-Seong; Cho, Yong Kyun; Chung, Eun Chul; Shin, Hocheol; Kim, Yeon Soo

2015-11-01

The goal of this study was to examine the association of sitting time and physical activity level with non-alcoholic fatty liver disease (NAFLD) in Korean men and women and to explore whether any observed associations were mediated by adiposity. A cross-sectional study was performed on 139,056 Koreans, who underwent a health examination between March 2011 and December 2013. Physical activity level and sitting time were assessed using the validated Korean version of the international Physical Activity Questionnaire Short Form. The presence of fatty liver was determined using ultrasonographic findings. Poisson regression models with robust variance were used to evaluate the association of sitting time and physical activity level with NAFLD. Of the 139,056 subjects, 39,257 had NAFLD. In a multivariable-adjusted model, both prolonged sitting time and decreased physical activity level were independently associated with increasing prevalence of NAFLD. The prevalence ratios (95% CIs) for NAFLD comparing 5-9 and ⩾10 h/day sitting time to <5h/day were 1.04 (1.02-1.07) and 1.09 (1.06-1.11), respectively (p for trend <0.001). These associations were still observed in subjects with BMI <23 kg/m(2). The prevalence ratios (95% CIs) for NAFLD comparing minimally active and health-enhancing physically active groups to the inactive group were 0.94 (0.92-0.95) and 0.80 (0.78-0.82), respectively (p for trend <0.001). Prolonged sitting time and decreased physical activity level were positively associated with the prevalence of NAFLD in a large sample of middle-aged Koreans, supporting the importance of reducing time spent sitting in addition to promoting physical activity. Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Is fatigue after work a barrier for leisure-time physical activity? Cross-sectional study among 10,000 adults from the general working population.

PubMed

Bláfoss, Rúni; Micheletti, Jéssica K; Sundstrup, Emil; Jakobsen, Markus D; Bay, Hans; Andersen, Lars L

2018-04-01

In spite of the many health-related benefits of regular physical activity, fatiguing work may be a barrier to performing leisure-time physical activity. This study investigates the association between work-related fatigue and the duration of low- and high-intensity leisure-time physical activity in workers with sedentary and physically demanding jobs. From the 2010 round of the Danish Work Environment Cohort Study, currently employed wage earners from the general working population ( N=10,427) replied to questions about work-related fatigue (predictor) and duration of low- and high-intensity leisure-time physical activity (outcome). Associations were modelled using general linear models controlling for various confounders. Among workers with physically demanding jobs, higher levels of work-related fatigue were associated with gradually lower levels of leisure-time physical activity - for low, moderate and high levels of work-related fatigue the duration of high-intensity leisure-time physical activity was 133 (95% confidence interval (CI) 127-178), 134 (95% CI 109-160) and 113 (95% CI 86-140) min per week, respectively (trend test p<0.001). The duration of high-intensity leisure-time physical activity was lower among older workers (≥50 years) compared to younger workers (<50 years) (132 ± 126 vs 168 ± 150 min per week) ( p<0.0001). The duration of high-intensity leisure-time physical activity gradually decreases with increased work-related fatigue in workers with physically demanding jobs. Older workers perform less high-intensity physical activity than younger workers. Workplaces should consider initiatives to allow workers with physically demanding jobs and older workers to perform physical exercise during working hours and thereby increase physical capacity to meet the job demands.

Objectively measured physical activity and sedentary time of breast cancer survivors, and associations with adiposity: findings from NHANES (2003-2006).

PubMed

Lynch, Brigid M; Dunstan, David W; Healy, Genevieve N; Winkler, Elisabeth; Eakin, Elizabeth; Owen, Neville

2010-02-01

Obesity and physical inactivity are poor prognostic indicators for breast cancer. Studies to date have relied on self-report measures of physical activity, which tend mainly to assess moderate-to-vigorous intensity leisure-time physical activity. We report the cross-sectional associations of objectively assessed physical activity and sedentary time with adiposity in a sample of breast cancer survivors from the United States. One hundred and eleven women from the National Health and Nutrition Examination Survey (NHANES) 2003-2004 and 2005-2006 reported a history of breast cancer. Participants wore an accelerometer for 7 days, and activity levels were summarized as moderate-to-vigorous intensity (accelerometer counts/min > or =1,952), light intensity (counts/min 100-1,951), and sedentary time (counts/min <100). Anthropometric measures were taken by study staff at examination centers. Participants spent the majority of their day in sedentary time (66%) or in light intensity activities (33%). Log moderate-to-vigorous intensity physical activity was negatively associated with adiposity (waist circumference beta = -9.805 [95% CI: -15.836, -3.775]; BMI beta = -3.576 [95% CI: -6.687, -0.464]). Light intensity physical activity was negatively associated with adiposity; however, the fully adjusted models did not retain statistical significance. Similarly, sedentary time was positively associated with adiposity, but the fully adjusted models were not statistically significant. This is the first study to describe the objectively assessed physical activity and sedentary time of breast cancer survivors. Increasing moderate-to-vigorous and light intensity physical activity, and decreasing sedentary time, may assist with weight management and improve other metabolic health outcomes for breast cancer survivors.

Model- based filtering for artifact and noise suppression with state estimation for electrodermal activity measurements in real time.

PubMed

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.

Outdoor time, physical activity, sedentary time, and health indicators at ages 7 to 14: 2012/2013 Canadian Health Measures Survey.

PubMed

Larouche, Richard; Garriguet, Didier; Gunnell, Katie E; Goldfield, Gary S; Tremblay, Mark S

2016-09-21

International data show that the majority of children and youth are not sufficiently active. According to recent research, children who spend more time outdoors accumulate more daily moderate-to-vigorous physical activity and engage in less sedentary behaviour. However, the generalizability of these findings is uncertain, and few studies investigated whether outdoor time is associated with other physical and psychosocial health indicators. This study examined associations between outdoor time and measures of physical activity, sedentary time, and physical and psychosocial health in a nationally representative sample of 7-to-14-year-olds (n = 1,159) who participated in the 2012/2013 Canadian Health Measures Survey. Physical activity and sedentary time were measured with Actical accelerometers. Direct measures of height, weight, waist circumference, grip strength, blood pressure, cholesterol, and glycohemoglobin were obtained. The Strengths and Difficulties Questionnaire was used to assess psychosocial health. Relationships between outdoor time and physical health measures were examined with multi-variable linear regression models adjusted for age, sex, parental education, and household income. Logistic regression models controlling for the same variables were used for psychosocial health. Each additional hour spent outdoors per day was associated with 7.0 more minutes of moderate-to-vigorous physical activity, 762 more steps, and 13 fewer minutes of sedentary time. As well, each hour outdoors was associated with lower odds of negative psychosocial outcomes (specifically, peer relationship problems and total difficulties score). Outdoor time was not associated with any of the measures of physical health. Children reporting more time outdoors are more active, less sedentary, and less likely to have peer relationship problems, compared with those who spend less time outdoors.

Effects of intra-aortic balloon pump timing on baroreflex activities in a closed-loop cardiovascular hybrid model.

PubMed

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. © 2012, Copyright the Authors. Artificial Organs © 2012, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Pre- and Postnatal Women's Leisure Time Physical Activity Patterns: A Multilevel Longitudinal Analysis

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…

An Empirical Model of Radiation Belt Electron Pitch Angle Distributions Based On Van Allen Probes Measurements

NASA Astrophysics Data System (ADS)

Zhao, H.; Friedel, R. H. W.; Chen, Y.; Reeves, G. D.; Baker, D. N.; Li, X.; Jaynes, A. N.; Kanekal, S. G.; Claudepierre, S. G.; Fennell, J. F.; Blake, J. B.; Spence, H. E.

2018-05-01

Based on over 4 years of Van Allen Probes measurements, an empirical model of radiation belt electron equatorial pitch angle distribution (PAD) is constructed. The model, developed by fitting electron PADs with Legendre polynomials, provides the statistical PADs as a function of L-shell (L = 1-6), magnetic local time, electron energy ( 30 keV to 5.2 MeV), and geomagnetic activity (represented by the Dst index) and is also the first empirical PAD model in the inner belt and slot region. For megaelectron volt electrons, model results show more significant day-night PAD asymmetry of electrons with higher energies and during disturbed times, which is caused by geomagnetic field configuration and flux radial gradient changes. Steeper PADs with higher fluxes around 90° pitch angle and lower fluxes at lower pitch angles for higher-energy electrons and during active times are also present, which could be due to electromagnetic ion cyclotron wave scattering. For hundreds of kiloelectron volt electrons, cap PADs are generally present in the slot region during quiet times and their energy-dependent features are consistent with hiss wave scattering, while during active times, cap PADs are less significant especially at outer part of slot region, which could be due to the complex energizing and transport processes. The 90°-minimum PADs are persistently present in the inner belt and appear in the slot region during active times, and minima at 90° pitch angle are more significant for electrons with higher energies, which could be a critical evidence in identifying the underlying physical processes responsible for the formation of 90°-minimum PADs.

Associations between home environment and after-school physical activity and sedentary time among 6th grade children

PubMed Central

Lau, Erica Y; Barr-Anderson, Daheia J; Dowda, Marsha; Forthofer, Melinda; Saunders, Ruth P; Pate, Russell R

2015-01-01

This study examined associations of various elements of the home environment with after-school physical activity and sedentary time in 671 sixth-grade children (Mage = 11.49 ± 0.5 years). Children’s after-school total physical activity (TPA), moderate-to-vigorous physical activity (MVPA) 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 TPA and negatively with after-school sedentary time in boys. Parental support was associated positively with after-school TPA 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

Frequency, Type, and Volume of Leisure-Time Physical Activity and Risk of Coronary Heart Disease in Young Women.

PubMed

Chomistek, Andrea K; Henschel, Beate; Eliassen, A Heather; Mukamal, Kenneth J; Rimm, Eric B

2016-07-26

The inverse association between physical activity and coronary heart disease (CHD) risk has primarily been shown in studies of middle-aged and older adults. Evidence for the benefits of frequency, type, and volume of leisure-time physical activity in young women is limited. We conducted a prospective analysis among 97 230 women aged 27 to 44 years at baseline in 1991. Leisure-time physical activity was assessed biennially by questionnaire. Cox proportional hazards models were used to examine the associations between physical activity frequency, type, and volume, and CHD risk. During 20 years of follow-up, we documented 544 incident CHD cases. In multivariable-adjusted models, the hazard ratio (95% confidence interval) of CHD comparing ≥30 with <1 metabolic equivalent of task-hours/wk of physical activity was 0.75 (0.57-0.99) (P, trend=0.01). Brisk walking alone was also associated with significantly lower CHD risk. Physical activity frequency was not associated with CHD risk when models also included overall activity volume. Finally, the association was not modified by body mass index (kg/m(2)) (P, interaction=0.70). Active women (≥30 metabolic equivalent of task-hours/wk) with body mass index<25 kg/m(2) had 0.52 (95% confidence interval, 0.35-0.78) times the rate of CHD in comparison with women who were obese (body mass index≥30 kg/m(2)) and inactive (physical activity <1 metabolic equivalent of task-hours/wk). These prospective data suggest that total volume of leisure-time physical activity is associated with lower risk of incident CHD among young women. In addition, this association was not modified by weight, emphasizing that it is important for normal weight, overweight, and obese women to be physically active. © 2016 American Heart Association, Inc.

Investigating the American Time Use Survey from an Exposure Modeling Perspective

EPA Science Inventory

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...

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

Antidepressant-like effects of methanol extract of Hibiscus tiliaceus flowers in mice

PubMed Central

2012-01-01

Background Hibiscus tiliaceus L. (Malvaceae) is used in postpartum disorders. Our purpose was to examine the antidepressant, anxiolytic and sedative actions of the methanol extract of H. tiliaceus flowers using animal models. Methods Adult male Swiss albino mice were treated with saline, standard drugs or methanol extract of H. tiliaceus and then subjected to behavioral tests. The forced swimming and tail suspension tests were used as predictive animal models of antidepressant activity, where the time of immobility was considered. The animals were submitted to the elevated plus-maze and ketamine-induced sleeping time to assess anxiolytic and sedative activities, respectively. Results Methanol extract of H. tiliaceus significantly decreased the duration of immobility in both animal models of antidepressant activity, forced swimming and tail suspension tests. This extract did not potentiate the effect of ketamine-induced hypnosis, as determined by the time to onset and duration of sleeping time. Conclusion Our results indicate an antidepressant-like profile of action for the extract of Hibiscus tiliaceus without sedative side effect. PMID:22494845

Recurrent dynamics in an epidemic model due to stimulated bifurcation crossovers

NASA Astrophysics Data System (ADS)

Juanico, Drandreb Earl

2015-05-01

Epidemics are known to persist in the form of recurrence cycles. Despite intervention efforts through vaccination and targeted social distancing, peaks of activity for infectious diseases like influenza reappear over time. Analysis of a stochastic model is here undertaken to explore a proposed cycle-generating mechanism - the bifurcation crossover. Time series from simulations of the model exhibit oscillations similar to the temporal signature of influenza activity. Power-spectral density indicates a resonant frequency, which corresponds to the annual seasonality of influenza in temperate zones. The study finds that intervention actions influence the extinguishability of epidemic activity. Asymptotic solution to a backward Kolmogorov equation corresponds to a mean extinction time that is a function of both intervention efficacy and population size. Intervention efficacy must be greater than a certain threshold to increase the chances of extinguishing the epidemic. Agreement of the model with several phenomenological features of epidemic cycles lends to it a tractability that may serve as early warning of imminent outbreaks.

Recurrent dynamics in an epidemic model due to stimulated bifurcation crossovers

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

Juanico, Drandreb Earl; National Institute of Physics, University of the Philippines, Diliman, Quezon City, Philippines 1101

Epidemics are known to persist in the form of recurrence cycles. Despite intervention efforts through vaccination and targeted social distancing, peaks of activity for infectious diseases like influenza reappear over time. Analysis of a stochastic model is here undertaken to explore a proposed cycle-generating mechanism – the bifurcation crossover. Time series from simulations of the model exhibit oscillations similar to the temporal signature of influenza activity. Power-spectral density indicates a resonant frequency, which corresponds to the annual seasonality of influenza in temperate zones. The study finds that intervention actions influence the extinguishability of epidemic activity. Asymptotic solution to a backwardmore » Kolmogorov equation corresponds to a mean extinction time that is a function of both intervention efficacy and population size. Intervention efficacy must be greater than a certain threshold to increase the chances of extinguishing the epidemic. Agreement of the model with several phenomenological features of epidemic cycles lends to it a tractability that may serve as early warning of imminent outbreaks.« less

Time series analysis of monthly pulpwood use in the Northeast

Treesearch

James T. Bones

1980-01-01

Time series analysis was used to develop a model that depicts pulpwood use in the Northeast. The model is useful in forecasting future pulpwood requirements (short term) or monitoring pulpwood-use activity in relation to past use patterns. The model predicted a downturn in use during 1980.

Evaluation of geomagnetic field models using magnetometer measurements for satellite attitude determination system at low earth orbits: Case studies

NASA Astrophysics Data System (ADS)

Cilden-Guler, Demet; Kaymaz, Zerefsan; Hajiyev, Chingiz

2018-01-01

In this study, different geomagnetic field models are compared in order to study the errors resulting from the representation of magnetic fields that affect the satellite attitude system. For this purpose, we used magnetometer data from two Low Earth Orbit (LEO) spacecraft and the geomagnetic models IGRF-12 (Thébault et al., 2015) and T89 (Tsyganenko, 1989) models to study the differences between the magnetic field components, strength and the angle between the predicted and observed vector magnetic fields. The comparisons were made during geomagnetically active and quiet days to see the effects of the geomagnetic storms and sub-storms on the predicted and observed magnetic fields and angles. The angles, in turn, are used to estimate the spacecraft attitude and hence, the differences between model and observations as well as between two models become important to determine and reduce the errors associated with the models under different space environment conditions. We show that the models differ from the observations even during the geomagnetically quiet times but the associated errors during the geomagnetically active times increase. We find that the T89 model gives closer predictions to the observations, especially during active times and the errors are smaller compared to the IGRF-12 model. The magnitude of the error in the angle under both environmental conditions was found to be less than 1°. For the first time, the geomagnetic models were used to address the effects of the near Earth space environment on the satellite attitude.

Predicting forest insect flight activity: A Bayesian network approach

PubMed Central

Pawson, Stephen M.; Marcot, Bruce G.; Woodberry, Owen G.

2017-01-01

Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model’s predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways. PMID:28953904

Leisure activities are linked to mental health benefits by providing time structure: comparing employed, unemployed and homemakers

PubMed Central

Goodman, William K; Geiger, Ashley M; Wolf, Jutta M

2017-01-01

Background Unemployment has consistently been linked to negative mental health outcomes, emphasising the need to characterise the underlying mechanisms. The current study aimed at testing whether compared with other employment groups, fewer leisure activities observed in unemployment may contribute to elevated risk for negative mental health via loss of time structure. Methods Depressive symptoms (Center for Epidemiologic Studies Depression), leisure activities (exercise, self-focused, social), and time structure (Time Structure Questionnaire (TSQ)) were assessed cross-sectionally in 406 participants (unemployed=155, employed=140, homemakers=111) recruited through Amazon Mechanical Turk. Results Controlling for gender and age, structural equation modelling revealed time structure partially (employed, homemakers) and fully (unemployed) mediated the relationship between leisure activities and depressive symptoms. With the exception of differential effects for structured routines, all other TSQ factors (sense of purpose, present orientation, effective organisation and persistence) contributed significantly to all models. Conclusions These findings support the idea that especially for the unemployed, leisure activities impose their mental health benefits through increasing individuals’ perception of spending their time effectively. Social leisure activities that provide a sense of daily structure may thereby be a particularly promising low-cost intervention to improve mental health in this population. PMID:27298424

Active Learning of Classification Models with Likert-Scale Feedback.

PubMed

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

Active Learning of Classification Models with Likert-Scale Feedback

PubMed Central

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone. PMID:28979827

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

PubMed

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of time and length size feature selections for human activity sequences recognition.

PubMed

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. © 2013 ISA Published by ISA All rights reserved.

The Use of Cyclone Modeling in the Erection of Precast Segmental Aerial Construction.

DTIC Science & Technology

1983-06-01

activity or completion of a work cycle within an activity. Marvin E. Mundel outlines the three methods31 as: 1. CONTINUOUS TIMING In continouous timing...technique described by Mundel and outlined in Chapter II in which actual times are recorded and durations for activities obtained later by suc- cessive...8. 28. Thomas, p. 264. 29. Thomas and Holland, p. 520. 30. Thomas and Holland, p. 521. 31. Marvin E. Mundel , Motion and Time Study, Improving

Posture and activity recognition and energy expenditure prediction in a wearable platform.

PubMed

Sazonova, Nadezhda; Browning, Raymond; Melanson, Edward; Sazonov, Edward

2014-01-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time prediction and display of time spent in various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we introduce new algorithms that require substantially less computational power. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. Use of Multinomial Logistic Discrimination (MLD) for posture and activity classification resulted in an accuracy comparable to that of Support Vector Machines (SVM) (90% vs. 95%-98%) while reducing the running time by a factor of 190 and reducing the memory requirement by a factor of 104. Per minute EE estimation using activity-specific models resulted in an accurate EE prediction (RMSE of 0.53 METs vs. RMSE of 0.69 METs using previously reported SVM-branched models). These results demonstrate successful implementation of real-time physical activity monitoring and EE prediction system on a wearable platform.

Physical activity, subjective sleep quality and time in bed do not vary by moon phase in German adolescents.

PubMed

Smith, Maia P; Standl, Marie; Schulz, Holger; Heinrich, Joachim

2017-06-01

Lunar periodicity in human biology and behaviour, particularly sleep, has been reported. However, estimated relationships vary in direction (more or less sleep with full moon) if they exist at all, and studies tend to be so small that there is potential for confounding by weekly or monthly cycles. Lunar variation in physical activity has been posited as a driver of this relationship, but is likewise not well studied. We explore the association between lunar cycle, sleep and physical activity in a population-based sample of 1411 Germans age 14-17 years (46% male). Physical activity (daily minutes moderate-to-vigorous activity) was objectively assessed by accelerometry for a total of 8832 days between 2011 and 2014. At the same time, time in bed (h) and subjective sleep quality (1-6) were diaried each morning. In models corrected for confounding, we found that lunar phase was not significantly associated with physical activity, subjective sleep quality or time in bed in either sex, regardless of season. Observed relationships varied randomly in direction between models, suggesting artefact. Thus, this large, objectively-measured and well-controlled population of adolescents displayed no lunar periodicity in objective physical activity, subjective sleep quality or time in bed. © 2016 European Sleep Research Society.

Circuit class therapy and 7-day-week therapy increase physiotherapy time, but not patient activity: early results from the CIRCIT trial.

PubMed

English, Coralie; Bernhardt, Julie; Hillier, Susan

2014-10-01

The optimum model of physiotherapy service delivery for maximizing active task practice during rehabilitation after stroke is unknown. The purpose of the study was to examine the relative effectiveness of 2 alternative models of physiotherapy service delivery against a usual care control with regard to increasing patient activity. Substudy within a large 3-armed randomized controlled trial, which compared 3 different models of physiotherapy service delivery, was provided for 4 weeks during subacute, inpatient rehabilitation (n=283). The duration of all physiotherapy sessions was recorded. In addition, 32 participants were observed at 10-minute intervals for 1 weekday and 1 weekend day between 8:00 am and 4:30 pm. At each observation, we recorded physical activity, location, and people present. Participants receiving 7-day-week and circuit class therapy received an additional 3 hours and 22 hours of physiotherapy time, respectively, when compared with usual care. Participants were standing or walking for a median of 8.2% of observations. On weekdays, circuit class therapy participants spent more time in therapy-related activity (10.2% of observations) when compared with usual care participants (6.1% of observations). On weekends, 7-day therapy participants spent more time in therapy-related activity (4.2% of observations) when compared with both usual care and circuit class therapy participants (0% of observations for both groups). Activity levels outside of therapy sessions did not differ between groups. A greater dosage of physiotherapy time did not translate into meaningful increases in physical activity across the day. http://www.anzctr.org.au/. Unique identifier: ACTRN12610000096055. © 2014 American Heart Association, Inc.

Time-activity patterns of pregnant women and changes during the course of pregnancy.

PubMed

Nethery, Elizabeth; Brauer, Michael; Janssen, Patti

2009-03-01

Numerous studies suggest that in utero exposures to environmental contaminants are associated with fetal development, congenital anomalies, learning difficulties or other health impacts later in life. Although location and time-activity data have been used to model exposure to specific contaminants in epidemiological studies, little information is available about time-activity patterns of pregnant women. We measured changes in location-based activity patterns over the course of pregnancy (48-h periods, during two or three trimesters) using a self-reported time-activity log among a nonrandom sample of pregnant women (n=62). We assessed the influence of demographics and personal factors on changes in activity over pregnancy using mixed effects regression models. Increasing weeks of pregnancy was a significant predictor for increased time spent at home (1 h/day increase for each trimester of pregnancy), after adjusting for income (2.6 more h/day at home in lowest income group), work status (3.5 more h/day at home for nonworkers) and other children in the family (1.5 more h/day at home with other children). No other measured activities (time outdoors, time in transit modalities or time in other indoor locations) were related to weeks of pregnancy. As our results indicate that pregnant women tend to spend more time at home during the latter stages of pregnancy, future exposure and epidemiological research should consider the potential increase in home-based exposures (i.e., indoor air pollution or chemicals in the home) late in pregnancy, and increased confidence in exposure proxies based on home locations or characteristics during the same period.

IRI STORM validation over Europe

NASA Astrophysics Data System (ADS)

Haralambous, Haris; Vryonides, Photos; Demetrescu, Crişan; Dobrică, Venera; Maris, Georgeta; Ionescu, Diana

2014-05-01

The International Reference Ionosphere (IRI) model includes an empirical Storm-Time Ionospheric Correction Model (STORM) extension to account for storm-time changes of the F layer peak electron density (NmF2) during increased geomagnetic activity. This model extension is driven by past history values of the geomagnetic index ap (The magnetic index applied is the integral of ap over the previous 33 hours with a weighting function deduced from physically based modeling) and it adjusts the quiet-time F layer peak electron density (NmF2) to account for storm-time changes in the ionosphere. In this investigation manually scaled hourly values of NmF2 measured during the main and recovery phases of selected storms for the maximum solar activity period of the current solar cycle are compared with the predicted IRI-2012 NmF2 over European ionospheric stations using the STORM model option. Based on the comparison a subsequent performance evaluation of the STORM option during this period is quantified.

Accelerometer measured daily physical activity and sedentary pursuits--comparison between two models of the Actigraph and the importance of data reduction.

PubMed

Tanha, Tina; Tornberg, Åsa; Dencker, Magnus; Wollmer, Per

2013-10-31

Very few validation studies have been performed between different generations of the commonly used Actigraph accelerometers. We compared daily physical activity data generated from the old generation Actigraph model 7164 with the new generation Actigraph GT1M accelerometer in 15 young females for eight consecutive days. We also investigated if different wear time thresholds had any impact on the findings. Minutes per day of moderate and vigorous physical activity (MVPA), vigorous physical activity (VPA) and very vigorous physical activity (VVPA) were calculated. Moreover, minutes of sedentary pursuits per day were calculated. There were significant (P < 0.05) differences between the Actigraph 7164 and the GT1M concerning MVPA (61 ± 21vs. 56 ± 23 min/day), VPA (12 ± 8 vs. 9 ± 3 min/day) and VVPA (3.2 ± 3.0 vs. 0.3 ± 1.1 min/day). The different wear time thresholds had little impact on minutes per day in different intensities. Median minutes of sedentary pursuits per day ranged from 159 to 438 minutes depending on which wear time threshold was used (i.e. 10, 30 or 60 minutes), whereas very small differences were observed between the two different models. Data from the old generation Actigraph 7164 and the new generation Actigraph GT1M accelerometers differ, where the Actigraph GT1M generates lower minutes spent in free living physical activity. Median minutes of sedentary pursuits per day are highly dependent on which wear time threshold that is used, and not by accelerometer model.

Physical, policy, and sociocultural characteristics of the primary school environment are positively associated with children's physical activity during class time.

PubMed

Martin, Karen; Bremner, Alexandra; Salmon, Jo; Rosenberg, Michael; Giles-Corti, Billie

2014-03-01

The objective of this study was to develop a multidomain model to identify key characteristics of the primary school environment associated with children's physical activity (PA) during class-time. Accelerometers were used to calculate time spent in moderate-to-vigorous physical activity during class-time (CMVPA) of 408 sixth-grade children (mean ± SD age 11.1 ± 0.43 years) attending 27 metropolitan primary schools in Perth Western Australia. Child and staff self-report instruments and a school physical environment scan administered by the research team were used to collect data about children and the class and school environments. Hierarchical modeling identified key variables associated with CMVPA. The final multilevel model explained 49% of CMVPA. A physically active physical education (PE) coordinator, fitness sessions incorporated into PE sessions and either a trained PE specialist, classroom teacher or nobody coordinating PE in the school, rather than the deputy principal, were associated with higher CMVPA. The amount of grassed area per student and sporting apparatus on grass were also associated with higher CMVPA. These results highlight the relevance of the school's sociocultural, policy and physical environments in supporting class-based PA. Interventions testing optimization of the school physical, sociocultural and policy environments to support physical activity are warranted.

Unscented Kalman Filter for Brain-Machine Interfaces

PubMed Central

Li, Zheng; O'Doherty, Joseph E.; Hanson, Timothy L.; Lebedev, Mikhail A.; Henriquez, Craig S.; Nicolelis, Miguel A. L.

2009-01-01

Brain machine interfaces (BMIs) are devices that convert neural signals into commands to directly control artificial actuators, such as limb prostheses. Previous real-time methods applied to decoding behavioral commands from the activity of populations of neurons have generally relied upon linear models of neural tuning and were limited in the way they used the abundant statistical information contained in the movement profiles of motor tasks. Here, we propose an n-th order unscented Kalman filter which implements two key features: (1) use of a non-linear (quadratic) model of neural tuning which describes neural activity significantly better than commonly-used linear tuning models, and (2) augmentation of the movement state variables with a history of n-1 recent states, which improves prediction of the desired command even before incorporating neural activity information and allows the tuning model to capture relationships between neural activity and movement at multiple time offsets simultaneously. This new filter was tested in BMI experiments in which rhesus monkeys used their cortical activity, recorded through chronically implanted multielectrode arrays, to directly control computer cursors. The 10th order unscented Kalman filter outperformed the standard Kalman filter and the Wiener filter in both off-line reconstruction of movement trajectories and real-time, closed-loop BMI operation. PMID:19603074

Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

PubMed

Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

2005-09-01

Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk.

Modeling the glass transition of amorphous networks for shape-memory behavior

NASA Astrophysics Data System (ADS)

Xiao, Rui; Choi, Jinwoo; Lakhera, Nishant; Yakacki, Christopher M.; Frick, Carl P.; Nguyen, Thao D.

2013-07-01

In this paper, a thermomechanical constitutive model was developed for the time-dependent behaviors of the glass transition of amorphous networks. The model used multiple discrete relaxation processes to describe the distribution of relaxation times for stress relaxation, structural relaxation, and stress-activated viscous flow. A non-equilibrium thermodynamic framework based on the fictive temperature was introduced to demonstrate the thermodynamic consistency of the constitutive theory. Experimental and theoretical methods were developed to determine the parameters describing the distribution of stress and structural relaxation times and the dependence of the relaxation times on temperature, structure, and driving stress. The model was applied to study the effects of deformation temperatures and physical aging on the shape-memory behavior of amorphous networks. The model was able to reproduce important features of the partially constrained recovery response observed in experiments. Specifically, the model demonstrated a strain-recovery overshoot for cases programmed below Tg and subjected to a constant mechanical load. This phenomenon was not observed for materials programmed above Tg. Physical aging, in which the material was annealed for an extended period of time below Tg, shifted the activation of strain recovery to higher temperatures and increased significantly the initial recovery rate. For fixed-strain recovery, the model showed a larger overshoot in the stress response for cases programmed below Tg, which was consistent with previous experimental observations. Altogether, this work demonstrates how an understanding of the time-dependent behaviors of the glass transition can be used to tailor the temperature and deformation history of the shape-memory programming process to achieve more complex shape recovery pathways, faster recovery responses, and larger activation stresses.

Modeling the heterogeneity of human dynamics based on the measurements of influential users in Sina Microblog

NASA Astrophysics Data System (ADS)

Wang, Chenxu; Guan, Xiaohong; Qin, Tao; Yang, Tao

2015-06-01

Online social network has become an indispensable communication tool in the information age. The development of microblog also provides us a great opportunity to study human dynamics that play a crucial role in the design of efficient communication systems. In this paper we study the characteristics of the tweeting behavior based on the data collected from Sina Microblog. The user activity level is measured to characterize how often a user posts a tweet. We find that the user activity level follows a bimodal distribution. That is, the microblog users tend to be either active or inactive. The inter-tweeting time distribution is then measured at both the aggregate and individual levels. We find that the inter-tweeting time follows a piecewise power law distribution of two tails. Furthermore, the exponents of the two tails have different correlations with the user activity level. These findings demonstrate that the dynamics of the tweeting behavior are heterogeneous in different time scales. We then develop a dynamic model co-driven by the memory and the interest mechanism to characterize the heterogeneity. The numerical simulations validate the model and verify that the short time interval tweeting behavior is driven by the memory mechanism while the long time interval behavior by the interest mechanism.

Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

NASA Astrophysics Data System (ADS)

Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

2018-02-01

A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

Psychological factors related to physical education classes as predictors of students' intention to partake in leisure-time physical activity.

PubMed

Baena-Extremera, Antonio; Granero-Gallegos, Antonio; Ponce-de-León-Elizondo, Ana; Sanz-Arazuri, Eva; Valdemoros-San-Emeterio, María de Los Ángeles; Martínez-Molina, Marina

2016-04-01

In view of the rise in sedentary lifestyle amongst young people, knowledge regarding their intention to partake in physical activity can be decisive when it comes to instilling physical activity habits to improve the current and future health of school students. Therefore, the object of this study was to find a predictive model of the intention to partake in leisure- time physical activity based on motivation, satisfaction and competence. The sample consisted of 347 Spanish, male, high school students and 411 female students aged between 13 and 18 years old. We used a questionnaire made up of the Sport Motivation Scale, Sport Satisfaction Instrument, and the competence factor in the Basic Psychological Needs in Exercise Scale and Intention to Partake in Leisure-Time Physical Activity, all of them adapted to school Physical Education. We carried out confirmatory factor analyses and structural equation models. The intention to partake in leisure-time physical activity was predicted by competence and the latter by satisfaction/fun. Intrinsic motivation was revealed to be the best predictor of satisfaction/fun. Intrinsic motivation should be enhanced in order to predict an intention to partake in physical activity in Physical Education students.

Atmospheric density models

NASA Technical Reports Server (NTRS)

Mueller, A. C.

1977-01-01

An atmospheric model developed by Jacchia, quite accurate but requiring a large amount of computer storage and execution time, was found to be ill-suited for the space shuttle onboard program. The development of a simple atmospheric density model to simulate the Jacchia model was studied. Required characteristics including variation with solar activity, diurnal variation, variation with geomagnetic activity, semiannual variation, and variation with height were met by the new atmospheric density model.

Standardizing clinical trials workflow representation in UML for international site comparison.

PubMed

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M O; Rodrigues, Maria J; Shah, Jatin; Loures, Marco R; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-11-09

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

PubMed Central

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M. O.; Rodrigues, Maria J.; Shah, Jatin; Loures, Marco R.; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-01-01

Background With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Methods Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Results Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. Conclusions This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows. PMID:21085484

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

The International Reference Ionosphere - Status 2013

NASA Astrophysics Data System (ADS)

Bilitza, Dieter

2015-04-01

This paper describes the latest version of the International Reference Ionosphere (IRI) model. IRI-2012 includes new models for the electron density and ion densities in the region below the F-peak, a storm-time model for the auroral E-region, an improved electron temperature model that includes variations with solar activity, and for the first time a description of auroral boundaries. In addition, the thermosphere model required for baseline neutral densities and temperatures was upgraded from MSIS-86 to the newer NRLMSIS-00 model and Corrected Geomagnetic coordinates (CGM) were included in IRI as an additional coordinate system for a better representation of auroral and polar latitudes. Ongoing IRI activities towards the inclusion of an improved model for the F2 peak height hmF2 are discussed as are efforts to develop a "Real-Time IRI". The paper is based on an IRI status report presented at the 2013 IRI Workshop in Olsztyn, Poland. The IRI homepage is at

Gastrointestinal Functionality of Aquatic Animal (Oreochromis niloticus) Carcass in Water Allows Estimating Time of Death.

PubMed

Hahor, Waraporn; Thongprajukaew, Karun; Yoonram, Krueawan; Rodjaroen, Somrak

2016-11-01

Postmortem changes have been previously studied in some terrestrial animal models, but no prior information is available on aquatic species. Gastrointestinal functionality was investigated in terms of indices, protein concentration, digestive enzyme activity, and scavenging activity, in an aquatic animal model, Nile tilapia, to assess the postmortem changes. Dead fish were floated indoors, and samples were collected within 48 h after death. Stomasomatic index decreased with postmortem time and correlated positively with protein, pepsin-specific activity, and stomach scavenging activity. Also intestosomatic index decreased significantly and correlated positively with protein, specific activity of trypsin, chymotrypsin, amylase, lipase, and intestinal scavenging activity. In their postmortem changes, the digestive enzymes exhibited earlier lipid degradation than carbohydrate or protein. The intestine changed more rapidly than the stomach. The findings suggest that the postmortem changes of gastrointestinal functionality can serve as primary data for the estimation of time of death of an aquatic animal. © 2016 American Academy of Forensic Sciences.

Predictors of premature gonadal failure in patients with systemic lupus erythematosus. Results from LUMINA, a multiethnic US cohort (LUMINA LVIII).

PubMed

González, L A; McGwin, G; Durán, S; Pons-Estel, G J; Apte, M; Vilá, L M; Reveille, J D; Alarcón, G S

2008-08-01

To examine the predictors of time to premature gonadal failure (PGF) in patients with systemic lupus erythematosus from LUMINA, a multiethnic US cohort. PGF was defined according to the SLICC Damage Index (SDI). Factors associated with time to PGF occurrence were examined by univariable and multivariable Cox proportional hazards regression analyses: three models according to cyclophosphamide use, at T0 (model 1), over time (model 2) and the total number of intravenous pulses (model 3). Thirty-seven of 316 women (11.7%) developed PGF (19 Texan-Hispanics, 14 African-Americans, four Caucasians and no Puerto Rican-Hispanics). By multivariable analyses, older age at T0 (hazards ratio (HR) = 1.10-1.14; 95% CI 1.02-1.05 to 1.19-1.23) and disease activity (Systemic Lupus Activity Measure-Revised) in all models (HR = 1.22-1.24; 95% CI 1.10-1.12 to 1.35-1.37), Texan-Hispanic ethnicity in models 2 and 3 (HR = 4.06-5.07; 95% CI 1.03-1.25 to 15.94-20.47) and cyclophosphamide use in models 1 and 3 (1-6 pulses) (HR = 4.01-4.65; 95% CI 1.55-1.68 to 9.56-13.94) were predictors of a shorter time to PGF. Disease activity and Texan-Hispanic ethnicity emerged as predictors of a shorter time to PGF while the associations with cyclophosphamide use and older age were confirmed. Furthermore, cyclophosphamide induction therapy emerged as an important determinant of PGF.

Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements.

PubMed

van Pelt, Roy; Nguyen, Huy; ter Haar Romeny, Bart; Vilanova, Anna

2012-03-01

Quantitative analysis of vascular blood flow, acquired by phase-contrast MRI, requires accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and the lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task requiring automation. Automated segmentation of large thoracic arteries, based solely on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data, was done. An active surface model, which is fast and topologically stable, was used. The active surface model requires an initial surface, approximating the desired segmentation. A method to generate this surface was developed based on a voxel-wise temporal maximum of blood-flow velocities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. The automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface and facilitates parametrization. An active surface approach for vessel lumen segmentation was developed, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to prior thresholding and level-set approaches, the active surface model is topologically stable. A method to generate an initial approximate surface was developed, and various features that influence the segmentation model were evaluated. The active surface segmentation results were shown to closely approximate manual segmentations.

Modeling the inactivation of ascaris eggs as a function of ammonia concentration and temperature.

PubMed

Fidjeland, J; Nordin, A; Pecson, B M; Nelson, K L; Vinnerås, B

2015-10-15

Ammonia sanitization is a promising technology for sanitizing human excreta intended for use as a fertilizer in agriculture. Ascaris eggs are the most persistent pathogens regarding ammonia inactivation and are commonly present in fecal sludge in low- and middle-income countries. In this study, a model for predicting ammonia inactivation of ascaris eggs was developed. Data from four previous studies were compiled and analyzed statistically, and a mathematical model for the treatment time required for inactivation was created. The inactivation rate increased with NH3 activity to the power of 0.7. The required treatment time was found to decrease 10-fold for each 16 °C temperature increase. Dry matter (DM) content and pH had no direct effect on inactivation, but had an indirect effect due to their impact on NH3 activity, which was estimated using the Pitzer approach. An additional model giving an approximation of Pitzer NH3 activity but based on the Emerson approach, DM content and total ammonia (NHTot) was also developed. The treatment time required for different log10 reductions of ascaris egg viability can thus easily be estimated by the model as a function of NH3 activity and temperature. The impact on treatment time by different treatment options can then be theoretically evaluated, promoting improvements of the treatment e.g. by adding urea or alkaline agents, or increasing the temperature by solar heating. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of the Extended Kalman Filter and the Unscented Kalman Filter for Magnetocardiography activation time imaging

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.

Using State-Space Model with Regime Switching to Represent the Dynamics of Facial Electromyography (EMG) Data

ERIC Educational Resources Information Center

Yang, Manshu; Chow, Sy-Miin

2010-01-01

Facial electromyography (EMG) is a useful physiological measure for detecting subtle affective changes in real time. A time series of EMG data contains bursts of electrical activity that increase in magnitude when the pertinent facial muscles are activated. Whereas previous methods for detecting EMG activation are often based on deterministic or…

Transtheoretical Model Constructs for Physical Activity Behavior are Invariant across Time among Ethnically Diverse Adults in Hawaii

PubMed Central

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

Pointillist, Cyclical, and Overlapping: Multidimensional Facets of Time in Online Learning

ERIC Educational Resources Information Center

Ihanainen, Pekka; Moravec, John W.

2011-01-01

A linear, sequential time conception based on in-person meetings and pedagogical activities is not enough for those who practice and hope to enhance contemporary education, particularly where online interactions are concerned. In this article, we propose a new model for understanding time in pedagogical contexts. Conceptual parts of the model will…

Active Transportation and Demand Management (ATDM) foundational research : Analysis, Modeling, and Simulation (AMS) capabilities assessment.

DOT National Transportation Integrated Search

2013-06-01

As part of the Federal Highway Administrations (FHWAs) Active Transportation and Demand Management (ATDM) Foundational Research, this publication identifies the AMS needs to support simulated real-time and real-time analysis to evaluate the imp...

Seismic hazard assessment over time: Modelling earthquakes in Taiwan

NASA Astrophysics Data System (ADS)

Chan, Chung-Han; Wang, Yu; Wang, Yu-Ju; Lee, Ya-Ting

2017-04-01

To assess the seismic hazard with temporal change in Taiwan, we develop a new approach, combining both the Brownian Passage Time (BPT) model and the Coulomb stress change, and implement the seismogenic source parameters by the Taiwan Earthquake Model (TEM). The BPT model was adopted to describe the rupture recurrence intervals of the specific fault sources, together with the time elapsed since the last fault-rupture to derive their long-term rupture probability. We also evaluate the short-term seismicity rate change based on the static Coulomb stress interaction between seismogenic sources. By considering above time-dependent factors, our new combined model suggests an increased long-term seismic hazard in the vicinity of active faults along the western Coastal Plain and the Longitudinal Valley, where active faults have short recurrence intervals and long elapsed time since their last ruptures, and/or short-term elevated hazard levels right after the occurrence of large earthquakes due to the stress triggering effect. The stress enhanced by the February 6th, 2016, Meinong ML 6.6 earthquake also significantly increased rupture probabilities of several neighbouring seismogenic sources in Southwestern Taiwan and raised hazard level in the near future. Our approach draws on the advantage of incorporating long- and short-term models, to provide time-dependent earthquake probability constraints. Our time-dependent model considers more detailed information than any other published models. It thus offers decision-makers and public officials an adequate basis for rapid evaluations of and response to future emergency scenarios such as victim relocation and sheltering.

Statistical theory of dynamo

NASA Astrophysics Data System (ADS)

Kim, E.; Newton, A. P.

2012-04-01

One major problem in dynamo theory is the multi-scale nature of the MHD turbulence, which requires statistical theory in terms of probability distribution functions. In this contribution, we present the statistical theory of magnetic fields in a simplified mean field α-Ω dynamo model by varying the statistical property of alpha, including marginal stability and intermittency, and then utilize observational data of solar activity to fine-tune the mean field dynamo model. Specifically, we first present a comprehensive investigation into the effect of the stochastic parameters in a simplified α-Ω dynamo model. Through considering the manifold of marginal stability (the region of parameter space where the mean growth rate is zero), we show that stochastic fluctuations are conductive to dynamo. Furthermore, by considering the cases of fluctuating alpha that are periodic and Gaussian coloured random noise with identical characteristic time-scales and fluctuating amplitudes, we show that the transition to dynamo is significantly facilitated for stochastic alpha with random noise. Furthermore, we show that probability density functions (PDFs) of the growth-rate, magnetic field and magnetic energy can provide a wealth of useful information regarding the dynamo behaviour/intermittency. Finally, the precise statistical property of the dynamo such as temporal correlation and fluctuating amplitude is found to be dependent on the distribution the fluctuations of stochastic parameters. We then use observations of solar activity to constrain parameters relating to the effect in stochastic α-Ω nonlinear dynamo models. This is achieved through performing a comprehensive statistical comparison by computing PDFs of solar activity from observations and from our simulation of mean field dynamo model. The observational data that are used are the time history of solar activity inferred for C14 data in the past 11000 years on a long time scale and direct observations of the sun spot numbers obtained in recent years 1795-1995 on a short time scale. Monte Carlo simulations are performed on these data to obtain PDFs of the solar activity on both long and short time scales. These PDFs are then compared with predicted PDFs from numerical simulation of our α-Ω dynamo model, where α is assumed to have both mean α0 and fluctuating α' parts. By varying the correlation time of fluctuating α', the ratio of the amplitude of the fluctuating to mean alpha <α'2>/α02 (where angular brackets <> denote ensemble average), and the ratio of poloidal to toroidal magnetic fields, we show that the results from our stochastic dynamo model can match the PDFs of solar activity on both long and short time scales. In particular, a good agreement is obtained when the fluctuation in alpha is roughly equal to the mean part with a correlation time shorter than the solar period.

Gender differences in social support and leisure-time physical activity.

PubMed

Oliveira, Aldair J; Lopes, Claudia S; Rostila, Mikael; Werneck, Guilherme Loureiro; Griep, Rosane Härter; Leon, Antônio Carlos Monteiro Ponce de; Faerstein, Eduardo

2014-08-01

To identify gender differences in social support dimensions' effect on adults' leisure-time physical activity maintenance, type, and time. Longitudinal study of 1,278 non-faculty public employees at a university in Rio de Janeiro, RJ, Southeastern Brazil. Physical activity was evaluated using a dichotomous question with a two-week reference period, and further questions concerning leisure-time physical activity type (individual or group) and time spent on the activity. Social support was measured with the Medical Outcomes Study Social Support Scale. For the analysis, logistic regression models were adjusted separately by gender. A multinomial logistic regression showed an association between material support and individual activities among women (OR = 2.76; 95%CI 1.2;6.5). Affective support was associated with time spent on leisure-time physical activity only among men (OR = 1.80; 95%CI 1.1;3.2). All dimensions of social support that were examined influenced either the type of, or the time spent on, leisure-time physical activity. In some social support dimensions, the associations detected varied by gender. Future studies should attempt to elucidate the mechanisms involved in these gender differences.

Isotemporal Substitution Paradigm for Physical Activity Epidemiology and Weight Change

PubMed Central

Willett, Walter C.; Hu, Frank B.; Ding, Eric L.

2009-01-01

For a fixed amount of time engaged in physical activity, activity choice may affect body weight differently depending partly on other activities’ displacement. Typical models used to evaluate effects of physical activity on body weight do not directly address these substitutions. An isotemporal substitution paradigm was developed as a new analytic model to study the time-substitution effects of one activity for another. In 1991–1997, the authors longitudinally examined the associations of discretionary physical activities, with varying activity displacements, with 6-year weight loss maintenance among 4,558 healthy, premenopausal US women who had previously lost >5% of their weight. Results of isotemporal substitution models indicated widely heterogeneous relations with each physical activity type (P < 0.001) depending on the displaced activities. Notably, whereas 30 minutes/day of brisk walking substituted for 30 minutes/day of jogging/running was associated with weight increase (1.57 kg, 95% confidence interval: 0.33, 2.82), brisk walking was associated with lower weight when substituted for slow walking (−1.14 kg, 95% confidence interval: −1.75, −0.53) and with even lower weight when substituted for TV watching. Similar heterogeneous relations with weight change were found for each activity type (TV watching, slow walking, brisk walking, jogging/running) when displaced by other activities across these various models. The isotemporal substitution paradigm may offer new insights for future public health recommendations. PMID:19584129

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

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.

Naturally Occurring Changes in Time Spent Watching Television Are Inversely Related to Frequency of Physical Activity during Early Adolescence

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…

Linguistic Models of FO Use, Physiological Models of FO Control, and the Issue of "Mean Response Time."

ERIC Educational Resources Information Center

Herman, Rebecca; Beckman, Mary; Honda, Kiyoshi

1999-01-01

Evaluates "mean response time" (MRT), a method used in previous studies to relate physiological evidence (recordings of electromyographic activity in the cricothyroid and sternohyoid) to acoustic evidence (fundamental frequency). (Author/VWL)

Population Pharmacokinetics to Model the Time-Varying Clearance of the PEGylated Asparaginase Oncaspar® in Children with Acute Lymphoblastic Leukemia.

PubMed

Würthwein, Gudrun; Lanvers-Kaminsky, Claudia; Hempel, Georg; Gastine, Silke; Möricke, Anja; Schrappe, Martin; Karlsson, Mats O; Boos, Joachim

2017-12-01

The pharmacokinetics of the polyethylene glycol (PEG)-conjugated asparaginase Oncaspar ® are characterized by an increase in elimination over time. The focus of our analysis is the better understanding of this time-dependency. In paediatric acute lymphoblastic leukemia therapy (AIEOP-BFM ALL 2009), two administrations of Oncaspar ® (2500 U/m 2 intravenously) in induction phase (14-day interval) and one single administration in reinduction were followed by weekly monitoring of asparaginase activity. Non-linear mixed-effects modeling techniques (NONMEM) were used. Samples indicating immunological inactivation were excluded to describe the pharmacokinetics under standard conditions. Models with time-constant or time-varying clearance (CL) as well as transit compartment models with an increase in CL over a chain of compartments were investigated. Models with time-constant elimination could not adequately describe 6107 asparaginase activities from 1342 patients. Implementing a time-varying CL improved the fit. Modeling an increase of CL over time after dose (E max - and Weibull-functions) were superior to models with an increase of CL over time after the first administration. However, a transit compartment model came out to be the best structural model. The increase in elimination of PEGylated asparaginase appears to be driven by physicochemical processes that are drug-related. The observed hydrolytically in vitro instability of the drug leads to the hypothesis that this increase in CL might be due to an in vivo hydrolysis of the instable ester bond between PEG and the enzyme combined with an increased elimination of the partly de-PEGylated enzyme (Trial registered at www.clinicaltrials.gov , NCT0111744).

A Coupled Epipelagic-Meso/Bathypelagic Particle Flux Model for the Bermuda Atlantic Time-series Station (BATS)/Oceanic Flux Program (OFP) Site

NASA Astrophysics Data System (ADS)

Glover, D. M.; Conte, M.

2002-12-01

Of considerable scientific interest is the role remineralization plays in the global carbon cycle. It is the ``biological pump'' that fixes carbon in the upper water column and exports it for long time periods to the deep ocean. From a global carbon cycle point-of-view, it is the processes that govern remineralization in the mid- to deep-ocean waters that provide the feedback to the biogeochemical carbon cycle. In this study we construct an ecosystem model that serves as a mechanistic link between euphotic processes and mesopelagic and bathypelagic processes. We then use this prognostic model to further our understanding of the unparalleled time-series of deep-water sediment traps (21+ years) at the Oceanic Flux Program (OFP) and the euphotic zone measurements (10+ years) at the Bermuda Atlantic Time-series Site (BATS). At the core of this mechanistic ecosystem model of the mesopelagic zone is a model that consists of an active feeding habit zooplankton, a passive feeding habit zooplankton, large detritus (sinks), small detritus (non-sinking), and a nutrient pool. As the detritus, the primary source of food, moves through the water column it is fed upon by the active/passive zooplankton pair and undergoes bacterially mediated remineralization into nutrients. The large detritus pool at depth gains material from the formation of fecal pellets from the passive and active zooplankton. Sloppy feeding habits of the active zooplankton contribute to the small detrital pool. Zooplankton mortality (both classes) also contribute directly to the large detritus pool. Aggregation and disaggregation transform detrital particles from one pool to the other and back again. The nutrients at each depth will gain from detrital remineralization and zooplankton excretion. The equations that model the active zooplankton, passive zooplankton, large detritus, small detritus, and nutrients will be reviewed, results shown and future model modifications discussed.

Playing Active Video Games may not develop movement skills: An intervention trial.

PubMed

Barnett, Lisa M; Ridgers, Nicola D; Reynolds, John; Hanna, Lisa; Salmon, Jo

2015-01-01

To investigate the impact of playing sports Active Video Games on children's actual and perceived object control skills. Intervention children played Active Video Games for 6 weeks (1 h/week) in 2012. The Test of Gross Motor Development-2 assessed object control skill. The Pictorial Scale of Perceived Movement Skill Competence assessed perceived object control skill. Repeated measurements of object control and perceived object control were analysed for the whole sample, using linear mixed models, which included fixed effects for group (intervention or control) and time (pre and post) and their interaction. The first model adjusted for sex only and the second model also adjusted for age, and prior ball sports experience (yes/no). Seven mixed-gender focus discussions were conducted with intervention children after programme completion. Ninety-five Australian children (55% girls; 43% intervention group) aged 4 to 8 years (M 6.2, SD 0.95) participated. Object control skill improved over time (p = 0.006) but there was no significant difference (p = 0.913) between groups in improvement (predicted means: control 31.80 to 33.53, SED = 0.748; intervention 30.33 to 31.83, SED = 0.835). A similar result held for the second model. Similarly the intervention did not change perceived object control in Model 1 (predicted means: control: 19.08 to 18.68, SED = 0.362; intervention 18.67 to 18.88, SED = 0.406) or Model 2. Children found the intervention enjoyable, but most did not perceive direct equivalence between Active Video Games and 'real life' activities. Whilst Active Video Game play may help introduce children to sport, this amount of time playing is unlikely to build skill.

Playing Active Video Games may not develop movement skills: An intervention trial

PubMed Central

Barnett, Lisa M.; Ridgers, Nicola D.; Reynolds, John; Hanna, Lisa; Salmon, Jo

2015-01-01

Background: To investigate the impact of playing sports Active Video Games on children's actual and perceived object control skills. Methods: Intervention children played Active Video Games for 6 weeks (1 h/week) in 2012. The Test of Gross Motor Development-2 assessed object control skill. The Pictorial Scale of Perceived Movement Skill Competence assessed perceived object control skill. Repeated measurements of object control and perceived object control were analysed for the whole sample, using linear mixed models, which included fixed effects for group (intervention or control) and time (pre and post) and their interaction. The first model adjusted for sex only and the second model also adjusted for age, and prior ball sports experience (yes/no). Seven mixed-gender focus discussions were conducted with intervention children after programme completion. Results: Ninety-five Australian children (55% girls; 43% intervention group) aged 4 to 8 years (M 6.2, SD 0.95) participated. Object control skill improved over time (p = 0.006) but there was no significant difference (p = 0.913) between groups in improvement (predicted means: control 31.80 to 33.53, SED = 0.748; intervention 30.33 to 31.83, SED = 0.835). A similar result held for the second model. Similarly the intervention did not change perceived object control in Model 1 (predicted means: control: 19.08 to 18.68, SED = 0.362; intervention 18.67 to 18.88, SED = 0.406) or Model 2. Children found the intervention enjoyable, but most did not perceive direct equivalence between Active Video Games and ‘real life’ activities. Conclusions: Whilst Active Video Game play may help introduce children to sport, this amount of time playing is unlikely to build skill. PMID:26844136

Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.

USGS Publications Warehouse

Peitzsch, Erich H.; Hendrikx, Jordy; Fagre, Daniel B.

2012-01-01

Wet snow avalanches pose a problem for annual spring road opening operations along the Going-to-the-Sun Road (GTSR) in Glacier National Park, Montana, USA. A suite of meteorological metrics and snow observations has been used to forecast for wet slab and glide avalanche activity. However, the timing of spring wet slab and glide avalanches is a difficult process to forecast and requires new capabilities. For the 2011 and 2012 spring seasons we tested a previously developed classification tree model which had been trained on data from 2003-2010. For 2011, this model yielded a 91% predictive rate for avalanche days. For 2012, the model failed to capture any of the avalanche days observed. We then investigated these misclassified avalanche days in the 2012 season by comparing them to the misclassified days from the original dataset from which the model was trained. Results showed no significant difference in air temperature variables between this year and the original training data set for these misclassified days. This indicates that 2012 was characterized by avalanche days most similar to those that the model struggled with in the original training data. The original classification tree model showed air temperature to be a significant variable in wet avalanche activity which implies that subsequent movement of meltwater through the snowpack is also important. To further understand the timing of water flow we installed two lysimeters in fall 2011 before snow accumulation. Water flow showed a moderate correlation with air temperature later in the season and no synchronous pattern associated with wet slab and glide avalanche activity. We also characterized snowpack structure as the snowpack transitioned from a dry to a wet snowpack throughout the spring. This helped to assess potential failure layers of wet snow avalanches and the timing of avalanches compared to water moving through the snowpack. These tools (classification tree model and lysimeter data), combined with standard meteorological and avalanche observations, proved useful to forecasters regarding the timing of wet snow avalanche activity along the GTSR.

Links between personality, time perspective, and intention to practice physical activity during cancer treatment: an exploratory study.

PubMed

Villaron, Charlène; Marqueste, Tanguy; Eisinger, François; Cappiello, Maria-Antonietta; Therme, Pierre; Cury, François

2017-04-01

The purpose of the study was to analyze links between personality, time perspective, and intention to practice physical activity during cancer treatment. One hundred forty-three patients participated in survey by questionnaire. Intention to practice physical activity, time perspective using Zimbardo Time Perspective Inventory, and personality with the Big Five Inventory were measured. Structural equation models using Lisrel were developed to examine hypothetical links between the variables. The adjusted model evidenced an excellent fit (comparative fit index = 0.92; root-mean-square error of approximation = 0.076; P = .014). Results showed that intention to practice exercise was positively linked with openness to experience and negatively with present fatalist time perspective. Moreover, conscientiousness and neuroticism were found to be linked with future time perspective, which was positively related with intention to practice physical activity. The present exploratory study with patients suffering from cancer underlined the importance of considering jointly time perspective dimensions and personality factors for health behavior recommendations. Based on our results, we propose some reflections on practice to help nurses and physicians increase patient's motivation to be physically active. Taking into account patients' personality and time perspective, we would be able to propose specific awareness messages and offer short interventions to have an impact on patients' motivation to practice. Copyright © 2016 John Wiley & Sons, Ltd.

A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors

PubMed Central

Han, Manhyung; Bang, Jae Hun; Nugent, Chris; McClean, Sally; Lee, Sungyoung

2014-01-01

Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user's activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. PMID:25184486

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

PubMed

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

Three-part joint modeling methods for complex functional data mixed with zero-and-one-inflated proportions and zero-inflated continuous outcomes with skewness.

PubMed

Li, Haocheng; Staudenmayer, John; Wang, Tianying; Keadle, Sarah Kozey; Carroll, Raymond J

2018-02-20

We take a functional data approach to longitudinal studies with complex bivariate outcomes. This work is motivated by data from a physical activity study that measured 2 responses over time in 5-minute intervals. One response is the proportion of time active in each interval, a continuous proportions with excess zeros and ones. The other response, energy expenditure rate in the interval, is a continuous variable with excess zeros and skewness. This outcome is complex because there are 3 possible activity patterns in each interval (inactive, partially active, and completely active), and those patterns, which are observed, induce both nonrandom and random associations between the responses. More specifically, the inactive pattern requires a zero value in both the proportion for active behavior and the energy expenditure rate; a partially active pattern means that the proportion of activity is strictly between zero and one and that the energy expenditure rate is greater than zero and likely to be moderate, and the completely active pattern means that the proportion of activity is exactly one, and the energy expenditure rate is greater than zero and likely to be higher. To address these challenges, we propose a 3-part functional data joint modeling approach. The first part is a continuation-ratio model to reorder the ordinal valued 3 activity patterns. The second part models the proportions when they are in interval (0,1). The last component specifies the skewed continuous energy expenditure rate with Box-Cox transformations when they are greater than zero. In this 3-part model, the regression structures are specified as smooth curves measured at various time points with random effects that have a correlation structure. The smoothed random curves for each variable are summarized using a few important principal components, and the association of the 3 longitudinal components is modeled through the association of the principal component scores. The difficulties in handling the ordinal and proportional variables are addressed using a quasi-likelihood type approximation. We develop an efficient algorithm to fit the model that also involves the selection of the number of principal components. The method is applied to physical activity data and is evaluated empirically by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.

Automated Interactive Simulation Model (AISIM) VAX Version 5.0 Training Manual.

DTIC Science & Technology

1987-05-29

action, activity, decision , etc. that consumes time. The entity is automatically created by the system when an ACTION Primitive is placed. 1.3.2.4 The...MODELED SYSTEM 1.3.2.1 The Process Entity. A Process is used to represent the operations, decisions , actions or activities that can be decomposed and...is associated with the Action entity described below, is included in Process definitions to indicate the time a certain Action (or process, decision

Modeling T-cell activation using gene expression profiling and state-space models.

PubMed

Rangel, Claudia; Angus, John; Ghahramani, Zoubin; Lioumi, Maria; Sotheran, Elizabeth; Gaiba, Alessia; Wild, David L; Falciani, Francesco

2004-06-12

We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc. Bootstrap confidence intervals are developed for parameters representing 'gene-gene' interactions over time. Our models represent the dynamics of T-cell activation and provide a methodology for the development of rational and experimentally testable hypotheses. Supplementary data and Matlab computer source code will be made available on the web at the URL given below. http://public.kgi.edu/~wild/LDS/index.htm

Spike avalanches in vivo suggest a driven, slightly subcritical brain state

PubMed Central

Priesemann, Viola; Wibral, Michael; Valderrama, Mario; Pröpper, Robert; Le Van Quyen, Michel; Geisel, Theo; Triesch, Jochen; Nikolić, Danko; Munk, Matthias H. J.

2014-01-01

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy. PMID:25009473

A Leisure Activities Curricular Component for Severely Handicapped Youth: Why and How.

ERIC Educational Resources Information Center

Voeltz, Luanna M.; Apffel, James A.

1981-01-01

A rationale for including a leisure time activities curriculum component in educational programing for severely handicapped individuals is presented. The importance of play and the constructive use of leisure time is described through the use of a model demonstration project. (JN)

Antithrombotic Potential of Tormentil Extract in Animal Models

PubMed Central

Marcinczyk, Natalia; Jarmoc, Dominika; Leszczynska, Agnieszka; Zakrzeska, Agnieszka; Kramkowski, Karol; Strawa, Jakub; Gromotowicz-Poplawska, Anna; Chabielska, Ewa; Tomczyk, Michal

2017-01-01

Potentilla species that have been investigated so far display pharmacological activity mainly due to the presence of polyphenols. Recently, it was shown that polyphenol-rich extract from rhizome of Potentilla erecta (tormentil extract) affects the metabolism of arachidonic acid and exerts both anti-inflammatory and anti-oxidant activities, suggesting a possible effect on thrombosis. Accordingly, the aim of the study was to evaluate the effect of tormentil extract on haemostasis in a rat model of thrombosis. Lyophilized water-methanol extract from P. erecta rhizome was administrated per os for 14 days in doses of 100, 200, and 400 mg/kg in a volume of 2 mL/kg in a 5% water solution of gummi arabici (VEH). In the in vivo experiment an electrically induced carotid artery thrombosis model with blood flow monitoring was used in Wistar rats. Collected blood samples were analyzed ex vivo functionally and biochemically for changes in haemostasis. Tormentil extract (400 mg/kg) significantly decreased thrombus weight and prolonged the time to carotid artery occlusion and bleeding time without changes in the blood pressure. In the ex vivo experiment tormentil extract (400 mg/kg) reduced thromboxane production and decreased t-PA activity, while total t-PA concentration, as well as total PAI-1 concentration and PAI-1 activity remained unchanged. Furthermore, tormentil extract (400 mg/kg) decreased bradykinin concentration and shortened the time to reach maximal optical density during fibrin generation. Prothrombin time, activated partial thromboplastin time, QUICK index, fibrinogen level, and collagen-induced aggregation remained unchanged. To investigate the involvement of platelets in the antithrombotic effect of tormentil, the extract was administrated per os for 2 days to mice and irreversible platelets activation after ferric chloride induced thrombosis was evaluated under intravital conditions using confocal microscopy system. In this model tormentil extract (400 mg/kg) significantly reduced platelet activation at the same extent as acetylsalicylic acid. Taken together, we have shown for the first time that tormentil extract inhibits arterial thrombosis in platelet- and endothelial-dependent mechanisms without hemodynamic changes. Further studies on the detailed mechanism of action of tormentil extract toward fibrinolysis and the kinin system should be carried out. PMID:28860991

Dynamic cardiac PET imaging: extraction of time-activity curves using ICA and a generalized Gaussian distribution model.

PubMed

Mabrouk, Rostom; Dubeau, François; Bentabet, Layachi

2013-01-01

Kinetic modeling of metabolic and physiologic cardiac processes in small animals requires an input function (IF) and a tissue time-activity curves (TACs). In this paper, we present a mathematical method based on independent component analysis (ICA) to extract the IF and the myocardium's TACs directly from dynamic positron emission tomography (PET) images. The method assumes a super-Gaussian distribution model for the blood activity, and a sub-Gaussian distribution model for the tissue activity. Our appreach was applied on 22 PET measurement sets of small animals, which were obtained from the three most frequently used cardiac radiotracers, namely: desoxy-fluoro-glucose ((18)F-FDG), [(13)N]-ammonia, and [(11)C]-acetate. Our study was extended to PET human measurements obtained with the Rubidium-82 ((82) Rb) radiotracer. The resolved mathematical IF values compare favorably to those derived from curves extracted from regions of interest (ROI), suggesting that the procedure presents a reliable alternative to serial blood sampling for small-animal cardiac PET studies.

Real-time biomimetic Central Pattern Generators in an FPGA for hybrid experiments

PubMed Central

Ambroise, Matthieu; Levi, Timothée; Joucla, Sébastien; Yvert, Blaise; Saïghi, Sylvain

2013-01-01

This investigation of the leech heartbeat neural network system led to the development of a low resources, real-time, biomimetic digital hardware for use in hybrid experiments. The leech heartbeat neural network is one of the simplest central pattern generators (CPG). In biology, CPG provide the rhythmic bursts of spikes that form the basis for all muscle contraction orders (heartbeat) and locomotion (walking, running, etc.). The leech neural network system was previously investigated and this CPG formalized in the Hodgkin–Huxley neural model (HH), the most complex devised to date. However, the resources required for a neural model are proportional to its complexity. In response to this issue, this article describes a biomimetic implementation of a network of 240 CPGs in an FPGA (Field Programmable Gate Array), using a simple model (Izhikevich) and proposes a new synapse model: activity-dependent depression synapse. The network implementation architecture operates on a single computation core. This digital system works in real-time, requires few resources, and has the same bursting activity behavior as the complex model. The implementation of this CPG was initially validated by comparing it with a simulation of the complex model. Its activity was then matched with pharmacological data from the rat spinal cord activity. This digital system opens the way for future hybrid experiments and represents an important step toward hybridization of biological tissue and artificial neural networks. This CPG network is also likely to be useful for mimicking the locomotion activity of various animals and developing hybrid experiments for neuroprosthesis development. PMID:24319408

Edgeworth expansions of stochastic trading time

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann

2010-08-01

Under most local and stochastic volatility models the underlying forward is assumed to be a positive function of a time-changed Brownian motion. It relates nicely the implied volatility smile to the so-called activity rate in the market. Following Young and DeWitt-Morette (1986) [8], we propose to apply the Duru-Kleinert process-cum-time transformation in path integral to formulate the transition density of the forward. The method leads to asymptotic expansions of the transition density around a Gaussian kernel corresponding to the average activity in the market conditional on the forward value. The approximation is numerically illustrated for pricing vanilla options under the CEV model and the popular normal SABR model. The asymptotics can also be used for Monte Carlo simulations or backward integration schemes.

Non-monotonicity and divergent time scale in Axelrod model dynamics

NASA Astrophysics Data System (ADS)

Vazquez, F.; Redner, S.

2007-04-01

We study the evolution of the Axelrod model for cultural diversity, a prototypical non-equilibrium process that exhibits rich dynamics and a dynamic phase transition between diversity and an inactive state. We consider a simple version of the model in which each individual possesses two features that can assume q possibilities. Within a mean-field description in which each individual has just a few interaction partners, we find a phase transition at a critical value qc between an active, diverse state for q < qc and a frozen state. For q lesssim qc, the density of active links is non-monotonic in time and the asymptotic approach to the steady state is controlled by a time scale that diverges as (q-qc)-1/2.

[Analysis of cost and efficiency of a medical nursing unit using time-driven activity-based costing].

PubMed

Lim, Ji Young; Kim, Mi Ja; Park, Chang Gi

2011-08-01

Time-driven activity-based costing was applied to analyze the nursing activity cost and efficiency of a medical unit. Data were collected at a medical unit of a general hospital. Nursing activities were measured using a nursing activities inventory and classified as 6 domains using Easley-Storfjell Instrument. Descriptive statistics were used to identify general characteristics of the unit, nursing activities and activity time, and stochastic frontier model was adopted to estimate true activity time. The average efficiency of the medical unit using theoretical resource capacity was 77%, however the efficiency using practical resource capacity was 96%. According to these results, the portion of non-added value time was estimated 23% and 4% each. The sums of total nursing activity costs were estimated 109,860,977 won in traditional activity-based costing and 84,427,126 won in time-driven activity-based costing. The difference in the two cost calculating methods was 25,433,851 won. These results indicate that the time-driven activity-based costing provides useful and more realistic information about the efficiency of unit operation compared to traditional activity-based costing. So time-driven activity-based costing is recommended as a performance evaluation framework for nursing departments based on cost management.

The effects of prior knowledge on study-time allocation and free recall: investigating the discrepancy reduction model.

PubMed

Verkoeijen, Peter P J L; Rikers, Remy M J P; Schmidt, Henk G

2005-01-01

In this study, the authors examined the influence of prior knowledge activation on information processing by means of a prior knowledge activation procedure adopted from the read-generate paradigm. On the basis of cue-target pairs, participants in the experimental groups generated two different sets of items before studying a relevant list. Subsequently, participants were informed that they had to study the items in the list and that they should try to remember as many items as possible. The authors assessed the processing time allocated to the items in the list and free recall of those items. The results revealed that the experimental groups spent less time on items that had already been activated. In addition, the experimental groups outperformed the control group in overall free recall and in free recall of the activated items. Between-group comparisons did not demonstrate significant effects with respect to the processing time and free recall of nonactivated items. The authors interpreted these results in terms of the discrepancy reduction model of regulating the amount of processing time allocated to different parts of the list.

Leisure activities are linked to mental health benefits by providing time structure: comparing employed, unemployed and homemakers.

PubMed

Goodman, William K; Geiger, Ashley M; Wolf, Jutta M

2017-01-01

Unemployment has consistently been linked to negative mental health outcomes, emphasising the need to characterise the underlying mechanisms. The current study aimed at testing whether compared with other employment groups, fewer leisure activities observed in unemployment may contribute to elevated risk for negative mental health via loss of time structure. Depressive symptoms (Center for Epidemiologic Studies Depression), leisure activities (exercise, self-focused, social), and time structure (Time Structure Questionnaire (TSQ)) were assessed cross-sectionally in 406 participants (unemployed=155, employed=140, homemakers=111) recruited through Amazon Mechanical Turk. Controlling for gender and age, structural equation modelling revealed time structure partially (employed, homemakers) and fully (unemployed) mediated the relationship between leisure activities and depressive symptoms. With the exception of differential effects for structured routines, all other TSQ factors (sense of purpose, present orientation, effective organisation and persistence) contributed significantly to all models. These findings support the idea that especially for the unemployed, leisure activities impose their mental health benefits through increasing individuals' perception of spending their time effectively. Social leisure activities that provide a sense of daily structure may thereby be a particularly promising low-cost intervention to improve mental health in this population. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A queueing network model to analyze the impact of parallelization of care on patient cycle time.

PubMed

Jiang, Lixiang; Giachetti, Ronald E

2008-09-01

The total time a patient spends in an outpatient facility, called the patient cycle time, is a major contributor to overall patient satisfaction. A frequently recommended strategy to reduce the total time is to perform some activities in parallel thereby shortening patient cycle time. To analyze patient cycle time this paper extends and improves upon existing multi-class open queueing network model (MOQN) so that the patient flow in an urgent care center can be modeled. Results of the model are analyzed using data from an urgent care center contemplating greater parallelization of patient care activities. The results indicate that parallelization can reduce the cycle time for those patient classes which require more than one diagnostic and/ or treatment intervention. However, for many patient classes there would be little if any improvement, indicating the importance of tools to analyze business process reengineering rules. The paper makes contributions by implementing an approximation for fork/join queues in the network and by improving the approximation for multiple server queues in both low traffic and high traffic conditions. We demonstrate the accuracy of the MOQN results through comparisons to simulation results.

Pharmacokinetic-Pharmacodynamic Modeling of the In Vitro Activities of Oxazolidinone Antimicrobial Agents against Methicillin-Resistant Staphylococcus aureus▿

PubMed Central

Schmidt, Stephan; Sabarinath, Sreedharan Nair; Barbour, April; Abbanat, Darren; Manitpisitkul, Prasarn; Sha, Sue; Derendorf, Hartmut

2009-01-01

Linezolid is the first FDA-approved oxazolidinone with activity against clinically important gram-positive pathogens, including methicillin (meticillin)-resistant Staphylococcus aureus (MRSA). RWJ-416457 is a new oxazolidinone with an antimicrobial spectrum similar to that of linezolid. The goal of the present study was to develop a general pharmacokinetic (PK)-pharmacodynamic (PD) model that allows the characterization and comparison of the in vitro activities of oxazolidinones, determined in time-kill curve experiments, against MRSA. The in vitro activities of RWJ-416457 and the first-in-class representative, linezolid, against MRSA OC2878 were determined in static and dynamic time-kill curve experiments over a wide range of concentrations: 0.125 to 8 μg/ml (MIC, 0.5 μg/ml) and 0.25 to 16 μg/ml (MIC, 1 μg/ml), respectively. After correction for drug degradation during the time-kill curve experiments, a two-subpopulation model was simultaneously fitted to all data in the NONMEM VI program. The robustness of the model and the precision of the parameter estimates were evaluated by internal model validation by nonparametric bootstrap analysis. A two-subpopulation model, consisting of a self-replicating, oxazolidinone-susceptible and a persistent, oxazolidinone-insusceptible pool of bacteria was appropriate for the characterization of the time-kill curve data. The PK-PD model identified was capable of accounting for saturation in growth, delays in the onsets of growth and drug-induced killing, as well as naturally occurring bacterial death. The simultaneous fit of the proposed indirect-response, maximum-effect model to the data resulted in concentrations that produced a half-maximum killing effect that were significantly (P < 0.05) lower for RWJ-416457 (0.41 μg/ml) than for linezolid (1.39 μg/ml). In combination with the appropriate PK data, the susceptibility-based two-subpopulation model identified may provide valuable guidance for the selection of oxazolidinone doses or dose regimens for use in clinical studies. PMID:19786607

Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity

PubMed Central

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 arson - An exercise in qualitative model building

NASA Technical Reports Server (NTRS)

Heineke, J. M.

1975-01-01

A detailed example is given of the role of von Neumann and Morgenstern's 1944 'expected utility theorem' (in the theory of games and economic behavior) in qualitative model building. Specifically, an arsonist's decision as to the amount of time to allocate to arson and related activities is modeled, and the responsiveness of this time allocation to changes in various policy parameters is examined. Both the activity modeled and the method of presentation are intended to provide an introduction to the scope and power of the expected utility theorem in modeling situations of 'choice under uncertainty'. The robustness of such a model is shown to vary inversely with the number of preference restrictions used in the analysis. The fewer the restrictions, the wider is the class of agents to which the model is applicable, and accordingly more confidence is put in the derived results. A methodological discussion on modeling human behavior is included.

Near real time inverse source modeling and stress filed assessment: the requirement of a volcano fast response system

NASA Astrophysics Data System (ADS)

Shirzaei, Manoochehr; Walter, Thomas

2010-05-01

Volcanic unrest and eruptions are one of the major natural hazards next to earthquakes, floods, and storms. It has been shown that many of volcanic and tectonic unrests are triggered by changes in the stress field induced by nearby seismic and magmatic activities. In this study, as part of a mobile volcano fast response system so-called "Exupery" (www.exupery-vfrs.de) we present an arrangement for semi real time assessing the stress field excited by volcanic activity. This system includes; (1) an approach called "WabInSAR" dedicated for advanced processing of the satellite data and providing an accurate time series of the surface deformation [1, 2], (2) a time dependent inverse source modeling method to investigate the source of volcanic unrest using observed surface deformation data [3, 4], (3) the assessment of the changes in stress field induced by magmatic activity at the nearby volcanic and tectonic systems. This system is implemented in a recursive manner that allows handling large 3D data sets in an efficient and robust way which is requirement of an early warning system. We have applied and validated this arrangement on Mauna Loa volcano, Hawaii Island, to assess the influence of the time dependent activities of Mauna Loa on earthquake occurrence at the Kaoiki seismic zone. References [1] M. Shirzaei and T. R. Walter, "Wavelet based InSAR (WabInSAR): a new advanced time series approach for accurate spatiotemporal surface deformation monitoring," IEEE, pp. submitted, 2010. [2] M. Shirzaei and R. T. Walter, "Deformation interplay at Hawaii Island through InSAR time series and modeling," J. Geophys Res., vol. submited, 2009. [3] M. Shirzaei and T. R. Walter, "Randomly Iterated Search and Statistical Competency (RISC) as powerful inversion tools for deformation source modeling: application to volcano InSAR data," J. Geophys. Res., vol. 114, B10401, doi:10.1029/2008JB006071, 2009. [4] M. Shirzaei and T. R. Walter, "Genetic algorithm combined with Kalman filter as powerful tool for nonlinear time dependent inverse modelling: Application to volcanic deformation time series," J. Geophys. Res., pp. submitted, 2010.

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

NASA Astrophysics Data System (ADS)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

Leisure-time physical activity in relation to occupational physical activity among women.

PubMed

Ekenga, Christine C; Parks, Christine G; Wilson, Lauren E; Sandler, Dale P

2015-05-01

The objective of this study is to examine the association between occupational physical activity and leisure-time physical activity among US women in the Sister Study. We conducted a cross-sectional study of 26,334 women who had been employed in their current job for at least 1 year at baseline (2004-2009). Occupational physical activity was self-reported and leisure-time physical activity was estimated in metabolic equivalent hours per week. Log multinomial regression was used to evaluate associations between occupational (sitting, standing, manually active) and leisure-time (insufficient, moderate, high) activity. Models were adjusted for age, race/ethnicity, education, income, geographic region, and body mass index. Only 54% of women met or exceeded minimum recommended levels of leisure-time physical activity (moderate 32% and high 22%). Women who reported sitting (prevalence ratio (PR)=0.82, 95% confidence interval (CI): 0.74-0.92) or standing (PR=0.84, 95% CI: 0.75-0.94) most of the time at work were less likely to meet the requirements for high leisure-time physical activity than manually active workers. Associations were strongest among women living in the Northeast and the South. In this nationwide study, low occupational activity was associated with lower leisure-time physical activity. Women who are not active in the workplace may benefit from strategies to promote leisure-time physical activity. Published by Elsevier Inc.

Leisure-time physical activity in relation to occupational physical activity among women

PubMed Central

Ekenga, Christine C.; Parks, Christine G.; Wilson, Lauren E.; Sandler, Dale P.

2017-01-01

Objective To examine the association between occupational physical activity and leisure-time physical activity among US women in the Sister Study. Methods We conducted a cross-sectional study of 26,334 women who had been employed in their current job for at least 1 year at baseline (2004–2009). Occupational physical activity was self-reported and leisure-time physical activity was estimated in metabolic equivalent hours per week. Log multinomial regression was used to evaluate associations between occupational (sitting, standing, manually active) and leisure-time (insufficient, moderate, high) activity. Models were adjusted for age, race/ethnicity, education, income, geographic region, and body mass index. Results Only 54% of women met or exceeded minimum recommended levels of leisure-time physical activity (moderate 32% and high 22%). Women who reported sitting (PR = 0.82, 95% CI: 0.74–0.92) or standing (PR = 0.84, 95% CI: 0.75–0.94) most of the time at work were less likely to meet the requirements for high leisure-time physical activity than manually active workers. Associations were strongest among women living in the Northeast and the South. Conclusion In this nationwide study, low occupational activity was associated with lower leisure-time physical activity. Women who are not active in the workplace may benefit from strategies to promote leisure-time physical activity. PMID:25773471

Modeling bursts and heavy tails in human dynamics

NASA Astrophysics Data System (ADS)

Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László

2006-03-01

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can hadle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(τw)˜τw-α with α=3/2 . The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by α=1 . We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display α=1 , the surface mail based communication belongs to the α=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.

Modeling bursts and heavy tails in human dynamics.

PubMed

Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László

2006-03-01

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can handle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(tau(w)) approximately tau(w)(-alpha) with alpha=3/2. The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by alpha=1. We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display alpha=1, the surface mail based communication belongs to the alpha=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

Unfolding large-scale online collaborative human dynamics

PubMed Central

Zha, Yilong; Zhou, Tao; Zhou, Changsong

2016-01-01

Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with a precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double–power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to previous actions with a power-law waiting time, and (iii) population growth due to the increasing number of interacting individuals. This unfolding allows us to obtain an analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal “simplicity” beyond complex interacting human activities. PMID:27911766

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Effect of a sport education program on motivation for physical education and leisure-time physical activity.

PubMed

Wallhead, Tristan L; Garn, Alex C; Vidoni, Carla

2014-12-01

The purpose of this study was to examine the effect of a high school sport education curriculum program on students' motivation for physical education and leisure-time physical activity. Participants were 568 high school students enrolled in the required physical education programs at 2 schools, 1 taught using sport education and the 2nd using a multiactivity model of instruction. A motivational profile survey, which included student psychological need satisfaction, autonomous motives, perceived effort and enjoyment in physical education, and physical activity intention and behavior, was completed by all participants prior to and at the end of the 2-year physical education program. Mixed-model analysis of variance tests revealed that the students in the sport education program reported greater increases in perceived effort and enjoyment of the program compared with the students taught within the multiactivity model. Hierarchical multiple regression analyses showed that these positive affective outcomes were facilitated by the development of more autonomous forms of motivation. RESULTS revealed limited support for the direct transfer of motivation from a sport education program to increases in leisure-time physical activity behavior. Sport education facilitates more internalized forms of student motivation in required physical education programs, but without the provision of an appropriately designed extracurricular outlet, the potential of transfer to leisure-time physical activity may not be achieved.

Perceptions and the role of group exercise among New York City adults, 2010-2011: an examination of interpersonal factors and leisure-time physical activity.

PubMed

Firestone, Melanie J; Yi, Stella S; Bartley, Katherine F; Eisenhower, Donna L

2015-03-01

To examine associations of descriptive norms (i.e., behaviors of social group members) and exercising 'with a partner' or 'as a part of a group' on weekly leisure-time physical activity. T-tests and adjusted multivariable linear models were used to test the associations between descriptive norms and exercising with a partner or as a part of a group with self-reported leisure-time physical activity using the cross-sectional, population-based New York City Physical Activity and Transit (PAT) Survey 2010-2011 (n=3806). Overall, 70.6% of adult New Yorkers reported having physically active friends. Having active friends was associated with increased leisure-time physical activity; however, the effect varied by sex. Compared to those who did not have active friends, males with active friends reported two times more activity (56 min/week) and women reported two and a half times more activity (35 min/week) (both p-values<0.001). Physically active males and females who usually engaged in leisure-time activities as a part of a group reported 1.4 times more activity than those who exercised alone (both p-values<0.03). Descriptive norms and group exercise were associated with leisure-time physical activity among adults. Based on these associations, encouraging group exercise may be an effective strategy for increasing leisure-time physical activity among certain subgroups. Copyright © 2015 Elsevier Inc. All rights reserved.

Kinetic modeling of benzodiazepine receptor binding with PET and high specific activity [(11)C]Iomazenil in healthy human subjects.

PubMed

Bremner, J D; Horti, A; Staib, L H; Zea-Ponce, Y; Soufer, R; Charney, D S; Baldwin, R

2000-01-01

Quantitation of the PET benzodiazepine receptor antagonist, [(11)C]Iomazenil, using low specific activity radioligand was recently described. The purpose of this study was to quantitate benzodiazepine receptor binding in human subjects using PET and high specific activity [(11)C]Iomazenil. Six healthy human subjects underwent PET imaging following a bolus injection of high specific activity (>100 Ci/mmol) [(11)C]iomazenil. Arterial samples were collected at multiple time points after injection for measurement of unmetabolized total and nonprotein-bound parent compound in plasma. Time activity curves of radioligand concentration in brain and plasma were analyzed using two and three compartment model. Kinetic rate constants of transfer of radioligand between plasma, nonspecifically bound brain tissue, and specifically bound brain tissue compartments were fitted to the model. Values for fitted kinetic rate constants were used in the calculation of measures of benzodiazepine receptor binding, including binding potential (the ratio of receptor density to affinity), and product of BP and the fraction of free nonprotein-bound parent compound (V(3)'). Use of the three compartment model improved the goodness of fit in comparison to the two compartment model. Values for kinetic rate constants and measures of benzodiazepine receptor binding, including BP and V(3)', were similar to results obtained with the SPECT radioligand [(123)I]iomazenil, and a prior report with low specific activity [(11)C]Iomazenil. Kinetic modeling using the three compartment model with PET and high specific activity [(11)C]Iomazenil provides a reliable measure of benzodiazepine receptor binding. Synapse 35:68-77, 2000. Published 2000 Wiley-Liss, Inc.

Forecasting landslide activations by means of GA-SAKe. An example of application to three case studies in Calabria (Southern Italy)

NASA Astrophysics Data System (ADS)

Iovine, Giulio G. R.; De Rango, Alessio; Gariano, Stefano L.; Terranova, Oreste G.

2016-04-01

GA-SAKe - the Genetic-Algorithm based release of the hydrological model SAKe (Self Adaptive Kernel) - allows to forecast the timing of activation of landslides [1, 2], based on dates of landslide activations and rainfall series. The model can be applied to either single or set of similar landslides in a homogeneous context. Calibration of the model is performed through Genetic-Algorithm, and provides families of optimal, discretized solutions (kernels) that maximize the fitness function. The mobility functions are obtained through convolution of the optimal kernels with rain series. The shape of the kernel, including its base time, is related to magnitude of the landslide and hydro-geological complexity of the slope. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall. GA-SAKe is here employed to analyse the historical activations of three rock slides in Calabria (Southern Italy), threatening villages and main infrastructures. In particular: 1) the Acri-Serra di Buda case, developed within a Sackung, involving weathered crystalline and metamorphic rocks; for this case study, 6 dates of activation are available; 2) the San Fili-Uncino case, developed in clay and conglomerate overlaying gneiss and biotitic schist; for this case study, 7 dates of activation are available [2]; 3) the San Benedetto Ullano-San Rocco case, developed in weathered metamorphic rocks; for this case study, 3 dates of activation are available [1, 3, 4, 5]. The obtained results are quite promising, given the high performance of the model against slope movements characterized by numerous historical activations. Obtained results, in terms of shape and base time of the kernels, are compared by taking into account types and sizes of the considered case studies, and involved rock types. References [1] Terranova O.G., Iaquinta P., Gariano S.L., Greco R. & Iovine G. (2013) In: Landslide Science and Practice, Margottini, Canuti, Sassa (Eds.), Vol. 3, pp.73-79. [2] Terranova O.G., Gariano S.L., Iaquinta P. & Iovine G.G.R. (2015). Geosci. Model Dev., 8, 1955-1978. [3] Iovine G., Iaquinta P. & Terranova O. (2009). In Anderssen, Braddock & Newham (Eds.), Proc. 18th World IMACS Congr. and MODSIM09 Int. Congr. on Modelling and Simulation, pp. 2686-2693. [4] Iovine G., Lollino P., Gariano S.L. & Terranova O.G. (2010). NHESS, 10, 2341-2354. [5] Capparelli G., Iaquinta P., Iovine G., Terranova O.G. & Versace P. (2012). Natural Hazards, 61(1), pp.247-256.

A unifying model of concurrent spatial and temporal modularity in muscle activity.

PubMed

Delis, Ioannis; Panzeri, Stefano; Pozzo, Thierry; Berret, Bastien

2014-02-01

Modularity in the central nervous system (CNS), i.e., the brain capability to generate a wide repertoire of movements by combining a small number of building blocks ("modules"), is thought to underlie the control of movement. Numerous studies reported evidence for such a modular organization by identifying invariant muscle activation patterns across various tasks. However, previous studies relied on decompositions differing in both the nature and dimensionality of the identified modules. Here, we derive a single framework that encompasses all influential models of muscle activation modularity. We introduce a new model (named space-by-time decomposition) that factorizes muscle activations into concurrent spatial and temporal modules. To infer these modules, we develop an algorithm, referred to as sample-based nonnegative matrix trifactorization (sNM3F). We test the space-by-time decomposition on a comprehensive electromyographic dataset recorded during execution of arm pointing movements and show that it provides a low-dimensional yet accurate, highly flexible and task-relevant representation of muscle patterns. The extracted modules have a well characterized functional meaning and implement an efficient trade-off between replication of the original muscle patterns and task discriminability. Furthermore, they are compatible with the modules extracted from existing models, such as synchronous synergies and temporal primitives, and generalize time-varying synergies. Our results indicate the effectiveness of a simultaneous but separate condensation of spatial and temporal dimensions of muscle patterns. The space-by-time decomposition accommodates a unified view of the hierarchical mapping from task parameters to coordinated muscle activations, which could be employed as a reference framework for studying compositional motor control.

Emotional moments across time: a possible neural basis for time perception in the anterior insula

PubMed Central

Craig, A.D. (Bud)

2009-01-01

A model of awareness based on interoceptive salience is described, which has an endogenous time base that might provide a basis for the human capacity to perceive and estimate time intervals in the range of seconds to subseconds. The model posits that the neural substrate for awareness across time is located in the anterior insular cortex, which fits with recent functional imaging evidence relevant to awareness and time perception. The time base in this model is adaptive and emotional, and thus it offers an explanation for some aspects of the subjective nature of time perception. This model does not describe the mechanism of the time base, but it suggests a possible relationship with interoceptive afferent activity, such as heartbeat-related inputs. PMID:19487195

Epidemic spreading on activity-driven networks with attractiveness.

PubMed

Pozzana, Iacopo; Sun, Kaiyuan; Perra, Nicola

2017-10-01

We study SIS epidemic spreading processes unfolding on a recent generalization of the activity-driven modeling framework. In this model of time-varying networks, each node is described by two variables: activity and attractiveness. The first describes the propensity to form connections, while the second defines the propensity to attract them. We derive analytically the epidemic threshold considering the time scale driving the evolution of contacts and the contagion as comparable. The solutions are general and hold for any joint distribution of activity and attractiveness. The theoretical picture is confirmed via large-scale numerical simulations performed considering heterogeneous distributions and different correlations between the two variables. We find that heterogeneous distributions of attractiveness alter the contagion process. In particular, in the case of uncorrelated and positive correlations between the two variables, heterogeneous attractiveness facilitates the spreading. On the contrary, negative correlations between activity and attractiveness hamper the spreading. The results presented contribute to the understanding of the dynamical properties of time-varying networks and their effects on contagion phenomena unfolding on their fabric.

Complex-envelope alternating-direction-implicit FDTD method for simulating active photonic devices with semiconductor/solid-state media.

PubMed

Singh, Gurpreet; Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2012-06-15

A complex-envelope (CE) alternating-direction-implicit (ADI) finite-difference time-domain (FDTD) approach to treat light-matter interaction self-consistently with electromagnetic field evolution for efficient simulations of active photonic devices is presented for the first time (to our best knowledge). The active medium (AM) is modeled using an efficient multilevel system of carrier rate equations to yield the correct carrier distributions, suitable for modeling semiconductor/solid-state media accurately. To include the AM in the CE-ADI-FDTD method, a first-order differential system involving CE fields in the AM is first set up. The system matrix that includes AM parameters is then split into two time-dependent submatrices that are then used in an efficient ADI splitting formula. The proposed CE-ADI-FDTD approach with AM takes 22% of the time as the approach of the corresponding explicit FDTD, as validated by semiconductor microdisk laser simulations.

Optimal weighted averaging of event related activity from acquisitions with artifacts.

PubMed

Vollero, Luca; Petrichella, Sara; Innello, Giulio

2016-08-01

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

Viscoelastic and elastomeric active matter: linear instability and nonlinear dynamics

NASA Astrophysics Data System (ADS)

Hemingway, Ewan J.; Cates, M. E.; Marchetti, M. C.; Fielding, S. M.

We consider a continuum model of active viscoelastic matter, whereby a model of an active nematic liquid-crystal is coupled to a minimal model of polymer dynamics with a viscoelastic relaxation time τc. To explore the resulting interplay between active and polymeric dynamics, we first generalise a linear stability analysis (from earlier studies without polymer) to derive criteria for the onset of spontaneous flow. Perhaps surprisingly, our results show that the spontaneous flow instability persists even for divergent polymer relaxation times. We explore the novel dynamical states to which these instabilities lead by means of nonlinear numerical simulations. This reveals oscillatory shear-banded states in 1D, and activity-driven turbulence in 2D, even in the limit τc --> ∞ . Adding polymer can also have calming effects, increasing the net throughput of spontaneous flow along a channel in a new type of ''drag-reduction'', an effect that may have implications for cytoplasmic streaming processes within the cell.

Response surface modeling of acid activation of raw diatomite using in sunflower oil bleaching by: Box-Behnken experimental design.

PubMed

Larouci, M; Safa, M; Meddah, B; Aoues, A; Sonnet, P

2015-03-01

The optimum conditions for acid activation of diatomite for maximizing bleaching efficiency of the diatomite in sun flower oil treatment were studied. Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed to obtain the optimum conditions of three independent variables (acid concentration, activation time and solid to liquid) for acid activation of diatomite. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95 % confidence limits (α = 0.05). The optimum values of the selected variables were obtained by solving the quadratic regression model, as well as by analyzing the response surface contour plots. The experimental conditions at this global point were determined to be acid concentration = 8.963 N, activation time = 11.9878 h, and solid to liquid ratio = 221.2113 g/l, the corresponding bleaching efficiency was found to be about 99 %.

Validity of "sputtering and re-condensation" model in active screen cage plasma nitriding process

NASA Astrophysics Data System (ADS)

Saeed, A.; Khan, A. W.; Jan, F.; Abrar, M.; Khalid, M.; Zakaullah, M.

2013-05-01

The validity of "sputtering and re-condensation" model in active screen plasma nitriding for nitrogen mass transfer mechanism is investigated. The dominant species including NH, Fe-I, N2+, N-I and N2 along with Hα and Hβ lines are observed in the optical emission spectroscopy (OES) analysis. Active screen cage and dc plasma nitriding of AISI 316 stainless steel as function of treatment time is also investigated. The structure and phases composition of the nitrided layer is studied by X-ray diffraction (XRD). Surface morphology is studied by scanning electron microscopy (SEM) and hardness profile is obtained by Vicker's microhardness tester. Increasing trend in microhardness is observed in both cases but the increase in active screen plasma nitriding is about 3 times greater than that achieved by dc plasma nitriding. On the basis of metallurgical and OES observations the use of "sputtering and re-condensation" model in active screen plasma nitriding is tested.

In Vitro Pharmacodynamic Activities of ABT-492, a Novel Quinolone, Compared to Those of Levofloxacin against Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis

PubMed Central

Gunderson, Shana M.; Hayes, Robert A.; Quinn, John P.; Danziger, Larry H.

2004-01-01

ABT-492 is a novel quinolone with potent activity against gram-positive, gram-negative, and atypical pathogens, making this compound an ideal candidate for the treatment of community-acquired pneumonia. We therefore compared the in vitro pharmacodynamic activity of ABT-492 to that of levofloxacin, an antibiotic commonly used for the treatment of pneumonia, through MIC determination and time-kill kinetic analysis. ABT-492 demonstrated potent activity against penicillin-sensitive, penicillin-resistant, and levofloxacin-resistant Streptococcus pneumoniae strains (MICs ranging from 0.0078 to 0.125 μg/ml); β-lactamase-positive and β-lactamase-negative Haemophilus influenzae strains (MICs ranging from 0.000313 to 0.00125 μg/ml); and β-lactamase-positive and β-lactamase-negative Moraxella catarrhalis strains (MICs ranging from 0.001 to 0.0025 μg/ml), with MICs being much lower than those of levofloxacin. Both ABT-492 and levofloxacin demonstrated concentration-dependent bactericidal activities in time-kill kinetics studies at four and eight times the MIC with 10 of 12 bacterial isolates exposed to ABT-492 and with 12 of 12 bacterial isolates exposed to levofloxacin. Sigmoidal maximal-effect models support concentration-dependent bactericidal activity. The model predicts that 50% of maximal activity can be achieved with concentrations ranging from one to two times the MIC for both ABT-492 and levofloxacin and that near-maximal activity (90% effective concentration) can be achieved at concentrations ranging from two to five times the MIC for ABT-492 and one to six times the MIC for levofloxacin. PMID:14693540

In vitro pharmacodynamic activities of ABT-492, a novel quinolone, compared to those of levofloxacin against Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis.

PubMed

Gunderson, Shana M; Hayes, Robert A; Quinn, John P; Danziger, Larry H

2004-01-01

ABT-492 is a novel quinolone with potent activity against gram-positive, gram-negative, and atypical pathogens, making this compound an ideal candidate for the treatment of community-acquired pneumonia. We therefore compared the in vitro pharmacodynamic activity of ABT-492 to that of levofloxacin, an antibiotic commonly used for the treatment of pneumonia, through MIC determination and time-kill kinetic analysis. ABT-492 demonstrated potent activity against penicillin-sensitive, penicillin-resistant, and levofloxacin-resistant Streptococcus pneumoniae strains (MICs ranging from 0.0078 to 0.125 micro g/ml); beta-lactamase-positive and beta-lactamase-negative Haemophilus influenzae strains (MICs ranging from 0.000313 to 0.00125 micro g/ml); and beta-lactamase-positive and beta-lactamase-negative Moraxella catarrhalis strains (MICs ranging from 0.001 to 0.0025 micro g/ml), with MICs being much lower than those of levofloxacin. Both ABT-492 and levofloxacin demonstrated concentration-dependent bactericidal activities in time-kill kinetics studies at four and eight times the MIC with 10 of 12 bacterial isolates exposed to ABT-492 and with 12 of 12 bacterial isolates exposed to levofloxacin. Sigmoidal maximal-effect models support concentration-dependent bactericidal activity. The model predicts that 50% of maximal activity can be achieved with concentrations ranging from one to two times the MIC for both ABT-492 and levofloxacin and that near-maximal activity (90% effective concentration) can be achieved at concentrations ranging from two to five times the MIC for ABT-492 and one to six times the MIC for levofloxacin.

[Influence of antitumor system rhenium-platinum on biochemical state of the liver].

PubMed

Ivchuk, V V; Polishko, T M; Golichenko, O A; Shtemenko, O V; Shtemenko, N I

2011-01-01

Influence of the antitumour rhenium-platinum system on biochemical liver characteristics in the model of tumor growth (Guerin carcinoma) was studied and possible hepatoprotective activity of rhenium cluster compounds when introducing them in different forms was shown, that was confirmed by decreasing of diagnostic enzymes activity in blood (aminotransferase--AST 6 times and ALT 5.6 times, lactatedehydrogenase 4.9 times, gamma-glutamyltranspeptidase 3.6 times) and normalization of morphological state of the liver cells. The hepatoprotective activity of the cluster rhenium compound with adamanthyl ligands was confirmed in the model of acute toxic hepatitis. Introduction of this compound led to reduction of the concentration of MDA in homogenates of liver tissue (2 times), and in blood plasma (3.8 times); to reduction of levels of diagnostic liver enzymes in blood--AST and ALT 5.8 and 5.5 times respectively in comparison with control group. Some aspects of the mechanism of hepatoprotection were discussed, that included the presence of conjugated systems around the quadrupol rhenium-rhenium bond and alkyl radicals with significant positive inductive effects.

Generation of the Human Biped Stance by a Neural Controller Able to Compensate Neurological Time Delay

PubMed Central

Jiang, Ping; Chiba, Ryosuke; Takakusaki, Kaoru; Ota, Jun

2016-01-01

The development of a physiologically plausible computational model of a neural controller that can realize a human-like biped stance is important for a large number of potential applications, such as assisting device development and designing robotic control systems. In this paper, we develop a computational model of a neural controller that can maintain a musculoskeletal model in a standing position, while incorporating a 120-ms neurological time delay. Unlike previous studies that have used an inverted pendulum model, a musculoskeletal model with seven joints and 70 muscular-tendon actuators is adopted to represent the human anatomy. Our proposed neural controller is composed of both feed-forward and feedback controls. The feed-forward control corresponds to the constant activation input necessary for the musculoskeletal model to maintain a standing posture. This compensates for gravity and regulates stiffness. The developed neural controller model can replicate two salient features of the human biped stance: (1) physiologically plausible muscle activations for quiet standing; and (2) selection of a low active stiffness for low energy consumption. PMID:27655271

Dynamics of human T-cell lymphotropic virus I (HTLV-I) infection of CD4+ T-cells.

PubMed

Katri, Patricia; Ruan, Shigui

2004-11-01

Stilianakis and Seydel (Bull. Math. Biol., 1999) proposed an ODE model that describes the T-cell dynamics of human T-cell lymphotropic virus I (HTLV-I) infection and the development of adult T-cell leukemia (ATL). Their model consists of four components: uninfected healthy CD4+ T-cells, latently infected CD4+ T-cells, actively infected CD4+ T-cells, and ATL cells. Mathematical analysis that completely determines the global dynamics of this model has been done by Wang et al. (Math. Biosci., 2002). In this note, we first modify the parameters of the model to distinguish between contact and infectivity rates. Then we introduce a discrete time delay to the model to describe the time between emission of contagious particles by active CD4+ T-cells and infection of pure cells. Using the results in Culshaw and Ruan (Math. Biosci., 2000) in the analysis of time delay with respect to cell-free viral spread of HIV, we study the effect of time delay on the stability of the endemically infected equilibrium. Numerical simulations are presented to illustrate the results.

Real-time hydrological early warning system at national scale for surface water and groundwater with stakeholder involvement

NASA Astrophysics Data System (ADS)

He, X.; Stisen, S.; Henriksen, H. J.

2015-12-01

Hydrological models are important tools to support decision making in water resource management in the past few decades. Nowadays, frequent occurrence of extreme hydrological events has put focus on development of real-time hydrological modeling and forecasting systems. Among the various types of hydrological models, it is only the rainfall-runoff models for surface water that are commonly used in the online real-time fashion; and there is never a tradition to use integrated hydrological models for both surface water and groundwater with large scale perspective. At the Geological Survey of Denmark and Greenland (GEUS), we have setup and calibrated an integrated hydrological model that covers the entire nation, namely the DK-model. So far, the DK-model has only been used in offline mode for historical and future scenario simulations. Therefore, challenges arise when operating the DK-model in real-time mode due to lack of technical experiences and stakeholder awareness. In the present study, we try to demonstrate the process of bringing the DK-model online while actively involving the opinions of the stakeholders. Although the system is not yet fully operational, a prototype has been finished and presented to the stakeholders which can simulate groundwater levels, streamflow and water content in the root zone with a lead time of 48 hours and refreshed every 6 hours. The active involvement of stakeholders has provided very valuable insights and feedbacks for future improvements.

Rethinking food anticipatory activity in the activity-based anorexia rat model.

PubMed

Wu, Hemmings; van Kuyck, Kris; Tambuyzer, Tim; Luyten, Laura; Aerts, Jean-Marie; Nuttin, Bart

2014-01-29

When a rat is on a limited fixed-time food schedule with full access to a running wheel (activity-based anorexia model, ABA), its activity level will increase hours prior to the feeding period. This activity, called food-anticipatory activity (FAA), is a hypothesized parallel to the hyperactivity symptom in human anorexia nervosa. To investigate in depth the characteristics of FAA, we retrospectively analyzed the level of FAA and activities during other periods in ABA rats. To our surprise, rats with the most body weight loss have the lowest level of FAA, which contradicts the previously established link between FAA and the severity of ABA symptoms. On the contrary, our study shows that postprandial activities are more directly related to weight loss. We conclude that FAA alone may not be sufficient to reflect model severity, and activities during other periods may be of potential value in studies using ABA model.

The p-wave upper mantle structure beneath an active spreading centre - The Gulf of California

NASA Technical Reports Server (NTRS)

Walck, M. C.

1984-01-01

Over 1400 seismograms of earthquakes in Mexico are analyzed and data sets for the travel time, apparent phase velocity, and relative amplitude information are utilized to produce a tightly constrained, detailed model for depths to 900 km beneath an active oceanic ridge region, the Gulf of California. The data are combined by first inverting the travel times, perturbing that model to fit the p-delta data, and then performing trial and error synthetic seismogram modelling to fit the short-period waveforms. The final model satisfies all three data sets. The ridge model is similar to existing upper mantle models for shield, tectonic-continental, and arc-trench regimes below 400 km, but differs significantly in the upper 350 km. Ridge model velocities are very low in this depth range; the model 'catches up' with the others with a very large velocity gradient from 225 to 390 km.

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property

PubMed Central

Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio

2017-01-01

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi. PMID:29308273

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property.

PubMed

Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio; Trovato, Antonio

2017-12-01

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida , a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence 'quenching' after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi .

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

USGS Publications Warehouse

Dorazio, Robert; Karanth, K. Ullas

2017-01-01

MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.

Developmental patterns and parental correlates of youth leisure-time physical activity.

PubMed

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. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Time with friends and physical activity as mechanisms linking obesity and television viewing among youth.

PubMed

Vandewater, Elizabeth A; Park, Seoung Eun; Hébert, Emily T; Cummings, Hope M

2015-07-27

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. 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). 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). 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 between weight status and television viewing to more nuanced explanatory models which attempt to identify and unpack the possible mechanisms linking them.

Genetic and environmental influences on the allocation of adolescent leisure time activities.

PubMed

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.

Genetic and Environmental Influences on the Allocation of Adolescent Leisure Time Activities

PubMed Central

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

Integrating the New Immigrant: A Model for Social Work Practice in Transitional States

ERIC Educational Resources Information Center

Golan, Naomi; Gruschka, Ruth

1971-01-01

The authors of this paper cast the process of immigration in the prevention intervention framework and offer a model for activity in six key areas: income management, health, housing, education, leisure time activities, and citizenship, by which the integration absorption crisis can be successfully resolved. (Author)

An Active Learning Approach to Teach Advanced Multi-Predictor Modeling Concepts to Clinicians

ERIC Educational Resources Information Center

Samsa, Gregory P.; Thomas, Laine; Lee, Linda S.; Neal, Edward M.

2012-01-01

Clinicians have characteristics--high scientific maturity, low tolerance for symbol manipulation and programming, limited time outside of class--that limit the effectiveness of traditional methods for teaching multi-predictor modeling. We describe an active-learning based approach that shows particular promise for accommodating these…

Gender differences in social support and leisure-time physical activity

PubMed Central

Oliveira, Aldair J; Lopes, Claudia S; Rostila, Mikael; Werneck, Guilherme Loureiro; Griep, Rosane Härter; de Leon, Antônio Carlos Monteiro Ponce; Faerstein, Eduardo

2014-01-01

OBJECTIVE To identify gender differences in social support dimensions’ effect on adults’ leisure-time physical activity maintenance, type, and time. METHODS Longitudinal study of 1,278 non-faculty public employees at a university in Rio de Janeiro, RJ, Southeastern Brazil. Physical activity was evaluated using a dichotomous question with a two-week reference period, and further questions concerning leisure-time physical activity type (individual or group) and time spent on the activity. Social support was measured with the Medical Outcomes Study Social Support Scale. For the analysis, logistic regression models were adjusted separately by gender. RESULTS A multinomial logistic regression showed an association between material support and individual activities among women (OR = 2.76; 95%CI 1.2;6.5). Affective support was associated with time spent on leisure-time physical activity only among men (OR = 1.80; 95%CI 1.1;3.2). CONCLUSIONS All dimensions of social support that were examined influenced either the type of, or the time spent on, leisure-time physical activity. In some social support dimensions, the associations detected varied by gender. Future studies should attempt to elucidate the mechanisms involved in these gender differences. PMID:25210819

Occupational Physical Activity Habits of UK Office Workers: Cross-Sectional Data from the Active Buildings Study.

PubMed

Smith, Lee; Sawyer, Alexia; Gardner, Benjamin; Seppala, Katri; Ucci, Marcella; Marmot, Alexi; Lally, Pippa; Fisher, Abi

2018-06-09

Habitual behaviours are learned responses that are triggered automatically by associated environmental cues. The unvarying nature of most workplace settings makes workplace physical activity a prime candidate for a habitual behaviour, yet the role of habit strength in occupational physical activity has not been investigated. Aims of the present study were to: (i) document occupational physical activity habit strength; and (ii) investigate associations between occupational activity habit strength and occupational physical activity levels. A sample of UK office-based workers ( n = 116; 53% female, median age 40 years, SD 10.52) was fitted with activPAL accelerometers worn for 24 h on five consecutive days, providing an objective measure of occupational step counts, stepping time, sitting time, standing time and sit-to-stand transitions. A self-report index measured the automaticity of two occupational physical activities (“being active” (e.g., walking to printers and coffee machines) and “stair climbing”). Adjusted linear regression models investigated the association between occupational activity habit strength and objectively-measured occupational step counts, stepping time, sitting time, standing time and sit-to-stand transitions. Eighty-one per cent of the sample reported habits for “being active”, and 62% reported habits for “stair climbing”. In adjusted models, reported habit strength for “being active” were positively associated with average occupational sit-to-stand transitions per hour (B = 0.340, 95% CI: 0.053 to 0.627, p = 0.021). “Stair climbing” habit strength was unexpectedly negatively associated with average hourly stepping time (B = −0.01, 95% CI: −0.01 to −0.00, p = 0.006) and average hourly occupational step count (B = −38.34, 95% CI: −72.81 to −3.88, p = 0.030), which may reflect that people with stronger stair-climbing habits compensate by walking fewer steps overall. Results suggest that stair-climbing and office-based occupational activity can be habitual. Interventions might fruitfully promote habitual workplace activity, although, in light of potential compensation effects, such interventions should perhaps focus on promoting moderate-intensity activity.

Dynamic 99mTc-MAG3 renography: images for quality control obtained by combining pharmacokinetic modelling, an anthropomorphic computer phantom and Monte Carlo simulated scintillation camera imaging

NASA Astrophysics Data System (ADS)

Brolin, Gustav; Sjögreen Gleisner, Katarina; Ljungberg, Michael

2013-05-01

In dynamic renal scintigraphy, the main interest is the radiopharmaceutical redistribution as a function of time. Quality control (QC) of renal procedures often relies on phantom experiments to compare image-based results with the measurement setup. A phantom with a realistic anatomy and time-varying activity distribution is therefore desirable. This work describes a pharmacokinetic (PK) compartment model for 99mTc-MAG3, used for defining a dynamic whole-body activity distribution within a digital phantom (XCAT) for accurate Monte Carlo (MC)-based images for QC. Each phantom structure is assigned a time-activity curve provided by the PK model, employing parameter values consistent with MAG3 pharmacokinetics. This approach ensures that the total amount of tracer in the phantom is preserved between time points, and it allows for modifications of the pharmacokinetics in a controlled fashion. By adjusting parameter values in the PK model, different clinically realistic scenarios can be mimicked, regarding, e.g., the relative renal uptake and renal transit time. Using the MC code SIMIND, a complete set of renography images including effects of photon attenuation, scattering, limited spatial resolution and noise, are simulated. The obtained image data can be used to evaluate quantitative techniques and computer software in clinical renography.

Time-driven activity-based costing: A dynamic value assessment model in pediatric appendicitis.

PubMed

Yu, Yangyang R; Abbas, Paulette I; Smith, Carolyn M; Carberry, Kathleen E; Ren, Hui; Patel, Binita; Nuchtern, Jed G; Lopez, Monica E

2017-06-01

Healthcare reform policies are emphasizing value-based healthcare delivery. We hypothesize that time-driven activity-based costing (TDABC) can be used to appraise healthcare interventions in pediatric appendicitis. Triage-based standing delegation orders, surgical advanced practice providers, and a same-day discharge protocol were implemented to target deficiencies identified in our initial TDABC model. Post-intervention process maps for a hospital episode were created using electronic time stamp data for simple appendicitis cases during February to March 2016. Total personnel and consumable costs were determined using TDABC methodology. The post-intervention TDABC model featured 6 phases of care, 33 processes, and 19 personnel types. Our interventions reduced duration and costs in the emergency department (-41min, -$23) and pre-operative floor (-57min, -$18). While post-anesthesia care unit duration and costs increased (+224min, +$41), the same-day discharge protocol eliminated post-operative floor costs (-$306). Our model incorporating all three interventions reduced total direct costs by 11% ($2753.39 to $2447.68) and duration of hospitalization by 51% (1984min to 966min). Time-driven activity-based costing can dynamically model changes in our healthcare delivery as a result of process improvement interventions. It is an effective tool to continuously assess the impact of these interventions on the value of appendicitis care. II, Type of study: Economic Analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

Fast maximum likelihood estimation using continuous-time neural point process models.

PubMed

Lepage, Kyle Q; MacDonald, Christopher J

2015-06-01

A recent report estimates that the number of simultaneously recorded neurons is growing exponentially. A commonly employed statistical paradigm using discrete-time point process models of neural activity involves the computation of a maximum-likelihood estimate. The time to computate this estimate, per neuron, is proportional to the number of bins in a finely spaced discretization of time. By using continuous-time models of neural activity and the optimally efficient Gaussian quadrature, memory requirements and computation times are dramatically decreased in the commonly encountered situation where the number of parameters p is much less than the number of time-bins n. In this regime, with q equal to the quadrature order, memory requirements are decreased from O(np) to O(qp), and the number of floating-point operations are decreased from O(np(2)) to O(qp(2)). Accuracy of the proposed estimates is assessed based upon physiological consideration, error bounds, and mathematical results describing the relation between numerical integration error and numerical error affecting both parameter estimates and the observed Fisher information. A check is provided which is used to adapt the order of numerical integration. The procedure is verified in simulation and for hippocampal recordings. It is found that in 95 % of hippocampal recordings a q of 60 yields numerical error negligible with respect to parameter estimate standard error. Statistical inference using the proposed methodology is a fast and convenient alternative to statistical inference performed using a discrete-time point process model of neural activity. It enables the employment of the statistical methodology available with discrete-time inference, but is faster, uses less memory, and avoids any error due to discretization.

Space-time evolution of a growth fold (Betic Cordillera, Spain). Evidences from 3D geometrical modelling

NASA Astrophysics Data System (ADS)

Martin-Rojas, Ivan; Alfaro, Pedro; Estévez, Antonio

2014-05-01

We present a study that encompasses several software tools (iGIS©, ArcGIS©, Autocad©, etc.) and data (geological mapping, high resolution digital topographic data, high resolution aerial photographs, etc.) to create a detailed 3D geometric model of an active fault propagation growth fold. This 3D model clearly shows structural features of the analysed fold, as well as growth relationships and sedimentary patterns. The results obtained permit us to discuss the kinematics and structural evolution of the fold and the fault in time and space. The study fault propagation fold is the Crevillente syncline. This fold represents the northern limit of the Bajo Segura Basin, an intermontane basin in the Eastern Betic Cordillera (SE Spain) developed from upper Miocene on. 3D features of the Crevillente syncline, including growth pattern, indicate that limb rotation and, consequently, fault activity was higher during Messinian than during Tortonian; consequently, fault activity was also higher. From Pliocene on our data point that limb rotation and fault activity steadies or probably decreases. This in time evolution of the Crevillente syncline is not the same all along the structure; actually the 3D geometric model indicates that observed lateral heterogeneity is related to along strike variation of fault displacement.

Marked point process for modelling seismic activity (case study in Sumatra and Java)

NASA Astrophysics Data System (ADS)

Pratiwi, Hasih; Sulistya Rini, Lia; Wayan Mangku, I.

2018-05-01

Earthquake is a natural phenomenon that is random, irregular in space and time. Until now the forecast of earthquake occurrence at a location is still difficult to be estimated so that the development of earthquake forecast methodology is still carried out both from seismology aspect and stochastic aspect. To explain the random nature phenomena, both in space and time, a point process approach can be used. There are two types of point processes: temporal point process and spatial point process. The temporal point process relates to events observed over time as a sequence of time, whereas the spatial point process describes the location of objects in two or three dimensional spaces. The points on the point process can be labelled with additional information called marks. A marked point process can be considered as a pair (x, m) where x is the point of location and m is the mark attached to the point of that location. This study aims to model marked point process indexed by time on earthquake data in Sumatra Island and Java Island. This model can be used to analyse seismic activity through its intensity function by considering the history process up to time before t. Based on data obtained from U.S. Geological Survey from 1973 to 2017 with magnitude threshold 5, we obtained maximum likelihood estimate for parameters of the intensity function. The estimation of model parameters shows that the seismic activity in Sumatra Island is greater than Java Island.

Hydromechanical Earthquake Nucleation Model Forecasts Onset, Peak, and Falling Rates of Induced Seismicity in Oklahoma and Kansas

NASA Astrophysics Data System (ADS)

Norbeck, J. H.; Rubinstein, J. L.

2018-04-01

The earthquake activity in Oklahoma and Kansas that began in 2008 reflects the most widespread instance of induced seismicity observed to date. We develop a reservoir model to calculate the hydrologic conditions associated with the activity of 902 saltwater disposal wells injecting into the Arbuckle aquifer. Estimates of basement fault stressing conditions inform a rate-and-state friction earthquake nucleation model to forecast the seismic response to injection. Our model replicates many salient features of the induced earthquake sequence, including the onset of seismicity, the timing of the peak seismicity rate, and the reduction in seismicity following decreased disposal activity. We present evidence for variable time lags between changes in injection and seismicity rates, consistent with the prediction from rate-and-state theory that seismicity rate transients occur over timescales inversely proportional to stressing rate. Given the efficacy of the hydromechanical model, as confirmed through a likelihood statistical test, the results of this study support broader integration of earthquake physics within seismic hazard analysis.

Modelling of different enzyme productions by solid-state fermentation on several agro-industrial residues.

PubMed

Diaz, Ana Belen; Blandino, Ana; Webb, Colin; Caro, Ildefonso

2016-11-01

A simple kinetic model, with only three fitting parameters, for several enzyme productions in Petri dishes by solid-state fermentation is proposed in this paper, which may be a valuable tool for simulation of this type of processes. Basically, the model is able to predict temporal fungal enzyme production by solid-state fermentation on complex substrates, maximum enzyme activity expected and time at which these maxima are reached. In this work, several fermentations in solid state were performed in Petri dishes, using four filamentous fungi grown on different agro-industrial residues, measuring xylanase, exo-polygalacturonase, cellulose and laccase activities over time. Regression coefficients after fitting experimental data to the proposed model turned out to be quite high in all cases. In fact, these results are very interesting considering, on the one hand, the simplicity of the model and, on the other hand, that enzyme activities correspond to different enzymes, produced by different fungi on different substrates.

Option pricing for stochastic volatility model with infinite activity Lévy jumps

NASA Astrophysics Data System (ADS)

Gong, Xiaoli; Zhuang, Xintian

2016-08-01

The purpose of this paper is to apply the stochastic volatility model driven by infinite activity Lévy processes to option pricing which displays infinite activity jumps behaviors and time varying volatility that is consistent with the phenomenon observed in underlying asset dynamics. We specially pay attention to three typical Lévy processes that replace the compound Poisson jumps in Bates model, aiming to capture the leptokurtic feature in asset returns and volatility clustering effect in returns variance. By utilizing the analytical characteristic function and fast Fourier transform technique, the closed form formula of option pricing can be derived. The intelligent global optimization search algorithm called Differential Evolution is introduced into the above highly dimensional models for parameters calibration so as to improve the calibration quality of fitted option models. Finally, we perform empirical researches using both time series data and options data on financial markets to illustrate the effectiveness and superiority of the proposed method.

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

DOT National Transportation Integrated Search

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Modeling growth of three bakery product spoilage molds as a function of water activity, temperature and pH.

PubMed

Dagnas, Stéphane; Onno, Bernard; Membré, Jeanne-Marie

2014-09-01

The objective of this study was to quantify the effect of water activity, pH and storage temperature on the growth of Eurotium repens, Aspergillus niger and Penicillium corylophilum, isolated from spoiled bakery products. Moreover, the behaviors of these three mold species were compared to assess whether a general modeling framework may be set and re-used in future research on bakery spoilage molds. The mold growth was modeled by building two distinct Gamma-type secondary models: one on the lag time for growth and another one on the radial growth rate. A set of 428 experimental growth curves was generated. The effect of temperature (15-35 °C), water activity (0.80-0.98) and pH (3-7) was assessed. Results showed that it was not possible to apply the same set of secondary model equations to the three mold species given that the growth rate varied significantly with the factors pH and water activity. In contrast, the temperature effect on both growth rate and lag time of the three mold species was described by the same equation. The equation structure and model parameter values of the Gamma models were also compared per mold species to assess whether a relationship between lag time and growth rate existed. There was no correlation between the two growth responses for E. repens, but a slight one for A. niger and P. corylophilum. These findings will help in determining bakery product shelf-life and guiding future work in the predictive mycology field. Copyright © 2014 Elsevier B.V. All rights reserved.

Activation Time of Cardiac Tissue In Response to a Linear Array of Spatial Alternating Bipolar Electrodes

NASA Astrophysics Data System (ADS)

Mashburn, David; Wikswo, John

2007-11-01

Prevailing theories about the response of the heart to high field shocks predict that local regions of high resistivity distributed throughout the heart create multiple small virtual electrodes that hyperpolarize or depolarize tissue and lead to widespread activation. This resetting of bulk tissue is responsible for the successful functioning of cardiac defibrillators. By activating cardiac tissue with regular linear arrays of spatially alternating bipolar currents, we can simulate these potentials locally. We have studied the activation time due to distributed currents in both a 1D Beeler-Reuter model and on the surface of the whole heart, varying the strength of each source and the separation between them. By comparison with activation time data from actual field shock of a whole heart in a bath, we hope to better understand these transient virtual electrodes. Our work was done on rabbit RV using florescent optical imaging and our Phased Array Stimulator for driving the 16 current sources. Our model shows that for a total absolute current delivered to a region of tissue, the entire region activates faster if above-threshold sources are more distributed.

Physical activity and fatigue in breast cancer survivors: a panel model examining the role of self-efficacy and depression.

PubMed

Phillips, Siobhan M; McAuley, Edward

2013-05-01

Physical activity is associated with reductions in fatigue in breast cancer survivors. However, mechanisms underlying this relationship are not well-understood. The purpose of this study was to longitudinally test a model examining the role of self-efficacy and depression as potential mediators of the relationship between physical activity and fatigue in a sample of breast cancer survivors using both self-report and objective measures of physical activity. All participants (N = 1,527) completed self-report measures of physical activity, self-efficacy, depression, and fatigue at baseline and 6 months. A subsample was randomly selected to wear an accelerometer at both time points. It was hypothesized that physical activity indirectly influences fatigue via self-efficacy and depression. Relationships among model constructs were examined over the 6-month period using panel analysis within a covariance modeling framework. The hypothesized model provided a good model-data fit (χ(2) = 599.66, df = 105, P ≤ 0.001; CFI = 0.96; SRMR = 0.02) in the full sample when controlling for covariates. At baseline, physical activity indirectly influenced fatigue via self-efficacy and depression. These relationships were also supported across time. In addition, the majority of the hypothesized relationships were supported in the subsample with accelerometer data (χ(2) = 387.48, df = 147, P ≤ 0.001, CFI = 0.94, SRMR = 0.04). This study provides evidence to suggest the relationship between physical activity and fatigue in breast cancer survivors may be mediated by more proximal, modifiable outcomes of physical activity participation. Recommendations are made relative to future applications and research concerning these relationships.

Behavioral Timing without Clockwork: Photoperiod-Dependent Trade-Off between Predation Hazard and Energy Balance in an Arctic Ungulate.

PubMed

Tyler, Nicholas J C; Gregorini, Pablo; Forchhammer, Mads C; Stokkan, Karl-Arne; van Oort, Bob E H; Hazlerigg, David G

2016-10-01

Occurrence of 24-h rhythms in species apparently lacking functional molecular clockwork indicates that strong circadian mechanisms are not essential prerequisites of robust timing, and that rhythmical patterns may arise instead as passive responses to periodically changing environmental stimuli. Thus, in a new synthesis of grazing in a ruminant (MINDY), crepuscular peaks of activity emerge from interactions between internal and external stimuli that influence motivation to feed, and the influence of the light/dark cycle is mediated through the effect of low nocturnal levels of food intake on gastric function. Drawing on risk allocation theory, we hypothesized that the timing of behavior in ruminants is influenced by the independent effects of light on motivation to feed and perceived risk of predation. We predicted that the antithetical relationship between these 2 drivers would vary with photoperiod, resulting in a systematic shift in the phase of activity relative to the solar cycle across the year. This prediction was formalized in a model in which phase of activity emerges from a photoperiod-dependent trade-off between food and safety. We tested this model using data on the temporal pattern of activity in reindeer/caribou Rangifer tarandus free-living at natural mountain pasture in sub-Arctic Norway. The resulting nonlinear relationship between the phasing of crepuscular activity and photoperiod, consistent with the model, suggests a mechanism for behavioral timing that is independent of the core circadian system. We anticipate that such timing depends on integration of metabolic feedback from the digestive system and the activity of the glucocorticoid axis which modulates the behavioral responses of the animal to environmental hazard. The hypothalamus is the obvious neural substrate to achieve this integration. © 2016 The Author(s).

Extending the Trans-Contextual Model in Physical Education and Leisure-Time Contexts: Examining the Role of Basic Psychological Need Satisfaction

ERIC Educational Resources Information Center

Barkoukis, Vassilis; Hagger, Martin S.; Lambropoulos, George; Tsorbatzoudis, Haralambos

2010-01-01

Background: The trans-contextual model (TCM) is an integrated model of motivation that aims to explain the processes by which agentic support for autonomous motivation in physical education promotes autonomous motivation and physical activity in a leisure-time context. It is proposed that perceived support for autonomous motivation in physical…

Modeling of water treatment plant using timed continuous Petri nets

NASA Astrophysics Data System (ADS)

Nurul Fuady Adhalia, H.; Subiono, Adzkiya, Dieky

2017-08-01

Petri nets represent graphically certain conditions and rules. In this paper, we construct a model of the Water Treatment Plant (WTP) using timed continuous Petri nets. Specifically, we consider that (1) the water pump always active and (2) the water source is always available. After obtaining the model, the flow through the transitions and token conservation laws are calculated.

Perceived Autonomy Support in Physical Education and Leisure-Time Physical Activity: A Cross-Cultural Evaluation of the Trans-Contextual Model

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…

The Effect of Inquiry Training Learning Model Based on Just in Time Teaching for Problem Solving Skill

ERIC Educational Resources Information Center

Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda

2016-01-01

One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…

Sociodemographic and Geographic Correlates of Meeting Current Recommendations for Physical Activity in Middle-Aged French Adults: the Supplémentation en Vitamines et Minéraux Antioxydants (SUVIMAX) Study

PubMed Central

Bertrais, Sandrine; Preziosi, Paul; Mennen, Louise; Galan, Pilar; Hercberg, Serge; Oppert, Jean-Michel

2004-01-01

Objective. We evaluated the characteristics of French subjects meeting current public health recommendations for physical activity. Methods. We assessed leisure-time physical activity cross-sectionally in 7404 adults aged 45 to 68 years with applied logistic regression models. Results. Meeting the recommended physical activity levels was more likely in subjects aged 60 years and older and in women with higher education levels or living in rural areas and was less likely in smokers. No association was found with time spent watching television. The contribution of vigorous activity to total time spent being active was approximately 2 times higher in subjects meeting recommendations. Conclusions. Participation in some vigorous activity may be viewed as a “facilitator” to attain physical activity recommendations. Relationships with physical environment variables in Europe need further investigation. PMID:15333315

GASAKe: forecasting landslide activations by a genetic-algorithms-based hydrological model

NASA Astrophysics Data System (ADS)

Terranova, O. G.; Gariano, S. L.; Iaquinta, P.; Iovine, G. G. R.

2015-07-01

GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic algorithms and allows one to obtain thresholds for the prediction of slope failures using dates of landslide activations and rainfall series. It can be applied to either single landslides or a set of similar slope movements in a homogeneous environment. Calibration of the model provides families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from the kernels, the corresponding mobility functions (i.e., the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to the hydro-geological complexity of the site. Generally, shorter base times are expected for shallow slope instabilities compared to larger-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall series. Examples of application of GASAKe to a medium-size slope movement (the Uncino landslide at San Fili, in Calabria, southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of occurrence of the slope movements. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e., neither missing nor false alarms) has been achieved using five activations. As for temporal validation, the experiments performed by considering further dates of activation have also proved satisfactory. In view of early-warning applications for civil protection, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model against different types of slope instabilities characterized by several historical activations. Nevertheless, further refinements are still needed for application to landslide risk mitigation within early-warning and decision-support systems.

The time course of activity in dorsolateral prefrontal cortex and anterior cingulate cortex during top-down attentional control.

PubMed

Silton, Rebecca Levin; Heller, Wendy; Towers, David N; Engels, Anna S; Spielberg, Jeffrey M; Edgar, J Christopher; Sass, Sarah M; Stewart, Jennifer L; Sutton, Bradley P; Banich, Marie T; Miller, Gregory A

2010-04-15

A network of brain regions has been implicated in top-down attentional control, including left dorsolateral prefrontal cortex (LDLPFC) and dorsal anterior cingulate cortex (dACC). The present experiment evaluated predictions of the cascade-of-control model (Banich, 2009), which predicts that during attentionally-demanding tasks, LDLPFC imposes a top-down attentional set which precedes late-stage selection performed by dACC. Furthermore, the cascade-of-control model argues that dACC must increase its activity to compensate when top-down control by LDLPFC is poor. The present study tested these hypotheses using fMRI and dense-array ERP data collected from the same 80 participants in separate sessions. fMRI results guided ERP source modeling to characterize the time course of activity in LDLPFC and dACC. As predicted, dACC activity subsequent to LDLPFC activity distinguished congruent and incongruent conditions on the Stroop task. Furthermore, when LDLPFC activity was low, the level of dACC activity was related to performance outcome. These results demonstrate that dACC responds to attentional demand in a flexible manner that is dependent on the level of LDLPFC activity earlier in a trial. Overall, results were consistent with the temporal course of regional brain function proposed by the cascade-of-control model. Copyright 2009 Elsevier Inc. All rights reserved.

Intra- and Interdimeric Caspase-8 Self-Cleavage Controls Strength and Timing of CD95-Induced Apoptosis

PubMed Central

Kallenberger, Stefan M.; Beaudouin, Joël; Claus, Juliane; Fischer, Carmen; Sorger, Peter K.; Legewie, Stefan; Eils, Roland

2014-01-01

Apoptosis in response to the ligand CD95L (also known as Fas ligand) is initiated by caspase-8, which is activated by dimerization and self-cleavage at death-inducing signaling complexes (DISCs). Previous work indicated that the degree of substrate cleavage by caspase-8 determines whether a cell dies or survives in response to a death stimulus. To determine how a death ligand stimulus is effectively translated into caspase-8 activity, we assessed this activity over time in single cells with compartmentalized probes that are cleaved by caspase-8, and used multiscale modeling to simultaneously describe single-cell and population data with an ensemble of single-cell models. We derived and experimentally validated a minimal model in which cleavage of caspase-8 in the enzymatic domain occurs in an interdimeric manner through interaction between DISCs, whereas prodomain cleavage sites are cleaved in an intradimeric manner within DISCs. Modeling indicated that sustained membrane-bound caspase-8 activity is followed by transient cytosolic activity, which can be interpreted as a molecular timer mechanism reflected by a limited lifetime of active caspase-8. The activation of caspase-8 by combined intra- and interdimeric cleavage ensures weak signaling at low concentrations of CD95L and strongly accelerated activation at higher ligand concentrations, thereby contributing to precise control of apoptosis. PMID:24619646

Dynamic model of the octopus arm. II. Control of reaching movements.

PubMed

Yekutieli, Yoram; Sagiv-Zohar, Roni; Hochner, Binyamin; Flash, Tamar

2005-08-01

The dynamic model of the octopus arm described in the first paper of this 2-part series was used here to investigate the neural strategies used for controlling the reaching movements of the octopus arm. These are stereotypical extension movements used to reach toward an object. In the dynamic model, sending a simple propagating neural activation signal to contract all muscles along the arm produced an arm extension with kinematic properties similar to those of natural movements. Control of only 2 parameters fully specified the extension movement: the amplitude of the activation signal (leading to the generation of muscle force) and the activation traveling time (the time the activation wave takes to travel along the arm). We found that the same kinematics could be achieved by applying activation signals with different activation amplitudes all exceeding some minimal level. This suggests that the octopus arm could use minimal amplitudes of activation to generate the minimal muscle forces required for the production of the desired kinematics. Larger-amplitude signals would generate larger forces that increase the arm's stability against perturbations without changing the kinematic characteristics. The robustness of this phenomenon was demonstrated by examining activation signals with either a constant or a bell-shaped velocity profile. Our modeling suggests that the octopus arm biomechanics may allow independent control of kinematics and resistance to perturbation during arm extension movements.

Physical activity classification with dynamic discriminative methods.

PubMed

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

2018-06-19

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

New Insights into Activity Patterns in Children, Found Using Functional Data Analyses.

PubMed

Goldsmith, Jeff; Liu, Xinyue; Jacobson, Judith S; Rundle, Andrew

2016-09-01

Continuous monitoring of activity using accelerometers and other wearable devices provides objective, unbiased measurement of physical activity in minute-by-minute or finer resolutions. Accelerometers have already been widely deployed in studies of healthy aging, recovery of function after heart surgery, and other outcomes. Although common analyses of accelerometer data focus on single summary variables, such as the total or average activity count, there is growing interest in the determinants of diurnal profiles of activity. We use tools from functional data analysis (FDA), an area with an established statistical literature, to treat complete 24-h diurnal profiles as outcomes in a regression model. We illustrate the use of such models by analyzing data collected in New York City from 420 children participating in a Head Start program. Covariates of interest include season, sex, body mass index z-score, presence of an asthma diagnosis, and mother's birthplace. The FDA model finds several meaningful associations between several covariates and diurnal profiles of activity. In some cases, including shifted activity patterns for children of foreign-born mothers and time-specific effects of asthma on activity, these associations exist for covariates that are not associated with average activity count. FDA provides a useful statistical framework for settings in which the effect of covariates on the timing of activity is of interest. The use of similar models in other applications should be considered, and we make code public to facilitate this process.

Mathematical supply-chain modelling: Product analysis of cost and time

NASA Astrophysics Data System (ADS)

Easters, D. J.

2014-03-01

Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each sub-section of the chain. Subsequently, the research findings allowed the division of supply-chain components into sub-sections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each subsection encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.

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 our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

Comparison of three approaches to model grapevine organogenesis in conditions of fluctuating temperature, solar radiation and soil water content.

PubMed

Pallas, B; Loi, C; Christophe, A; Cournède, P H; Lecoeur, J

2011-04-01

There is increasing interest in the development of plant growth models representing the complex system of interactions between the different determinants of plant development. These approaches are particularly relevant for grapevine organogenesis, which is a highly plastic process dependent on temperature, solar radiation, soil water deficit and trophic competition. The extent to which three plant growth models were able to deal with the observed plasticity of axis organogenesis was assessed. In the first model, axis organogenesis was dependent solely on temperature, through thermal time. In the second model, axis organogenesis was modelled through functional relationships linking meristem activity and trophic competition. In the last model, the rate of phytomer appearence on each axis was modelled as a function of both the trophic status of the plant and the direct effect of soil water content on potential meristem activity. The model including relationships between trophic competition and meristem behaviour involved a decrease in the root mean squared error (RMSE) for the simulations of organogenesis by a factor nine compared with the thermal time-based model. Compared with the model in which axis organogenesis was driven only by trophic competition, the implementation of relationships between water deficit and meristem behaviour improved organogenesis simulation results, resulting in a three times divided RMSE. The resulting model can be seen as a first attempt to build a comprehensive complete plant growth model simulating the development of the whole plant in fluctuating conditions of temperature, solar radiation and soil water content. We propose a new hypothesis concerning the effects of the different determinants of axis organogenesis. The rate of phytomer appearance according to thermal time was strongly affected by the plant trophic status and soil water deficit. Furthermore, the decrease in meristem activity when soil water is depleted does not result from source/sink imbalances.

Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

Active contour configuration model for estimating the posterior ablative margin in image fusion of real-time ultrasound and 3D ultrasound or magnetic resonance images for radiofrequency ablation: an experimental study.

PubMed

Lee, Junkyo; Lee, Min Woo; Choi, Dongil; Cha, Dong Ik; Lee, Sunyoung; Kang, Tae Wook; Yang, Jehoon; Jo, Jaemoon; Bang, Won-Chul; Kim, Jongsik; Shin, Dongkuk

2017-12-21

The purpose of this study was to evaluate the accuracy of an active contour model for estimating the posterior ablative margin in images obtained by the fusion of real-time ultrasonography (US) and 3-dimensional (3D) US or magnetic resonance (MR) images of an experimental tumor model for radiofrequency ablation. Chickpeas (n=12) and bovine rump meat (n=12) were used as an experimental tumor model. Grayscale 3D US and T1-weighted MR images were pre-acquired for use as reference datasets. US and MR/3D US fusion was performed for one group (n=4), and US and 3D US fusion only (n=8) was performed for the other group. Half of the models in each group were completely ablated, while the other half were incompletely ablated. Hyperechoic ablation areas were extracted using an active contour model from real-time US images, and the posterior margin of the ablation zone was estimated from the anterior margin. After the experiments, the ablated pieces of bovine rump meat were cut along the electrode path and the cut planes were photographed. The US images with the estimated posterior margin were compared with the photographs and post-ablation MR images. The extracted contours of the ablation zones from 12 US fusion videos and post-ablation MR images were also matched. In the four models fused under real-time US with MR/3D US, compression from the transducer and the insertion of an electrode resulted in misregistration between the real-time US and MR images, making the estimation of the ablation zones less accurate than was achieved through fusion between real-time US and 3D US. Eight of the 12 post-ablation 3D US images were graded as good when compared with the sectioned specimens, and 10 of the 12 were graded as good in a comparison with nicotinamide adenine dinucleotide staining and histopathologic results. Estimating the posterior ablative margin using an active contour model is a feasible way of predicting the ablation area, and US/3D US fusion was more accurate than US/MR fusion.

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Kang, In-Sik; Reale, Oreste

2009-01-01

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Population pharmacokinetics of recombinant coagulation factor VIII-SingleChain in patients with severe hemophilia A.

PubMed

Zhang, Y; Roberts, J; Tortorici, M; Veldman, A; St Ledger, K; Feussner, A; Sidhu, J

2017-06-01

Essentials rVIII-SingleChain is a unique recombinant factor VIII (FVIII) molecule. A population pharmacokinetic model was based on FVIII activity of severe hemophilia A patients. The model was used to simulate factor VIII activity-time profiles for various dosing scenarios. The model supports prolonged dosing of rVIII-SingleChain with intervals of up to twice per week. Background Single-chain recombinant coagulation factor VIII (rVIII-SingleChain) is a unique recombinant coagulation factor VIII molecule. Objectives To: (i) characterize the population pharmacokinetics (PK) of rVIII-SingleChain in patients with severe hemophilia A; (ii) identify correlates of variability in rVIII-SingleChain PK; and (iii) simulate various dosing scenarios of rVIII-SingleChain. Patients/Methods A population PK model was developed, based on FVIII activity levels of 130 patients with severe hemophilia A (n = 91 for ≥ 12-65 years; n = 39 for < 12 years) who had participated in a single-dose PK investigation with rVIII-SingleChain 50 IU kg -1 . PK sampling was performed for up to 96 h. Results A two-compartment population PK model with first-order elimination adequately described FVIII activity. Body weight and predose level of von Willebrand factor were significant covariates on clearance, and body weight was a significant covariate on the central distribution volume. Simulations using the model with various dosing scenarios estimated that > 85% and > 93% of patients were predicted to maintain FVIII activity level above 1 IU dL -1 , at all times with three-times-weekly dosing (given on days 0, 2, and 4.5) at the lowest (20 IU kg -1 ) and highest (50 IU kg -1 ) doses, respectively. For twice weekly dosing (days 0 and 3.5) of 50 IU kg -1 rVIII-SingleChain, 62-80% of patients across all ages were predicted to maintain a FVIII activity level above 1 IU dL -1 at day 7. Conclusions The population PK model adequately characterized rVIII-SingleChain PK, and the model can be utilized to simulate FVIII activity-time profiles for various dosing scenarios. © 2017 The Authors. Journal of Thrombosis and Haemostasis published by Wiley Periodicals, Inc. on behalf of International Society on Thrombosis and Haemostasis.

Modelling the participation decision and duration of sporting activity in Scotland

PubMed Central

Eberth, Barbara; Smith, Murray D.

2010-01-01

Motivating individuals to actively engage in physical activity due to its beneficial health effects has been an integral part of Scotland's health policy agenda. The current Scottish guidelines recommend individuals participate in physical activity of moderate vigour for 30 min at least five times per week. For an individual contemplating the recommendation, decisions have to be made in regard of participation, intensity, duration and multiplicity. For the policy maker, understanding the determinants of each decision will assist in designing an intervention to effect the recommended policy. With secondary data sourced from the 2003 Scottish Health Survey (SHeS) we statistically model the combined decisions process, employing a copula approach to model specification. In taking this approach the model flexibly accounts for any statistical associations that may exist between the component decisions. Thus, we model the endogenous relationship between the decision of individuals to participate in sporting activities and, amongst those who participate, the duration of time spent undertaking their chosen activities. The main focus is to establish whether dependence exists between the two random variables assuming the vigour with which sporting activity is performed to be independent of the participation and duration decision. We allow for a variety of controls including demographic factors such as age and gender, economic factors such as income and educational attainment, lifestyle factors such as smoking, alcohol consumption, healthy eating and medical history. We use the model to compare the effect of interventions designed to increase the vigour with which individuals undertake their sport, relating it to obesity as a health outcome. PMID:20640033

Localized Fluctuant Oscillatory Activity by Working Memory Load: A Simultaneous EEG-fMRI Study.

PubMed

Zhao, Xiaojie; Li, Xiaoyun; Yao, Li

2017-01-01

Working memory (WM) is a resource-limited memory system for temporary storage and processing of brain information during the execution of cognitive tasks. Increased WM load will increase the amount and difficulty of memory information. Several studies have used electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) to explore load-dependent cognition processing according to the time courses of electrophysiological activity or the spatial pattern of blood oxygen metabolic activity. However, the relationships between these two activities and the underlying neural mechanism are still unclear. In this study, using simultaneously collected EEG and fMRI data under an n-back verbal WM task, we modeled the spectral perturbation of EEG oscillation and fMRI activation through joint independent component analysis (JICA). Multi-channel oscillation features were also introduced into the JICA model for further analysis. The results showed that time-locked activity of theta and beta were modulated by memory load in the early stimuli evaluation stage, corresponding to the enhanced activation in the frontal and parietal lobe, which were involved in stimulus discrimination, information encoding and delay-period activity. In the late response selection stage, alpha and gamma activity changes dependent on the load correspond to enhanced activation in the areas of frontal, temporal and parietal lobes, which played important roles in attention, information extraction and memory retention. These findings suggest that the increases in memory load not only affect the intensity and time course of the EEG activities, but also lead to the enhanced activation of brain regions which plays different roles during different time periods of cognitive process of WM.

The Potential of Micro Electro Mechanical Systems and Nanotechnology for the U.S. Army

DTIC Science & Technology

2001-05-01

Quantitative Structure Activity Relationship ( QSAR ) model . The QSAR model calculates the proper composition of the polymer-carbon black matrix...example, the BEI Gyrochip Model QRS11 from Systron Donner Inertial Division has a startup time of less than 1 second, a Mean Time Between Failure (MTBF... modeling from many equations per atom to a few lines of code. This approach is amenable to parallel processing. Nevertheless, their programs require

Physical activity and risk of alcohol use disorders: results from a prospective cohort study.

PubMed

Ejsing, Louise Kristiansen; Becker, Ulrik; Tolstrup, Janne S; Flensborg-Madsen, Trine

2015-03-01

To examine the effect of physical activity on risk of developing alcohol use disorders in a large prospective cohort study with focus on leisure-time physical activity. Data came from the four examinations of the Copenhagen City Heart Study (CCHS), performed in 1976-1978, 1981-1983, 1991-1994 and 2001-2003. Information on physical activity (classified as Moderate/high, low or sedentary) and covariates was obtained through self-administered questionnaires, and information on alcohol use disorders was obtained from the Danish Hospital Discharge Register, the Danish Psychiatric Central Research Register and the Winalco database. In total, 18,359 people participated in the study, a mean follow-up time of 20.9 years. Cox proportional hazards model with delayed entry was used. Models were adjusted for available covariates (age, smoking habits, alcohol intake, education, income and cohabitation status) including updated time-dependent variables whenever possible. A low or moderate/high leisure-time physical activity was associated with almost half the risk of developing alcohol use disorder compared with a sedentary leisure-time physical activity. This translates into a 1.5- to 2-fold increased risk of developing alcohol use disorder (Hazard ratios for men 1.64; 95% CI 1.29-2.10 and women 1.45; 1.01-2.09) in individuals with a sedentary leisure-time physical activity, compared with a moderate to high level. However, when stratifying by presence of other psychiatric disorders, no association was observed in women with psychiatric comorbidity. Residual confounding may have been present in this study, especially according to rough measures of income and education. In both men and women, being sedentary in leisure time was a risk factor for developing an alcohol use disorder. © The Author 2014. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Mobility Status as a Predictor of Obesity, Physical Activity, and Screen Time Use among Children Aged 5-11 Years in the United States.

PubMed

Wilson, Patrick B; Haegele, Justin A; Zhu, Xihe

2016-09-01

To examine physical activity participation, screen time habits, and the prevalence of overweight/obesity among children in the general population with mobility limitations and those enrolled in special education services. An observational, cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination Survey, a representative sample of the US population. Mobility limitations, special education services utilization, proxy-reported physical activity and screen time, and overweight/obesity status were assessed in children aged 5-11 years. Boys with mobility limitations were less likely to meet physical activity guidelines (≥60 minutes daily) compared with those with no limitations (58.1% vs 74.4%, adjusted F = 4.61, P = .04). In a logistic regression model, boys with mobility limitations had significantly lower odds (0.42, 95% CI 0.20-0.86) of meeting physical activity guidelines. The prevalence of children meeting screen time recommendations (≤2 hours daily) among those receiving special education services (42.4%) was lower than children not receiving services (53.2%; adjusted F = 8.87, P < .01). In a logistic regression model, children receiving special education services showed a trend toward significantly lower odds (0.74, 95% CI 0.54-1.03, P = .07) of meeting screen time recommendations. No statistically significant differences for overweight/obesity were found. Clear differences were present in physical activity between boys with and without mobility limitations. Furthermore, children receiving special education services demonstrated a lower likelihood of meeting screen time recommendations. Children with disabilities may benefit from targeted interventions aimed at increasing physical activity while decreasing screen time. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of Analgesic Activity of the Methanol Extract from the Galls of Quercus infectoria (Olivier) in Rats

PubMed Central

Ali, Noraisah Akbar

2014-01-01

The present study aims to investigate the analgesic activity of the methanol extract of the galls of Quercus infectoria in rats using hot plate and tail-flick methods. The extract was administered intraperitoneally at a dose of 20 mg/kg while morphine sulfate and sodium salicylate (10 mg/kg) served as standards. The methanol extract exhibited significant analgesic activity in the tail-flick model (P < 0.05) by increasing the reaction time of the rats to 8.0 sec at 30 min after treatment in comparison to control (4.4 sec). Morphine sulfate produced a reaction time of 11.9 sec in the same test. At the peak of activity (30 min), the extract produced maximum possible analgesia (MPA) of 34.2%, whilst morphine sulfate achieved a peak MPA of 70.9%. No analgesic effects have been observed using sodium salicylate in the tail-flick model. In the same model, the extract and sodium salicylate demonstrated comparable reaction times. Tail-flick is a better method to evaluate analgesic activity as no significant results were observed for all treatments using hot plate with the exception of morphine sulfate, which showed significant results only at 45 and 60 min after treatment. In conclusion, the methanol extract of the galls of Quercus infectoria displayed analgesic activity. PMID:25254062

AC field exposure study: human exposure to 60-Hz electric fields

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

Silva, J.M.

1985-04-01

The objective of this study was to develop a method of estimating human exposure to the 60 Hz electric fields created by transmission lines. The Activity Systems Model simulates human activities in a variety of situations where exposure to electric fields is possible. The model combines maps of electric fields, activity maps, and experimentally determined activity factors to provide histograms of time spent in electric fields of various strengths in the course of agricultural, recreational, and domestic activities. For corroboration, the study team measured actual human exposure at locations across the United States near transmission lines ranging in voltage frommore » 115 to 1200 kV. The data were collected with a specially designed vest that measures exposure. These data demonstrate the accuracy of the exposure model presented in this report and revealed that most exposure time is spent in fields of magnitudes similar to many household situations. The report provides annual exposure estimates for human activities near transmission lines and in the home and compares them with exposure data from typical laboratory animal experiments. For one exposure index, the cumulative product of time and electric field, exposure during some of the laboratory animal experiments is two to four orders of magnitude greater than cumulative exposure for a human during one year of outdoor work on a farm crossed by a transmission line.« less

A validation of ground ambulance pre-hospital times modeled using geographic information systems.

PubMed

Patel, Alka B; Waters, Nigel M; Blanchard, Ian E; Doig, Christopher J; Ghali, William A

2012-10-03

Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area.

Critical bounds on noise and SNR for robust estimation of real-time brain activity from functional near infra-red spectroscopy.

PubMed

Aqil, Muhammad; Jeong, Myung Yung

2018-04-24

The robust characterization of real-time brain activity carries potential for many applications. However, the contamination of measured signals by various instrumental, environmental, and physiological sources of noise introduces a substantial amount of signal variance and, consequently, challenges real-time estimation of contributions from underlying neuronal sources. Functional near infra-red spectroscopy (fNIRS) is an emerging imaging modality whose real-time potential is yet to be fully explored. The objectives of the current study are to (i) validate a time-dependent linear model of hemodynamic responses in fNIRS, and (ii) test the robustness of this approach against measurement noise (instrumental and physiological) and mis-specification of the hemodynamic response basis functions (amplitude, latency, and duration). We propose a linear hemodynamic model with time-varying parameters, which are estimated (adapted and tracked) using a dynamic recursive least square algorithm. Owing to the linear nature of the activation model, the problem of achieving robust convergence to an accurate estimation of the model parameters is recast as a problem of parameter error stability around the origin. We show that robust convergence of the proposed method is guaranteed in the presence of an acceptable degree of model misspecification and we derive an upper bound on noise under which reliable parameters can still be inferred. We also derived a lower bound on signal-to-noise-ratio over which the reliable parameters can still be inferred from a channel/voxel. Whilst here applied to fNIRS, the proposed methodology is applicable to other hemodynamic-based imaging technologies such as functional magnetic resonance imaging. Copyright © 2018 Elsevier Inc. All rights reserved.

Extending the trans-contextual model in physical education and leisure-time contexts: examining the role of basic psychological need satisfaction.

PubMed

Barkoukis, Vassilis; Hagger, Martin S; Lambropoulos, George; Tsorbatzoudis, Haralambos

2010-12-01

The trans-contextual model (TCM) is an integrated model of motivation that aims to explain the processes by which agentic support for autonomous motivation in physical education promotes autonomous motivation and physical activity in a leisure-time context. It is proposed that perceived support for autonomous motivation in physical education is related to autonomous motivation in physical education and leisure-time contexts. Furthermore, relations between autonomous motivation and the immediate antecedents of intentions to engage in physical activity behaviour and actual behaviour are hypothesized. The purpose of the present study was to incorporate the constructs of basic psychological need satisfaction in the TCM to provide a more comprehensive explanation of motivation and demonstrate the robustness of the findings of previous tests of the model that have not incorporated these constructs. Students (N=274) from Greek secondary schools. Participants completed self-report measures of perceived autonomy support, autonomous motivation, and basic psychological need satisfaction in physical education. Follow-up measures of these variables were taken in a leisure-time context along with measures of attitudes, subjective norms, perceived behavioural control (PBC), and intentions from the theory of planned behaviour 1 week later. Self-reported physical activity behaviour was measured 4 weeks later. Results supported TCM hypotheses. Basic psychological need satisfaction variables uniquely predicted autonomous motivation in physical education and leisure time as well as the antecedents of intention, namely, attitudes, and PBC. The basic psychological need satisfaction variables also mediated the effects of perceived autonomy support on autonomous motivation in physical education. Findings support the TCM and provide further information of the mechanisms in the model and integrated theories of motivation in physical education and leisure time.

Stochastic model for the long-term transport of stored sediment in a river channel

USGS Publications Warehouse

Kelsey, Harvey M.; Lamberson, Roland; Madej, Mary Ann

1987-01-01

We develop a stochastic model for the transport of stored sediment down a river channel. The model is based on probabilities of transition of particles among four different sediment storage reservoirs, called active (often mobilized), semiactive, inactive, and stable (hardly ever mobilized). The probabilities are derived from computed sediment residence times. Two aspects of sediment storage are investigated: flushing times of sediment out of a storage reservoir and changes in the quantity of sediment stored in different reservoirs due to seasonal sediment transport into, and out of, a reach. We apply the model to Redwood Creek, a gravel bed river in northern California. Although the Redwood Creek data set is incomplete, the application serves as an example of the sorts of analyses that can be done with the method. The application also provides insights into the sediment storage process. Sediment flushing times are highly dependent on the degree of interaction of the stable reservoir with the more mobile sediment reservoirs. The most infrequent and highest intensity storm events, which mobilize the stable reservoir, are responsible for the long-term shifts in sediment storage. Turnover times of channel sediment in all but the stable reservoir are on the order of 750 years, suggesting this is all the time needed for thorough interchange between these sediment compartments and cycling of most sediment particles from the initial reservoir to the ocean. Finally, the Markov model has adequately characterized sediment storage changes in Redwood Creek for 1947–1982, especially for the active reservoir. The model replicates field observation of the passage of a slug of sediment through the active reservoir of the middle reach of Redwood Creek in the 18 years following a major storm in 1964 that introduced large quantities of landslide debris to the channel.

The Influence of Self-Determination in Physical Education on Leisure-Time Physical Activity Behavior

ERIC Educational Resources Information Center

Shen, Bo; McCaughtry, Nate; Martin, Jeffrey

2007-01-01

Using a multitheory approach, this study was designed to investigate the influence of urban adolescents' perceived autonomy and competence in physical education on their physical activity intentions and behaviors during leisure time. A transcontextual model was hypothesized and tested. Urban adolescents (N = 653, ages 11-15 years) completed…

Timetabling and Extracurricular Activities: A Study of Teachers' Attitudes towards Preparation Time

ERIC Educational Resources Information Center

Whiteley, Robert F.; Richard, George

2012-01-01

Many models of timetabling exist in secondary schools in Western educational jurisdictions. This study examines whether or not teachers teaching a full course load without preparation time during a semester are willing to volunteer to participate in extracurricular activities. This research was conducted in a rural school district in British…

Out-of-School Time Activity Participation among US-Immigrant Youth

ERIC Educational Resources Information Center

Yu, Stella M.; Newport-Berra, McHale; Liu, Jihong

2015-01-01

Background: Structured out-of-school time (OST) activities are associated with positive academic and psychosocial outcomes. Methods: Data came from the 2007 National Survey of Children's Health, restricted to 36,132 youth aged 12-17?years. Logistic regression models were used to examine the joint effects of race/ethnicity and immigrant family type…

Differential transcriptional regulation by alternatively designed mechanisms: A mathematical modeling approach.

PubMed

Yildirim, Necmettin; Aktas, Mehmet Emin; Ozcan, Seyma Nur; Akbas, Esra; Ay, Ahmet

2017-01-01

Cells maintain cellular homeostasis employing different regulatory mechanisms to respond external stimuli. We study two groups of signal-dependent transcriptional regulatory mechanisms. In the first group, we assume that repressor and activator proteins compete for binding to the same regulatory site on DNA (competitive mechanisms). In the second group, they can bind to different regulatory regions in a noncompetitive fashion (noncompetitive mechanisms). For both competitive and noncompetitive mechanisms, we studied the gene expression dynamics by increasing the repressor or decreasing the activator abundance (inhibition mechanisms), or by decreasing the repressor or increasing the activator abundance (activation mechanisms). We employed delay differential equation models. Our simulation results show that the competitive and noncompetitive inhibition mechanisms exhibit comparable repression effectiveness. However, response time is fastest in the noncompetitive inhibition mechanism due to increased repressor abundance, and slowest in the competitive inhibition mechanism by increased repressor level. The competitive and noncompetitive inhibition mechanisms through decreased activator abundance show comparable and moderate response times, while the competitive and noncompetitive activation mechanisms by increased activator protein level display more effective and faster response. Our study exemplifies the importance of mathematical modeling and computer simulation in the analysis of gene expression dynamics.

A simple model of entropy relaxation for explaining effective activation energy behavior below the glass transition temperature.

PubMed

Bisquert, Juan; Henn, François; Giuntini, Jean-Charles

2005-03-01

Strong changes in relaxation rates observed at the glass transition region are frequently explained in terms of a physical singularity of the molecular motions. We show that the unexpected trends and values for activation energy and preexponential factor of the relaxation time tau, obtained at the glass transition from the analysis of the thermally stimulated current signal, result from the use of the Arrhenius law for treating the experimental data obtained in nonstationary experimental conditions. We then demonstrate that a simple model of structural relaxation based on a time dependent configurational entropy and Adam-Gibbs relaxation time is sufficient to explain the experimental behavior, without invoking a kinetic singularity at the glass transition region. The pronounced variation of the effective activation energy appears as a dynamic signature of entropy relaxation that governs the change of relaxation time in nonstationary conditions. A connection is demonstrated between the peak of apparent activation energy measured in nonequilibrium dielectric techniques, with the overshoot of the dynamic specific heat that is obtained in calorimetry techniques.

Tridacna Derived ENSO Records From The Philippines During The Last Interglacial Show Similar ENSO Activity To The Present Day

NASA Astrophysics Data System (ADS)

Welsh, K.; Morgan, Z.; Suzuki, A.

2016-12-01

Although modeled predictions for the relative strength and frequency of ENSO under mean warming conditions suggest an increase in the number and strength of ENSO event, however there are limited seasonally resolved records of ENSO variability during previous warm periods for example the last interglacial to test these models as reliable archives such as corals are not generally well preserved over these time periods. Presented here are two multi decadal Tridacna gigas derived stable isotopic time series from a coral terrace on the island of Cebu in the Philippines that formed during MIS5e based upon geomorphology and open-system corrected U/Th dating of corals. The ENSO activity observed in these time well preserved records indicate a similar level of ENSO activity during the last interglacial period as the present day based upon comparisons with recent coral derived stable isotopic records. Though these are relatively short records they provide further windows into ENSO activity from this important time period and demonstrate this area may be provide more opportunities to gather these archives.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models

PubMed Central

Grün, Sonja; Helias, Moritz

2017-01-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition. PMID:28968396

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

PubMed

Rostami, Vahid; Porta Mana, PierGianLuca; Grün, Sonja; Helias, Moritz

2017-10-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.

Cookie-Ases: Interactive Models for Teaching Genotype-Phenotype Relationships

ERIC Educational Resources Information Center

Seipelt, Rebecca L.

2006-01-01

Several hands-on and wet laboratory activities have been proposed to model the genetic concepts of genotypes and phenotypes and their relationship. The exercise presented in this article is a novel, time effective, student-centered, role-playing activity in which students learn about the intricate connection between genotype and phenotype by…

HEALTH PROGRAM INPLEMENTATION THROUGH PERT, ADMINISTRATIVE AND EDUCATIONAL USES.

ERIC Educational Resources Information Center

ARNOLD, MARY F.; AND OTHERS

THE MAIN ADVANTAGE OF THE PROGRAM EVALUATION AND REVIEW TECHNIQUE (PERT) IS THE PROVISION OF A GRAPHIC MODEL OF ACTIVITIES WITH ESTIMATES OF THE TIME, RESOURCES, PERSONNEL, AND FACILITIES NECESSARY TO ACCOMPLISH A SEQUENCE OF INTERDEPENDENT ACTIVITIES, AS IN PROGRAM IMPLEMENTATION. A PERT MODEL CAN ALSO IMPROVE COMMUNICATION BETWEEN PERSONS AND…

The Kallikrein Inhibitor from Bauhinia bauhinioides (BbKI) shows antithrombotic properties in venous and arterial thrombosis models.

PubMed

Brito, Marlon V; de Oliveira, Cleide; Salu, Bruno R; Andrade, Sonia A; Malloy, Paula M D; Sato, Ana C; Vicente, Cristina P; Sampaio, Misako U; Maffei, Francisco H A; Oliva, Maria Luiza V

2014-05-01

The Bauhinia bauhinioides Kallikrein Inhibitor (BbKI) is a Kunitz-type serine peptidase inhibitor of plant origin that has been shown to impair the viability of some tumor cells and to feature a potent inhibitory activity against human and rat plasma kallikrein (Kiapp 2.4 nmol/L and 5.2 nmol/L, respectively). This inhibitory activity is possibly responsible for an effect on hemostasis by prolonging activated partial thromboplastin time (aPTT). Because the association between cancer and thrombosis is well established, we evaluated the possible antithrombotic activity of this protein in venous and arterial thrombosis models. Vein thrombosis was studied in the vena cava ligature model in Wistar rats, and arterial thrombosis in the photochemical induced endothelium lesion model in the carotid artery of C57 black 6 mice. BbKI at a concentration of 2.0 mg/kg reduced the venous thrombus weight by 65% in treated rats in comparison to rats in the control group. The inhibitor prolonged the time for total artery occlusion in the carotid artery model mice indicating that this potent plasma kallikrein inhibitor prevented thrombosis. Copyright © 2014 Elsevier Ltd. All rights reserved.

After-School Activities, Misbehavior in School, and Delinquency from the End of Elementary School through the Beginning of High School: A Test of Social Development Model Hypotheses

ERIC Educational Resources Information Center

Fleming, Charles B.; Catalano, Richard F.; Mazza, James J.; Brown, Eric C.; Haggerty, Kevin P.; Harachi, Tracy W.

2008-01-01

Annual survey data on 776 students from sixth through ninth grade were used to examine the relationships among after-school activities, misbehavior in school, and delinquency. The social development model hypothesizes that antisocial behavior in one developmental time period leads to less involvement in activities and interactions that have…

Trends in participation rates for wildlife-associated outdoor recreation activities by age and race/ethnicity: implications for cohort-component projection models

Treesearch

John F. Dwyer; Allan Marsinko

1998-01-01

Cohort-component projection models have been used to explore the implications of increased aging and growth of racial/ethnic minority groups on number of participants in outdoor recreation activities in the years ahead. Projections usually assume that participation rates by age and race/ethnicity remain constant over time. This study looks at trends in activity...

Assessment of physical activity of the human body considering the thermodynamic system.

PubMed

Hochstein, Stefan; Rauschenberger, Philipp; Weigand, Bernhard; Siebert, Tobias; Schmitt, Syn; Schlicht, Wolfgang; Převorovská, Světlana; Maršík, František

2016-01-01

Correctly dosed physical activity is the basis of a vital and healthy life, but the measurement of physical activity is certainly rather empirical resulting in limited individual and custom activity recommendations. Certainly, very accurate three-dimensional models of the cardiovascular system exist, however, requiring the numeric solution of the Navier-Stokes equations of the flow in blood vessels. These models are suitable for the research of cardiac diseases, but computationally very expensive. Direct measurements are expensive and often not applicable outside laboratories. This paper offers a new approach to assess physical activity using thermodynamical systems and its leading quantity of entropy production which is a compromise between computation time and precise prediction of pressure, volume, and flow variables in blood vessels. Based on a simplified (one-dimensional) model of the cardiovascular system of the human body, we develop and evaluate a setup calculating entropy production of the heart to determine the intensity of human physical activity in a more precise way than previous parameters, e.g. frequently used energy considerations. The knowledge resulting from the precise real-time physical activity provides the basis for an intelligent human-technology interaction allowing to steadily adjust the degree of physical activity according to the actual individual performance level and thus to improve training and activity recommendations.

[Analysis on prevalence of physical activity time <1 hour and related factors in students aged 9-22 years in China, 2014].

PubMed

Wang, Z H; Dong, Y H; Song, Y; Yang, Z P; Ma, J

2017-03-10

Objective: To explore the prevalence of physical activity time <1 hour and related factors in students aged 9-22 years in China. Methods: A total of 220 159 students (110 039 boys and 110 120 girls) aged 9-22 years who completed the questionnaire of physical activity and lifestyle behaviors were selected from " 2014 National Physical Fitness and Health Surveillance" for the current study. All the participants were divided into 2 groups, i.e. physical activity time <1 hour and physical activity time ≥1 hour according the suggestion of Central Government, stratified by age and gender. χ (2) tests were used to compare the difference in the prevalence of physical activity time <1 hour between boys and girls in every age groups. Univariate and multivariate log-binomial regression models were used to explore the factors that influenced the prevalence of physical activity time <1 hour. Results: The boy's prevalence of physical activity time <1 hour was 73.3%, with the lowest (57.0%) in 9-years-old group, and highest (82.5%) in 18 years old group. The girl's prevalence of physical activity time <1 hour was 79.1%, with the lowest (60.1%) in 9-years-old group, and highest (89.8%) in 21 years old group. Overall, The prevalence of physical activity time <1 hour was significantly higher in girls than in boys ( P <0.001), and the prevalence were significantly higher in girls than in boys in all the age groups ( P <0.001), and it was observed that the prevalence of physical activity <1 hour increased with age in both boys and girls ( P <0.001). Multivariate log-binomial regression model found that being girl ( PR =1.05, 95 %CI : 1.05-1.06), parents' disliking children to participate physical activity ( PR =1.08, 95 % CI : 1.07-1.09), heavy homework ( PR =1.13, 95 % CI : 1.12-1.14), long homework time ( PR =1.08, 95 %CI : 1.07-1.08), long time spending on electronic screen watching ( PR =1.01, 95 %CI : 1.00-1.01) and disliking physical class ( PR =1.11, 95 %CI : 1.10-1.12) could be the risk factors for physical activity time <1 hour, however, living in rural area ( PR =0.99, 95 % CI : 0.98-0.99) and no supporting from parents for children to participate physical activity ( PR =0.99, 95 %CI : 1.98-1.00) could be the protective factors, but no consistent association with the time of TV watching was observed ( P =0.226). Conclusions: The prevalence of physical activity time <1 hour was high in students aged 9-22 years in China. Female, parents; disliking children to participate physical activity, heavy homework, long homework time, long electronic screen watching time and disliking physical class might be the risk factors.

Health-Related Quality of Life, Self-Efficacy and Enjoyment Keep the Socially Vulnerable Physically Active in Community-Based Physical Activity Programs: A Sequential Cohort Study

PubMed Central

Herens, Marion; Bakker, Evert Jan; van Ophem, Johan; Wagemakers, Annemarie; Koelen, Maria

2016-01-01

Physical inactivity is most commonly found in socially vulnerable groups. Dutch policies target these groups through community-based health-enhancing physical activity (CBHEPA) programs. As robust evidence on the effectiveness of this approach is limited, this study investigated whether CBHEPA programs contribute to an increase in and the maintenance of physical activity in socially vulnerable groups. In four successive cohorts, starting at a six-month interval, 268 participants from 19 groups were monitored for twelve months in seven CBHEPA programs. Data collection was based on repeated questionnaires. Socio-economic indicators, program participation and coping ability were measured at baseline. Physical activity, health-related quality of life and on-going program participation were measured three times. Self-efficacy and enjoyment were measured at baseline and at twelve months. Statistical analyses were based on a quasi-RCT design (independent t-tests), a comparison of participants and dropouts (Mann-Whitney test), and multilevel modelling to assess change in individual physical activity, including group level characteristics. Participants of CBHEPA programs are socially vulnerable in terms of low education (48.6%), low income (52.4%), non-Dutch origin (64.6%) and health-related quality of life outcomes. Physical activity levels were not below the Dutch average. No increase in physical activity levels over time was observed. The multilevel models showed significant positive associations between health-related quality of life, self-efficacy and enjoyment, and leisure-time physical activity over time. Short CBHEPA programs (10–13 weeks) with multiple trainers and gender-homogeneous groups were associated with lower physical activity levels over time. At twelve months, dropouts' leisure-time physical activity levels were significantly lower compared to continuing participants, as were health-related quality of life, self-efficacy and enjoyment outcomes. BMI and care consumption scored significantly higher among dropouts. In conclusion, Dutch CBHEPA programs reach socially vulnerable, but not necessarily inactive, groups in terms of socio-economic and health-related quality of life outcomes. Our findings suggest that CBHEPA programs particularly contribute to physical activity maintenance in socially vulnerable groups, rather than to an increase in physical activity behaviour over time. PMID:26909696

Health-Related Quality of Life, Self-Efficacy and Enjoyment Keep the Socially Vulnerable Physically Active in Community-Based Physical Activity Programs: A Sequential Cohort Study.

PubMed

Herens, Marion; Bakker, Evert Jan; van Ophem, Johan; Wagemakers, Annemarie; Koelen, Maria

2016-01-01

Physical inactivity is most commonly found in socially vulnerable groups. Dutch policies target these groups through community-based health-enhancing physical activity (CBHEPA) programs. As robust evidence on the effectiveness of this approach is limited, this study investigated whether CBHEPA programs contribute to an increase in and the maintenance of physical activity in socially vulnerable groups. In four successive cohorts, starting at a six-month interval, 268 participants from 19 groups were monitored for twelve months in seven CBHEPA programs. Data collection was based on repeated questionnaires. Socio-economic indicators, program participation and coping ability were measured at baseline. Physical activity, health-related quality of life and on-going program participation were measured three times. Self-efficacy and enjoyment were measured at baseline and at twelve months. Statistical analyses were based on a quasi-RCT design (independent t-tests), a comparison of participants and dropouts (Mann-Whitney test), and multilevel modelling to assess change in individual physical activity, including group level characteristics. Participants of CBHEPA programs are socially vulnerable in terms of low education (48.6%), low income (52.4%), non-Dutch origin (64.6%) and health-related quality of life outcomes. Physical activity levels were not below the Dutch average. No increase in physical activity levels over time was observed. The multilevel models showed significant positive associations between health-related quality of life, self-efficacy and enjoyment, and leisure-time physical activity over time. Short CBHEPA programs (10-13 weeks) with multiple trainers and gender-homogeneous groups were associated with lower physical activity levels over time. At twelve months, dropouts' leisure-time physical activity levels were significantly lower compared to continuing participants, as were health-related quality of life, self-efficacy and enjoyment outcomes. BMI and care consumption scored significantly higher among dropouts. In conclusion, Dutch CBHEPA programs reach socially vulnerable, but not necessarily inactive, groups in terms of socio-economic and health-related quality of life outcomes. Our findings suggest that CBHEPA programs particularly contribute to physical activity maintenance in socially vulnerable groups, rather than to an increase in physical activity behaviour over time.

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

PubMed

Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

2018-02-01

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

Cost analysis of prenatal care using the activity-based costing model: a pilot study.

PubMed

Gesse, T; Golembeski, S; Potter, J

1999-01-01

The cost of prenatal care in a private nurse-midwifery practice was examined using the activity-based costing system. Findings suggest that the activities of the nurse-midwife (the health care provider) constitute the major cost driver of this practice and that the model of care and associated, time-related activities influence the cost. This pilot study information will be used in the development of a comparative study of prenatal care, client education, and self care.

Cost Analysis of Prenatal Care Using the Activity-Based Costing Model: A Pilot Study

PubMed Central

Gesse, Theresa; Golembeski, Susan; Potter, Jonell

1999-01-01

The cost of prenatal care in a private nurse-midwifery practice was examined using the activity-based costing system. Findings suggest that the activities of the nurse-midwife (the health care provider) constitute the major cost driver of this practice and that the model of care and associated, time-related activities influence the cost. This pilot study information will be used in the development of a comparative study of prenatal care, client education, and self care. PMID:22945985

Bayesian analysis of volcanic eruptions

NASA Astrophysics Data System (ADS)

Ho, Chih-Hsiang

1990-10-01

The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.

Source analysis of electrophysiological correlates of beat induction as sensory-guided action

PubMed Central

Todd, Neil P. M.; Lee, Christopher S.

2015-01-01

In this paper we present a reanalysis of electrophysiological data originally collected to test a sensory-motor theory of beat induction (Todd et al., 2002; Todd and Seiss, 2004; Todd and Lee, 2015). The reanalysis is conducted in the light of more recent findings and in particular the demonstration that auditory evoked potentials contain a vestibular dependency. At the core of the analysis is a model which predicts brain dipole source current activity over time in temporal and frontal lobe areas during passive listening to a rhythm, or active synchronization, where it dissociates the frontal activity into distinct sources which can be identified as respectively pre-motor and motor in origin. The model successfully captures the main features of the rhythm in showing that the metrical structure is manifest in an increase in source current activity during strong compared to weak beats. In addition the outcomes of modeling suggest that: (1) activity in both temporal and frontal areas contribute to the metrical percept and that this activity is distributed over time; (2) transient, time-locked activity associated with anticipated beats is increased when a temporal expectation is confirmed following a previous violation, such as a syncopation; (3) two distinct processes are involved in auditory cortex, corresponding to tangential and radial (possibly vestibular dependent) current sources. We discuss the implications of these outcomes for the insights they give into the origin of metrical structure and the power of syncopation to induce movement and create a sense of groove. PMID:26321991

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.

Assessing the Effectiveness of a Hybrid-Flipped Model of Learning on Fluid Mechanics Instruction: Overall Course Performance, Homework, and Far- and Near-Transfer of Learning

ERIC Educational Resources Information Center

Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

2017-01-01

To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity…

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Activity Profile and Energy Expenditure Among Active Older Adults, British Columbia, 2011-2012.

PubMed

Madden, Kenneth M; Ashe, Maureen C; Chase, Jocelyn M

2015-07-16

Time spent by young adults in moderate to vigorous activity predicts daily caloric expenditure. In contrast, caloric expenditure among older adults is best predicted by time spent in light activity. We examined highly active older adults to examine the biggest contributors to energy expenditure in this population. Fifty-four community-dwelling men and women aged 65 years or older (mean, 71.4 y) were enrolled in this cross-sectional observational study. All were members of the Whistler Senior Ski Team, and all met current American guidelines for physical activity. Activity levels (sedentary, light, and moderate to vigorous) were recorded by accelerometers worn continuously for 7 days. Caloric expenditure was measured using accelerometry, galvanic skin response, skin temperature, and heat flux. Significant variables were entered into a stepwise multivariate linear model consisting of activity level, age, and sex. The average (standard deviation [SD]) daily nonlying sedentary time was 564 (92) minutes (9.4 [1.5] h) per day. The main predictors of higher caloric expenditure were time spent in moderate to vigorous activity (standardized β = 0.42 [SE, 0.08]; P < .001) and male sex (standardized β = 1.34 [SE, 0.16]; P < .001). A model consisting of only moderate to vigorous physical activity and sex explained 68% of the variation in caloric expenditure. An increase in moderate to vigorous physical activity by 1 minute per day was associated with an additional 16 kcal expended in physical activity. The relationship between activity intensity and caloric expenditure in athletic seniors is similar to that observed in young adults. Active older adults still spend a substantial proportion of the day engaged in sedentary behaviors.

Activity Profile and Energy Expenditure Among Active Older Adults, British Columbia, 2011–2012

PubMed Central

Ashe, Maureen C.; Chase, Jocelyn M.

2015-01-01

Introduction Time spent by young adults in moderate to vigorous activity predicts daily caloric expenditure. In contrast, caloric expenditure among older adults is best predicted by time spent in light activity. We examined highly active older adults to examine the biggest contributors to energy expenditure in this population. Methods Fifty-four community-dwelling men and women aged 65 years or older (mean, 71.4 y) were enrolled in this cross-sectional observational study. All were members of the Whistler Senior Ski Team, and all met current American guidelines for physical activity. Activity levels (sedentary, light, and moderate to vigorous) were recorded by accelerometers worn continuously for 7 days. Caloric expenditure was measured using accelerometry, galvanic skin response, skin temperature, and heat flux. Significant variables were entered into a stepwise multivariate linear model consisting of activity level, age, and sex. Results The average (standard deviation [SD]) daily nonlying sedentary time was 564 (92) minutes (9.4 [1.5] h) per day. The main predictors of higher caloric expenditure were time spent in moderate to vigorous activity (standardized β = 0.42 [SE, 0.08]; P < .001) and male sex (standardized β = 1.34 [SE, 0.16]; P < .001). A model consisting of only moderate to vigorous physical activity and sex explained 68% of the variation in caloric expenditure. An increase in moderate to vigorous physical activity by 1 minute per day was associated with an additional 16 kcal expended in physical activity. Conclusion The relationship between activity intensity and caloric expenditure in athletic seniors is similar to that observed in young adults. Active older adults still spend a substantial proportion of the day engaged in sedentary behaviors. PMID:26182147

The activation energy of stabilised/solidified contaminated soils.

PubMed

Chitambira, B; Al-Tabbaa, A; Perera, A S R; Yu, X D

2007-03-15

Developing an understanding of the time-related performance of cement-treated materials is essential in understanding their durability and long-term effectiveness. A number of models have been developed to predict this time-related performance. One such model is the maturity concept which involves use of the 'global' activation energy which derives from the Arrhenius equation. The accurate assessment of the activation energy is essential in the realistic modelling of the accelerated ageing of cement-treated soils. Experimentally, this model is applied to a series of tests performed at different elevated temperatures. Experimental work, related to the results of a time-related performance on a contaminated site in the UK treated with in situ stabilisation/solidification was carried out. Three different cement-based grouts were used on two model site soils which were both contaminated with a number of heavy metals and a hydrocarbon. Uncontaminated soils were also tested. Elevated temperatures up to 60 degrees C and curing periods up to 90 days were used. The resulting global activation energies for the uncontaminated and contaminated soils were compared. Lower values were obtained for the contaminated soils reflecting the effect of the contaminants. The resulting equivalent ages for the uncontaminated and contaminated mixes tested were 5.1-7.4 and 0.8-4.1 years, respectively. This work shows how a specific set of contaminants affect the E(a) values for particular cementitious systems and how the maturity concept can be applied to cement-treated contaminated soils.

ActivityAware: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.

PubMed

Boateng, George; Batsis, John A; Halter, Ryan; Kotz, David

2017-03-01

Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware , an application on the Amulet wrist-worn device that measures daily activity levels (sedentary, moderate and vigorous) of individuals, continuously and in real-time. The app implements an activity-level detection model, continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day's accumulated time spent at that activity level, logs the data for later analysis, and displays the results on the screen. We developed an activity-level detection model using a Support Vector Machine (SVM). We trained our classifiers using data from a user study, where subjects performed the following physical activities: sit, stand, lay down, walk and run. With 10-fold cross validation and leave-one-subject-out (LOSO) cross validation, we obtained preliminary results that suggest accuracies up to 98%, for n=14 subjects. Testing the ActivityAware app revealed a projected battery life of up to 4 weeks before needing to recharge. The results are promising, indicating that the app may be used for activity-level monitoring, and eventually for the development of interventions that could improve the health of individuals.

Gross-alpha and gross-beta activities in airborne particulate samples. Analysis and prediction models.

PubMed

Dueñas, C; Fernández, M C; Carretero, J; Liger, E; Cañete, S

2001-04-01

Measurements of gross-alpha and gross-beta activities were made every week during the years 1992-1997 for airborne particulate samples collected using air filters at a clear site. The data are sufficiently numerous to allow the examination of variations in time and by these measurements to establish several features that should be important in understanding any trends of atmospheric radioactivity. Two models were used to predict the gross-alpha and gross-beta activities. A good agreement between the results of these models and the measurements was highlighted.

Evaluation of a Stochastic Inactivation Model for Heat-Activated Spores of Bacillus spp. ▿

PubMed Central

Corradini, Maria G.; Normand, Mark D.; Eisenberg, Murray; Peleg, Micha

2010-01-01

Heat activates the dormant spores of certain Bacillus spp., which is reflected in the “activation shoulder” in their survival curves. At the same time, heat also inactivates the already active and just activated spores, as well as those still dormant. A stochastic model based on progressively changing probabilities of activation and inactivation can describe this phenomenon. The model is presented in a fully probabilistic discrete form for individual and small groups of spores and as a semicontinuous deterministic model for large spore populations. The same underlying algorithm applies to both isothermal and dynamic heat treatments. Its construction does not require the assumption of the activation and inactivation kinetics or knowledge of their biophysical and biochemical mechanisms. A simplified version of the semicontinuous model was used to simulate survival curves with the activation shoulder that are reminiscent of experimental curves reported in the literature. The model is not intended to replace current models to predict dynamic inactivation but only to offer a conceptual alternative to their interpretation. Nevertheless, by linking the survival curve's shape to probabilities of events at the individual spore level, the model explains, and can be used to simulate, the irregular activation and survival patterns of individual and small groups of spores, which might be involved in food poisoning and spoilage. PMID:20453137

Activated aging dynamics and effective trap model description in the random energy model

NASA Astrophysics Data System (ADS)

Baity-Jesi, M.; Biroli, G.; Cammarota, C.

2018-01-01

We study the out-of-equilibrium aging dynamics of the random energy model (REM) ruled by a single spin-flip Metropolis dynamics. We focus on the dynamical evolution taking place on time-scales diverging with the system size. Our aim is to show to what extent the activated dynamics displayed by the REM can be described in terms of an effective trap model. We identify two time regimes: the first one corresponds to the process of escaping from a basin in the energy landscape and to the subsequent exploration of high energy configurations, whereas the second one corresponds to the evolution from a deep basin to the other. By combining numerical simulations with analytical arguments we show why the trap model description does not hold in the former but becomes exact in the second.

Evidence for a bimodal distribution in human communication.

PubMed

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-11-02

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Evidence for a bimodal distribution in human communication

PubMed Central

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-01-01

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc. PMID:20959414

Physical Activity and Screen Time in Adolescents and Their Friends

PubMed Central

Sirard, John R.; Bruening, Meg; Wall, Melanie M.; Eisenberg, Marla E.; Kim, Sun K.; Neumark-Sztainer, Dianne

2012-01-01

Background Little is known about the actual physical activity and screen time behaviors of an adolescent’s friends relative to the individual’s behavior. Purpose To determine the associations between an adolescent’s physical activity and screen time and his/her nominated friends’ physical activity and screen time. Methods Data were obtained from EAT 2010 (Eating and Activity Among Teens), a large cross-sectional study (n=2126) conducted in 20 middle schools and high schools in Minneapolis/St. Paul MN during the 2009–2010 academic year and analyzed during 2011. Each participant nominated up to six friends from a school roster, and data from those friends were obtained as part of the school-based data collection procedures. Physical activity and screen time were assessed with previously used and validated questionnaires. Generalized estimating equation models, stratified by gender, were used to assess associations between adolescents’ physical activity and screen time and their friends’ physical activity and screen time. Results Physical activity for female adolescents was associated with their male and female friends’ physical activity, including their male and female best friends (all p<0.05). Males’ physical activity was associated with their female friends’ physical activity (p<0.03). Females’ screen time was associated with their male and female friends’ screen time (p≤0.03), but not with that of their best friends. Males’ screen time was associated with only their female friends’ screen time (p=0.04). Conclusions The consistent association between female adolescents’ physical activity and their friends’ physical activity indicates a need to include peer effects on adolescent female physical activity in future intervention work. PMID:23253649

Time spent in housework and leisure: links with parents' physiological recovery from work.

PubMed

Saxbe, Darby E; Repetti, Rena L; Graesch, Anthony P

2011-04-01

Spouses' balancing of housework and leisure activities at home may affect their recovery from work. This paper reports on a study of everyday family life in which 30 dual-earner couples were tracked around their homes by researchers who recorded their locations and activities every 10 min. For women, the most frequently pursued activities at home were housework, communication, and leisure; husbands spent the most time in leisure activities, followed by communication and housework. Spouses differed in their total time at home and their proportion of time devoted to leisure and housework activities, with wives observed more often in housework and husbands observed more often in leisure activities. Both wives and husbands who devoted more time to housework had higher levels of evening cortisol and weaker afternoon-to-evening recovery. For wives, husbands' increased housework time also predicted stronger evening cortisol recovery. When both spouses' activities were entered in the same model, leisure predicted husbands' evening cortisol, such that husbands who apportioned more time to leisure, and whose wives apportioned less time to leisure, showed stronger after-work recovery. These results suggest that the division of labor within couples may have implications for physical health.

Field evaluation of a random forest activity classifier for wrist-worn accelerometer data.

PubMed

Pavey, Toby G; Gilson, Nicholas D; Gomersall, Sjaan R; Clark, Bronwyn; Trost, Stewart G

2017-01-01

Wrist-worn accelerometers are convenient to wear and associated with greater wear-time compliance. Previous work has generally relied on choreographed activity trials to train and test classification models. However, validity in free-living contexts is starting to emerge. Study aims were: (1) train and test a random forest activity classifier for wrist accelerometer data; and (2) determine if models trained on laboratory data perform well under free-living conditions. Twenty-one participants (mean age=27.6±6.2) completed seven lab-based activity trials and a 24h free-living trial (N=16). Participants wore a GENEActiv monitor on the non-dominant wrist. Classification models recognising four activity classes (sedentary, stationary+, walking, and running) were trained using time and frequency domain features extracted from 10-s non-overlapping windows. Model performance was evaluated using leave-one-out-cross-validation. Models were implemented using the randomForest package within R. Classifier accuracy during the 24h free living trial was evaluated by calculating agreement with concurrently worn activPAL monitors. Overall classification accuracy for the random forest algorithm was 92.7%. Recognition accuracy for sedentary, stationary+, walking, and running was 80.1%, 95.7%, 91.7%, and 93.7%, respectively for the laboratory protocol. Agreement with the activPAL data (stepping vs. non-stepping) during the 24h free-living trial was excellent and, on average, exceeded 90%. The ICC for stepping time was 0.92 (95% CI=0.75-0.97). However, sensitivity and positive predictive values were modest. Mean bias was 10.3min/d (95% LOA=-46.0 to 25.4min/d). The random forest classifier for wrist accelerometer data yielded accurate group-level predictions under controlled conditions, but was less accurate at identifying stepping verse non-stepping behaviour in free living conditions Future studies should conduct more rigorous field-based evaluations using observation as a criterion measure. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Modeling and control of active twist aircraft

NASA Astrophysics Data System (ADS)

Cramer, Nicholas Bryan

The Wright Brothers marked the beginning of powered flight in 1903 using an active twist mechanism as their means of controlling roll. As time passed due to advances in other technologies that transformed aviation the active twist mechanism was no longer used. With the recent advances in material science and manufacturability, the possibility of the practical use of active twist technologies has emerged. In this dissertation, the advantages and disadvantages of active twist techniques are investigated through the development of an aeroelastic modeling method intended for informing the designs of such technologies and wind tunnel testing to confirm the capabilities of the active twist technologies and validate the model. Control principles for the enabling structural technologies are also proposed while the potential gains of dynamic, active twist are analyzed.

Spatial optimization of prairie dog colonies for black-footed ferret recovery

Treesearch

Michael Bevers; John G. Hof; Daniel W. Uresk; Gregory L. Schenbeck

1997-01-01

A discrete-time reaction-diffusion model for black-footed ferret release, population growth, and dispersal is combined with ferret carrying capacity constraints based on prairie dog population management decisions to form a spatial optimization model. Spatial arrangement of active prairie dog colonies within a ferret reintroduction area is optimized over time for...

Fitness to work of astronauts in conditions of action of the extreme emotional factors

NASA Astrophysics Data System (ADS)

Prisniakova, L. M.

2004-01-01

The theoretical model for the quantitative determination of influence of a level of emotional exertion on the success of human activity is presented. The learning curves of fixed words in the groups with a different level of the emotional exertion are analyzed. The obtained magnitudes of time constant T depending on a type of the emotional exertion are a quantitative measure of the emotional exertion. Time constants could also be of use for a prediction of the characteristic of fitness to work of an astronaut in conditions of extreme factors. The inverse of the sign of influencing on efficiency of activity of the man is detected. The paper offers a mathematical model of the relation between successful activity and motivations or the emotional exertion (Yerkes-Dodson law). Proposed models can serve by the theoretical basis of the quantitative characteristics of an estimation of activity of astronauts in conditions of the emotional factors at a phase of their selection.

Fitness to work of astronauts in conditions of action of the extreme emotional factors.

PubMed

Prisniakova, L M

2004-01-01

The theoretical model for the quantitative determination of influence of a level of emotional exertion on the success of human activity is presented. The learning curves of fixed words in the groups with a different level of the emotional exertion are analyzed. The obtained magnitudes of time constant T depending on a type of the emotional exertion are a quantitative measure of the emotional exertion. Time constants could also be of use for a prediction of the characteristic of fitness to work of an astronaut in conditions of extreme factors. The inverse of the sign of influencing on efficiency of activity of the man is detected. The paper offers a mathematical model of the relation between successful activity and motivations or the emotional exertion (Yerkes-Dodson law). Proposed models can serve by the theoretical basis of the quantitative characteristics of an estimation of activity of astronauts in conditions of the emotional factors at a phase of their selection. Published by Elsevier Ltd on behalf of COSPAR.

Stochastic modeling of the hypothalamic pulse generator activity.

PubMed

Camproux, A C; Thalabard, J C; Thomas, G

1994-11-01

Luteinizing hormone (LH) is released by the pituitary in discrete pulses. In the monkey, the appearance of LH pulses in the plasma is invariably associated with sharp increases (i.e, volleys) in the frequency of the hypothalamic pulse generator electrical activity, so that continuous monitoring of this activity by telemetry provides a unique means to study the temporal structure of the mechanism generating the pulses. To assess whether the times of occurrence and durations of previous volleys exert significant influence on the timing of the next volley, we used a class of periodic counting process models that specify the stochastic intensity of the process as the product of two factors: 1) a periodic baseline intensity and 2) a stochastic regression function with covariates representing the influence of the past. This approach allows the characterization of circadian modulation and memory range of the process underlying hypothalamic pulse generator activity, as illustrated by fitting the model to experimental data from two ovariectomized rhesus monkeys.

A longitudinal investigation of older adults' physical activity: Testing an integrated dual-process model.

PubMed

Arnautovska, Urska; Fleig, Lena; O'Callaghan, Frances; Hamilton, Kyra

2017-02-01

To assess the effects of conscious and non-conscious processes for prediction of older adults' physical activity (PA), we tested a dual-process model that integrated motivational (behavioural intention) and volitional (action planning and coping planning) processes with non-conscious, automatic processes (habit). Participants (N = 215) comprised community-dwelling older adults (M = 73.8 years). A longitudinal design was adopted to investigate direct and indirect effects of intentions, habit strength (Time 1), and action planning and coping planning (Time 2) on PA behaviour (Time 3). Structural equation modelling was used to evaluate the model. The model provided a good fit to the data, accounting for 44% of the variance in PA behaviour at Time 3. PA was predicted by intentions, action planning, and habit strength, with action planning mediating the intention-behaviour relationship. An effect of sex was also found where males used fewer planning strategies and engaged in more PA than females. By investigating an integration of conscious and non-conscious processes, this study provides a novel understanding of older adults' PA. Interventions aiming to promote PA behaviour of older adults should target the combination of psychological processes.

Artificial neural network and particle swarm optimization for removal of methyl orange by gold nanoparticles loaded on activated carbon and Tamarisk.

PubMed

Ghaedi, M; Ghaedi, A M; Ansari, A; Mohammadi, F; Vafaei, A

2014-11-11

The influence of variables, namely initial dye concentration, adsorbent dosage (g), stirrer speed (rpm) and contact time (min) on the removal of methyl orange (MO) by gold nanoparticles loaded on activated carbon (Au-NP-AC) and Tamarisk were investigated using multiple linear regression (MLR) and artificial neural network (ANN) and the variables were optimized by partial swarm optimization (PSO). Comparison of the results achieved using proposed models, showed the ANN model was better than the MLR model for prediction of methyl orange removal using Au-NP-AC and Tamarisk. Using the optimal ANN model the coefficient of determination (R2) for the test data set were 0.958 and 0.989; mean squared error (MSE) values were 0.00082 and 0.0006 for Au-NP-AC and Tamarisk adsorbent, respectively. In this study a novel and green approach were reported for the synthesis of gold nanoparticle and activated carbon by Tamarisk. This material was characterized using different techniques such as SEM, TEM, XRD and BET. The usability of Au-NP-AC and activated carbon (AC) Tamarisk for the methyl orange from aqueous solutions was investigated. The effect of variables such as pH, initial dye concentration, adsorbent dosage (g) and contact time (min) on methyl orange removal were studied. Fitting the experimental equilibrium data to various isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin-Radushkevich models show the suitability and applicability of the Langmuir model. Kinetic models such as pseudo-first order, pseudo-second order, Elovich and intraparticle diffusion models indicate that the second-order equation and intraparticle diffusion models control the kinetic of the adsorption process. The small amount of proposed Au-NP-AC and activated carbon (0.015 g and 0.75 g) is applicable for successful removal of methyl orange (>98%) in short time (20 min for Au-NP-AC and 45 min for Tamarisk-AC) with high adsorption capacity 161 mg g(-1) for Au-NP-AC and 3.84 mg g(-1) for Tamarisk-AC. Copyright © 2014 Elsevier B.V. All rights reserved.

Artificial neural network and particle swarm optimization for removal of methyl orange by gold nanoparticles loaded on activated carbon and Tamarisk

NASA Astrophysics Data System (ADS)

Ghaedi, M.; Ghaedi, A. M.; Ansari, A.; Mohammadi, F.; Vafaei, A.

2014-11-01

The influence of variables, namely initial dye concentration, adsorbent dosage (g), stirrer speed (rpm) and contact time (min) on the removal of methyl orange (MO) by gold nanoparticles loaded on activated carbon (Au-NP-AC) and Tamarisk were investigated using multiple linear regression (MLR) and artificial neural network (ANN) and the variables were optimized by partial swarm optimization (PSO). Comparison of the results achieved using proposed models, showed the ANN model was better than the MLR model for prediction of methyl orange removal using Au-NP-AC and Tamarisk. Using the optimal ANN model the coefficient of determination (R2) for the test data set were 0.958 and 0.989; mean squared error (MSE) values were 0.00082 and 0.0006 for Au-NP-AC and Tamarisk adsorbent, respectively. In this study a novel and green approach were reported for the synthesis of gold nanoparticle and activated carbon by Tamarisk. This material was characterized using different techniques such as SEM, TEM, XRD and BET. The usability of Au-NP-AC and activated carbon (AC) Tamarisk for the methyl orange from aqueous solutions was investigated. The effect of variables such as pH, initial dye concentration, adsorbent dosage (g) and contact time (min) on methyl orange removal were studied. Fitting the experimental equilibrium data to various isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin-Radushkevich models show the suitability and applicability of the Langmuir model. Kinetic models such as pseudo-first order, pseudo-second order, Elovich and intraparticle diffusion models indicate that the second-order equation and intraparticle diffusion models control the kinetic of the adsorption process. The small amount of proposed Au-NP-AC and activated carbon (0.015 g and 0.75 g) is applicable for successful removal of methyl orange (>98%) in short time (20 min for Au-NP-AC and 45 min for Tamarisk-AC) with high adsorption capacity 161 mg g-1 for Au-NP-AC and 3.84 mg g-1 for Tamarisk-AC.

Patterns of Yoga Practice and Physical Activity Following a Yoga Intervention for Adults With or at Risk for Type 2 Diabetes

PubMed Central

Alexander, Gina; Innes, Kim E.; Bourguignon, Cheryl; Bovbjerg, Viktor E.; Kulbok, Pamela; Taylor, Ann Gill

2012-01-01

Background The current study described patterns of yoga practice and examined differences in physical activity over time between individuals with or at risk for type 2 diabetes who completed an 8-week yoga intervention compared with controls. Methods A longitudinal comparative design measured the effect of a yoga intervention on yoga practice and physical activity, using data at baseline and postintervention months 3, 6, and 15. Results Disparate patterns of yoga practice occurred between intervention and control participants over time, but the subjective definition of yoga practice limits interpretation. Multilevel model estimates indicated that treatment group did not have a significant influence in the rate of change in physical activity over the study period. While age and education were not significant individual predictors, the inclusion of these variables in the model did improve fit. Conclusions Findings indicate that an 8-week yoga intervention had little effect on physical activity over time. Further research is necessary to explore the influence of yoga on behavioral health outcomes among individuals with or at risk for type 2 diabetes. PMID:22232506

Patterns of yoga practice and physical activity following a yoga intervention for adults with or at risk for type 2 diabetes.

PubMed

Alexander, Gina; Innes, Kim E; Bourguignon, Cheryl; Bovbjerg, Viktor E; Kulbok, Pamela; Taylor, Ann Gill

2012-01-01

The current study described patterns of yoga practice and examined differences in physical activity over time between individuals with or at risk for type 2 diabetes who completed an 8-week yoga intervention compared with controls. A longitudinal comparative design measured the effect of a yoga intervention on yoga practice and physical activity, using data at baseline and postintervention months 3, 6, and 15. Disparate patterns of yoga practice occurred between intervention and control participants over time, but the subjective definition of yoga practice limits interpretation. Multilevel model estimates indicated that treatment group did not have a significant influence in the rate of change in physical activity over the study period. While age and education were not significant individual predictors, the inclusion of these variables in the model did improve fit. Findings indicate that an 8-week yoga intervention had little effect on physical activity over time. Further research is necessary to explore the influence of yoga on behavioral health outcomes among individuals with or at risk for type 2 diabetes.

Transformation of Context-dependent Sensory Dynamics into Motor Behavior

PubMed Central

Latorre, Roberto; Levi, Rafael; Varona, Pablo

2013-01-01

The intrinsic dynamics of sensory networks play an important role in the sensory-motor transformation. In this paper we use conductance based models and electrophysiological recordings to address the study of the dual role of a sensory network to organize two behavioral context-dependent motor programs in the mollusk Clione limacina. We show that: (i) a winner take-all dynamics in the gravimetric sensory network model drives the typical repetitive rhythm in the wing central pattern generator (CPG) during routine swimming; (ii) the winnerless competition dynamics of the same sensory network organizes the irregular pattern observed in the wing CPG during hunting behavior. Our model also shows that although the timing of the activity is irregular, the sequence of the switching among the sensory cells is preserved whenever the same set of neurons are activated in a given time window. These activation phase locks in the sensory signals are transformed into specific events in the motor activity. The activation phase locks can play an important role in motor coordination driven by the intrinsic dynamics of a multifunctional sensory organ. PMID:23459114

An updated concept of coagulation with clinical implications.

PubMed

Romney, Gregory; Glick, Michael

2009-05-01

Over the past century, a series of models have been put forth to explain the coagulation mechanism. The coagulation cascade/waterfall model has gained the most widespread acceptance. This model, however, has problems when it is used in different clinical scenarios. A more recently proposed cell-based model better describes the coagulation process in vivo and provides oral health care professionals (OHCPs) with a better understanding of the clinical implications of providing dental care to patients with potentially increased bleeding tendencies. The authors conducted a literature search using the PubMed database. They searched for key words including "coagulation," "hemostasis," "bleeding," "coagulation factors," "models," "prothrombin time," "activated partial thromboplastin time," "international normalized ratio," "anticoagulation therapy" and "hemophilia" separately and in combination. The coagulation cascade/waterfall model is insufficient to explain coagulation in vivo, predict a patient's bleeding tendency, or correlate clinical outcomes with specific laboratory screening tests such as prothrombin time, activated partial thromboplastin time and international normalized ratio. However, the cell-based model of coagulation that reflects the in vivo process of coagulation provides insight into the clinical ramifications of treating dental patients with specific coagulation factor deficiencies. Understanding the in vivo coagulation process will help OHCPs better predict a patient's bleeding tendency. In addition, applying the theoretical concept of the cell-based model of coagulation to commonly used laboratory screening tests for coagulation and bleeding will result in safer and more appropriate dental care.

Population pharmacokinetics and pharmacodynamics of rivaroxaban in patients with non-valvular atrial fibrillation: results from ROCKET AF.

PubMed

Girgis, I G; Patel, M R; Peters, G R; Moore, K T; Mahaffey, K W; Nessel, C C; Halperin, J L; Califf, R M; Fox, K A A; Becker, R C

2014-08-01

Two once-daily rivaroxaban dosing regimens were compared with warfarin for stroke prevention in patients with non-valvular atrial fibrillation in ROCKET AF: 20 mg for patients with normal/mildly impaired renal function and 15 mg for patients with moderate renal impairment. Rivaroxaban population pharmacokinetic (PK)/pharmacodynamic (PD) modeling data from ROCKET AF patients (n = 161) are reported and are used to confirm established rivaroxaban PK and PK/PD models and to re-estimate values of the models' parameters for the current AF population. An oral one-compartment model with first-order absorption adequately described rivaroxaban PK. Age, renal function, and lean body mass influenced the PK model. Prothrombin time and prothrombinase-induced clotting time exhibited a near-linear relationship with rivaroxaban plasma concentration; inhibitory effects were observed through to 24 hours post-dose. Rivaroxaban plasma concentration and factor Xa activity had an inhibitory maximum-effect (Emax ) relationship. Renal function (on prothrombin time; prothrombinase-induced clotting time) and age (on factor Xa activity) had moderate effects on PK/PD models. PK and PK/PD models were shown to be adequate for describing the current dataset. These findings confirm the modeling and empirical results that led to the selection of doses tested against warfarin in ROCKET AF. © 2014, The American College of Clinical Pharmacology.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

NASA Technical Reports Server (NTRS)

Goodman, Michael L.; Kwan, Chiman; Ayhan, Bulent; Shang, Eric L.

2017-01-01

There are many flare forecasting models. For an excellent review and comparison of some of them see Barnes et al. (2016). All these models are successful to some degree, but there is a need for better models. We claim the most successful models explicitly or implicitly base their forecasts on various estimates of components of the photospheric current density J, based on observations of the photospheric magnetic field B. However, none of the models we are aware of compute the complete J. We seek to develop a better model based on computing the complete photospheric J. Initial results from this model are presented in this talk. We present a data driven, near photospheric, 3 D, non-force free magnetohydrodynamic (MHD) model that computes time series of the total J, and associated resistive heating rate in each pixel at the photosphere in the neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of B measured by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series of B in every AR pixel. Errors in B due to these periods can be significant.

Associations between active commuting and physical activity in working adults: Cross-sectional results from the Commuting and Health in Cambridge study

PubMed Central

Yang, Lin; Panter, Jenna; Griffin, Simon J.; Ogilvie, David

2012-01-01

Objective To quantify the association between time spent in active commuting and in moderate to vigorous physical activity (MVPA) in a sample of working adults living in both urban and rural locations. Methods In 2009, participants in the Commuting and Health in Cambridge study were sent questionnaires enquiring about sociodemographic characteristics and weekly time spent in active commuting. They were also invited to wear an accelerometer for seven days. Accelerometer data were used to compute the time spent in MVPA. Multiple regression models were used to examine the association between time spent in active commuting and MVPA. Results 475 participants (70% female) provided valid data. On average, participants recorded 55 (SD: 23.02) minutes of MVPA per day. For women, reporting 150 or more minutes of active commuting per week was associated with an estimated 8.50 (95% CI: 1.75 to 51.26, p = 0.01) additional minutes of daily MVPA compared to those who reported no time in active commuting. No overall associations were found in men. Conclusions Promoting active commuting might be an important way of increasing levels of physical activity, particularly in women. Further research should assess whether increases in time spent in active commuting are associated with increases in physical activity. PMID:22964003

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

PubMed

Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

2017-03-01

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans. © 2016 John Wiley & Sons Ltd.

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

USGS Publications Warehouse

Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

2017-01-01

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Neural mechanisms of planning: A computational analysis using event-related fMRI

PubMed Central

Fincham, Jon M.; Carter, Cameron S.; van Veen, Vincent; Stenger, V. Andrew; Anderson, John R.

2002-01-01

To investigate the neural mechanisms of planning, we used a novel adaptation of the Tower of Hanoi (TOH) task and event-related functional MRI. Participants were trained in applying a specific strategy to an isomorph of the five-disk TOH task. After training, participants solved novel problems during event-related functional MRI. A computational cognitive model of the task was used to generate a reference time series representing the expected blood oxygen level-dependent response in brain areas involved in the manipulation and planning of goals. This time series was used as one term within a general linear modeling framework to identify brain areas in which the time course of activity varied as a function of goal-processing events. Two distinct time courses of activation were identified, one in which activation varied parametrically with goal-processing operations, and the other in which activation became pronounced only during goal-processing intensive trials. Regions showing the parametric relationship comprised a frontoparietal system and include right dorsolateral prefrontal cortex [Brodmann's area (BA 9)], bilateral parietal (BA 40/7), and bilateral premotor (BA 6) areas. Regions preferentially engaged only during goal-intensive processing include left inferior frontal gyrus (BA 44). The implications of these results for the current model, as well as for our understanding of the neural mechanisms of planning and functional specialization of the prefrontal cortex, are discussed. PMID:11880658

Application of the Augmented Operator Function Model for Developing Cognitive Metrics in Persistent Surveillance

DTIC Science & Technology

2013-09-26

vehicle-lengths between frames. The low specificity of object detectors in WAMI means all vehicle detections are treated equally. Motion clutter...timing of the anomaly . If an anomaly was detected , recent activity would have a priority over older activity. This is due to the reasoning that if the...this could be a potential anomaly detected . Other baseline activities include normal work hours, religious observance times and interactions between

Study of the effect of electron irradiation on the density of the activated sludge in aqueous solution

NASA Astrophysics Data System (ADS)

Kupchishin, A. I.; Niyazov, M. N.; Taipova, B. G.; Voronova, N. A.; Khodarina, N. N.

2018-01-01

Complex experimental studies on the effect of electron irradiation on the deposition rate of active sludge in aqueous systems by the optical method have been carried out. The obtained dependences of density (ρ) on time (t) are of the same nature for different radiation sources. The experimental curves of the dependence of the active sludge density on time are satisfactorily described by an exponential model.

On the CCN (de)activation nonlinearities

NASA Astrophysics Data System (ADS)

Arabas, Sylwester; Shima, Shin-ichiro

2017-09-01

We take into consideration the evolution of particle size in a monodisperse aerosol population during activation and deactivation of cloud condensation nuclei (CCN). Our analysis reveals that the system undergoes a saddle-node bifurcation and a cusp catastrophe. The control parameters chosen for the analysis are the relative humidity and the particle concentration. An analytical estimate of the activation timescale is derived through estimation of the time spent in the saddle-node bifurcation bottleneck. Numerical integration of the system coupled with a simple air-parcel cloud model portrays two types of activation/deactivation hystereses: one associated with the kinetic limitations on droplet growth when the system is far from equilibrium, and one occurring close to equilibrium and associated with the cusp catastrophe. We discuss the presented analyses in context of the development of particle-based models of aerosol-cloud interactions in which activation and deactivation impose stringent time-resolution constraints on numerical integration.

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration values. The main advantage of the proposed model is that it requires only upper half of the breakthrough curve and is capable of predicting source parameters when the lag time is not known. Linking of ANN model with proposed optimization model reduces the dimensionality of the decision variables of the optimization model by one and hence complexity of optimization model is reduced. The results show that our proposed linked ANN-Optimization model is able to predict the source parameters for the error-free data accurately. The proposed model was run several times to obtain the mean, standard deviation and interval estimate of the predicted parameters for observations with random measurement errors. It was observed that mean values as predicted by the model were quite close to the exact values. An increasing trend was observed in the standard deviation of the predicted values with increasing level of measurement error. The model appears to be robust and may be efficiently utilized to solve the inverse pollution source identification problem.

Parent and child physical activity and sedentary time: do active parents foster active children?

PubMed

Jago, Russell; Fox, Kenneth R; Page, Angie S; Brockman, Rowan; Thompson, Janice L

2010-04-15

Physical activity has many positive effects on children's health while TV viewing has been associated with adverse health outcomes. Many children do not meet physical activity recommendations and exceed TV viewing guidelines. Parents are likely to be an important influence on their children's behaviour. There is an absence of information about the associations between parents' and children's physical activity and TV viewing. Year 6 children and their parent were recruited from 40 primary schools. Results are presented for the 340 parent-child dyads with accelerometer data that met a > or = 3 day inclusion criteria and the 431 parent-child dyads with complete self-reported TV viewing. Over 80% of the dyads with valid TV viewing data included mothers and their child. Mean minutes of moderate to vigorous physical activity (MVPA), minutes of sedentary time per day and counts per minute were assessed by accelerometer. Self-reported hours of TV viewing were coded into 3 groups (< 2 hours per day, 2-4 hours per day and >4 hours per day. Linear and multi-nominal regression models were run by child gender to examine parent-child associations. In linear regression models there was an association for the overall sedentary time of girls and their parents (t = 2.04. p = .020) but there was no association between girls' and parents' physical activity. There were no associations between parents' and boys' sedentary or physical activity time. For girls, the risk of watching more than 4 hours of TV per day, (reference = 2 hours of TV per day), was 3.67 times higher if the girl's parent watched 2-4 hours of TV per day (p = 0.037). For boys, the risk of watching more than 4 hours of TV per day, was 10.47 times higher if the boy's parent watched more than 4 hours of TV per day (p = 0.038). There are associations in the sedentary time of parents and daughters. Higher parental TV viewing was associated with an increased risk of high levels of TV viewing for both boys and girls. There were no associations between the time that parents and children spend engaged in physical activity.

Population decoding of motor cortical activity using a generalized linear model with hidden states.

PubMed

Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas; Paninski, Liam

2010-06-15

Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (reducing the mean square error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Population Decoding of Motor Cortical Activity using a Generalized Linear Model with Hidden States

PubMed Central

Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas G.; Paninski, Liam

2010-01-01

Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (lowering the Mean Square Error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. PMID:20359500

Estimating the Full Cost of Family-Financed Time Inputs to Education.

ERIC Educational Resources Information Center

Levine, Victor

This paper presents a methodology for estimating the full cost of parental time allocated to child-care activities at home. Building upon the human capital hypothesis, a model is developed in which the cost of an hour diverted from labor market activity is seen as consisting of three components: 1) direct wages foregone; 2) investments in…

Group-Based Modeling of Time Spent in Structured Activity Trajectories from Middle Childhood into Early Adolescence

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,…

Gender Differences in College Leisure Time Physical Activity: Application of the Theory of Planned Behavior and Integrated Behavioral Model

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…

A Pro-active Real-time Forecasting and Decision Support System for Daily Management of Marine Works

NASA Astrophysics Data System (ADS)

Bollen, Mark; Leyssen, Gert; Smets, Steven; De Wachter, Tom

2016-04-01

Marine Works involving turbidity generating activities (eg. dredging, dredge spoil placement) can generate environmental stress in and around a project area in the form of sediment plumes causing light reduction and sedimentation. If these works are situated near sensitive habitats like sea-grass beds, coral reefs or sensitive human activities eg. aquaculture farms or water intakes, or if contaminants are present in the water soil environmental scrutiny is advised. Environmental Regulations can impose limitations to these activities in the form of turbidity thresholds, spill budgets, contaminant levels. Breaching environmental regulations can result in increased monitoring, adaptation of the works planning and production rates and ultimately in a (temporary) stop of activities all of which entail time and cost impacts for a contractor and/or client. Sediment plume behaviour is governed by the dredging process, soil properties and ambient conditions (currents, water depth) and can be modelled. Usually this is done during the preparatory EIA phase of a project, for estimation of environmental impact based on climatic scenarios. An operational forecasting tool is developed to adapt marine work schedules to the real-time circumstances and thus evade exceedance of critical threshold levels at sensitive areas. The forecasting system is based on a Python-based workflow manager with a MySQL database and a Django frontend web tool for user interaction and visualisation of the model results. The core consists of a numerical hydrodynamic model with sediment transport module (Mike21 from DHI). This model is driven by space and time varying wind fields and wave boundary conditions, and turbidity inputs (suspended sediment source terms) based on marine works production rates and soil properties. The resulting threshold analysis allows the operator to indicate potential impact at the sensitive areas and instigate an adaption of the marine work schedule if needed. In order to use this toolbox in real-time situations and facilitate forecasting of impacts of planned dredge works, the following operational online functionalities are implemented: • Automated fetch and preparation of the input data, including 7 day forecast wind and wave fields and real-time measurements, and user defined the turbidity inputs based on scheduled marine works. • Generate automated forecasts and running user configurable scenarios at the same time in parallel. • Export and convert the model results, time series and maps, into a standardized format (netcdf). • Automatic analysis and processing of model results, including the calculation of indicator turbidity values and the exceedance analysis of threshold levels at the different sensitive areas. Data assimilation with the real time on site turbidity measurements is implemented in this threshold analysis. • Pre-programmed generation of animated sediment plumes, specific charts and pdf reports to allow a rapid interpretation of the model results by the operators and facilitating decision making in the operational planning. The performed marine works, resulting from the marine work schedule proposed by the forecasting system, are evaluated by a threshold analysis on the validated turbidity measurements on the sensitive sites. This machine learning loop allows a check of the system in order to evaluate forecast and model uncertainties.

Habitat suitability models for cavity-nesting birds in a postfire landscape

Treesearch

Robin E. Russell; Victoria A. Saab; Jonathan G. Dudley

2007-01-01

Models of habitat suitability in postfire landscapes are needed by land managers to make timely decisions regarding postfire timber harvest and other management activities. Many species of cavity-nesting birds are dependent on postfire landscapes for breeding and other aspects of their life history and are responsive to postfire management activities (e.g., timber...

Forest growth and timber quality: crown models and simulation methods for sustainable forest management

Treesearch

Dennis P. Dykstra; Robert A. Monserud

2009-01-01

The purpose of the international conference from which these proceedings are drawn was to explore relationships between forest management activities and timber quality. Sessions were organized to explore models and simulation methodologies that contribute to an understanding of tree development over time and the ways that management and harvesting activities can...

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.

Drift in Neural Population Activity Causes Working Memory to Deteriorate Over Time.

PubMed

Schneegans, Sebastian; Bays, Paul M

2018-05-23

Short-term memories are thought to be maintained in the form of sustained spiking activity in neural populations. Decreases in recall precision observed with increasing number of memorized items can be accounted for by a limit on total spiking activity, resulting in fewer spikes contributing to the representation of each individual item. Longer retention intervals likewise reduce recall precision, but it is unknown what changes in population activity produce this effect. One possibility is that spiking activity becomes attenuated over time, such that the same mechanism accounts for both effects of set size and retention duration. Alternatively, reduced performance may be caused by drift in the encoded value over time, without a decrease in overall spiking activity. Human participants of either sex performed a variable-delay cued recall task with a saccadic response, providing a precise measure of recall latency. Based on a spike integration model of decision making, if the effects of set size and retention duration are both caused by decreased spiking activity, we would predict a fixed relationship between recall precision and response latency across conditions. In contrast, the drift hypothesis predicts no systematic changes in latency with increasing delays. Our results show both an increase in latency with set size, and a decrease in response precision with longer delays within each set size, but no systematic increase in latency for increasing delay durations. These results were quantitatively reproduced by a model based on a limited neural resource in which working memories drift rather than decay with time. SIGNIFICANCE STATEMENT Rapid deterioration over seconds is a defining feature of short-term memory, but what mechanism drives this degradation of internal representations? Here, we extend a successful population coding model of working memory by introducing possible mechanisms of delay effects. We show that a decay in neural signal over time predicts that the time required for memory retrieval will increase with delay, whereas a random drift in the stored value predicts no effect of delay on retrieval time. Testing these predictions in a multi-item memory task with an eye movement response, we identified drift as a key mechanism of memory decline. These results provide evidence for a dynamic spiking basis for working memory, in contrast to recent proposals of activity-silent storage. Copyright © 2018 Schneegans and Bays.

Abdominal surgery process modeling framework for simulation using spreadsheets.

PubMed

Boshkoska, Biljana Mileva; Damij, Talib; Jelenc, Franc; Damij, Nadja

2015-08-01

We provide a continuation of the existing Activity Table Modeling methodology with a modular spreadsheets simulation. The simulation model developed is comprised of 28 modeling elements for the abdominal surgery cycle process. The simulation of a two-week patient flow in an abdominal clinic with 75 beds demonstrates the applicability of the methodology. The simulation does not include macros, thus programming experience is not essential for replication or upgrading the model. Unlike the existing methods, the proposed solution employs a modular approach for modeling the activities that ensures better readability, the possibility of easily upgrading the model with other activities, and its easy extension and connectives with other similar models. We propose a first-in-first-served approach for simulation of servicing multiple patients. The uncertain time duration of the activities is modeled using the function "rand()". The patients movements from one activity to the next one is tracked with nested "if()" functions, thus allowing easy re-creation of the process without the need of complex programming. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Contagion processes on the static and activity-driven coupling networks

NASA Astrophysics Data System (ADS)

Lei, Yanjun; Jiang, Xin; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

2016-03-01

The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated as either static or time-varying, supposing the whole network is observed in the same time window. In this paper, we consider the epidemics spreading on a network which has both static and time-varying structures. Meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity-driven coupling (SADC) network model to characterize the coupling between the static ("strong") structure and the dynamic ("weak") structure. Epidemic thresholds of the SIS and SIR models are studied using the SADC model both analytically and numerically under various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from the SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that a weak structure might make the epidemic threshold low in homogeneous networks but high in heterogeneous cases. Furthermore, we show that the weak structure has a substantive effect on the outbreak of the epidemics. This result might be useful in designing some efficient control strategies for epidemics spreading in networks.

The Association between Leisure-Time Physical Activity and Risk of Undetected Prediabetes

PubMed Central

Wang, Jia; Wu, Yili; Ning, Feng; Zhang, Chaoying

2017-01-01

Aims. The purpose of the study was to assess the effects of leisure-time physical activity on undetected prediabetes. Methods. Data from the National Health and Nutrition Examination Survey 2007–2012 were used in our analyses. Logistic regression was conducted to estimate the odds ratios (ORs) with 95% confidence intervals (CIs) of prediabetes associated with leisure-time physical activity. Results. A total of 8204 subjects were eligible for our analyses. For all subjects, high level of total leisure-time physical activity (OR = 0.78, 95% CI: 0.66, 0.94) and low level of vigorous leisure-time physical activity (OR = 0.72, 95% CI: 0.58, 0.90) were inversely associated with the risk of prediabetes in multivariate-adjusted model. For subjects under 45 years of age, high level of total leisure-time physical activity (OR = 0.78, 95% CI: 0.61, 0.99) and low (OR = 0.61, 95% CI: 0.45, 0.83) and high (OR = 0.72, 95% CI: 0.53, 1.00) level of vigorous leisure-time physical activity were associated with a decreased risk of prediabetes. In the 45 to 65 age group, only high level of total leisure-time physical activity (OR = 0.73, 95% CI: 0.57, 0.95) had protective effect on prediabetes. Conclusions. Leisure-time physical activity may be associated with a decreased risk of prediabetes. PMID:28367452

Modeling the effects of tree species and incubation temperature on soil's extracellular enzyme activity in 78-year-old tree plantations

NASA Astrophysics Data System (ADS)

Zhou, Xiaoqi; Wang, Shen S. J.; Chen, Chengrong

2017-12-01

Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C/N model to investigate how temperature and tree species influence soil C/N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and kauri pine (Agathis robusta C. Moore). Our results will be helpful for understanding the mechanisms of soil C and N cycling by different tree species, which will have implications for forest management.

Web-Based Real Time Earthquake Forecasting and Personal Risk Management

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

2012-12-01

Earthquake forecasts have been computed by a variety of countries and economies world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. One example is the Working Group on California Earthquake Probabilities that has been responsible for the official California earthquake forecast since 1988. However, in a time of increasingly severe global financial constraints, we are now moving inexorably towards personal risk management, wherein mitigating risk is becoming the responsibility of individual members of the public. Under these circumstances, open access to a variety of web-based tools, utilities and information is a necessity. Here we describe a web-based system that has been operational since 2009 at www.openhazards.com and www.quakesim.org. Models for earthquake physics and forecasting require input data, along with model parameters. The models we consider are the Natural Time Weibull (NTW) model for regional earthquake forecasting, together with models for activation and quiescence. These models use small earthquakes ('seismicity-based models") to forecast the occurrence of large earthquakes, either through varying rates of small earthquake activity, or via an accumulation of this activity over time. These approaches use data-mining algorithms combined with the ANSS earthquake catalog. The basic idea is to compute large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Each of these approaches has computational challenges associated with computing forecast information in real time. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we show that real-time forecasting is possible at a grid scale of 0.1o. We have analyzed the performance of these models using Reliability/Attributes and standard Receiver Operating Characteristic (ROC) tests. We show how the Reliability and ROC tests allow us to judge data completeness and estimate error. It is clear from much of the analysis that data quality is a major limitation on the accurate computation of earthquake probabilities. We discuss the challenges and pitfalls in serving up these datasets over the web.

Planning for Retirement: Longitudinal Effect on Retirement Resources and Post-retirement Well-being

PubMed Central

Yeung, Dannii Y.; Zhou, Xiaoyu

2017-01-01

Retirement is a major life event, and a positive adjustment to retirement is essential for maintaining physical and psychological well-being in later life. Previous research demonstrates that pre-retirement planning predicts post-retirement well-being. This study further explores the underlying mechanism between planning activities and post-retirement well-being. By applying the resource-based dynamic model (Wang et al., 2011), the present longitudinal study examines whether pre-retirement planning activities can increase the total resources of retirees, including tangible, mental and social resources, and consequently contribute to better psychological and physical well-being 1 year after actual retirement. A total of 118 Hong Kong Chinese retirees completed three assessments: Time 1 assessment was conducted 6 months before retirement, and Times 2 and 3 assessments were carried out 6 and 12 months, respectively, after retirement. Latent growth models were employed to examine changes in retirement resources and post-retirement well-being over time. Consistent with the proposition of the resource-based dynamic model, positive changes in well-being were observed in the retirees with increases in retirement resources between pre- and post-retirement phases. The results of the latent growth mediation models also support our prediction: retirees with more preparatory activities before retirement acquire greater resources at the initial stage, which contribute to positive changes in post-retirement well-being over time. PMID:28798716

Planning for Retirement: Longitudinal Effect on Retirement Resources and Post-retirement Well-being.

PubMed

Yeung, Dannii Y; Zhou, Xiaoyu

2017-01-01

Retirement is a major life event, and a positive adjustment to retirement is essential for maintaining physical and psychological well-being in later life. Previous research demonstrates that pre-retirement planning predicts post-retirement well-being. This study further explores the underlying mechanism between planning activities and post-retirement well-being. By applying the resource-based dynamic model (Wang et al., 2011), the present longitudinal study examines whether pre-retirement planning activities can increase the total resources of retirees, including tangible, mental and social resources, and consequently contribute to better psychological and physical well-being 1 year after actual retirement. A total of 118 Hong Kong Chinese retirees completed three assessments: Time 1 assessment was conducted 6 months before retirement, and Times 2 and 3 assessments were carried out 6 and 12 months, respectively, after retirement. Latent growth models were employed to examine changes in retirement resources and post-retirement well-being over time. Consistent with the proposition of the resource-based dynamic model, positive changes in well-being were observed in the retirees with increases in retirement resources between pre- and post-retirement phases. The results of the latent growth mediation models also support our prediction: retirees with more preparatory activities before retirement acquire greater resources at the initial stage, which contribute to positive changes in post-retirement well-being over time.

The effects of noise on binocular rivalry waves: a stochastic neural field model

NASA Astrophysics Data System (ADS)

Webber, Matthew A.; Bressloff, Paul C.

2013-03-01

We analyze the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We first show how, in the absence of any noise, the system supports a propagating composite wave consisting of an invading activity front in one network co-moving with a retreating front in the other network. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how extrinsic noise in the activity variables leads to a diffusive-like displacement (wandering) of the composite wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. We use our analysis to calculate the first-passage-time distribution for a stochastic rivalry wave to travel a fixed distance, which we find to be given by an inverse Gaussian. Finally, we investigate the effects of noise in the depression variables, which under an adiabatic approximation lead to quenched disorder in the neural fields during propagation of a wave.

Resonant activation of population extinctions

NASA Astrophysics Data System (ADS)

Spalding, Christopher; Doering, Charles R.; Flierl, Glenn R.

2017-10-01

Understanding the mechanisms governing population extinctions is of key importance to many problems in ecology and evolution. Stochastic factors are known to play a central role in extinction, but the interactions between a population's demographic stochasticity and environmental noise remain poorly understood. Here we model environmental forcing as a stochastic fluctuation between two states, one with a higher death rate than the other. We find that, in general, there exists a rate of fluctuations that minimizes the mean time to extinction, a phenomenon previously dubbed "resonant activation." We develop a heuristic description of the phenomenon, together with a criterion for the existence of resonant activation. Specifically, the minimum extinction time arises as a result of the system approaching a scenario wherein the severity of rare events is balanced by the time interval between them. We discuss our findings within the context of more general forms of environmental noise and suggest potential applications to evolutionary models.

Accelerometry-based classification of human activities using Markov modeling.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2011-01-01

Accelerometers are a popular choice as body-motion sensors: the reason is partly in their capability of extracting information that is useful for automatically inferring the physical activity in which the human subject is involved, beside their role in feeding biomechanical parameters estimators. Automatic classification of human physical activities is highly attractive for pervasive computing systems, whereas contextual awareness may ease the human-machine interaction, and in biomedicine, whereas wearable sensor systems are proposed for long-term monitoring. This paper is concerned with the machine learning algorithms needed to perform the classification task. Hidden Markov Model (HMM) classifiers are studied by contrasting them with Gaussian Mixture Model (GMM) classifiers. HMMs incorporate the statistical information available on movement dynamics into the classification process, without discarding the time history of previous outcomes as GMMs do. An example of the benefits of the obtained statistical leverage is illustrated and discussed by analyzing two datasets of accelerometer time series.

Physical fitness and performance. Cardiorespiratory fitness in girls-change from middle to high school.

PubMed

Pfeiffer, Karin A; Dowda, Marsha; Dishman, Rod K; Sirard, John R; Pate, Russell R

2007-12-01

To determine how factors are related to change in cardiorespiratory fitness (CRF) across time in middle school girls followed through high school. Adolescent girls (N = 274, 59% African American, baseline age = 13.6 +/- 0.6 yr) performed a submaximal fitness test (PWC170) in 8th, 9th, and 12th grades. Height, weight, sports participation, and physical activity were also measured. Moderate-to-vigorous physical activity (MVPA) and vigorous physical activity (VPA) were determined by the number of blocks reported on the 3-Day Physical Activity Recall (3DPAR). Individual differences and developmental change in CRF were assessed simultaneously by calculating individual growth curves for each participant, using growth curve modeling. Both weight-relative and absolute CRF increased from 8th to 9th grade and decreased from 9th to 12th grade. On average, girls lost 0.16 kg.m.min.kg.yr in weight-relative PWC170 scores (P < 0.01) and gained 10.3 kg.m.min.yr in absolute PWC170 scores. Girls reporting two or more blocks of MVPA or one or more blocks of VPA at baseline showed an average increase in PWC170 scores of 0.40-0.52 kg.m.min.kg.yr (weight relative) and 22-28 kg.m.min.yr (absolute) in CRF. In weight-relative models, girls with higher BMI showed lower CRF (approximately 0.37 g.m.min.kg.yr), but this was not shown in absolute models. In absolute models, white girls (approximately 40 kg.m.min.yr) and sport participants (approximately 28 kg.m.min.yr) showed an increase in CRF over time. Although there were fluctuations in PWC170 scores across time, average scores decreased during 4 yr. Physical activity was related to change in CRF over time; BMI, race, and sport participation were also important factors related to change over time in CRF (depending on expression of CRF-weight-relative vs absolute). Subsequent research should focus on explaining the complex longitudinal interactions between CRF, physical activity, race, BMI, and sports participation.

The exercise and affect relationship: evidence for the dual-mode model and a modified opponent process theory.

PubMed

Markowitz, Sarah M; Arent, Shawn M

2010-10-01

This study examined the relationship between exertion level and affect using the framework of opponent-process theory and the dual-mode model, with the Activation-Deactivation Adjective Checklist and the State Anxiety Inventory among 14 active and 14 sedentary participants doing 20 min of treadmill exercise at speeds of 5% below, 5% above, and at lactate threshold (LT). We found a significant effect of time, condition, Time × Condition, and Time × Group, but no group, Group × Condition, or Time × Group × Condition effects, such that the 5% above LT condition produced a worsening of affect in-task compared with all other conditions whereas, across conditions, participants experienced in-task increases in energy and tension, and in-task decreases in tiredness and calmness relative to baseline. Posttask, participants experienced mood improvement (decreased tension, anxiety, and increased calmness) across conditions, with a 30-min delay in the above LT condition. These results partially support the dual-mode model and a modified opponent-process theory.

People detection in crowded scenes using active contour models

NASA Astrophysics Data System (ADS)

Sidla, Oliver

2009-01-01

The detection of pedestrians in real-world scenes is a daunting task, especially in crowded situations. Our experience over the last years has shown that active shape models (ASM) can contribute significantly to a robust pedestrian detection system. The paper starts with an overview of shape model approaches, it then explains our approach which builds on top of Eigenshape models which have been trained using real-world data. These models are placed over candidate regions and matched to image gradients using a scoring function which integrates i) point distribution, ii) local gradient orientations iii) local image gradient strengths. A matching and shape model update process is iteratively applied in order to fit the flexible models to the local image content. The weights of the scoring function have a significant impact on the ASM performance. We analyze different settings of scoring weights for gradient magnitude, relative orientation differences, distance between model and gradient in an experiment which uses real-world data. Although for only one pedestrian model in an image computation time is low, the number of necessary processing cycles which is needed to track many people in crowded scenes can become the bottleneck in a real-time application. We describe the measures which have been taken in order to improve the speed of the ASM implementation and make it real-time capable.

Objectively Measured Sedentary Time and Cardiometabolic Biomarkers in US Hispanic/Latino Adults: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

PubMed

Qi, Qibin; Strizich, Garrett; Merchant, Gina; Sotres-Alvarez, Daniela; Buelna, Christina; Castañeda, Sheila F; Gallo, Linda C; Cai, Jianwen; Gellman, Marc D; Isasi, Carmen R; Moncrieft, Ashley E; Sanchez-Johnsen, Lisa; Schneiderman, Neil; Kaplan, Robert C

2015-10-20

Sedentary behavior is recognized as a distinct construct from lack of moderate-vigorous physical activity and is associated with deleterious health outcomes. Previous studies have primarily relied on self-reported data, whereas data on the relationship between objectively measured sedentary time and cardiometabolic biomarkers are sparse, especially among US Hispanics/Latinos. We examined associations of objectively measured sedentary time (via Actical accelerometers for 7 days) and multiple cardiometabolic biomarkers among 12 083 participants, aged 18 to 74 years, from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hispanics/Latinos of diverse backgrounds (Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American) were recruited from 4 US cities between 2008 and 2011. Sedentary time (<100 counts/min) was standardized to 16 hours/d of wear time. The mean sedentary time was 11.9 hours/d (74% of accelerometer wear time). After adjustment for moderate-vigorous physical activity and confounding variables, prolonged sedentary time was associated with decreased high-density lipoprotein cholesterol (P=0.04), and increased triglycerides, 2-hour glucose, fasting insulin, and homeostatic model assessment of insulin resistance (all P<0.0001). These associations were generally consistent across age, sex, Hispanic/Latino backgrounds, and physical activity levels. Even among individuals meeting physical activity guidelines, sedentary time was detrimentally associated with several cardiometabolic biomarkers (diastolic blood pressure, high-density lipoprotein cholesterol, fasting and 2-hour glucose, fasting insulin and homeostatic model assessment of insulin resistance; all P<0.05). Our large population-based, objectively derived data showed deleterious associations between sedentary time and cardiometabolic biomarkers, independent of physical activity, in US Hispanics/Latinos. Our findings emphasize the importance of reducing sedentary behavior for the prevention of cardiometabolic diseases, even in those who meet physical activity recommendations. © 2015 American Heart Association, Inc.

Time with friends and physical activity as mechanisms linking obesity and television viewing among youth

PubMed Central

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 between weight status and television viewing to more nuanced explanatory models which attempt to identify and unpack the possible mechanisms linking them. PMID:26221737

Physical activity and risk of colon cancer in a cohort of Danish middle-aged men and women.

PubMed

Johnsen, Nina Føns; Christensen, Jane; Thomsen, Birthe Lykke; Olsen, Anja; Loft, Steffen; Overvad, Kim; Tjønneland, Anne

2006-01-01

To investigate the effects of occupational activity and leisure time activity on incident colon cancer risk in a Danish middle-aged population. In the cohort, Diet, Cancer and Health, which included 28,356 women and 26,122 men aged 50-64 years at baseline, 140 women and 157 men were diagnosed with colon cancer from 1993 to 2003. The associations between occupational and leisure time activity in terms of a MET-score and the single activities, sports, cycling, walking, gardening, housework and do-it-yourself work, and incident colon cancer were investigated. Leisure time activity was investigated in two ways using the Cox proportional hazards model: by comparison of active versus non-active and by investigating a possible dose-response relationship while allowing a separate association for non-active individuals. No associations were found between risk of colon cancer and occupational activity, MET-hours per week of total leisure time activity, residuals from a regression of each activity on the total MET-hours or the time spent on any of the six types of leisure time activities. However, a borderline significant association was found with the number of activities in which the participants were active. For each additional activity IRR = 0.87 (0.76-1.00) for women and IRR = 0.88 (0.78-1.00) for men. Our data do not support the evidence of an inverse association between colon cancer risk and occupational activity or leisure time activity, but avoiding a sedentary lifestyle by participating in different activities may reduce colon cancer risk.

Contributions of aircraft arrivals and departures to ultrafine particle counts near Los Angeles International Airport.

PubMed

Hsu, Hsiao-Hsien; Adamkiewicz, Gary; Houseman, E Andres; Zarubiak, Darcy; Spengler, John D; Levy, Jonathan I

2013-02-01

While commercial aircraft are known sources of ultrafine particulate matter (UFP), the relationship between airport activity and local real-time UFP concentrations has not been quantified. Understanding these associations will facilitate interpretation of the exposure and health risk implications of UFP related to aviation emissions. We used time-resolved UFP data along with flight activity and meteorological information to determine the contributions of aircraft departures and arrivals to UFP concentrations. Aircraft flight activity and near-field continuous UFP concentrations (≧ 6 nm) were measured at five monitoring sites over a 42-day field campaign at Los Angeles International Airport (LAX). We developed regression models of UFP concentrations as a function of time-lagged landing and take-off operations (LTO) activity, in the form of arrivals or departures weighted by engine-specific estimates of fuel consumption. Our regression models demonstrate a strong association between departures and elevated total UFP concentrations at the end of the departure runway, with diminishing magnitude and time-lagged impacts with distance from the source. LTO activity contributed a median (95th, 99th percentile) UFP concentration of approximately 150,000 particles/cm(3) (2,000,000, 7,100,000) at a monitor at the end of the departure runway, versus 19,000 particles/cm(3) (80,000, 140,000), and 17,000 particles/cm(3) (50,000, 72,000) for monitors 250 m and 500 m further downwind, respectively. We demonstrated significant contributions from aircraft departure activities to UFP concentrations in close proximity to departure runways, with evidence of rapid plume evolution in the near field. Our methods can inform source attribution and interpretation of dispersion modeling outputs. Copyright © 2012 Elsevier B.V. All rights reserved.

Examining the Impact of the Walking School Bus With an Agent-Based Model

PubMed Central

Diez-Roux, Ana; Evenson, Kelly R.; Colabianchi, Natalie

2014-01-01

We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness. PMID:24832410

Antimicrobial Penetration and Efficacy in an In Vitro Oral Biofilm Model ▿ †

PubMed Central

Corbin, Audrey; Pitts, Betsey; Parker, Albert; Stewart, Philip S.

2011-01-01

The penetration and overall efficacy of six mouthrinse actives was evaluated by using an in vitro flow cell oral biofilm model. The technique involved preloading biofilm cells with a green fluorescent dye that leaked out as the cells were permeabilized by a treatment. The loss of green color, and of biomass, was observed by time-lapse microscopy during 60 min of treatment under continuous flow conditions. The six actives analyzed were ethanol, sodium lauryl sulfate, triclosan, chlorhexidine digluconate (CHX), cetylpyridinium chloride, and nisin. Each of these agents effected loss of green fluorescence throughout biofilm cell clusters, with faster action at the edge of a cell cluster and slower action in the cluster center. The time to reach half of the initial fluorescent intensity at the center of a cell cluster, which can be viewed as a combined penetration and biological action time, ranged from 0.6 to 19 min for the various agents. These times are much longer than the predicted penetration time based on diffusion alone, suggesting that anti-biofilm action was controlled more by the biological action time than by the penetration time of the active. None of the agents tested caused any removal of the biofilm. The extent of fluorescence loss after 1 h of exposure to an active ranged from 87 to 99.5%, with CHX being the most effective. The extent of fluorescence loss in vitro, but not penetration and action time, correlated well with the relative efficacy data from published clinical trials. PMID:21537022

IABP timing and ventricular performance--comparison between a compliant and a stiffer aorta: a hybrid model study including baroreflex.

PubMed

Fresiello, Libera; Khir, Ashraf W; Di Molfetta, Arianna; Kozarski, Maciej; Ferrari, Gianfranco

2013-11-01

The aim of this study was to investigate the effects of the intra aortic balloon pump (IABP) and of aortic compliance on left ventricular performance, including the effects of baroreflex control.
 The study was conducted using a hybrid cardiovascular simulator, including a computational cardiovascular sub-model, a hydraulic sub-model of the descending aorta, and a baroreflex computational sub-model. A 40 cc balloon was inserted into a rubber tube component of the hydraulic sub-model. A comparative analysis was conducted for two aortic compliances (C1 = 2.4 and C2 = 1.43 cm3/mmHg, corresponding to an aortic pulse pressure of 23 mmHg and 35 mmHg, respectively), driving the balloon for different trigger timings.
 Under C1 conditions, the IABP induced higher effects on baroreflex activity (decrement of sympathetic efferent activity: 10% for C1 and 14.7% for C2) and ventricular performance (increment of cardiac output (CO): 3.7% for C1 and 5.2% for C2, increment of endocardial viability ratio (EVR): 24.8% for C1 and 55% for C2). The best balloon timing was different for C1 and C2: inflation trigger timing (from the dicrotic notch) -0.09 s for C1 and -0.04 s for C2, inflation duration 0.25 s for C1 and 0.2 s for C2.
 Early inflation ensures better EVR, CO, and an increment of the afferent nerve activity, hence causing peripheral resistance and heart rate to decrease. The best balloon timing depends on aortic compliance, thus suggesting the need for a therapy tailored to the specific conditions of individual patients.

Origin and structures of solar eruptions II: Magnetic modeling

NASA Astrophysics Data System (ADS)

Guo, Yang; Cheng, Xin; Ding, MingDe

2017-07-01

The topology and dynamics of the three-dimensional magnetic field in the solar atmosphere govern various solar eruptive phenomena and activities, such as flares, coronal mass ejections, and filaments/prominences. We have to observe and model the vector magnetic field to understand the structures and physical mechanisms of these solar activities. Vector magnetic fields on the photosphere are routinely observed via the polarized light, and inferred with the inversion of Stokes profiles. To analyze these vector magnetic fields, we need first to remove the 180° ambiguity of the transverse components and correct the projection effect. Then, the vector magnetic field can be served as the boundary conditions for a force-free field modeling after a proper preprocessing. The photospheric velocity field can also be derived from a time sequence of vector magnetic fields. Three-dimensional magnetic field could be derived and studied with theoretical force-free field models, numerical nonlinear force-free field models, magnetohydrostatic models, and magnetohydrodynamic models. Magnetic energy can be computed with three-dimensional magnetic field models or a time series of vector magnetic field. The magnetic topology is analyzed by pinpointing the positions of magnetic null points, bald patches, and quasi-separatrix layers. As a well conserved physical quantity, magnetic helicity can be computed with various methods, such as the finite volume method, discrete flux tube method, and helicity flux integration method. This quantity serves as a promising parameter characterizing the activity level of solar active regions.

THE EFFECT OF A DYNAMIC INNER HELIOSHEATH THICKNESS ON COSMIC-RAY MODULATION

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

Manuel, R.; Ferreira, S. E. S.; Potgieter, M. S., E-mail: rexmanuel@live.com

2015-02-01

The time-dependent modulation of galactic cosmic rays in the heliosphere is studied over different polarity cycles by computing 2.5 GV proton intensities using a two-dimensional, time-dependent modulation model. By incorporating recent theoretical advances in the relevant transport parameters in the model, we showed in previous work that this approach gave realistic computed intensities over a solar cycle. New in this work is that a time dependence of the solar wind termination shock (TS) position is implemented in our model to study the effect of a dynamic inner heliosheath thickness (the region between the TS and heliopause) on the solar modulationmore » of galactic cosmic rays. The study reveals that changes in the inner heliosheath thickness, arising from a time-dependent shock position, does affect cosmic-ray intensities everywhere in the heliosphere over a solar cycle, with the smallest effect in the innermost heliosphere. A time-dependent TS position causes a phase difference between the solar activity periods and the corresponding intensity periods. The maximum intensities in response to a solar minimum activity period are found to be dependent on the time-dependent TS profile. It is found that changing the width of the inner heliosheath with time over a solar cycle can shift the time of when the maximum or minimum cosmic-ray intensities occur at various distances throughout the heliosphere, but more significantly in the outer heliosphere. The time-dependent extent of the inner heliosheath, as affected by solar activity conditions, is thus an additional time-dependent factor to be considered in the long-term modulation of cosmic rays.« less

Safety of LigaSure in recurrent laryngeal nerve dissection-porcine model using continuous monitoring.

PubMed

Dionigi, Gianlorenzo; Chiang, Feng-Yu; Kim, Hoon Yub; Randolph, Gregory W; Mangano, Alberto; Chang, Pi-Ying; Lu, I-Cheng; Lin, Yi-Chu; Chen, Hui-Chun; Wu, Che-Wei

2017-07-01

This study investigated recurrent laryngeal nerve (RLN) real-time electromyography (EMG) data to define optimal safety parameters of the LigaSure Small Jaw (LSJ) instrument during thyroidectomy. Prospective animal model. Dynamic EMG tracings were recorded from 32 RLNs (16 piglets) during various applications of LSJ around using continuous electrophysiologic monitoring. At varying distances from the RLN, the LSJ was activated (activation study). The LSJ was also applied to the RLN at timed intervals after activation and after a cooling maneuver through placement on the sternocleidomastoid muscle (cooling study). In the activation study, there was no adverse EMG event at 2 to 5 mm distance (16 RLNs, 96 tests). In the cooling study, there was no adverse EMG event after 2-second cooling time (16 RLNs, 96 tests) or after the LSJ cooling maneuver on the surrounding muscle before reaching the RLNs (8 RLNs, 24 tests). Based on EMG functional assessment, the safe distance for LSJ activation was 2 mm. Further LSJ-RLN contact was safe if the LSJ was cooled for more than 2 seconds or cooled by touch muscle maneuver. The LSJ should be used with these distance and time parameters in mind to avoid RLN injury. N/A. Laryngoscope, 127:1724-1729, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Scopes for Schools: A Low-Cost Model for Bringing Hands-On Astronomy to the K-12 Classroom

NASA Astrophysics Data System (ADS)

Stassun, K. G.; Lattis, J.

1999-12-01

We present a low-cost, field-tested model for astronomy and space-related outreach aimed at minority and under-serviced populations at the middle-school and high-school levels. The model centers around the creation of an extracurricular astronomy ``club" at a middle school or high school, and an in-service training activity for teachers who will serve as club leaders. Students in the club engage in two hands-on activities: telescope-building and model rocketry. Implementation of the model requires a time investment of 1--2 hours per week over the course of one school year. The primary end products are (1) an ongoing extracurricular school club with trained teacher-leaders, (2) a set of portable Dobsonian telescopes for night-time sky-viewing sessions performed by the club as a service to the community, and (3) basic materials for continued model-rocketry activities. In its ideal implementation, the model brings together teachers and amateur astronomers in a lasting partnership. A specific example for funding an outreach program based on this model is presented. This outreach development was funded by a Special Initiatives outreach grant from the Wisconsin Space Grant Consortium, and by the UW-Madison College Access Program. Additional support was provided by Madison's amateur astronomy organization, the Madison Astronomical Society.

Bringing Astronomy to the Classroom: A Model for Planting Seeds of Interest

NASA Astrophysics Data System (ADS)

Stassun, K. G.; Lattis, J.

1999-05-01

We present a low-cost, field-tested model for astronomy and space-related outreach aimed at minority and under-serviced populations at the middle-school and high-school levels. The model centers around the creation of an extracurricular astronomy ``club" at a middle school or high school, and an in-service training activity for teachers who will serve as club leaders. Students in the club engage in two hands-on activities: telescope-building and model rocketry. Implementation of the model requires a time investment of 1--2 hours per week over the course of one school year. The primary end products are (1) an ongoing extracurricular school club with trained teacher-leaders, (2) a set of portable Dobsonian telescopes for night-time sky-viewing sessions performed by the club as a service to the community, and (3) basic materials for continued model-rocketry activities. In its ideal implementation, the model brings together teachers and amateur astronomers in a lasting partnership. A specific example for funding an outreach program based on this model is presented. This outreach development was funded by a Special Initiatives outreach grant from the Wisconsin Space Grant Consortium, and by the UW-Madison College Access Program. Additional support was provided by Madison's organization of amateur astronomers, the Madison Astronomical Society.

Simulation and analysis of vertical displacement characteristics of three wheels reverse trike vehicle with PID controller application

NASA Astrophysics Data System (ADS)

Wibowo, Lambang, Lullus; Erick Chandra, N.; Muhayat, Nurul; Jaka S., B.

2017-08-01

The purpose of this research is to obtain a mathematical model (Full Vehicle Model) and compare the performance of passive and active suspension systems of a Three-Wheels Reverse Trike vehicle. Vehicle suspension system should able to provide good steering handling and passenger comfort. Vehicle suspension system generally only uses passive suspension components with fix spring and damper coefficients. An active suspension developed from the traditional (passive) suspension design can directly control the actuator force in the suspension system. In this paper, modeling and simulation of passive and active suspension system for a Full Vehicle Model is performed using Simulink-MATLAB software. Ziegler & Nichols tuning method is used to obtain controller parameters of Proportional Integral Derivative (PID) controller. Comparison between passive and active suspension with PID controller is conducted for disturbances input of single bump road surface profile 0.1 meters. The results are the displacement and acceleration of the vehicle body in the vertical direction of active suspension system with PID control is better in providing handling capabilities and comfort for the driver than of passive suspension system. The acceleration of 1,8G with the down time of 2.5 seconds is smaller than the acceleration of 2.5G with down time of 5.5 seconds.

Influence of socio-demographic factors on physical activity participation in a sample of adults in Penang, Malaysia.

PubMed

Cheah, Y K

2011-12-01

Given the importance of physical activity to health, this study investigated the socio-demographic determinants of physical activity participation in a sample of adults in Penang. Through convenience sampling, a total of 398 adults agreed to answer a prepared questionnaire on their socio-demographic background and physical activity participation. The data were analysed using the binary logit model. Frequent physical activity participation is defined as taking part more than 11 times in leisure-time physical activity such as swimming and jogging, each time lasting more than 15 minutes in a typical month, whereas participation that is less than the frequency and time duration specified above is referred to as infrequent physical activity. Age, male, being Chinese, high educational attainment, self-rated excellent health status and presence of family illnesses are positively associated with the likelihood of frequent participation in physical activity. On the contrary, being married, having low income and residing in rural areas are inversely related with the propensity of frequent physical activity participation. The majority in this sample of adults do not participate in physical activity frequently, and the reasons given include lack of health awareness, limited leisure time, budget constraints, and lack of sports amenities.

Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization

PubMed Central

Strobbe, Gregor; Carrette, Evelien; López, José David; Montes Restrepo, Victoria; Van Roost, Dirk; Meurs, Alfred; Vonck, Kristl; Boon, Paul; Vandenberghe, Stefaan; van Mierlo, Pieter

2016-01-01

Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources. PMID:26958464

Trunk muscle recruitment patterns in simulated precrash events.

PubMed

Ólafsdóttir, Jóna Marín; Fice, Jason B; Mang, Daniel W H; Brolin, Karin; Davidsson, Johan; Blouin, Jean-Sébastien; Siegmund, Gunter P

2018-02-28

To quantify trunk muscle activation levels during whole body accelerations that simulate precrash events in multiple directions and to identify recruitment patterns for the development of active human body models. Four subjects (1 female, 3 males) were accelerated at 0.55 g (net Δv = 4.0 m/s) in 8 directions while seated on a sled-mounted car seat to simulate a precrash pulse. Electromyographic (EMG) activity in 4 trunk muscles was measured using wire electrodes inserted into the left rectus abdominis, internal oblique, iliocostalis, and multifidus muscles at the L2-L3 level. Muscle activity evoked by the perturbations was normalized by each muscle's isometric maximum voluntary contraction (MVC) activity. Spatial tuning curves were plotted at 150, 300, and 600 ms after acceleration onset. EMG activity remained below 40% MVC for the three time points for most directions. At the 150- and 300 ms time points, the highest EMG amplitudes were observed during perturbations to the left (-90°) and left rearward (-135°). EMG activity diminished by 600 ms for the anterior muscles, but not for the posterior muscles. These preliminary results suggest that trunk muscle activity may be directionally tuned at the acceleration level tested here. Although data from more subjects are needed, these preliminary data support the development of modeled trunk muscle recruitment strategies in active human body models that predict occupant responses in precrash scenarios.

Superheated water pretreatment combined with CO2 activation/regeneration of the exhausted activated carbon used in the treatment of industrial wastewater.

PubMed

Xiao, Jin; Yu, Bailie; Zhong, Qifan; Yuan, Jie; Yao, Zhen; Zhang, Liuyun

2017-10-01

This paper examines a novel method of regenerating saturated activated carbon after adsorption of complex phenolic, polycyclic aromatic hydrocarbons with low energy consumption by using superheated water pretreatment combined with CO 2 activation. The effects of the temperature of the superheated water, liquid-solid ratio, soaking time, activation temperature, activation time, and CO 2 flow rate of regeneration and adsorption of coal-powdered activated carbon (CPAC) were studied. The results show that the adsorption capacity of iodine values on CPAC recovers to 102.25% of the fresh activated carbon, and the recovery rate is 79.8% under optimal experimental conditions. The adsorption model and adsorption kinetics of methylene blue on regenerated activated carbon (RAC) showed that the adsorption process was in accordance with the Langmuir model and the pseudo-second-order kinetics model. Furthermore, the internal diffusion process was the main controlling step. The surface properties, Brunauer-Emmett-Teller (BET) surface area, and pore size distribution were characterized by Fourier transform infrared spectroscopy (FT-IR) and BET, which show that the RAC possesses more oxygen-containing functional groups with a specific surface area of 763.39 m 2 g -1 and a total pore volume of 0.3039 cm 3 g -1 . Micropores account for 79.8% and mesopores account for 20.2%.

Global model of the F2 layer peak height for low solar activity based on GPS radio-occultation data

NASA Astrophysics Data System (ADS)

Shubin, V. N.; Karpachev, A. T.; Tsybulya, K. G.

2013-11-01

We propose a global median model SMF2 (Satellite Model of the F2 layer) of the ionospheric F2-layer height maximum (hmF2), based on GPS radio-occultation data for low solar activity periods (F10.7A<80). The model utilizes data provided by GPS receivers onboard satellites CHAMP (~100,000 hmF2 values), GRACE (~70,000) and COSMIC (~2,000,000). The data were preprocessed to remove cases where the absolute maximum of the electron density lies outside the F2 region. Ground-based ionospheric sounding data were used for comparison and validation. Spatial dependence of hmF2 is modeled by a Legendre-function expansion. Temporal dependence, as a function of Universal Time (UT), is described by a Fourier expansion. Inputs of the model are: geographical coordinates, month and F10.7A solar activity index. The model is designed for quiet geomagnetic conditions (Kр=1-2), typical for low solar activity. SMF2 agrees well with the International Reference Ionosphere model (IRI) in those regions, where the ground-based ionosonde network is dense. Maximal difference between the models is found in the equatorial belt, over the oceans and the polar caps. Standard deviations of the radio-occultation and Digisonde data from the predicted SMF2 median are 10-16 km for all seasons, against 13-29 km for IRI-2012. Average relative deviations are 3-4 times less than for IRI, 3-4% against 9-12%. Therefore, the proposed hmF2 model is more accurate than IRI-2012.

Modelling nanoflares in active regions and implications for coronal heating mechanisms

PubMed Central

Cargill, P. J.; Warren, H. P.; Bradshaw, S. J.

2015-01-01

Recent observations from the Hinode and Solar Dynamics Observatory spacecraft have provided major advances in understanding the heating of solar active regions (ARs). For ARs comprising many magnetic strands or sub-loops heated by small, impulsive events (nanoflares), it is suggested that (i) the time between individual nanoflares in a magnetic strand is 500–2000 s, (ii) a weak ‘hot’ component (more than 106.6 K) is present, and (iii) nanoflare energies may be as low as a few 1023 ergs. These imply small heating events in a stressed coronal magnetic field, where the time between individual nanoflares on a strand is of order the cooling time. Modelling suggests that the observed properties are incompatible with nanoflare models that require long energy build-up (over 10 s of thousands of seconds) and with steady heating. PMID:25897093

Predicting mountain lion activity using radiocollars equipped with mercury tip-sensors

USGS Publications Warehouse

Janis, Michael W.; Clark, Joseph D.; Johnson, Craig

1999-01-01

Radiotelemetry collars with tip-sensors have long been used to monitor wildlife activity. However, comparatively few researchers have tested the reliability of the technique on the species being studied. To evaluate the efficacy of using tip-sensors to assess mountain lion (Puma concolor) activity, we radiocollared 2 hand-reared mountain lions and simultaneously recorded their behavior and the associated telemetry signal characteristics. We noted both the number of pulse-rate changes and the percentage of time the transmitter emitted a fast pulse rate (i.e., head up) within sampling intervals ranging from 1-5 minutes. Based on 27 hours of observations, we were able to correctly distinguish between active and inactive behaviors >93% of the time using a logistic regression model. We present several models to predict activity of mountain lions; the selection of which to us would depend on study objectives and logistics. Our results indicate that field protocols that use only pulse-rate changes to indicate activity can lead to significant classification errors.

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

NASA Astrophysics Data System (ADS)

Nita, Gelu M.; Viall, Nicholeen M.; Klimchuk, James A.; Loukitcheva, Maria A.; Gary, Dale E.; Kuznetsov, Alexey A.; Fleishman, Gregory D.

2018-01-01

The study of time-dependent solar active region (AR) morphology and its relation to eruptive events requires analysis of imaging data obtained in multiple wavelength domains with differing spatial and time resolution, ideally in combination with 3D physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tool, GX_Simulator, previously developed for modeling microwave and X-ray emission from flaring loops, to allow it to simulate quiescent emission from solar ARs. The framework includes new tools for building the atmospheric model and enhanced routines for calculating emission that include new wavelengths. In this paper, we use our upgraded tool to model and analyze an AR and compare the synthetic emission maps with observations. We conclude that the modeled magneto-thermal structure is a reasonably good approximation of the real one.

Comparative evaluation of features and techniques for identifying activity type and estimating energy cost from accelerometer data

PubMed Central

Kate, Rohit J.; Swartz, Ann M.; Welch, Whitney A.; Strath, Scott J.

2016-01-01

Wearable accelerometers can be used to objectively assess physical activity. However, the accuracy of this assessment depends on the underlying method used to process the time series data obtained from accelerometers. Several methods have been proposed that use this data to identify the type of physical activity and estimate its energy cost. Most of the newer methods employ some machine learning technique along with suitable features to represent the time series data. This paper experimentally compares several of these techniques and features on a large dataset of 146 subjects doing eight different physical activities wearing an accelerometer on the hip. Besides features based on statistics, distance based features and simple discrete features straight from the time series were also evaluated. On the physical activity type identification task, the results show that using more features significantly improve results. Choice of machine learning technique was also found to be important. However, on the energy cost estimation task, choice of features and machine learning technique were found to be less influential. On that task, separate energy cost estimation models trained specifically for each type of physical activity were found to be more accurate than a single model trained for all types of physical activities. PMID:26862679

Physical activity and calorie intake mediate the relationship from depression to body fat mass among female Mexican health workers.

PubMed

Quezada, Amado D; Macías-Waldman, Nayeli; Salmerón, Jorge; Swigart, Tessa; Gallegos-Carrillo, Katia

2017-11-17

Depression is a foremost cause of morbidity throughout the world and the prevalence of depression in women is about twice as high as men. Additionally, overweight and obesity are major global health concerns. We explored the relationship between depression and body fat, and the role of physical activity and diet as mediators of this relationship in a sample of 456 adult female Mexican health workers. Longitudinal and cross-sectional analyses using data from adult women of the Health Workers Cohort Study (HWCS) Measures of body fat mass (kg from DEXA), dietary intake (kcal from FFQ), leisure time activity (METs/wk) and depression (CES-D) were determined in two waves (2004-2006 and 2010-2011). We explored the interrelation between body fat, diet, leisure time, physical activity, and depression using a cross-lagged effects model fitted to longitudinal data. We also fitted a structural equations model to cross-sectional data with body fat as the main outcome, and dietary intake and physical activity from leisure time as mediators between depression and body fat. Baseline depression was significantly related to higher depression, higher calorie intake, and lower leisure time physical activity at follow-up. From our cross-sectional model, each standard deviation increase in the depression score was associated with an average increase of 751 ± 259 g (± standard error) in body fat through the mediating effects of calorie intake and physical activity. The results of this study show how depression may influence energy imbalance between calories consumed and calories expended, resulting in higher body fat among those with a greater depression score. Evaluating the role of mental conditions like depression in dietary and physical activity behaviors should be positioned as a key research goal for better designed and targeted public health interventions. The HealthWorkers Cohort Study (HWCS) has been approved by the Institutional IRB. Number: 2005-785-012.

Quantification of the Bioturbation Activity of Lumbriculus Variegatus Worms Using Fluorescent Particulate Tracers

NASA Astrophysics Data System (ADS)

Hernandez-Gonzalez, L. M.; Roche, K. R.; Xie, M.; Packman, A. I.

2014-12-01

Important biological, physical and chemical processes, such as fluxes of oxygen, nutrients and contaminants, occur across sediment-water interfaces. These processes are influenced by bioturbation activities of benthic animals. Bioturbation is thought to be significant in releasing metals to the water column from contaminated sediments, but metals contamination also affects organism activity. Consequently, the aim of this study was to consider the interactions of biological activity, sediment chemistry, pore water transport, and chemical reactions in sediment mixing and the flux and toxicity of metals in sediments. Prior studies have modeled bioturbation as a diffusive process. However, diffusion models often do not describe accurately sediment mixing due to bioturbation. To this end, we used the continuous time random walk (CTRW) model to assess sediment mixing caused by bioturbation activity of Lumbriculus variegatus worms. We performed experiments using fine-grained sediments with different levels of zinc contamination from Lake DePue, which is a Superfund Site in Illinois. The tests were conducted in an aerated fresh water chamber. Fluorescent particulate tracers were added to the sediment surface to quantify mixing processes and the influence of metals contaminants on L. variegatus bioturbation activity. We observed sediment mixing and organism activity by time-lapse photography over 14 days. Then, we analyzed the images to characterize the fluorescent particle concentration as a function of sediment depth and time. Results reveal that sediment mixing caused by L. variegatus is subdiffusive in time and superdiffusive in space. These results suggest that anomalous sediment mixing is probably a ubiquitous process, as this behavior has only been observed previously in marine sediments. Also, the experiments indicate that bioturbation and sediment mixing decreased in the presence of higher metals concentrations in sediments. This process is expected to decrease efflux of metals from highly contaminated sediments by reducing biological activity.

Changes in Drosophila melanogaster Sleep-Wake Behavior Due to Lotus (Nelumbo nucifera) Seed and Hwang Jeong (Polygonatum sibiricum) Extracts

PubMed Central

Jo, Kyungae; Jeon, SangDuk; Ahn, Chang-Won; Han, Sung Hee; Suh, Hyung Joo

2017-01-01

We evaluated the sleep enhancement activity of the medicinal herbs valerian (Valeriana officinalis), jujube (Ziziphus jujube), lotus seed (Nelumbo nucifera), Gastrodia elata, Polygonatum sibiricum, and baekbokryung (Poria cocos), which can relieve insomnia in a Drosophila model. Locomotor activity was measured in the Drosophila model to evaluate the sleep activity of Korean medicinal herbs traditionally used as sleep aids. The group treated with lotus seed extract showed less nocturnal activity. Treatment with 10 or 20 mg/mL of P. sibiricum significantly reduced nocturnal activity compared to the control group (P<0.05). The activity and sleep bouts of fruit flies were significantly decreased by a high-dose treatment (10 mg/mL) of lotus or P. sibiricum extracts at night. Caffeine-treated Drosophila showed increased nocturnal activity and decreased total sleep time (P<0.05). Flies receiving the 10 mg-doses of lotus seed or P. sibiricum extract showed significantly different nocturnal locomotor activity and total sleep time compared to caffeine-treated Drosophila. Lotus seed and P. sibiricum extracts are attractive and valuable sleep-potentiating nutraceuticals. PMID:29333381

Evaluation of wound healing and anti-inflammatory activity of the rhizomes of Rumex abyssinicus J. (Polygonaceae) in mice.

PubMed

Mulisa, Eshetu; Asres, Kaleab; Engidawork, Ephrem

2015-09-30

Rumex abyssinicus Jacq (Polygonaceae) is widely used in Ethiopia for treatment of wound and other diseases. Although reports are available in the literature on some of the claimed activities, nothing has so far been reported about the wound healing activity of R. abyssinicus. Thus, this work was initiated to investigate the wound healing and anti-inflammatory activities of 80% methanol extract of the rhizomes of R. abyssinicus in mice. Following extraction of the rhizomes of the plant with 80% methanol, the extract was formulated as ointment (5% & 10% w/w) with simple ointment base B.P. The ointment was then evaluated for wound healing activity using excision and incision wound models. Parameters, including wound contraction, epithelization time and hydroxyproline content were determined using the excision model, whereas tensile strength was measured from the incision model. In parallel, anti-inflammatory activity of the rhizome was evaluated with carrageenan induced hind paw edema model by dissolving the 80% methanol extract in 1% carboxyl methyl cellulose and administering orally in various doses (250, 500 and 750 mg/kg). Wound treated with 5% and 10% (w/w) hydroalcoholic extract ointment exhibited significant wound healing activity in both models, as evidenced by increased wound contraction, shorter epithelization time, higher tissue breaking strength and increased hydroxyproline content. The hydroalcoholic extract also produced dose-related significant reduction (p < 0.05-0.001) of inflammation. The results of this study demonstrated that the hydroalcoholic extract of the rhizomes of R. abyssinicus facilitated wound healing at least in part via its anti-inflammatory activity, supporting its traditional claim as a wound healing agent.

Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction.

PubMed

Yu, Zirui; Peldszus, Sigrid; Huck, Peter M

2009-03-01

The adsorption of two representative pharmaceutically active compounds (PhACs)-naproxen and carbamazepine and one endocrine disrupting compound (EDC)-nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol.

Passive and active ventricular elastances of the left ventricle

PubMed Central

Zhong, Liang; Ghista, Dhanjoo N; Ng, Eddie YK; Lim, Soo T

2005-01-01

Background Description of the heart as a pump has been dominated by models based on elastance and compliance. Here, we are presenting a somewhat new concept of time-varying passive and active elastance. The mathematical basis of time-varying elastance of the ventricle is presented. We have defined elastance in terms of the relationship between ventricular pressure and volume, as: dP = EdV + VdE, where E includes passive (Ep) and active (Ea) elastance. By incorporating this concept in left ventricular (LV) models to simulate filling and systolic phases, we have obtained the time-varying expression for Ea and the LV-volume dependent expression for Ep. Methods and Results Using the patient's catheterization-ventriculogram data, the values of passive and active elastance are computed. Ea is expressed as: ; Epis represented as: . Ea is deemed to represent a measure of LV contractility. Hence, Peak dP/dt and ejection fraction (EF) are computed from the monitored data and used as the traditional measures of LV contractility. When our computed peak active elastance (Ea,max) is compared against these traditional indices by linear regression, a high degree of correlation is obtained. As regards Ep, it constitutes a volume-dependent stiffness property of the LV, and is deemed to represent resistance-to-filling. Conclusions Passive and active ventricular elastance formulae can be evaluated from a single-beat P-V data by means of a simple-to-apply LV model. The active elastance (Ea) can be used to characterize the ventricle's contractile state, while passive elastance (Ep) can represent a measure of resistance-to-filling. PMID:15707494

Time Use and Educational Attainment: A Study of Undergraduate Students.

ERIC Educational Resources Information Center

Etcheverry, Emily J.; And Others

1993-01-01

A Canadian university study of 308 students' time use in academic areas used a model relating variables of social background, social psychological characteristics, time use, and educational attainment. Findings suggested that, taking into account these other variables, the time students spend on academic activities and paid employment has little…

BrainLiner: A Neuroinformatics Platform for Sharing Time-Aligned Brain-Behavior Data

PubMed Central

Takemiya, Makoto; Majima, Kei; Tsukamoto, Mitsuaki; Kamitani, Yukiyasu

2016-01-01

Data-driven neuroscience aims to find statistical relationships between brain activity and task behavior from large-scale datasets. To facilitate high-throughput data processing and modeling, we created BrainLiner as a web platform for sharing time-aligned, brain-behavior data. Using an HDF5-based data format, BrainLiner treats brain activity and data related to behavior with the same salience, aligning both behavioral and brain activity data on a common time axis. This facilitates learning the relationship between behavior and brain activity. Using a common data file format also simplifies data processing and analyses. Properties describing data are unambiguously defined using a schema, allowing machine-readable definition of data. The BrainLiner platform allows users to upload and download data, as well as to explore and search for data from the web platform. A WebGL-based data explorer can visualize highly detailed neurophysiological data from within the web browser, and a data-driven search feature allows users to search for similar time windows of data. This increases transparency, and allows for visual inspection of neural coding. BrainLiner thus provides an essential set of tools for data sharing and data-driven modeling. PMID:26858636

Productivity and cost of marking activities for single-tree selection and thinning treatments in Arkansas

Treesearch

Tymur Sydor; Richard A. Kluender; Rodney L. Busby; Matthew Pelkki

2004-01-01

An activity algorithm was developed for standard marking methods for natural pine stands in Arkansas. For the two types of marking methods examined, thinning (selection from below) and single-tree selection (selection from above), cycle time and cost models were developed. Basal area (BA) removed was the major influencing factor in both models. Marking method was...

Health Optimizing Physical Education (HOPE): A New Curriculum for School Programs--Part 1: Establishing the Need and Describing the Model

ERIC Educational Resources Information Center

Metzler, Michael W.; McKenzie, Thomas L.; van der Mars, Hans; Barrett-Williams, Shannon L.; Ellis, Rebecca

2013-01-01

Comprehensive School Physical Activity Programs (CSPAP) are designed to provide expanded opportunities for physical activity beyond regularly scheduled physical education time-including before, during, and after school, as well as at home and in the community. While CSPAPs are gaining support, currently there are no models for designing,…

Starspot detection and properties

NASA Astrophysics Data System (ADS)

Savanov, I. S.

2013-07-01

I review the currently available techniques for the starspots detection including the one-dimensional spot modelling of photometric light curves. Special attention will be paid to the modelling of photospheric activity based on the high-precision light curves obtained with space missions MOST, CoRoT, and Kepler. Physical spot parameters (temperature, sizes and variability time scales including short-term activity cycles) are discussed.

AERIS--applications for the environment : real-time information synthesis state-of-the-practice support : state of the practice scan of behavioral and activity-based models.

DOT National Transportation Integrated Search

2011-06-19

This report has been developed under the Track 1 effort of Phase 1 of the AERIS program and presents the findings of the state-of-the-practice scan of behavioral and activity-based models and their ability to predict traveler choices and behavior in ...

Investigation of toilet activities in elderly patients with dementia from the viewpoint of motivation and self-awareness.

PubMed

Uchimoto, Kazuki; Yokoi, Teruo; Yamashita, Teruo; Okamura, Hitoshi

2013-08-01

Toilet activities of the elderly patients with dementia were observed focusing on care conditions and investigated based on Hull's drive reduction theory (behavior = drive × habit × incentive) and our self-awareness model (consisting of theory of mind, self-evaluation, and self-consciousness) to evaluate the association between self-awareness and toilet activities in patients with dementia and to explain the time when and the reason why a series of toilet activities as habit once acquired become unfeasible. If theory of mind is lost, awareness of one's desire and intention becomes vague, and toilet activities begin to collapse. Furthermore, if incentive disappears, one's intention hardly arises and toilet activities further collapse. If self-evaluation is lost, time sense fades, future goals based on the present time cannot exist, and behavior loses directivity. As a result, toilet activities collapse, and with a decrease in drive toilet activities cease.

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

PubMed Central

Wagatsuma, Nobuhiko; Sakai, Ko

2017-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision. PMID:28163688

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions.

PubMed

Wagatsuma, Nobuhiko; Sakai, Ko

2016-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision.

A validation of ground ambulance pre-hospital times modeled using geographic information systems

PubMed Central

2012-01-01

Background Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. Methods The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. Results There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7–8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. Conclusions The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area. PMID:23033894

Evaluation of the Circulatory Dynamics by using the Windkessel Model in Different Body Positions

NASA Astrophysics Data System (ADS)

Kotani, Kiyoshi; Iida, Fumiaki; Ogawa, Yutaro; Takamasu, Kiyoshi; Jimbo, Yasuhiko

Autonomic nervous system is important in maintaining homeostasis by the opposing effects of sympathetic and parasympathetic nervous activity on organs. However, it is known that they are at times simultaneously increased or decreased in cases of strong fear or depression. Therefore, it is required to evaluate sympathetic and parasympathetic nervous activity independently. In this paper, we propose a method to evaluate sympathetic nervous activity by analyzing the decreases in blood pressure by utilizing the Windkessel model. Experiments are performed in sitting and standing positions for 380 s, respectively. First, we evaluate the effects of length for analysis on the Windkessel time constant. We shorten the length for analysis by multiplying constant coefficients (1.0, 0.9, and 0.8) to the length of blood pressure decrease and then cut-out the waveform for analysis. Then it is found that the Windkessel time constant is decreased as the length for analysis is shortened. This indicates that the length for analysis should be matched when the different experiments are compared. Second, we compare the Windkessel time constant of sitting to that of standing by matching their length for analysis. With statistically significant difference (P<0.05) the results indicate that the Windkessel time constant is larger in the sitting position. Through our observations this difference in the Windkessel time constant is caused by sympathetic nervous activity on vascular smooth muscle.

Modeling early events in Francisella tularensis pathogenesis.

PubMed

Gillard, Joseph J; Laws, Thomas R; Lythe, Grant; Molina-París, Carmen

2014-01-01

Computational models can provide valuable insights into the mechanisms of infection and be used as investigative tools to support development of medical treatments. We develop a stochastic, within-host, computational model of the infection process in the BALB/c mouse, following inhalational exposure to Francisella tularensis SCHU S4. The model is mechanistic and governed by a small number of experimentally verifiable parameters. Given an initial dose, the model generates bacterial load profiles corresponding to those produced experimentally, with a doubling time of approximately 5 h during the first 48 h of infection. Analytical approximations for the mean number of bacteria in phagosomes and cytosols for the first 24 h post-infection are derived and used to verify the stochastic model. In our description of the dynamics of macrophage infection, the number of bacteria released per rupturing macrophage is a geometrically-distributed random variable. When combined with doubling time, this provides a distribution for the time taken for infected macrophages to rupture and release their intracellular bacteria. The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics. Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.

Missing pieces to modeling the Arctic-Boreal puzzle

NASA Astrophysics Data System (ADS)

Fisher, Joshua B.; Hayes, Daniel J.; Schwalm, Christopher R.; Huntzinger, Deborah N.; Stofferahn, Eric; Schaefer, Kevin; Luo, Yiqi; Wullschleger, Stan D.; Goetz, Scott; Miller, Charles E.; Griffith, Peter; Chadburn, Sarah; Chatterjee, Abhishek; Ciais, Philippe; Douglas, Thomas A.; Genet, Hélène; Ito, Akihiko; Neigh, Christopher S. R.; Poulter, Benjamin; Rogers, Brendan M.; Sonnentag, Oliver; Tian, Hanqin; Wang, Weile; Xue, Yongkang; Yang, Zong-Liang; Zeng, Ning; Zhang, Zhen

2018-02-01

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

Antihypoxic activities of Eryngium caucasicum and Urtica dioica.

PubMed

Khalili, M; Dehdar, T; Hamedi, F; Ebrahimzadeh, M A; Karami, M

2015-09-01

Urtica dioica and Eryngium spp. have been used in traditional medicine for many years. In spite of many works, nothing is known about their protective effect against hypoxia-induced lethality. Protective effects of U. dioica (UD) aerial parts and E. caucasicum (EC) inflorescence against hypoxia-induced lethality in mice were evaluated by three experimental models of hypoxia, asphyctic, haemic and circulatory. Statistically significant protective activities were established in some doses of extracts in three models. Antihypoxic activity was especially pronounced in polyphenol fractions in asphyctic model. EC polyphenol fraction at 400 mg/kg prolonged survival time (48.80 ± 4.86, p < 0.001) which was comparable with that of phenytoin (p > 0.05). It was the most effective extract in circulatory model, too. It prolonged survival time significantly respect to control group (p < 0.001). UD extracts protected the mice but the response was not dose-dependent. In haemic model, extracts of EP significantly and dose dependently prolonged survival time as compared to control group (p < 0.001). At 600 mg/kg, EP was the most effective one, being capable of keeping the mice alive for 12.71 ± 0.75 min. Only the concentration of 300 mg/kg of UD was effective (p < 0.001). Extracts showed remarkable antihypoxic effects. Pharmacological effects may be attributed to the presence of polyphenols in the extracts.

DEVELOPING MEANINGFUL COHORTS FOR HUMAN EXPOSURE MODELS

EPA Science Inventory

This paper summarizes numerous statistical analyses focused on the U.S. Environmental Protection Agency's Consolidated Human Activity Database (CHAD), used by many exposure modelers as the basis for data on what people do and where they spend their time. In doing so, modelers ...

The Dynamics of Phonological Planning

ERIC Educational Resources Information Center

Roon, Kevin D.

2013-01-01

This dissertation proposes a dynamical computational model of the timecourse of phonological parameter setting. In the model, phonological representations embrace phonetic detail, with phonetic parameters represented as activation fields that evolve over time and determine the specific parameter settings of a planned utterance. Existing models of…

Negotiating on location, timing, duration, and participant in agent-mediated joint activity-travel scheduling

NASA Astrophysics Data System (ADS)

Ma, Huiye; Ronald, Nicole; Arentze, Theo A.; Timmermans, Harry J. P.

2013-10-01

Agent-based simulation has become an important modeling approach in activity-travel analysis. Social activities account for a large amount of travel and have an important effect on activity-travel scheduling. Participants in joint activities usually have various options regarding location, participants, and timing and take different approaches to make their decisions. In this context, joint activity participation requires negotiation among agents involved, so that conflicts among the agents can be addressed. Existing mechanisms do not fully provide a solution when utility functions of agents are nonlinear and non-monotonic. Considering activity-travel scheduling in time and space as an application, we propose a novel negotiation approach, which takes into account these properties, such as continuous and discrete issues, and nonlinear and non-monotonic utility functions, by defining a concession strategy and a search mechanism. The results of experiments show that agents having these properties can negotiate efficiently. Furthermore, the negotiation procedure affects individuals’ choices of location, timing, duration, and participants.

A hidden Markov model for decoding and the analysis of replay in spike trains.

PubMed

Box, Marc; Jones, Matt W; Whiteley, Nick

2016-12-01

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of position, which we find to be a more parsimonious description of the system than other models. We use a sequential Monte Carlo algorithm for Bayesian inference of model parameters, including the state space dimension, and we explain how to estimate position from spike train observations (decoding). We obtain greater accuracy over other methods in the conditions of high temporal resolution and small neuronal sample size. We also present a novel, model-based approach to the study of replay: the expression of spike train activity related to behaviour during times of motionlessness or sleep, thought to be integral to the consolidation of long-term memories. We demonstrate how we can detect the time, information content and compression rate of replay events in simulated and real hippocampal data recorded from rats in two different environments, and verify the correlation between the times of detected replay events and of sharp wave/ripples in the local field potential.

Time evolution of interhemispheric coupling in a model of focal neocortical epilepsy in mice

NASA Astrophysics Data System (ADS)

Vallone, F.; Vannini, E.; Cintio, A.; Caleo, M.; Di Garbo, A.

2016-09-01

Epilepsy is characterized by substantial network rearrangements leading to spontaneous seizures and little is known on how an epileptogenic focus impacts on neural activity in the contralateral hemisphere. Here, we used a model of unilateral epilepsy induced by injection of the synaptic blocker tetanus neurotoxin (TeNT) in the mouse primary visual cortex (V1). Local field potential (LFP) signals were simultaneously recorded from both hemispheres of each mouse in acute phase (peak of toxin action) and chronic condition (completion of TeNT effects). To characterize the neural electrical activities the corresponding LFP signals were analyzed with several methods of time series analysis. For the epileptic mice, the spectral analysis showed that TeNT determines a power redistribution among the different neurophysiological bands in both acute and chronic phases. Using linear and nonlinear interdependence measures in both time and frequency domains, it was found in the acute phase that TeNT injection promotes a reduction of the interhemispheric coupling for high frequencies (12 -30 Hz) and small time lag (<20 ms), whereas an increase of the coupling is present for low frequencies (0.5 -4 Hz) and long time lag (>40 ms). On the other hand, the chronic period is characterized by a partial or complete recovery of the interhemispheric interdependence level. Granger causality test and symbolic transfer entropy indicate a greater driving influence of the TeNT-injected side on activity in the contralateral hemisphere in the chronic phase. Lastly, based on experimental observations, we built a computational model of LFPs to investigate the role of the ipsilateral inhibition and exicitatory interhemispheric connections in the dampening of the interhemispheric coupling. The time evolution of the interhemispheric coupling in such a relevant model of epilepsy has been addressed here.

Time evolution of interhemispheric coupling in a model of focal neocortical epilepsy in mice.

PubMed

Vallone, F; Vannini, E; Cintio, A; Caleo, M; Di Garbo, A

2016-09-01

Epilepsy is characterized by substantial network rearrangements leading to spontaneous seizures and little is known on how an epileptogenic focus impacts on neural activity in the contralateral hemisphere. Here, we used a model of unilateral epilepsy induced by injection of the synaptic blocker tetanus neurotoxin (TeNT) in the mouse primary visual cortex (V1). Local field potential (LFP) signals were simultaneously recorded from both hemispheres of each mouse in acute phase (peak of toxin action) and chronic condition (completion of TeNT effects). To characterize the neural electrical activities the corresponding LFP signals were analyzed with several methods of time series analysis. For the epileptic mice, the spectral analysis showed that TeNT determines a power redistribution among the different neurophysiological bands in both acute and chronic phases. Using linear and nonlinear interdependence measures in both time and frequency domains, it was found in the acute phase that TeNT injection promotes a reduction of the interhemispheric coupling for high frequencies (12-30 Hz) and small time lag (<20 ms), whereas an increase of the coupling is present for low frequencies (0.5-4 Hz) and long time lag (>40 ms). On the other hand, the chronic period is characterized by a partial or complete recovery of the interhemispheric interdependence level. Granger causality test and symbolic transfer entropy indicate a greater driving influence of the TeNT-injected side on activity in the contralateral hemisphere in the chronic phase. Lastly, based on experimental observations, we built a computational model of LFPs to investigate the role of the ipsilateral inhibition and exicitatory interhemispheric connections in the dampening of the interhemispheric coupling. The time evolution of the interhemispheric coupling in such a relevant model of epilepsy has been addressed here.

An open simulation approach to identify chances and limitations for vulnerable road user (VRU) active safety.

PubMed

Seiniger, Patrick; Bartels, Oliver; Pastor, Claus; Wisch, Marcus

2013-01-01

It is commonly agreed that active safety will have a significant impact on reducing accident figures for pedestrians and probably also bicyclists. However, chances and limitations for active safety systems have only been derived based on accident data and the current state of the art, based on proprietary simulation models. The objective of this article is to investigate these chances and limitations by developing an open simulation model. This article introduces a simulation model, incorporating accident kinematics, driving dynamics, driver reaction times, pedestrian dynamics, performance parameters of different autonomous emergency braking (AEB) generations, as well as legal and logical limitations. The level of detail for available pedestrian accident data is limited. Relevant variables, especially timing of the pedestrian appearance and the pedestrian's moving speed, are estimated using assumptions. The model in this article uses the fact that a pedestrian and a vehicle in an accident must have been in the same spot at the same time and defines the impact position as a relevant accident parameter, which is usually available from accident data. The calculations done within the model identify the possible timing available for braking by an AEB system as well as the possible speed reduction for different accident scenarios as well as for different system configurations. The simulation model identifies the lateral impact position of the pedestrian as a significant parameter for system performance, and the system layout is designed to brake when the accident becomes unavoidable by the vehicle driver. Scenarios with a pedestrian running from behind an obstruction are the most demanding scenarios and will very likely never be avoidable for all vehicle speeds due to physical limits. Scenarios with an unobstructed person walking will very likely be treatable for a wide speed range for next generation AEB systems.

Delayed reverberation through time windows as a key to cerebellar function.

PubMed

Kistler, W M; Leo van Hemmen, J

1999-11-01

We present a functional model of the cerebellum comprising cerebellar cortex, inferior olive, deep cerebellar nuclei, and brain stem nuclei. The discerning feature of the model being time coding, we consistently describe the system in terms of postsynaptic potentials, synchronous action potentials, and propagation delays. We show by means of detailed single-neuron modeling that (i) Golgi cells can fulfill a gating task in that they form short and well-defined time windows within which granule cells can reach firing threshold, thus organizing neuronal activity in discrete 'time slices', and that (ii) rebound firing in cerebellar nuclei cells is a robust mechanism leading to a delayed reverberation of Purkinje cell activity through cerebellar-reticular projections back to the cerebellar cortex. Computer simulations of the whole cerebellar network consisting of several thousand neurons reveal that reverberation in conjunction with long-term plasticity at the parallel fiber-Purkinje cell synapses enables the system to learn, store, and recall spatio-temporal patterns of neuronal activity. Climbing fiber spikes act both as a synchronization and as a teacher signal, not as an error signal. They are due to intrinsic oscillatory properties of inferior olivary neurons and to delayed reverberation within the network. In addition to clear experimental predictions the present theory sheds new light on a number of experimental observation such as the synchronicity of climbing fiber spikes and provides a novel explanation of how the cerebellum solves timing tasks on a time scale of several hundreds of milliseconds.

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition

PubMed Central

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-01-01

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. PMID:28208736

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition.

PubMed

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-02-08

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates ( F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware.

PHYSICAL ACTIVITY INDEX FOR CHILDREN: A COMPARISON OF LITERATURE VALUES AND EPA'S CHAD

EPA Science Inventory

The physical activity index (PAI) is a measure of an individual's energy expenditure level (and thus oxygen consumption) calculated as a time-weighted average of metabolic equivalents (METS) over the individual's activities. Many exposure models rely upon EPA's CHAD data base to ...

Model of chromosomal loci dynamics in bacteria as fractional diffusion with intermittent transport

NASA Astrophysics Data System (ADS)

Gherardi, Marco; Calabrese, Ludovico; Tamm, Mikhail; Cosentino Lagomarsino, Marco

2017-10-01

The short-time dynamics of bacterial chromosomal loci is a mixture of subdiffusive and active motion, in the form of rapid relocations with near-ballistic dynamics. While previous work has shown that such rapid motions are ubiquitous, we still have little grasp on their physical nature, and no positive model is available that describes them. Here, we propose a minimal theoretical model for loci movements as a fractional Brownian motion subject to a constant but intermittent driving force, and compare simulations and analytical calculations to data from high-resolution dynamic tracking in E. coli. This analysis yields the characteristic time scales for intermittency. Finally, we discuss the possible shortcomings of this model, and show that an increase in the effective local noise felt by the chromosome associates to the active relocations.

Hybrid Markov-mass action law model for cell activation by rare binding events: Application to calcium induced vesicular release at neuronal synapses.

PubMed

Guerrier, Claire; Holcman, David

2016-10-18

Binding of molecules, ions or proteins to small target sites is a generic step of cell activation. This process relies on rare stochastic events where a particle located in a large bulk has to find small and often hidden targets. We present here a hybrid discrete-continuum model that takes into account a stochastic regime governed by rare events and a continuous regime in the bulk. The rare discrete binding events are modeled by a Markov chain for the encounter of small targets by few Brownian particles, for which the arrival time is Poissonian. The large ensemble of particles is described by mass action laws. We use this novel model to predict the time distribution of vesicular release at neuronal synapses. Vesicular release is triggered by the binding of few calcium ions that can originate either from the synaptic bulk or from the entry through calcium channels. We report here that the distribution of release time is bimodal although it is triggered by a single fast action potential. While the first peak follows a stimulation, the second corresponds to the random arrival over much longer time of ions located in the synaptic terminal to small binding vesicular targets. To conclude, the present multiscale stochastic modeling approach allows studying cellular events based on integrating discrete molecular events over several time scales.

Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

We present further simulation results of the model of two reciprocally connected visual areas proposed in the first paper [Knoblauch and Palm (2002) Biol Cybern 87:151-167]. One area corresponds to the orientation-selective subsystem of the primary visual cortex, the other is modeled as an associative memory representing stimulus objects according to Hebbian learning. We examine the scene-segmentation capability of our model on larger time and space scales, and relate it to experimental findings. Scene segmentation is achieved by attention switching on a time-scale longer than the gamma range. We find that the time-scale can vary depending on habituation parameters in the range of tens to hundreds of milliseconds. The switching process can be related to findings concerning attention and biased competition, and we reproduce experimental poststimulus time histograms (PSTHs) of single neurons under different stimulus and attentional conditions. In a larger variant the model exhibits traveling waves of activity on both slow and fast time-scales, with properties similar to those found in experiments. An apparent weakness of our standard model is the tendency to produce anti-phase correlations for fast activity from the two areas. Increasing the inter-areal delays in our model produces alternations of in-phase and anti-phase oscillations. The experimentally observed in-phase correlations can most naturally be obtained by the involvement of both fast and slow inter-areal connections; e.g., by two axon populations corresponding to fast-conducting myelinated and slow-conducting unmyelinated axons.

Multiplicative point process as a model of trading activity

NASA Astrophysics Data System (ADS)

Gontis, V.; Kaulakys, B.

2004-11-01

Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

Kinetic evaluation and test-retest reproducibility of [11C]UCB-J, a novel radioligand for positron emission tomography imaging of synaptic vesicle glycoprotein 2A in humans.

PubMed

Finnema, Sjoerd J; Nabulsi, Nabeel B; Mercier, Joël; Lin, Shu-Fei; Chen, Ming-Kai; Matuskey, David; Gallezot, Jean-Dominique; Henry, Shannan; Hannestad, Jonas; Huang, Yiyun; Carson, Richard E

2017-01-01

Synaptic vesicle glycoprotein 2A (SV2A) is ubiquitously present in presynaptic terminals. Here we report kinetic modeling and test-retest reproducibility assessment of the SV2A positron emission tomography (PET) radioligand [ 11 C]UCB-J in humans. Five volunteers were examined twice on the HRRT after bolus injection of [ 11 C]UCB-J. Arterial blood samples were collected for measurements of radiometabolites and free fraction. Regional time-activity curves were analyzed with 1-tissue (1T) and 2-tissue (2T) compartment models to estimate volumes of distribution ( V T ). Parametric maps were generated using the 1T model. [ 11 C]UCB-J metabolized fairly quickly, with parent fraction of 36 ± 13% at 15 min after injection. Plasma free fraction was 32 ± 1%. Regional time-activity curves displayed rapid kinetics and were well described by the 1T model, except for the cerebellum and hippocampus. V T values estimated with the 2T model were similar to 1T values. Parametric maps were of high quality and V T values correlated well with time activity curve (TAC)-based estimates. Shortening of acquisition time from 120 min to 60 min had a negligible effect on V T values. The mean absolute test-retest reproducibility for V T was 3-9% across regions. In conclusion, [ 11 C]UCB-J exhibited excellent PET tracer characteristics and has potential as a general purpose tool for measuring synaptic density in neurodegenerative disorders.

Family time, parental behaviour model and the initiation of smoking and alcohol use by ten-year-old children: an epidemiological study in Kaunas, Lithuania.

PubMed

Garmiene, Asta; Zemaitiene, Nida; Zaborskis, Apolinaras

2006-11-23

Family is considered to be the first and the most important child development and socialization bond. Nevertheless, parental behaviour model importance for the children, as well as family time for shared activity amount influence upon the child's health-related behaviour habit development has not been yet thoroughly examined. The aim of this paper is to indicate the advanced health-hazardous behaviour modelling possibilities in the families, as well as time spent for joint family activities, and to examine the importance of time spent for joint family activities for the smoking and alcohol use habit initiation among children. This research was carried out in Kaunas, Lithuania, during the school year 2004-2005. The research population consisted of 369 fifth-grade schoolchildren (211 (57.2%) boys and 158 (42.8%) girls) and 565 parents: 323 (57.2%) mothers and 242 (48.2%) fathers. The response rate was 80.7% for children; 96.1% and 90.6% for mothers and fathers correspondingly. Eating a meal together was the most frequent joint family activity, whereas visiting friends or relatives together, going for a walk, or playing sports were the most infrequent joint family activities. More than two thirds (81.5%) of parents (248 (77.0%) mothers and 207 (85.9%) fathers (p < 0.05)) reported frequenting alcohol furnished parties at least once a month. About half of the surveyed fathers (50.6%) together with one fifth of the mothers (19.9%) (p < 0.001) were smokers. More frequently than girls, boys reported having tried smoking (6.6% and 23.0% respectively; p < 0.001) as well as alcohol (31.16% and 40.1% respectively; p < 0.05). Child alcohol use was associated both with paternal alcohol use, and with the time, spent in joint family activities. For instance, boys were more prone to try alcohol, if their fathers frequented alcohol furnished parties, whereas girls were more prone to try alcohol, if family members spent less time together. Joint family activity time deficit together with frequent parental examples of smoking and alcohol use underlie the development of alcohol and smoking addictions in children to some extent. The above-mentioned issues are suggested to be widely addressed in the comprehensive family health education programs.

The influence of self-reported leisure time physical activity and the body mass index on recovery from persistent back pain among men and women: a population-based cohort study.

PubMed

Bohman, Tony; Alfredsson, Lars; Hallqvist, Johan; Vingård, Eva; Skillgate, Eva

2013-04-25

There is limited knowledge about leisure time physical activity and the body mass index (BMI) as prognostic factors for recovery from persistent back pain. The aim of this study was to assess the influence of leisure time physical activity and BMI on recovery from persistent back pain among men and women in a general population. The study population (n=1836) in this longitudinal cohort study consisted of participants reporting persistent back pain in the baseline questionnaire in 2002-2003. Data on leisure time physical activity, BMI and potential confounders were also collected at baseline. Information on recovery from persistent back pain (no back pain periods ≥ 7 days during the last 5 years) was obtained from the follow-up questionnaire in 2007. Log-binomial models were applied to calculate Risk Ratios with 95 percent Confidence Intervals (CI) comparing physically active and normal weight groups versus sedentary and overweight groups. Compared to a sedentary leisure time, all measured levels of leisure time physical activity were associated with a greater chance of recovery from persistent back pain among women. The adjusted Risk Ratios was 1.46 (95% CI: 1.06, 2.01) for low leisure time physical activity, 1.51 (95% CI: 1.02, 2.23) for moderate leisure time physical activity, and 1.67 (95% CI: 1.08, 2.58) for high leisure time physical activity. There were no indications that leisure time physical activity influenced recovery among men, or that BMI was associated with recovery from persistent back pain either among men or among women. Regular leisure time physical activity seems to improve recovery from persistent back pain among women.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.

PubMed

Li, Chen; Nagasaki, Masao; Saito, Ayumu; Miyano, Satoru

2010-04-01

With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.

Social contagions on time-varying community networks

NASA Astrophysics Data System (ADS)

Liu, Mian-Xin; Wang, Wei; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng

2017-05-01

Time-varying community structures exist widely in real-world networks. However, previous studies on the dynamics of spreading seldom took this characteristic into account, especially those on social contagions. To study the effects of time-varying community structures on social contagions, we propose a non-Markovian social contagion model on time-varying community networks based on the activity-driven network model. A mean-field theory is developed to analyze the proposed model. Through theoretical analyses and numerical simulations, two hierarchical features of the behavior adoption processes are found. That is, when community strength is relatively large, the behavior can easily spread in one of the communities, while in the other community the spreading only occurs at higher behavioral information transmission rates. Meanwhile, in spatial-temporal evolution processes, hierarchical orders are observed for the behavior adoption. Moreover, under different information transmission rates, three distinctive patterns are demonstrated in the change of the whole network's final adoption proportion along with the growing community strength. Within a suitable range of transmission rate, an optimal community strength can be found that can maximize the final adoption proportion. Finally, compared with the average activity potential, the promoting or inhibiting of social contagions is much more influenced by the number of edges generated by active nodes.

Performance evaluation of linear time-series ionospheric Total Electron Content model over low latitude Indian GPS stations

NASA Astrophysics Data System (ADS)

Dabbakuti, J. R. K. Kumar; Venkata Ratnam, D.

2017-10-01

Precise modeling of the ionospheric Total Electron Content (TEC) is a critical aspect of Positioning, Navigation, and Timing (PNT) services intended for the Global Navigation Satellite Systems (GNSS) applications as well as Earth Observation System (EOS), satellite communication, and space weather forecasting applications. In this paper, linear time series modeling has been carried out on ionospheric TEC at two different locations at Koneru Lakshmaiah University (KLU), Guntur (geographic 16.44° N, 80.62° E; geomagnetic 7.55° N) and Bangalore (geographic 12.97° N, 77.59° E; geomagnetic 4.53° N) at the northern low-latitude region, for the year 2013 in the 24th solar cycle. The impact of the solar and geomagnetic activity on periodic oscillations of TEC has been investigated. Results confirm that the correlation coefficient of the estimated TEC from the linear model TEC and the observed GPS-TEC is around 93%. Solar activity is the key component that influences ionospheric daily averaged TEC while periodic component reveals the seasonal dependency of TEC. Furthermore, it is observed that the influence of geomagnetic activity component on TEC is different at both the latitudes. The accuracy of the model has been assessed by comparing the International Reference Ionosphere (IRI) 2012 model TEC and TEC measurements. Moreover, the absence of winter anomaly is remarkable, as determined by the Root Mean Square Error (RMSE) between the linear model TEC and GPS-TEC. On the contrary, the IRI2012 model TEC evidently failed to predict the absence of winter anomaly in the Equatorial Ionization Anomaly (EIA) crest region. The outcome of this work will be useful for improving the ionospheric now-casting models under various geophysical conditions.

Minimal agent based model for financial markets I. Origin and self-organization of stylized facts

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The model can be easily generalized to consider more realistic variants.

Modeling methylene chloride exposure-reduction options for home paint-stripper users.

PubMed

Riley, D M; Small, M J; Fischhoff, B

2000-01-01

Home improvement is a popular activity, but one that can also involve exposure to hazardous substances. Paint stripping is of particular concern because of the high potential exposures to methylene chloride, a solvent that is a potential human carcinogen and neurotoxicant. This article presents a general methodology for evaluating the effectiveness of behavioral interventions for reducing these risks. It doubles as a model that assesses exposure patterns, incorporating user time-activity patterns and risk-mitigation strategies. The model draws upon recent innovations in indoor air-quality modeling to estimate exposure through inhalation and dermal pathways to paint-stripper users. It is designed to use data gathered from home paint-stripper users about room characteristics, amount of stripper used, time-activity patterns and exposure-reduction strategies (e.g., increased ventilation and modification in the timing of stripper application, scraping, and breaks). Results indicate that the effectiveness of behavioral interventions depends strongly on characteristics of the room (e.g., size, number and size of doors and windows, base air-exchange rates). The greatest simple reduction in exposure is achieved by using an exhaust fan in addition to opening windows and doors. These results can help identify the most important information for product labels and other risk-communication materials.

Adsorption of methyl orange using activated carbon prepared from lignin by ZnCl2 treatment

NASA Astrophysics Data System (ADS)

Mahmoudi, K.; Hamdi, N.; Kriaa, A.; Srasra, E.

2012-08-01

Lignocellulosic materials are good and cheap precursors for the production of activated carbon. In this study, activated carbons were prepared from the lignin at different temperatures (200 to 500°C) by ZnCl2. The effects influencing the surface area of the resulting activated carbon are activation temperature, activation time and impregnation ratio. The optimum condition, are found an impregnation ratio of 2, an activation temperature of 450°C, and an activation time of 2 h. The results showed that the surface area and micropores volume of activated carbon at the experimental conditions are achieved to 587 and 0.23 cm3 g-1, respectively. The adsorption behavior of methyl orange dye from aqueous solution onto activated lignin was investigated as a function of equilibrium time, pH and concentration. The Langmuir and Freundlich adsorption models were applied to describe the equilibrium isotherms. A maximum adsorption capacity of 300 mg g-1 of methyl orange by activated carbon was achieved.

Phrenic and hypoglossal nerve activity during respiratory response to hypoxia in 6-OHDA unilateral model of Parkinson's disease.

PubMed

Andrzejewski, Kryspin; Budzińska, Krystyna; Kaczyńska, Katarzyna

2017-07-01

Parkinson's disease (PD) patients apart from motor dysfunctions exhibit respiratory disturbances. Their mechanism is still unknown and requires investigation. Our research was designed to examine the activity of phrenic (PHR) and hypoglossal (HG) nerves activity during a hypoxic respiratory response in the 6-hydroxydopamine (6-OHDA) model of PD. Male adult Wistar rats were injected unilaterally with 6-OHDA (20μg) or the vehicle into the right medial forebrain bundle (MFB). Two weeks after the surgery the activity of the phrenic and hypoglossal nerve was registered in anesthetized, vagotomized, paralyzed, and mechanically ventilated rats under normoxic and hypoxic conditions. Lesion effectiveness was confirmed by the cylinder test, performed before the MFB injection and 14days after, before the respiratory experiment. 6-OHDA lesioned animals showed a significant increase in normoxic inspiratory time. Expiratory time and total time of the respiratory cycle were prolonged in PD rats after hypoxia. The amplitude of the PHR activity and its minute activity were increased in comparison to the sham group at recovery time and during 30s of hypoxia. The amplitude of the HG activity was increased in response to hypoxia in 6-OHDA lesioned animals. The degeneration of dopaminergic neurons decreased the pre-inspiratory/inspiratory ratio of the hypoglossal burst amplitude during and after hypoxia. Unilateral MFB lesion changed the activity of the phrenic and hypoglossal nerves. The altered pre-inspiratory hypoglossal nerve activity indicates modifications to the central mechanisms controlling the activity of the HG nerve and may explain respiratory disorders seen in PD, i.e. apnea. Copyright © 2017 Elsevier Inc. All rights reserved.

A New Model for Real-Time Regional Vertical Total Electron Content and Differential Code Bias Estimation Using IGS Real-Time Service (IGS-RTS) Products

NASA Astrophysics Data System (ADS)

Abdelazeem, Mohamed; Çelik, Rahmi N.; El-Rabbany, Ahmed

2016-04-01

The international global navigation satellite system (GNSS) real-time service (IGS-RTS) products have been used extensively for real-time precise point positioning and ionosphere modeling applications. In this study, we develop a regional model for real-time vertical total electron content (RT-VTEC) and differential code bias (RT-DCB) estimation over Europe using the IGS-RTS satellite orbit and clock products. The developed model has a spatial and temporal resolution of 1°×1° and 15 minutes, respectively. GPS observations from a regional network consisting of 60 IGS and EUREF reference stations are processed in the zero-difference mode using the Bernese-5.2 software package in order to extract the geometry-free linear combination of the smoothed code observations. The spherical harmonic expansion function is used to model the VTEC, the receiver and the satellite DCBs. To validate the proposed model, the RT-VTEC values are computed and compared with the final IGS-global ionospheric map (IGS-GIM) counterparts in three successive days under high solar activity including one of an extreme geomagnetic activity. The real-time satellite DCBs are also estimated and compared with the IGS-GIM counterparts. Moreover, the real-time receiver DCB for six IGS stations are obtained and compared with the IGS-GIM counterparts. The examined stations are located in different latitudes with different receiver types. The findings reveal that the estimated RT-VTEC values show agreement with the IGS-GIM counterparts with root mean-square-errors (RMSEs) values less than 2 TEC units. In addition, RMSEs of both the satellites and receivers DCBs are less than 0.85 ns and 0.65 ns, respectively in comparison with the IGS-GIM.

Comparison of the oxime-induced reactivation of rhesus monkey, swine and guinea pig erythrocyte acetylcholinesterase following inhibition by sarin or paraoxon, using a perfusion model for the real-time determination of membrane-bound acetylcholinesterase activity.

PubMed

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.

A New Global Empirical Model of the Electron Temperature with the Inclusion of the Solar Activity Variations for IRI

NASA Technical Reports Server (NTRS)

Truhlik, V.; Triskova, L.

2012-01-01

A data-base of electron temperature (T(sub e)) comprising of most of the available LEO satellite measurements in the altitude range from 350 to 2000 km has been used for the development of a new global empirical model of T(sub e) for the International Reference Ionosphere (IRI). For the first time this will include variations with solar activity. Variations at five fixed altitude ranges centered at 350, 550, 850, 1400, and 2000 km and three seasons (summer, winter, and equinox) were represented by a system of associated Legendre polynomials (up to the 8th order) in terms of magnetic local time and the earlier introduced in vdip latitude. The solar activity variations of T(sub e) are represented by a correction term of the T(sub e) global pattern and it has been derived from the empirical latitudinal profiles of T(sub e) for day and night (Truhlik et al., 2009a). Comparisons of the new T(sub e) model with data and with the IRI 2007 Te model show that the new model agrees well with the data generally within standard deviation limits and that the model performs better than the current IRI T(sub e) model.

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.

Large-scale and Long-duration Simulation of a Multi-stage Eruptive Solar Event

NASA Astrophysics Data System (ADS)

Jiang, chaowei; Hu, Qiang; Wu, S. T.

2015-04-01

We employ a data-driven 3D MHD active region evolution model by using the Conservation Element and Solution Element (CESE) numerical method. This newly developed model retains the full MHD effects, allowing time-dependent boundary conditions and time evolution studies. The time-dependent simulation is driven by measured vector magnetograms and the method of MHD characteristics on the bottom boundary. We have applied the model to investigate the coronal magnetic field evolution of AR11283 which was characterized by a pre-existing sigmoid structure in the core region and multiple eruptions, both in relatively small and large scales. We have succeeded in producing the core magnetic field structure and the subsequent eruptions of flux-rope structures (see https://dl.dropboxusercontent.com/u/96898685/large.mp4 for an animation) as the measured vector magnetograms on the bottom boundary evolve in time with constant flux emergence. The whole process, lasting for about an hour in real time, compares well with the corresponding SDO/AIA and coronagraph imaging observations. From these results, we show the capability of the model, largely data-driven, that is able to simulate complex, topological, and highly dynamic active region evolutions. (We acknowledge partial support of NSF grants AGS 1153323 and AGS 1062050, and data support from SDO/HMI and AIA teams).

Active buildings: modelling physical activity and movement in office buildings. An observational study protocol.

PubMed

Smith, Lee; Ucci, Marcella; Marmot, Alexi; Spinney, Richard; Laskowski, Marek; Sawyer, Alexia; Konstantatou, Marina; Hamer, Mark; Ambler, Gareth; Wardle, Jane; Fisher, Abigail

2013-11-12

Health benefits of regular participation in physical activity are well documented but population levels are low. Office layout, and in particular the number and location of office building destinations (eg, print and meeting rooms), may influence both walking time and characteristics of sitting time. No research to date has focused on the role that the layout of the indoor office environment plays in facilitating or inhibiting step counts and characteristics of sitting time. The primary aim of this study was to investigate associations between office layout and physical activity, as well as sitting time using objective measures. Active buildings is a unique collaboration between public health, built environment and computer science researchers. The study involves objective monitoring complemented by a larger questionnaire arm. UK office buildings will be selected based on a variety of features, including office floor area and number of occupants. Questionnaires will include items on standard demographics, well-being, physical activity behaviour and putative socioecological correlates of workplace physical activity. Based on survey responses, approximately 30 participants will be recruited from each building into the objective monitoring arm. Participants will wear accelerometers (to monitor physical activity and sitting inside and outside the office) and a novel tracking device will be placed in the office (to record participant location) for five consecutive days. Data will be analysed using regression analyses, as well as novel agent-based modelling techniques. The results of this study will be disseminated through peer-reviewed publications and scientific presentations. Ethical approval was obtained through the University College London Research Ethics Committee (Reference number 4400/001).

KOI-256's Magnetic Activity Under the Influence of the White Dwarf

NASA Astrophysics Data System (ADS)

Yoldaş, Ezgi; Dal, Hasan Ali

2017-11-01

We present the findings about chromospheric activity nature of KOI-256 obtained from the Kepler Mission data. First, it was found that there are some sinusoidal variations out-of-eclipses due to cool spot activity. The sinusoidal variations modelled by the spotmodel program indicate that the active component has two different active regions. Their longitudinal variation revealed that one of them has a migration period of 3.95 yrs, while the other has a migration period of 8.37 yrs. Second, 225 flares were detected from the short cadence data in total. The parameters, such as increase (T r) and decay (T d) times, total flare time (T t), equivalent durations (P), were calculated for each flare. The distribution of equivalent durations versus total flare times in logarithmic scale is modelled to find flare activity level. The Plateau value known as the saturation level of the active component was calculated to be 2.3121 ± 0.0964 s, and the Half-life value, which is required flare total time to reach the saturation, was computed to be 2233.6 s. In addition, the frequency of N 1, which is the number of flares per an hour in the system, was found to be 0.05087 h-1, while the flare frequency N 2 that the flare-equivalent duration emitting per an hour was found to be 0.00051. Contrary to the spot activity, it has been found that the flares are in tends to appear at specific phases due to the white dwarf component.

Chromospheric activity in open clusters

NASA Technical Reports Server (NTRS)

Pilger, E. J.

1987-01-01

Spectra of Ca II H and K are being taken for stars of similar mass in the Hyades, the Pleiades, and NGC 752. These spectra will be used to create indices of chromospheric activity on these stars. The dispersion in these indices will then be compared to model dispersions which take into account stellar inclination, position of active regions, and filling factor. Only a few observations have been made to date. These show that a high signal to noise is achievable over reasonable exposure times. Modeling has only just begun.

Application of the Socio-Ecological Model to predict physical activity behaviour among Nigerian University students.

PubMed

Essiet, Inimfon Aniema; Baharom, Anisah; Shahar, Hayati Kadir; Uzochukwu, Benjamin

2017-01-01

Physical activity among university students is a catalyst for habitual physical activity in adulthood. Physical activity has many health benefits besides the improvement in academic performance. The present study assessed the predictors of physical activity among Nigerian university students using the Social Ecological Model (SEM). This cross-sectional study recruited first-year undergraduate students in the University of Uyo, Nigeria by multistage sampling. The International Physical Activity Questionnaire (IPAQ) short-version was used to assess physical activity in the study. Factors were categorised according to the Socio-Ecological Model which consisted of individual, social environment, physical environment and policy level. Data was analysed using the IBM SPSS statistical software, version 22. Simple and multiple logistic regression were used to determine the predictors of sufficient physical activity. A total of 342 respondents completed the study questionnaire. Majority of the respondents (93.6%) reported sufficient physical activity at 7-day recall. Multivariate analysis revealed that respondents belonging to the Ibibio ethnic group were about four times more likely to be sufficiently active compared to those who belonged to the other ethnic groups (AOR = 3.725, 95% CI = 1.383 to 10.032). Also, participants who had a normal weight were about four times more likely to be physically active compared to those who were underweight (AOR = 4.268, 95% CI = 1.323 to 13.772). This study concluded that there was sufficient physical activity levels among respondents. It is suggested that emphasis be given to implementing interventions aimed at sustaining sufficient levels of physical activity among students.

Estimating municipal solid waste generation by different activities and various resident groups: a case study of Beijing.

PubMed

Li, Zhen-shan; Fu, Hui-zhen; Qu, Xiao-yan

2011-09-15

Reliable and accurate determinations of the quantities and composition of wastes is required for the planning of municipal solid waste (MSW) management systems. A model, based on the interrelationships of expenditure on consumer goods, time distribution, daily activities, residents groups, and waste generation, was developed and employed to estimate MSW generation by different activities and resident groups in Beijing. The principle is that MSW is produced by consumption of consumer goods by residents in their daily activities: 'Maintenance' (meeting the basic needs of food, housing and personal care), 'Subsistence' (providing the financial requirements) and 'Leisure' (social and recreational pursuits) activities. Three series of important parameters - waste generation per unit of consumer expenditure, consumer expenditure distribution to activities in unit time, and time assignment to activities by different resident groups - were determined using a statistical analysis, a sampling survey and the Analytic Hierarchy Process, respectively. Data for analysis were obtained from the Beijing Statistical Yearbook (2004-2008) and questionnaire survey. The results reveal that 'Maintenance' activity produced the most MSW, distantly followed by 'Leisure' and 'Subsistence' activities. In 2008, in descending order of MSW generation the different resident groups were floating population, non-civil servants, retired people, civil servants, college students (including both undergraduates and graduates), primary and secondary students, and preschoolers. The new estimation model, which was successful in fitting waste generation by different activities and resident groups over the investigated years, was amenable to MSW prediction. Copyright © 2011 Elsevier B.V. All rights reserved.

The TimeGeo modeling framework for urban mobility without travel surveys

PubMed Central

Jiang, Shan; Yang, Yingxiang; Gupta, Siddharth; Veneziano, Daniele; Athavale, Shounak; González, Marta C.

2016-01-01

Well-established fine-scale urban mobility models today depend on detailed but cumbersome and expensive travel surveys for their calibration. Not much is known, however, about the set of mechanisms needed to generate complete mobility profiles if only using passive datasets with mostly sparse traces of individuals. In this study, we present a mechanistic modeling framework (TimeGeo) that effectively generates urban mobility patterns with resolution of 10 min and hundreds of meters. It ties together the inference of home and work activity locations from data, with the modeling of flexible activities (e.g., other) in space and time. The temporal choices are captured by only three features: the weekly home-based tour number, the dwell rate, and the burst rate. These combined generate for each individual: (i) stay duration of activities, (ii) number of visited locations per day, and (iii) daily mobility networks. These parameters capture how an individual deviates from the circadian rhythm of the population, and generate the wide spectrum of empirically observed mobility behaviors. The spatial choices of visited locations are modeled by a rank-based exploration and preferential return (r-EPR) mechanism that incorporates space in the EPR model. Finally, we show that a hierarchical multiplicative cascade method can measure the interaction between land use and generation of trips. In this way, urban structure is directly related to the observed distance of travels. This framework allows us to fully embrace the massive amount of individual data generated by information and communication technologies (ICTs) worldwide to comprehensively model urban mobility without travel surveys. PMID:27573826

The TimeGeo modeling framework for urban motility without travel surveys.

PubMed

Jiang, Shan; Yang, Yingxiang; Gupta, Siddharth; Veneziano, Daniele; Athavale, Shounak; González, Marta C

2016-09-13

Well-established fine-scale urban mobility models today depend on detailed but cumbersome and expensive travel surveys for their calibration. Not much is known, however, about the set of mechanisms needed to generate complete mobility profiles if only using passive datasets with mostly sparse traces of individuals. In this study, we present a mechanistic modeling framework (TimeGeo) that effectively generates urban mobility patterns with resolution of 10 min and hundreds of meters. It ties together the inference of home and work activity locations from data, with the modeling of flexible activities (e.g., other) in space and time. The temporal choices are captured by only three features: the weekly home-based tour number, the dwell rate, and the burst rate. These combined generate for each individual: (i) stay duration of activities, (ii) number of visited locations per day, and (iii) daily mobility networks. These parameters capture how an individual deviates from the circadian rhythm of the population, and generate the wide spectrum of empirically observed mobility behaviors. The spatial choices of visited locations are modeled by a rank-based exploration and preferential return (r-EPR) mechanism that incorporates space in the EPR model. Finally, we show that a hierarchical multiplicative cascade method can measure the interaction between land use and generation of trips. In this way, urban structure is directly related to the observed distance of travels. This framework allows us to fully embrace the massive amount of individual data generated by information and communication technologies (ICTs) worldwide to comprehensively model urban mobility without travel surveys.

Examining the Relations of Time Management and Procrastination within a Model of Self-Regulated Learning

ERIC Educational Resources Information Center

Wolters, Christopher A.; Won, Sungjun; Hussain, Maryam

2017-01-01

The primary goal of this study was to investigate whether college students' academic time management could be used to understand their engagement in traditional and active forms of procrastination within a model of self-regulated learning. College students (N = 446) completed a self-report survey that assessed motivational and strategic aspects of…

Stochastic agent-based modeling of tuberculosis in Canadian Indigenous communities.

PubMed

Tuite, Ashleigh R; Gallant, Victor; Randell, Elaine; Bourgeois, Annie-Claude; Greer, Amy L

2017-01-13

In Canada, active tuberculosis (TB) disease rates remain disproportionately higher among the Indigenous population, especially among the Inuit in the north. We used mathematical modeling to evaluate how interventions might enhance existing TB control efforts in a region of Nunavut. We developed a stochastic, agent-based model of TB transmission that captured the unique household and community structure. Evaluated interventions included: (i) rapid treatment of active cases; (ii) rapid contact tracing; (iii) expanded screening programs for latent TB infection (LTBI); and (iv) reduced household density. The outcomes of interest were incident TB infections and total diagnosed active TB disease over a 10- year time period. Model-projected incidence in the absence of additional interventions was highly variable (range: 33-369 cases) over 10 years. Compared to the 'no additional intervention' scenario, reducing the time between onset of active TB disease and initiation of treatment reduced both the number of new TB infections (47% reduction, relative risk of TB = 0.53) and diagnoses of active TB disease (19% reduction, relative risk of TB = 0.81). Expanding general population screening was also projected to reduce the burden of TB, although these findings were sensitive to assumptions around the relative amount of transmission occurring outside of households. Other potential interventions examined in the model (school-based screening, rapid contact tracing, and reduced household density) were found to have limited effectiveness. In a region of northern Canada experiencing a significant TB burden, more rapid treatment initiation in active TB cases was the most impactful intervention evaluated. Mathematical modeling can provide guidance for allocation of limited resources in a way that minimizes disease transmission and protects population health.

Mitigating active shooter impact: Analysis for policy options based on agent/computer-based modeling.

PubMed

Anklam, Charles; Kirby, Adam; Sharevski, Filipo; Dietz, J Eric

2015-01-01

Active shooting violence at confined settings, such as educational institutions, poses serious security concerns to public safety. In studying the effects of active shooter scenarios, the common denominator associated with all events, regardless of reason/intent for shooter motives, or type of weapons used, was the location chosen and time expended between the beginning of the event and its culmination. This in turn directly correlates to number of casualties incurred in any given event. The longer the event protracts, the more casualties are incurred until law enforcement or another barrier can react and culminate the situation. Using AnyLogic technology, devise modeling scenarios to test multiple hypotheses against free-agent modeling simulation to determine the best method to reduce casualties associated with active shooter scenarios. Test four possible scenarios of responding to active shooter in a public school setting using agent-based computer modeling techniques-scenario 1: basic scenario where no access control or any type of security is used within the school; scenario 2, scenario assumes that concealed carry individual(s) (5-10 percent of the work force) are present in the school; scenario 3, scenario assumes that the school has assigned resource officer; scenario 4, scenario assumes that the school has assigned resource officer and concealed carry individual(s) (5-10 percent) present in the school. Statistical data from modeling scenarios indicating which tested hypothesis resulted in fewer casualties and quicker culmination of event. The use of AnyLogic proved the initial hypothesis that a decrease on response time to an active shooter scenario directly reduced victim casualties. Modeling tests show statistically significant fewer casualties in scenarios where on scene armed responders such as resource officers and concealed carry personnel were present.

The benefits of bad economies: Business cycles and time-based work-life conflict.

PubMed

Barnes, Christopher M; Lefter, Alexandru M; Bhave, Devasheesh P; Wagner, David T

2016-04-01

Recent management research has indicated the importance of family, sleep, and recreation as nonwork activities of employees. Drawing from entrainment theory, we develop an expanded model of work-life conflict to contend that macrolevel business cycles influence the amount of time employees spend on both work and nonwork activities. Focusing solely on working adults, we test this model in a large nationally representative dataset from the Bureau of Labor Statistics that spans an 8-year period, which includes the "Great Recession" from 2007 through 2009. We find that during economic booms, employees work more and therefore spend less time with family, sleeping, and recreating. In contrast, in recessionary economies, employees spend less time working and therefore more time with family, sleeping, and recreating. Thus, we extend the theory on time-based work-to-family conflict, showing that there are potential personal and relational benefits for employees in recessionary economies. (c) 2016 APA, all rights reserved).

Idea Bank.

ERIC Educational Resources Information Center

Science Teacher, 1989

1989-01-01

Describes classroom activities and models for migration, mutation, and isolation; a diffusion model; Bernoulli's principle; sound in a vacuum; time regression mystery of DNA; seating chart lesson plan; algae mystery laboratory; water as mass; science fair; flipped book; making a cloud; wet mount slide; timer adaptation; thread slide model; and…

WILDLAND FIRE EMISSION MODELING FOR CMAQ: AN UPDATE

EPA Science Inventory

This paper summarizes recent efforts to improve the methods used for modeling wild land fire emissions both for retrospective modeling and real-time forecasting. These improvements focus on the temporal and spatial resolution of the activity data as well as the methods to estimat...

Solar activity simulation and forecast with a flux-transport dynamo

NASA Astrophysics Data System (ADS)

Macario-Rojas, Alejandro; Smith, Katharine L.; Roberts, Peter C. E.

2018-06-01

We present the assessment of a diffusion-dominated mean field axisymmetric dynamo model in reproducing historical solar activity and forecast for solar cycle 25. Previous studies point to the Sun's polar magnetic field as an important proxy for solar activity prediction. Extended research using this proxy has been impeded by reduced observational data record only available from 1976. However, there is a recognised need for a solar dynamo model with ample verification over various activity scenarios to improve theoretical standards. The present study aims to explore the use of helioseismology data and reconstructed solar polar magnetic field, to foster the development of robust solar activity forecasts. The research is based on observationally inferred differential rotation morphology, as well as observed and reconstructed polar field using artificial neural network methods via the hemispheric sunspot areas record. Results show consistent reproduction of historical solar activity trends with enhanced results by introducing a precursor rise time coefficient. A weak solar cycle 25, with slow rise time and maximum activity -14.4% (±19.5%) with respect to the current cycle 24 is predicted.

Activity-based differentiation of pathologists' workload in surgical pathology.

PubMed

Meijer, G A; Oudejans, J J; Koevoets, J J M; Meijer, C J L M

2009-06-01

Adequate budget control in pathology practice requires accurate allocation of resources. Any changes in types and numbers of specimens handled or protocols used will directly affect the pathologists' workload and consequently the allocation of resources. The aim of the present study was to develop a model for measuring the pathologists' workload that can take into account the changes mentioned above. The diagnostic process was analyzed and broken up into separate activities. The time needed to perform these activities was measured. Based on linear regression analysis, for each activity, the time needed was calculated as a function of the number of slides or blocks involved. The total pathologists' time required for a range of specimens was calculated based on standard protocols and validated by comparing to actually measured workload. Cutting up, microscopic procedures and dictating turned out to be highly correlated to number of blocks and/or slides per specimen. Calculated workload per type of specimen was significantly correlated to the actually measured workload. Modeling pathologists' workload based on formulas that calculate workload per type of specimen as a function of the number of blocks and slides provides a basis for a comprehensive, yet flexible, activity-based costing system for pathology.

Static and Impulsive Models of Solar Active Regions

NASA Technical Reports Server (NTRS)

Patsourakos, S.; Klimchuk, James A.

2008-01-01

The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.

Removal of hexavalent chromium by using red mud activated with cetyltrimethylammonium bromide.

PubMed

Li, Deliang; Ding, Ying; Li, Lingling; Chang, Zhixian; Rao, Zhengyong; Lu, Ling

2015-01-01

The removal of hexavalent chromium [Cr(VI)] from aqueous solution by using red mud activated with cetyltrimethylammonium bromide (CTAB) was studied. The optimum operation parameters, such as CTAB concentration, pH values, contact time, and initial Cr(VI) concentration, were investigated. The best concentration of CTAB for modifying red mud was found to be 0.50% (mCTAB/VHCl,0.6 mol/L). The lower pH (<2) was found to be much more favourable for the removal of Cr(VI). Red mud activated with CTAB can greatly improve the removal ratio of Cr(VI) as high as four times than that of original red mud. Adsorption equilibrium was reached within 30 min under the initial Cr(VI) concentration of 100 mg L(-1). The isotherm data were analysed using Langmuir and Freundlich models. The adsorption of Cr(VI) on activated red mud fitted well to the Langmuir isotherm model, and the maximum adsorption capacity was estimated as 22.20 mg g(-1) (Cr/red mud). The adsorption process could be well described using the pseudo-second-order model. The result shows that activated red mud is a promising agent for low-cost water treatment.

Testing an integrated behavioural and biomedical model of disability in N-of-1 studies with chronic pain.

PubMed

Quinn, Francis; Johnston, Marie; Johnston, Derek W

2013-01-01

Previous research has supported an integrated biomedical and behavioural model explaining activity limitations. However, further tests of this model are required at the within-person level, because while it proposes that the constructs are related within individuals, it has primarily been tested between individuals in large group studies. We aimed to test the integrated model at the within-person level. Six correlational N-of-1 studies in participants with arthritis, chronic pain and walking limitations were carried out. Daily measures of theoretical constructs were collected using a hand-held computer (PDA), the activity was assessed by self-report and accelerometer and the data were analysed using time-series analysis. The biomedical model was not supported as pain impairment did not predict activity, so the integrated model was supported partially. Impairment predicted intention to move around, while perceived behavioural control (PBC) and intention predicted activity. PBC did not predict activity limitation in the expected direction. The integrated model of disability was partially supported within individuals, especially the behavioural elements. However, results suggest that different elements of the model may drive activity (limitations) for different individuals. The integrated model provides a useful framework for understanding disability and suggests interventions, and the utility of N-of-1 methodology for testing theory is illustrated.

Stopping Childhood Obesity before It Begins

ERIC Educational Resources Information Center

Mazzeo, Deborah; Arens, Sheila A.; Germeroth, Carrie; Hein, Heather

2012-01-01

Preschool is a crucial time for obesity prevention, as children are developing eating and physical activity habits. A lack of physical activity at preschool may contribute more to overweight children than parental influences such as modeling and supporting physical activity or providing fitness equipment in the home. Let Me Play is a comprehensive…

Activity Theory as a Framework for Designing the Model of College English Listening

ERIC Educational Resources Information Center

Zhang, Jianfeng

2014-01-01

Activity theory signifies that activities are at the centre of human behaviour and it has been used to study cognitive process in many fields. Nowadays, college English listening learning is time-consuming but less effective in China, so enhancing the performance of listening instruction is a very hot topic. Theoretically, activity theory is able…

Participation in regular leisure-time physical activity among individuals with type 2 diabetes not meeting Canadian guidelines: the influence of intention, perceived behavioral control, and moral norm.

PubMed

Boudreau, François; Godin, Gaston

2014-12-01

Most people with type 2 diabetes do not engage in regular leisure-time physical activity. The theory of planned behavior and moral norm construct can enhance our understanding of physical activity intention and behavior among this population. This study aims to identify the determinants of both intention and behavior to participate in regular leisure-time physical activity among individuals with type 2 diabetes who not meet Canada's physical activity guidelines. By using secondary data analysis of a randomized computer-tailored print-based intervention, participants (n = 200) from the province of Quebec (Canada) completed and returned a baseline questionnaire measuring their attitude, perceived behavioral control, and moral norm. One month later, they self-reported their level of leisure-time physical activity. A hierarchical regression equation showed that attitude (beta = 0.10, P < 0.05), perceived behavioral control (beta = 0.37, P < 0.001), and moral norm (beta = 0.45, P < 0.001) were significant determinants of intention, with the final model explaining 63% of the variance. In terms of behavioral prediction, intention (beta = 0.34, P < 0.001) and perceived behavioral control (beta = 0.16, P < 0.05) added 17% to the variance, after controlling the effects of the experimental condition (R (2) = 0.04, P < 0.05) and past participation in leisure-time physical activity (R (2) = 0.22, P < 0.001). The final model explained 43% of the behavioral variance. Finally, the bootstrapping procedure indicated that the influence of moral norm on behavior was mediated by intention and perceived behavioral control. The determinants investigated offered an excellent starting point for designing appropriate counseling messages to promote leisure-time physical activity among individuals with type 2 diabetes.

Hierarchy of treatment variables affecting outcome of 131I therapy in thyroid cancer patients with lung metastases.

PubMed

Kozak, Oksana V; Sukach, Georgiy G; Korchinskaya, Oksana I; Trembach, Alexander M; Turicina, Viktoria L; Voit, Natalia U

2005-06-01

To assess the correlations between the first 131I activity value, time interval between the courses of radioiodine treatment and the overall number of courses required for total destruction of lung metastases in patients with differentiated thyroid cancer with metastatic lesions in lungs. 27 patients with differentiated thyroid cancer with metastases in lungs have been treated with radioiodine after surgical intervention. Activities administered amounted from 1600 to 7980 MBq. The number of radioiodine courses before total ablation of all metastatic lesions amounted from 1 to 10. Time interval between the 1st and the 2nd courses amounted from 3.5 to 11.5 months (6 months in average). The regression analysis of the data has been made. The exponential model fits the actual number of courses as a function of the first-second activity value and time interval between the courses. The first activity has a decisive influence on the number of courses required for total metastases ablation. The greater was the first activity value, the lesser was the overall number of courses. Increasing time interval between 1st and 2nd courses to 10 months seems to result in reducing the number of courses. Nevertheless even in the case of high activities the probability to undergone less then 3 courses is low. According to the proposed model in thyroid cancer patients with metastases in lungs the first activity should be not lesser than 6000 MBq, time interval between treatments--approximately 10 months. The results of our study suggest that individual factors such as histology, the number and the size of metastases in lymph nodes could not contribute more to the final outcome than the treatment variables, namely the first-second activity and time interval, nor could they affect the hierarchy of the effects revealed for the treatment variables.

"Go home, sit less: The impact of home versus hospital rehabilitation environment on activity levels of stroke survivors".

PubMed

Simpson, Dawn B; Breslin, Monique; Cumming, Toby; de Zoete, Sam; Gall, Seana L; Schmidt, Matthew; English, Coralie; Callisaya, Michele L

2018-05-08

To examine whether change in rehabilitation environment (hospital or home) and other factors, influence time spent sitting, upright and walking after stroke. Observational study. Two inpatient rehabilitation units, and community residences following discharge. Thirty-four participants with stroke were recruited. An activity monitor was worn continuously for 7 days during the final week in hospital, and first week home. Other covariates included mood, fatigue, physical function, pain and cognition. Linear mixed models were performed to examine the associations between the environment (exposure) and physical activity levels (outcome) in hospital and at home. Interaction terms between the exposure and other covariates were added to the model to determine whether they modified activity with change in environment. The mean age of participants was 68 [SD 13] years and 53% were male. At home, participants spent 45 fewer minutes sitting (95% CI -84.8, -6.1; p=0.02), 45 more minutes upright (95% CI 6.1, 84.8; p=0.02), 12 more minutes walking (95% CI 5, 19; p=0.001) and completed 724 additional steps (95% CI 199, 1250; p=0.01) each day compared to in hospital. Depression at discharge predicted greater sitting time and less upright time (p=0.03 respectively) at home. Environmental change from hospital to home was associated with reduced sitting time and increased the time spent physically active, though depression modified this change. The rehabilitation environment may be a target to reduce sitting and promote physical activity. Copyright © 2018. Published by Elsevier Inc.

Removal of Hexavalent Chromium by Adsorption on Microwave Assisted Activated Carbon Prepared from Stems of Leucas Aspera

NASA Astrophysics Data System (ADS)

Shanmugalingam, A.; Murugesan, A.

2018-05-01

This study reports adsorption of Cr(VI) ions from aqueous solution using activated carbon that was prepared from stems of Leucas aspera. Eight hundred and fifty watts power of microwave radiation, 12 min of radiation time, 60% of ZnCl2 solution and 24 h of impregnation time are the optimal parameters to prepare efficient carbon effective activated carbon. It was designated as MWLAC (Microwave assisted Zinc chloride activated Leucas aspera carbon). Various adsorption characteristics such as dose of the adsorbent, agitation time, initial Cr(VI) ion concentration, pH of the solution and temperature on adsorption were studied for removal of Cr(VI) ions from aqueous solution by batch mode. Also the equilibrium adsorption was analyzed by the Langmuir, Freundlich, Tempkin and D-R isotherm models. The order of best describing isotherms was given based on R2 value. The pseudo-second-order kinetic model best fitted with the Cr(VI) adsorption data. Thermodynamic parameters were also determined and results suggest that the adsorption process is a spontaneous, endothermic and proceeded with increased randomness.

Multimodal transport and dispersion of organelles in narrow tubular cells

NASA Astrophysics Data System (ADS)

Mogre, Saurabh S.; Koslover, Elena F.

2018-04-01

Intracellular components explore the cytoplasm via active motor-driven transport in conjunction with passive diffusion. We model the motion of organelles in narrow tubular cells using analytical techniques and numerical simulations to study the efficiency of different transport modes in achieving various cellular objectives. Our model describes length and time scales over which each transport mode dominates organelle motion, along with various metrics to quantify exploration of intracellular space. For organelles that search for a specific target, we obtain the average capture time for given transport parameters and show that diffusion and active motion contribute to target capture in the biologically relevant regime. Because many organelles have been found to tether to microtubules when not engaged in active motion, we study the interplay between immobilization due to tethering and increased probability of active transport. We derive parameter-dependent conditions under which tethering enhances long-range transport and improves the target capture time. These results shed light on the optimization of intracellular transport machinery and provide experimentally testable predictions for the effects of transport regulation mechanisms such as tethering.

KIC 9451096: Magnetic Activity, Flares and Differential Rotation

NASA Astrophysics Data System (ADS)

Özdarcan, O.; Yoldaş, E.; Dal, H. A.

2018-04-01

We present a spectroscopic and photometric analysis of KIC 9451096. The combined spectroscopic and photometric modelling shows that the system is a detached eclipsing binary in a circular orbit and composed of F5V + K2V components. Subtracting the best-fitting light curve model from the whole long cadence data reveals additional low (mmag) amplitude light variations in time and occasional flares, suggesting a low, but still remarkable level of magnetic spot activity on the K2V component. Analyzing the rotational modulation of the light curve residuals enables us to estimate the differential rotation coefficient of the K2V component as k = 0.069 ± 0.008, which is 3 times weaker compared with the solar value of k = 0.19, assuming a solar type differential rotation. We find the stellar flare activity frequency for the K2V component as 0.000368411 h-1 indicating a low magnetic activity level.

The Flipped Classroom: An active teaching and learning strategy for making the sessions more interactive and challenging.

PubMed

Sultan, Amber Shamim

2018-04-01

Flipping the classroom is a pedagogical model that employs easy to use, readily accessible technology based resources such as video lectures, reading handouts, and practice problems outside the classroom, whereas interactive group-based, problem-solving activities conducted in the classroom. This strategy permits for an extended range of learning activities during the session. Using class time for active learning provides greater opportunity for mentoring and peer to peer collaboration. Instead of spending too much time on delivering lectures, class time can best be utilized by interacting with students, discussing their concerns related to the particular topic to be taught, providing real life examples relevant to the course content, challenging students to think in a broader aspect about complex process and encouraging different team based learning activities.

Engagement in Vocational Activities Promotes Behavioral Development for Adults with Autism Spectrum Disorders

PubMed Central

Taylor, Julie Lounds; Smith, Leann E.; Mailick, Marsha R.

2014-01-01

This study examined the bidirectional relations over time between behavioral functioning (autism symptoms, maladaptive behaviors, activities of daily living) and vocational/educational activities of adults with autism spectrum disorders (ASD). Participants were 153 adults with ASD (M age = 30.2 years) who were part of a larger longitudinal study. Data were collected at two time points separated by 5.5 years. Cross-lag models were used, which accounted for stability over time while testing both directions of cross-lagged effects. Results suggested that greater vocational independence and engagement was related to subsequent reductions in autism symptoms and maladaptive behaviors, and improvements in activities of daily living. Relations between earlier behavioral variables (symptoms, behaviors, and activities of daily living) and later vocational independence were not statistically significant. PMID:24287880

Convolutional virtual electric field for image segmentation using active contours.

PubMed

Wang, Yuanquan; Zhu, Ce; Zhang, Jiawan; Jian, Yuden

2014-01-01

Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

Optimization of production conditions for activated carbons from Tamarind wood by zinc chloride using response surface methodology.

PubMed

Sahu, J N; Acharya, Jyotikusum; Meikap, B C

2010-03-01

The low-cost activated carbon was prepared from Tamarind wood an agricultural waste material, by chemical activation with zinc chloride. Activated carbon adsorption is an effective means for reducing organic chemicals, chlorine, heavy metals and unpleasant tastes and odours in effluent or colored substances from gas or liquid streams. Central composite design (CCD) was applied to study the influence of activation temperature, chemical ratio of zinc chloride to Tamarind wood and activation time on the chemical activation process of Tamarind wood. Two quadratic models were developed for yield of activated carbon and adsorption of malachite green oxalate using Design-Expert software. The models were used to calculate the optimum operating conditions for production of activated carbon providing a compromise between yield and adsorption of the process. The yield (45.26 wt.%) and adsorption (99.9%) of the activated carbon produced at these operating conditions showed an excellent agreement with the amounts predicted by the models. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Enzymatic digestive activity and absorption efficiency in Tagelus dombeii upon Alexandrium catenella exposure

NASA Astrophysics Data System (ADS)

Fernández-Reiriz, M. J.; Navarro, J. M.; Cisternas, B. A.; Babarro, J. M. F.; Labarta, U.

2013-12-01

We analyzed absorption efficiency (AE) and digestive enzyme activity (amylase, cellulase complex, and laminarinase) of the infaunal bivalve Tagelus dombeii originating from two geographic sites, Corral-Valdivia and Melinka-Aysén, which have different long-term paralytic shellfish poisoning (PSP) exposure rates. We report the effects of past feeding history (origin) on T. dombeii exposed to a mixed diet containing the toxic dinoflagellate Alexandrium catenella and another dinoflagellate-free control diet over a 12-day period in the laboratory. Absorption efficiency values of T. dombeii individuals that experienced PSP exposure in their habitat (Melinka-Aysén) remained unchanged during exposure to toxic food in the laboratory. In contrast, T. dombeii from a non-PSP exposure field site (Corral-Valdivia) showed a significant reduction in AE with toxic exposure time. This study established that the amylase and cellulase complexes were the most important enzymes in the digestive glands of Tagelus from both sites. The temporal evolution of enzymatic activity under toxic diet was fitted to exponential (amylase and cellulase) and to a logarithmic (laminarinase) models. In all fits, we found significant effect of origin in the model parameters. At the beginning of the experiment, higher enzymatic activity was observed for clams from Corral-Valdivia. The amylase activity decreased with time exposure for individuals from Corral and increased for individuals from Melinka. Cellulase activity did not vary over time for clams from Corral, but increased for individuals from Melinka and laminarinase activity decreased over time for individuals from Corral and remained unchanged over time for Melinka. A feeding history of exposure to the dinoflagellate A. catenella was reflected in the digestive responses of both T. dombeii populations.

Revisiting the Time Trade-Off Hypothesis: Work, Organized Activities, and Academics During College.

PubMed

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).

Revisiting the Time Trade-off Hypothesis: Work, Organized Activities, and Academics during College

PubMed Central

Maggs, Jennifer L.

2014-01-01

How adolescents spend their time has long-term implications for their educational, health, and labor market outcomes, yet surprisingly little research has explored the time use of students across days and semesters. The current study used longitudinal daily diary data from a sample of college students attending a large public university in the Northeastern US (n = 726, Mage = 18.4) that was followed for 14 days within each of 7 semesters (for up to 98 diary days per student). The study had two primary aims. The first aim was to explore demographic correlates of employment time, organized activity time, and academic time. The second aim was to provide a rigorous test of the time trade-off hypothesis, which suggests that students will spend less time on academics when they spend more time on employment and extracurricular activities. The results demonstrated that time use varied by gender, parental education, and race/ethnicity. Furthermore, the results from multi-level models provided some support for the time trade-off hypothesis, although associations varied by the activity type and whether the day was a weekend. More time spent on employment was linked to less time spent on academics across days and semesters whereas organized activities were associated with less time on academics at the daily level only. The negative associations between employment and academics were most pronounced on weekdays. These results suggest that students may balance certain activities across days, whereas other activities may be in competition over longer time frames (i.e., semesters). PMID:25381597

Flashlight™ Cost Analysis Handbook: Modeling Resource Use in Teaching and Learning with Technology. Version 2.0

ERIC Educational Resources Information Center

Ehrmann, Stephen C.; Milam, John H., Jr.

2003-01-01

This volume describes for educators how to create simple models of the full costs of educational innovations, including the costs for time devoted to the activity, space needed for the activity, etc. Examples come from educational uses of technology in higher education in the United States and China. Real case studies illustrate the method in use:…

Flexible statistical modelling detects clinical functional magnetic resonance imaging activation in partially compliant subjects.

PubMed

Waites, Anthony B; Mannfolk, Peter; Shaw, Marnie E; Olsrud, Johan; Jackson, Graeme D

2007-02-01

Clinical functional magnetic resonance imaging (fMRI) occasionally fails to detect significant activation, often due to variability in task performance. The present study seeks to test whether a more flexible statistical analysis can better detect activation, by accounting for variance associated with variable compliance to the task over time. Experimental results and simulated data both confirm that even at 80% compliance to the task, such a flexible model outperforms standard statistical analysis when assessed using the extent of activation (experimental data), goodness of fit (experimental data), and area under the operator characteristic curve (simulated data). Furthermore, retrospective examination of 14 clinical fMRI examinations reveals that in patients where the standard statistical approach yields activation, there is a measurable gain in model performance in adopting the flexible statistical model, with little or no penalty in lost sensitivity. This indicates that a flexible model should be considered, particularly for clinical patients who may have difficulty complying fully with the study task.

2D Time-lapse Seismic Tomography Using An Active Time Constraint (ATC) Approach

EPA Science Inventory

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...

A regressive storm model for extreme space weather

NASA Astrophysics Data System (ADS)

Terkildsen, Michael; Steward, Graham; Neudegg, Dave; Marshall, Richard

2012-07-01

Extreme space weather events, while rare, pose significant risk to society in the form of impacts on critical infrastructure such as power grids, and the disruption of high end technological systems such as satellites and precision navigation and timing systems. There has been an increased focus on modelling the effects of extreme space weather, as well as improving the ability of space weather forecast centres to identify, with sufficient lead time, solar activity with the potential to produce extreme events. This paper describes the development of a data-based model for predicting the occurrence of extreme space weather events from solar observation. The motivation for this work was to develop a tool to assist space weather forecasters in early identification of solar activity conditions with the potential to produce extreme space weather, and with sufficient lead time to notify relevant customer groups. Data-based modelling techniques were used to construct the model, and an extensive archive of solar observation data used to train, optimise and test the model. The optimisation of the base model aimed to eliminate false negatives (missed events) at the expense of a tolerable increase in false positives, under the assumption of an iterative improvement in forecast accuracy during progression of the solar disturbance, as subsequent data becomes available.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

PubMed

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.