Daily life activity routine discovery in hemiparetic rehabilitation patients using topic models.

PubMed

Seiter, J; Derungs, A; Schuster-Amft, C; Amft, O; Tröster, G

2015-01-01

Monitoring natural behavior and activity routines of hemiparetic rehabilitation patients across the day can provide valuable progress information for therapists and patients and contribute to an optimized rehabilitation process. In particular, continuous patient monitoring could add type, frequency and duration of daily life activity routines and hence complement standard clinical scores that are assessed for particular tasks only. Machine learning methods have been applied to infer activity routines from sensor data. However, supervised methods require activity annotations to build recognition models and thus require extensive patient supervision. Discovery methods, including topic models could provide patient routine information and deal with variability in activity and movement performance across patients. Topic models have been used to discover characteristic activity routine patterns of healthy individuals using activity primitives recognized from supervised sensor data. Yet, the applicability of topic models for hemiparetic rehabilitation patients and techniques to derive activity primitives without supervision needs to be addressed. We investigate, 1) whether a topic model-based activity routine discovery framework can infer activity routines of rehabilitation patients from wearable motion sensor data. 2) We compare the performance of our topic model-based activity routine discovery using rule-based and clustering-based activity vocabulary. We analyze the activity routine discovery in a dataset recorded with 11 hemiparetic rehabilitation patients during up to ten full recording days per individual in an ambulatory daycare rehabilitation center using wearable motion sensors attached to both wrists and the non-affected thigh. We introduce and compare rule-based and clustering-based activity vocabulary to process statistical and frequency acceleration features to activity words. Activity words were used for activity routine pattern discovery using topic models based on Latent Dirichlet Allocation. Discovered activity routine patterns were then mapped to six categorized activity routines. Using the rule-based approach, activity routines could be discovered with an average accuracy of 76% across all patients. The rule-based approach outperformed clustering by 10% and showed less confusions for predicted activity routines. Topic models are suitable to discover daily life activity routines in hemiparetic rehabilitation patients without trained classifiers and activity annotations. Activity routines show characteristic patterns regarding activity primitives including body and extremity postures and movement. A patient-independent rule set can be derived. Including expert knowledge supports successful activity routine discovery over completely data-driven clustering.

Inhibitor-based validation of a homology model of the active-site of tripeptidyl peptidase II.

PubMed

De Winter, Hans; Breslin, Henry; Miskowski, Tamara; Kavash, Robert; Somers, Marijke

2005-04-01

A homology model of the active site region of tripeptidyl peptidase II (TPP II) was constructed based on the crystal structures of four subtilisin-like templates. The resulting model was subsequently validated by judging expectations of the model versus observed activities for a broad set of prepared TPP II inhibitors. The structure-activity relationships observed for the prepared TPP II inhibitors correlated nicely with the structural details of the TPP II active site model, supporting the validity of this model and its usefulness for structure-based drug design and pharmacophore searching experiments.

Testing Theory of Planned Behavior and Neo-Socioanalytic Theory models of trait activity, industriousness, exercise social cognitions, exercise intentions, and physical activity in a representative U.S. sample

PubMed Central

Vo, Phuong T.; Bogg, Tim

2015-01-01

Prior research identified assorted relations between trait and social cognition models of personality and engagement in physical activity. Using a representative U.S. sample (N = 957), the goal of the present study was to test two alternative structural models of the relationships among the extraversion-related facet of activity, the conscientiousness-related facet of industriousness, social cognitions from the Theory of Planned Behavior (perceived behavioral control, affective attitudes, subjective norms, intentions), Social Cognitive Theory (self-efficacy, outcome expectancies), and the Transtheoretical Model (behavioral processes of change), and engagement in physical activity. Path analyses with bootstrapping procedures were used to model direct and indirect effects of trait and social cognition constructs on physical activity through two distinct frameworks – the Theory of Planned Behavior and Neo-Socioanalytic Theory. While both models showed good internal fit, comparative model information criteria showed the Theory-of-Planned-Behavior-informed model provided a better fit. In the model, social cognitions fully mediated the relationships from the activity facet and industriousness to intentions for and engagement in physical activity, such that the relationships were primarily maintained by positive affective evaluations, positive expected outcomes, and confidence in overcoming barriers related to physical activity engagement. The resultant model – termed the Disposition-Belief-Motivation model– is proposed as a useful framework for organizing and integrating personality trait facets and social cognitions from various theoretical perspectives to investigate the expression of health-related behaviors, such as physical activity. Moreover, the results are discussed in terms of extending the application of the Disposition-Belief-Motivation model to longitudinal and intervention designs for physical activity engagement. PMID:26300811

Managing Analysis Models in the Design Process

NASA Technical Reports Server (NTRS)

Briggs, Clark

2006-01-01

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

Preservice Secondary Teachers' Conceptions from a Mathematical Modeling Activity and Connections to the Common Core State Standards

ERIC Educational Resources Information Center

Stohlmann, Micah; Maiorca, Cathrine; Olson, Travis A.

2015-01-01

Mathematical modeling is an essential integrated piece of the Common Core State Standards. However, researchers have shown that mathematical modeling activities can be difficult for teachers to implement. Teachers are more likely to implement mathematical modeling activities if they have their own successful experiences with such activities. This…

Pre-Service Teachers' Modelling Processes through Engagement with Model Eliciting Activities with a Technological Tool

ERIC Educational Resources Information Center

Daher, Wajeeh M.; Shahbari, Juhaina Awawdeh

2015-01-01

Engaging mathematics students with modelling activities helps them learn mathematics meaningfully. This engagement, in the case of model eliciting activities, helps the students elicit mathematical models by interpreting real-world situation in mathematical ways. This is especially true when the students utilize technology to build the models.…

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

USGS Publications Warehouse

Muller, Benjamin J.; Cade, Brian S.; Schwarzkoph, Lin

2018-01-01

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (Rhinella marina) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

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.

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

Distributed activation energy model parameters of some Turkish coals

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

Gunes, M.; Gunes, S.K.

2008-07-01

A multi-reaction model based on distributed activation energy has been applied to some Turkish coals. The kinetic parameters of distributed activation energy model were calculated via computer program developed for this purpose. It was observed that the values of mean of activation energy distribution vary between 218 and 248 kJ/mol, and the values of standard deviation of activation energy distribution vary between 32 and 70 kJ/mol. The correlations between kinetic parameters of the distributed activation energy model and certain properties of coal have been investigated.

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

Active lifestyles in older adults: an integrated predictive model of physical activity and exercise

PubMed Central

Galli, Federica; Chirico, Andrea; Mallia, Luca; Girelli, Laura; De Laurentiis, Michelino; Lucidi, Fabio; Giordano, Antonio; Botti, Gerardo

2018-01-01

Physical activity and exercise have been identified as behaviors to preserve physical and mental health in older adults. The aim of the present study was to test the Integrated Behavior Change model in exercise and physical activity behaviors. The study evaluated two different samples of older adults: the first engaged in exercise class, the second doing spontaneous physical activity. The key analyses relied on Variance-Based Structural Modeling, which were performed by means of WARP PLS 6.0 statistical software. The analyses estimated the Integrated Behavior Change model in predicting exercise and physical activity, in a longitudinal design across two months of assessment. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research. PMID:29875997

AST: Activity-Security-Trust driven modeling of time varying networks.

PubMed

Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

2016-02-18

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

Progress with modeling activity landscapes in drug discovery.

PubMed

Vogt, Martin

2018-04-19

Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.

Activity-Based Travel Demand Modeling for Metropolitan Areas in Texas: Model Components and Mathematical Formulations

DOT National Transportation Integrated Search

2001-09-01

The goal of this project is to comprehensively model the activity-travel patterns of workers as well as non-workers in a household. The activity-travel system will take as input various land use, socio-demographic, activity system, and transportation...

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model

PubMed Central

Graffigna, Guendalina; Bonanomi, Andrea

2017-01-01

Background Increasing bodies of scientific research today examines the factors and interventions affecting patients’ ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients’ ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. Objective To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. Material and methods This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 –short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients’ emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. Results According to the theoretical model we hypothesized, research results confirmed that patients’ activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients’ quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Conclusions Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence. PMID:28654686

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model.

PubMed

Graffigna, Guendalina; Barello, Serena; Bonanomi, Andrea

2017-01-01

Increasing bodies of scientific research today examines the factors and interventions affecting patients' ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients' ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 -short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients' emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. According to the theoretical model we hypothesized, research results confirmed that patients' activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients' quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence.

MODELING ENERGY EXPENDITURE AND OXYGEN CONSUMPTION IN HUMAN EXPOSURE MODELS: ACCOUNTING FOR FATIGUE AND EPOC

EPA Science Inventory

Human exposure and dose models often require a quantification of oxygen consumption for a simulated individual. Oxygen consumption is dependent on the modeled Individual's physical activity level as described in an activity diary. Activity level is quantified via standardized val...

Disposable Electronic Cigarettes and Electronic Hookahs: Evaluation of Performance

PubMed Central

Williams, Monique; Ghai, Sanjay

2015-01-01

Introduction: The purpose of this study was to characterize the performance of disposable button-activated and disposable airflow-activated electronic cigarettes (EC) and electronic hookahs (EH). Methods: The airflow rate required to produce aerosol, pressure drop, and the aerosol absorbance at 420nm were measured during smoke-outs of 9 disposable products. Three units of each product were tested in these experiments. Results: The airflow rates required to produce aerosol and the aerosol absorbances were lower for button-activated models (3mL/s; 0.41–0.55 absorbance) than for airflow-activated models (7–17mL/s; 0.48–0.84 absorbance). Pressure drop was also lower across button-activated products (range = 6–12mm H2O) than airflow-activated products (range = 15–67mm H20). For 25 of 27 units tested, airflow did not have to be increased during smoke-out to maintain aerosol production, unlike earlier generation models. Two brands had uniform performance characteristics for all parameters, while 3 had at least 1 product that did not function normally. While button-activated models lasted 200 puffs or less and EH airflow-activated models often lasted 400 puffs, none of the models produced as many puffs as advertised. Puff number was limited by battery life, which was shorter in button-activated models. Conclusion: The performance of disposable products was differentiated mainly by the way the aerosol was produced (button vs airflow-activated) rather than by product type (EC vs EH). Users needed to take harder drags on airflow-activated models. Performance varied within models, and battery life limited the number of puffs. Data suggest quality control in manufacturing varies among brands. PMID:25104117

Ferromagnetic interaction model of activity level in workplace communication

NASA Astrophysics Data System (ADS)

Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

2013-03-01

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

Designing an activity-based costing model for a non-admitted prisoner healthcare setting.

PubMed

Cai, Xiao; Moore, Elizabeth; McNamara, Martin

2013-09-01

To design and deliver an activity-based costing model within a non-admitted prisoner healthcare setting. Key phases from the NSW Health clinical redesign methodology were utilised: diagnostic, solution design and implementation. The diagnostic phase utilised a range of strategies to identify issues requiring attention in the development of the costing model. The solution design phase conceptualised distinct 'building blocks' of activity and cost based on the speciality of clinicians providing care. These building blocks enabled the classification of activity and comparisons of costs between similar facilities. The implementation phase validated the model. The project generated an activity-based costing model based on actual activity performed, gained acceptability among clinicians and managers, and provided the basis for ongoing efficiency and benchmarking efforts.

Muscle Activation During Peripheral Nerve Field Stimulation Occurs Due to Recruitment of Efferent Nerve Fibers, Not Direct Muscle Activation.

PubMed

Frahm, Ken Steffen; Hennings, Kristian; Vera-Portocarrero, Louis; Wacnik, Paul W; Mørch, Carsten Dahl

2016-08-01

Peripheral nerve field stimulation (PNFS) is a potential treatment for chronic low-back pain. Pain relief using PNFS is dependent on activation of non-nociceptive Aβ-fibers. However, PNFS may also activate muscles, causing twitches and discomfort. In this study, we developed a mathematical model, to investigate the activation of sensory and motor nerves, as well as direct muscle fiber activation. The extracellular field was estimated using a finite element model based on the geometry of CT scanned lumbar vertebrae. The electrode was modeled as being implanted to a depth of 10-15 mm. Three implant directions were modeled; horizontally, vertically, and diagonally. Both single electrode and "between-lead" stimulation between contralateral electrodes were modeled. The extracellular field was combined with models of sensory Aβ-nerves, motor neurons and muscle fibers to estimate their activation thresholds. The model showed that sensory Aβ fibers could be activated with thresholds down to 0.563 V, and the lowest threshold for motor nerve activation was 7.19 V using between-lead stimulation with the cathode located closest to the nerves. All thresholds for direct muscle activation were above 500 V. The results suggest that direct muscle activation does not occur during PNFS, and concomitant motor and sensory nerve fiber activation are only likely to occur when using between-lead configuration. Thus, it may be relevant to investigate the location of the innervation zone of the low-back muscles prior to electrode implantation to avoid muscle activation. © 2016 International Neuromodulation Society.

Epistemic Gameplay and Discovery in Computational Model-Based Inquiry Activities

ERIC Educational Resources Information Center

Wilkerson, Michelle Hoda; Shareff, Rebecca; Laina, Vasiliki; Gravel, Brian

2018-01-01

In computational modeling activities, learners are expected to discover the inner workings of scientific and mathematical systems: First elaborating their understandings of a given system through constructing a computer model, then "debugging" that knowledge by testing and refining the model. While such activities have been shown to…

Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry.

PubMed

Garnotel, M; Bastian, T; Romero-Ugalde, H M; Maire, A; Dugas, J; Zahariev, A; Doron, M; Jallon, P; Charpentier, G; Franc, S; Blanc, S; Bonnet, S; Simon, C

2018-03-01

Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions. NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.

Preconditioning electromyographic data for an upper extremity model using neural networks

NASA Technical Reports Server (NTRS)

Roberson, D. J.; Fernjallah, M.; Barr, R. E.; Gonzalez, R. V.

1994-01-01

A back propagation neural network has been employed to precondition the electromyographic signal (EMG) that drives a computational model of the human upper extremity. This model is used to determine the complex relationship between EMG and muscle activation, and generates an optimal muscle activation scheme that simulates the actual activation. While the experimental and model predicted results of the ballistic muscle movement are very similar, the activation function between the start and the finish is not. This neural network preconditions the signal in an attempt to more closely model the actual activation function over the entire course of the muscle movement.

AST: Activity-Security-Trust driven modeling of time varying networks

PubMed Central

Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

2016-01-01

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents’ interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes. PMID:26888717

Scaffolding Students' Online Critiquing of Expert- and Peer-generated Molecular Models of Chemical Reactions

NASA Astrophysics Data System (ADS)

Chang, Hsin-Yi; Chang, Hsiang-Chi

2013-08-01

In this study, we developed online critiquing activities using an open-source computer learning environment. We investigated how well the activities scaffolded students to critique molecular models of chemical reactions made by scientists, peers, and a fictitious peer, and whether the activities enhanced the students' understanding of science models and chemical reactions. The activities were implemented in an eighth-grade class with 28 students in a public junior high school in southern Taiwan. The study employed mixed research methods. Data collected included pre- and post-instructional assessments, post-instructional interviews, and students' electronic written responses and oral discussions during the critiquing activities. The results indicated that these activities guided the students to produce overall quality critiques. Also, the students developed a more sophisticated understanding of chemical reactions and scientific models as a result of the intervention. Design considerations for effective model critiquing activities are discussed based on observational results, including the use of peer-generated artefacts for critiquing to promote motivation and collaboration, coupled with critiques of scientific models to enhance students' epistemological understanding of model purpose and communication.

Probabilistic seismic hazard study based on active fault and finite element geodynamic models

NASA Astrophysics Data System (ADS)

Kastelic, Vanja; Carafa, Michele M. C.; Visini, Francesco

2016-04-01

We present a probabilistic seismic hazard analysis (PSHA) that is exclusively based on active faults and geodynamic finite element input models whereas seismic catalogues were used only in a posterior comparison. We applied the developed model in the External Dinarides, a slow deforming thrust-and-fold belt at the contact between Adria and Eurasia.. is the Our method consists of establishing s two earthquake rupture forecast models: (i) a geological active fault input (GEO) model and, (ii) a finite element (FEM) model. The GEO model is based on active fault database that provides information on fault location and its geometric and kinematic parameters together with estimations on its slip rate. By default in this model all deformation is set to be released along the active faults. The FEM model is based on a numerical geodynamic model developed for the region of study. In this model the deformation is, besides along the active faults, released also in the volumetric continuum elements. From both models we calculated their corresponding activity rates, its earthquake rates and their final expected peak ground accelerations. We investigated both the source model and the earthquake model uncertainties by varying the main active fault and earthquake rate calculation parameters through constructing corresponding branches of the seismic hazard logic tree. Hazard maps and UHS curves have been produced for horizontal ground motion on bedrock conditions VS 30 ≥ 800 m/s), thereby not considering local site amplification effects. The hazard was computed over a 0.2° spaced grid considering 648 branches of the logic tree and the mean value of 10% probability of exceedance in 50 years hazard level, while the 5th and 95th percentiles were also computed to investigate the model limits. We conducted a sensitivity analysis to control which of the input parameters influence the final hazard results in which measure. The results of such comparison evidence the deformation model and with their internal variability together with the choice of the ground motion prediction equations (GMPEs) are the most influencing parameter. Both of these parameters have significan affect on the hazard results. Thus having good knowledge of the existence of active faults and their geometric and activity characteristics is of key importance. We also show that PSHA models based exclusively on active faults and geodynamic inputs, which are thus not dependent on past earthquake occurrences, provide a valid method for seismic hazard calculation.

Examination of a muscular activity estimation model using a Bayesian network for the influence of an ankle foot orthosis.

PubMed

Inoue, Jun; Kawamura, Kazuya; Fujie, Masakatsu G

2012-01-01

In the present paper, we examine the appropriateness of a new model to examine the activity of the foot in gait. We developed an estimation model for foot-ankle muscular activity in the design of an ankle-foot orthosis by means of a statistical method. We chose three muscles for measuring muscular activity and built a Bayesian network model to confirm the appropriateness of the estimation model. We experimentally examined the normal gait of a non-disabled subject. We measured the muscular activity of the lower foot muscles using electromyography, the joint angles, and the pressure on each part of the sole. From these data, we obtained the causal relationship at every 10% level for these factors and built models for the stance phase, control term, and propulsive term. Our model has three advantages. First, it can express the influences that change during gait because we use 10% level nodes for each factor. Second, it can express the influences of factors that differ for low and high muscular-activity levels. Third, we created divided models that are able to reflect the actual features of gait. In evaluating the new model, we confirmed it is able to estimate all muscular activity level with an accuracy of over 90%.

IASM: Individualized activity space modeler

NASA Astrophysics Data System (ADS)

Hasanzadeh, Kamyar

2018-01-01

Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.

[Competence development in undergraduate medical schools: a model with entrusted professional activities].

PubMed

Torruco-García, Uri; Ortiz-Montalvo, Armando; Varela-Ruiz, Margarita Elena; Hamui-Sutton, Alicia

2016-01-01

Today´s relevant educational models emphasize that a great part of learning be situated and reflexive; one of those is the Entrusted Professional Activities model. The study objective was to develop a model that integrates Entrusted Professional Activities with a medical school curriculum. From October 2012 a multidisciplinary group met to develop a model with the specialty of obstetrics and gynecology. From two published models of Entrusted Professional Activities and the curriculum of a school of medicine, blocks, units, and daily clinical practice charts were developed. The thematic content of the curriculum was integrated with the appropriate milestones for undergraduate students and the clinical practice needed to achieve it. We wrote a manual with 37 daily clinical practice charts for students (18 of gynecology and 19 of obstetrics) and 37 for teachers. Each chart content was the daily clinical practice, reflection activities, assessment instruments, and bibliography. It is feasible to combine a model of Entrusted Professional Activities with an undergraduate curriculum, which establishes a continuum with postgraduate education.

A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing

PubMed Central

Long, Chengjiang; Hua, Gang; Kapoor, Ashish

2015-01-01

We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892

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.

IHY Modeling Support at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Chulaki, A.; Hesse, Michael; Kuznetsova, Masha; MacNeice, P.; Rastaetter, L.

2005-01-01

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. In particular, the CCMC provides to the research community the execution of "runs-onrequest" for specific events of interest to space science researchers. Through this activity and the concurrent development of advanced visualization tools, CCMC provides, to the general science community, unprecedented access to a large number of state-of-the-art research models. CCMC houses models that cover the entire domain from the Sun to the Earth. In this presentation, we will provide an overview of CCMC modeling services that are available to support activities during the International Heliospheric Year. In order to tailor CCMC activities to IHY needs, we will also invite community input into our IHY planning activities.

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.

Automated time activity classification based on global positioning system (GPS) tracking data

PubMed Central

2011-01-01

Background Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. Methods We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Results Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Conclusions Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns. PMID:22082316

Automated time activity classification based on global positioning system (GPS) tracking data.

PubMed

Wu, Jun; Jiang, Chengsheng; Houston, Douglas; Baker, Dean; Delfino, Ralph

2011-11-14

Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

A cluster expansion model for predicting activation barrier of atomic processes

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

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

2013-06-15

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

Correlation lengths in hydrodynamic models of active nematics.

PubMed

Hemingway, Ewan J; Mishra, Prashant; Marchetti, M Cristina; Fielding, Suzanne M

2016-09-28

We examine the scaling with activity of the emergent length scales that control the nonequilibrium dynamics of an active nematic liquid crystal, using two popular hydrodynamic models that have been employed in previous studies. In both models we find that the chaotic spatio-temporal dynamics in the regime of fully developed active turbulence is controlled by a single active scale determined by the balance of active and elastic stresses, regardless of whether the active stress is extensile or contractile in nature. The observed scaling of the kinetic energy and enstrophy with activity is consistent with our single-length scale argument and simple dimensional analysis. Our results provide a unified understanding of apparent discrepancies in the previous literature and demonstrate that the essential physics is robust to the choice of model.

Systems Studies

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

Graham, R.L.

1998-03-17

The Systems Studies Activity had two objectives: (1) to investigate nontechnical barriers to the deployment of biomass production and supply systems and (2) to enhance and extend existing systems models of bioenergy supply and use. For the first objective, the Activity focused on existing bioenergy markets. Four projects were undertaken: a comparative analysis of bioenergy in Sweden and Austria; a one-day workshop on nontechnical barriers jointly supported by the Production Systems Activity; the development and testing of a framework for analyzing barriers and drivers to bioenergy markets; and surveys of wood pellet users in Sweden, Austria and the US. Formore » the second objective, two projects were undertaken. First, the Activity worked with the Integrated BioEnergy Systems (TBS) Activity of TEA Bioenergy Task XIII to enhance the BioEnergy Assessment Model (BEAM). This model is documented in the final report of the IBS Activity. The Systems Studies Activity contributed to enhancing the feedstock portion of the model by developing a coherent set of willow, poplar, and switchgrass production modules relevant to both the US and the UK. The Activity also developed a pretreatment module for switchgrass. Second, the Activity sponsored a three-day workshop on modeling bioenergy systems with the objectives of providing an overview of the types of models used to evaluate bioenergy and promoting communication among bioenergy modelers. There were nine guest speakers addressing different types of models used to evaluate different aspects of bioenergy, ranging from technoeconomic models based on the ASPEN software to linear programming models to develop feedstock supply curves for the US. The papers from this workshop have been submitted to Biomass and Bioenergy and are under editorial review.« less

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.

The generalized Hill model: A kinematic approach towards active muscle contraction

NASA Astrophysics Data System (ADS)

Göktepe, Serdar; Menzel, Andreas; Kuhl, Ellen

2014-12-01

Excitation-contraction coupling is the physiological process of converting an electrical stimulus into a mechanical response. In muscle, the electrical stimulus is an action potential and the mechanical response is active contraction. The classical Hill model characterizes muscle contraction though one contractile element, activated by electrical excitation, and two non-linear springs, one in series and one in parallel. This rheology translates into an additive decomposition of the total stress into a passive and an active part. Here we supplement this additive decomposition of the stress by a multiplicative decomposition of the deformation gradient into a passive and an active part. We generalize the one-dimensional Hill model to the three-dimensional setting and constitutively define the passive stress as a function of the total deformation gradient and the active stress as a function of both the total deformation gradient and its active part. We show that this novel approach combines the features of both the classical stress-based Hill model and the recent active-strain models. While the notion of active stress is rather phenomenological in nature, active strain is micro-structurally motivated, physically measurable, and straightforward to calibrate. We demonstrate that our model is capable of simulating excitation-contraction coupling in cardiac muscle with its characteristic features of wall thickening, apical lift, and ventricular torsion.

Using animal models to determine the significance of complement activation in Alzheimer's disease

PubMed Central

Loeffler, David A

2004-01-01

Complement inflammation is a major inflammatory mechanism whose function is to promote the removal of microorganisms and the processing of immune complexes. Numerous studies have provided evidence for an increase in this process in areas of pathology in the Alzheimer's disease (AD) brain. Because complement activation proteins have been demonstrated in vitro to exert both neuroprotective and neurotoxic effects, the significance of this process in the development and progression of AD is unclear. Studies in animal models of AD, in which brain complement activation can be experimentally altered, should be of value for clarifying this issue. However, surprisingly little is known about complement activation in the transgenic animal models that are popular for studying this disorder. An optimal animal model for studying the significance of complement activation on Alzheimer's – related neuropathology should have complete complement activation associated with senile plaques, neurofibrillary tangles (if present), and dystrophic neurites. Other desirable features include both classical and alternative pathway activation, increased neuronal synthesis of native complement proteins, and evidence for an increase in complement activation prior to the development of extensive pathology. In order to determine the suitability of different animal models for studying the role of complement activation in AD, the extent of complement activation and its association with neuropathology in these models must be understood. PMID:15479474

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

PubMed Central

Marai, G. Elisabeta

2018-01-01

Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature. PMID:28866550

Testing a Theoretical Model of Immigration Transition and Physical Activity.

PubMed

Chang, Sun Ju; Im, Eun-Ok

2015-01-01

The purposes of the study were to develop a theoretical model to explain the relationships between immigration transition and midlife women's physical activity and test the relationships among the major variables of the model. A theoretical model, which was developed based on transitions theory and the midlife women's attitudes toward physical activity theory, consists of 4 major variables, including length of stay in the United States, country of birth, level of acculturation, and midlife women's physical activity. To test the theoretical model, a secondary analysis with data from 127 Hispanic women and 123 non-Hispanic (NH) Asian women in a national Internet study was used. Among the major variables of the model, length of stay in the United States was negatively associated with physical activity in Hispanic women. Level of acculturation in NH Asian women was positively correlated with women's physical activity. Country of birth and level of acculturation were significant factors that influenced physical activity in both Hispanic and NH Asian women. The findings support the theoretical model that was developed to examine relationships between immigration transition and physical activity; it shows that immigration transition can play an essential role in influencing health behaviors of immigrant populations in the United States. The NH theoretical model can be widely used in nursing practice and research that focus on immigrant women and their health behaviors. Health care providers need to consider the influences of immigration transition to promote immigrant women's physical activity.

Modeling open-set spoken word recognition in postlingually deafened adults after cochlear implantation: some preliminary results with the neighborhood activation model.

PubMed

Meyer, Ted A; Frisch, Stefan A; Pisoni, David B; Miyamoto, Richard T; Svirsky, Mario A

2003-07-01

Do cochlear implants provide enough information to allow adult cochlear implant users to understand words in ways that are similar to listeners with acoustic hearing? Can we use a computational model to gain insight into the underlying mechanisms used by cochlear implant users to recognize spoken words? The Neighborhood Activation Model has been shown to be a reasonable model of word recognition for listeners with normal hearing. The Neighborhood Activation Model assumes that words are recognized in relation to other similar-sounding words in a listener's lexicon. The probability of correctly identifying a word is based on the phoneme perception probabilities from a listener's closed-set consonant and vowel confusion matrices modified by the relative frequency of occurrence of the target word compared with similar-sounding words (neighbors). Common words with few similar-sounding neighbors are more likely to be selected as responses than less common words with many similar-sounding neighbors. Recent studies have shown that several of the assumptions of the Neighborhood Activation Model also hold true for cochlear implant users. Closed-set consonant and vowel confusion matrices were obtained from 26 postlingually deafened adults who use cochlear implants. Confusion matrices were used to represent input errors to the Neighborhood Activation Model. Responses to the different stimuli were then generated by the Neighborhood Activation Model after incorporating the frequency of occurrence counts of the stimuli and their neighbors. Model outputs were compared with obtained performance measures on the Consonant-Vowel Nucleus-Consonant word test. Information transmission analysis was used to assess whether the Neighborhood Activation Model was able to successfully generate and predict word and individual phoneme recognition by cochlear implant users. The Neighborhood Activation Model predicted Consonant-Vowel Nucleus-Consonant test words at levels similar to those correctly identified by the cochlear implant users. The Neighborhood Activation Model also predicted phoneme feature information well. The results obtained suggest that the Neighborhood Activation Model provides a reasonable explanation of word recognition by postlingually deafened adults after cochlear implantation. It appears that multichannel cochlear implants give cochlear implant users access to their mental lexicons in a manner that is similar to listeners with acoustic hearing. The lexical properties of the test stimuli used to assess performance are important to spoken-word recognition and should be included in further models of the word recognition process.

Using lab notebooks to examine students' engagement in modeling in an upper-division electronics lab course

NASA Astrophysics Data System (ADS)

Stanley, Jacob T.; Su, Weifeng; Lewandowski, H. J.

2017-12-01

We demonstrate how students' use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students' written work and to identify how students' model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students' model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.

A Disability Studies Framework for Policy Activism in Postsecondary Education

ERIC Educational Resources Information Center

Gabel, Susan L.

2010-01-01

This article uses disability studies and the social model of disability as theoretical foundations for policy activism in postsecondary education. The social model is discussed and a model for policy activism is described. A case study of how disability studies and policy activism can be applied is provided utilizing the "3C Project to Provide…

24 CFR 1000.112 - How will HUD determine whether to approve model housing activities?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false How will HUD determine whether to approve model housing activities? 1000.112 Section 1000.112 Housing and Urban Development Regulations... Activities § 1000.112 How will HUD determine whether to approve model housing activities? HUD will review all...

Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach.

PubMed

Murphy, Matthew C; Poplawsky, Alexander J; Vazquez, Alberto L; Chan, Kevin C; Kim, Seong-Gi; Fukuda, Mitsuhiro

2016-08-15

Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

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 ...

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.

A casemix model for estimating the impact of hospital access block on the emergency department.

PubMed

Stuart, Peter

2004-06-01

To determine the ED activity and costs resulting from access block. A casemix model (AWOOS) was developed to measure activity due to access block. Using data from four hospitals between 1998 and 2002, ED activity was measured using the urgency and disposition group (UDG) casemix model and the AWOOS model with the purpose of determining the change in ED activity due to access block. Whilst the mean length of stay in ED (admitted patients) increased by 93% between 1998 and 2002, mean UDG activity increased by 0.63% compared to a mean increase in AWOOS activity of 24.5%. The 23.9% difference between UDG and AWOOS activity represents the (unmeasured) increase in ED activity and costs for the period 1998-2002 resulting from access block. The UDG system significantly underestimates the activity in EDs experiencing marked access block.

Self-organized energetic model for collective activity on animal tissue

NASA Astrophysics Data System (ADS)

Dos Santos, Michelle C. Varela; Macedo-Filho, Antonio; Dos Santos Lima, Gustavo Zampier; Corso, Gilberto

We construct a self-organized critical (SOC) model to explain spontaneous collective activity in animal tissue without the necessity of a muscular or a central control nervous system. Our prototype model is an epithelial cuboid tissue formed by a single layer of cells as the internal digestive cavity of primitive animals. The tissue is composed by cells that absorb nutrients and store energy, with probability p, to participate in a collective tissue activity. Each cell can be in two states: at high energy and able to became active or at low metabolic energy and remain at rest. Any cell can spontaneously, with a very low probability, spark a collective activity across its neighbors that share a minimal energy. Cells participating in tissue activity consume all their energy. A power-law relation P(s)∝sγ for the probability of having a collective activity with s cells is observed. By construction this model is analogue to the forest fire SOC model. Our approach produces naturally a critical state for the activity in animal tissue, besides it explains self-sustained activity in a living animal tissue without feedback control.

3D MHD Models of Active Region Loops

NASA Technical Reports Server (NTRS)

Ofman, Leon

2004-01-01

Present imaging and spectroscopic observations of active region loops allow to determine many physical parameters of the coronal loops, such as the density, temperature, velocity of flows in loops, and the magnetic field. However, due to projection effects many of these parameters remain ambiguous. Three dimensional imaging in EUV by the STEREO spacecraft will help to resolve the projection ambiguities, and the observations could be used to setup 3D MHD models of active region loops to study the dynamics and stability of active regions. Here the results of 3D MHD models of active region loops are presented, and the progress towards more realistic 3D MHD models of active regions. In particular the effects of impulsive events on the excitation of active region loop oscillations, and the generation, propagations and reflection of EIT waves are shown. It is shown how 3D MHD models together with 3D EUV observations can be used as a diagnostic tool for active region loop physical parameters, and to advance the science of the sources of solar coronal activity.

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.

Toward a complex system understanding of bipolar disorder: A chaotic model of abnormal circadian activity rhythms in euthymic bipolar disorder.

PubMed

Hadaeghi, Fatemeh; Hashemi Golpayegani, Mohammad Reza; Jafari, Sajad; Murray, Greg

2016-08-01

In the absence of a comprehensive neural model to explain the underlying mechanisms of disturbed circadian function in bipolar disorder, mathematical modeling is a helpful tool. Here, circadian activity as a response to exogenous daily cycles is proposed to be the product of interactions between neuronal networks in cortical (cognitive processing) and subcortical (pacemaker) areas of the brain. To investigate the dynamical aspects of the link between disturbed circadian activity rhythms and abnormalities of neurotransmitter functioning in frontal areas of the brain, we developed a novel mathematical model of a chaotic system which represents fluctuations in circadian activity in bipolar disorder as changes in the model's parameters. A novel map-based chaotic system was developed to capture disturbances in circadian activity across the two extreme mood states of bipolar disorder. The model uses chaos theory to characterize interplay between neurotransmitter functions and rhythm generation; it aims to illuminate key activity phenomenology in bipolar disorder, including prolonged sleep intervals, decreased total activity and attenuated amplitude of the diurnal activity rhythm. To test our new cortical-circadian mathematical model of bipolar disorder, we utilized previously collected locomotor activity data recorded from normal subjects and bipolar patients by wrist-worn actigraphs. All control parameters in the proposed model have an important role in replicating the different aspects of circadian activity rhythm generation in the brain. The model can successfully replicate deviations in sleep/wake time intervals corresponding to manic and depressive episodes of bipolar disorder, in which one of the excitatory or inhibitory pathways is abnormally dominant. Although neuroimaging research has strongly implicated a reciprocal interaction between cortical and subcortical regions as pathogenic in bipolar disorder, this is the first model to mathematically represent this multilevel explanation of the phenomena of bipolar disorder. © The Royal Australian and New Zealand College of Psychiatrists 2016.

Test, revision, and cross-validation of the Physical Activity Self-Definition Model.

PubMed

Kendzierski, Deborah; Morganstein, Mara S

2009-08-01

Structural equation modeling was used to test an extended version of the Kendzierski, Furr, and Schiavoni (1998) Physical Activity Self-Definition Model. A revised model using data from 622 runners fit the data well. Cross-validation indices supported the revised model, and this model also provided a good fit to data from 397 cyclists. Partial invariance was found across activities. In both samples, perceived commitment and perceived ability had direct effects on self-definition, and perceived wanting, perceived trying, and enjoyment had indirect effects. The contribution of perceived ability to self-definition did not differ across activities. Implications concerning the original model, indirect effects, skill salience, and the role of context in self-definition are discussed.

Activity-Based Costing in the Naval Postgraduate School

DTIC Science & Technology

2015-03-01

SCHOOL ACTIVITY-BASED COSTING MODEL ...29 A. MODELING ISSUES AND LIMITATIONS ..............................................29 B. COST POOL ALLOCATIONS TO PRODUCTION DEPARTMENTS...Activity, Monterey Bay (NSAMB). As such, MWR is not included in the costing model . Similarly, the cost of student salaries and benefits are not

Preference as a Function of Active Interresponse Times: A Test of the Active Time Model

ERIC Educational Resources Information Center

Misak, Paul; Cleaveland, J. Mark

2011-01-01

In this article, we describe a test of the active time model for concurrent variable interval (VI) choice. The active time model (ATM) suggests that the time since the most recent response is one of the variables controlling choice in concurrent VI VI schedules of reinforcement. In our experiment, pigeons were trained in a multiple concurrent…

Evaluating a Model of Youth Physical Activity

PubMed Central

Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary

2011-01-01

Objective To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a sample of youth aged 10–17 years (N=720). Results Peer support, parent physical activity, and perceived barriers were directly related to youth activity. The proposed model accounted for 14.7% of the variance in physical activity. Conclusions The results demonstrate a need to further explore additional individual, social, and environmental factors that may influence youth’s regular participation in physical activity. PMID:20524889

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Fish biomarkers for environmental monitoring: An integrated model supporting enzyme activity and histopathological lesions

NASA Astrophysics Data System (ADS)

Neta, Raimunda Nonata Fortes Carvalho; Torres Junior, Audalio Rebelo

2014-10-01

We present a mathematical model describing the association between glutathione-S-transferase activity and brachial lesions in the catfish, Sciades herzbergii (Ariidae) from a polluted port. The catfish were sampled from a port known to be contaminated with heavy metals and organic compounds and from a natural reserve in São Marcos Bay, Brazil. Two biomarkers, hepatic glutathione S-transferase (GST) activity and histopathological lesions, in gills tissue were measured. The values for GST activity were modeled with the occurrence of branchial lesions by fitting a third order polynomial. Results from the mathematical model indicate that GST activity has a strong polynomial relationship with the occurrence of branchial lesions in both the wet and the dry seasons, but only at the polluted port site. The model developed in this study indicates that branchial and hepatic lesions are initiated when GST activity reaches 2.15 μmol min-1 mg protein-1. Beyond this limit, GST activity decreased to very low levels and irreversible histopathological lesions occurred. This mathematical model provides a realistic approach to analyze predictive biomarkers of environmental health status.

Modelling and study of active vibration control for off-road vehicle

NASA Astrophysics Data System (ADS)

Zhang, Junwei; Chen, Sizhong

2014-05-01

In view of special working characteristics and structure, engineering machineries do not have conventional suspension system typically. Consequently, operators have to endure severe vibrations which are detrimental both to their health and to the productivity of the loader. Based on displacement control, a kind of active damping method is developed for a skid-steer loader. In this paper, the whole hydraulic system for active damping method is modelled which include swash plate dynamics model, proportional valve model, piston accumulator model, pilot-operated check valve model, relief valve model, pump loss model, and cylinder model. A new road excitation model is developed for the skid-steer loader specially. The response of chassis vibration acceleration to road excitation is verified through simulation. The simulation result of passive accumulator damping is compared with measurements and the comparison shows that they are close. Based on this, parallel PID controller and track PID controller with acceleration feedback are brought into the simulation model, and the simulation results are compared with passive accumulator damping. It shows that the active damping methods with PID controllers are better in reducing chassis vibration acceleration and pitch movement. In the end, the test work for active damping method is proposed for the future work.

Improving the modelling of irradiation-induced brain activation for in vivo PET verification of proton therapy.

PubMed

Bauer, Julia; Chen, Wenjing; Nischwitz, Sebastian; Liebl, Jakob; Rieken, Stefan; Welzel, Thomas; Debus, Juergen; Parodi, Katia

2018-04-24

A reliable Monte Carlo prediction of proton-induced brain tissue activation used for comparison to particle therapy positron-emission-tomography (PT-PET) measurements is crucial for in vivo treatment verification. Major limitations of current approaches to overcome include the CT-based patient model and the description of activity washout due to tissue perfusion. Two approaches were studied to improve the activity prediction for brain irradiation: (i) a refined patient model using tissue classification based on MR information and (ii) a PT-PET data-driven refinement of washout model parameters. Improvements of the activity predictions compared to post-treatment PT-PET measurements were assessed in terms of activity profile similarity for six patients treated with a single or two almost parallel fields delivered by active proton beam scanning. The refined patient model yields a generally higher similarity for most of the patients, except in highly pathological areas leading to tissue misclassification. Using washout model parameters deduced from clinical patient data could considerably improve the activity profile similarity for all patients. Current methods used to predict proton-induced brain tissue activation can be improved with MR-based tissue classification and data-driven washout parameters, thus providing a more reliable basis for PT-PET verification. Copyright © 2018 Elsevier B.V. All rights reserved.

Recognition of human activity characteristics based on state transitions modeling technique

NASA Astrophysics Data System (ADS)

Elangovan, Vinayak; Shirkhodaie, Amir

2012-06-01

Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.

Suppression of Antigen-Specific Lymphocyte Activation in Simulated Microgravity

NASA Technical Reports Server (NTRS)

Cooper, David; Pride, Michael W.; Brown, Eric L.; Risin, Diana; Pellis, Neal R.

1999-01-01

Various parameters of immune suppression are observed in astronauts during and after spaceflight, and in isolated immune cells in true and simulated microgravity. Specifically, polyclonal activation of T cells is severely suppressed in true and simulated microgravity. These recent findings with various polyclonal activators suggests a suppression of oligoclonal lymphocyte activation in microgravity. We utilized rotating wall vessel (RWV) bioreactors that simulate aspects of microgravity for cell cultures to analyze three models of antigen-specific activation. A mixed-lymphocyte reaction (MLR), as a model for a primary immune response; a tetanus toxoid (TT) response and a B. burgdorferi (Bb) response, as models of a secondary immune response, were all suppressed in the RWV bioreactor. Our findings confirm that the suppression of activation observed with polyclonal models also encompasses oligoclonal antigen-specific activation.

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

Suppression of antigen-specific lymphocyte activation in modeled microgravity

NASA Technical Reports Server (NTRS)

Cooper, D.; Pride, M. W.; Brown, E. L.; Risin, D.; Pellis, N. R.; McIntire, L. V. (Principal Investigator)

2001-01-01

Various parameters of immune suppression are observed in lymphocytes from astronauts during and after a space flight. It is difficult to ascribe this suppression to microgravity effects on immune cells in crew specimens, due to the complex physiological response to space flight and the resultant effect on in vitro immune performance. Use of isolated immune cells in true and modeled microgravity in immune performance tests, suggests a direct effect of microgravity on in vitro cellular function. Specifically, polyclonal activation of T-cells is severely suppressed in true and modeled microgravity. These recent findings suggest a potential suppression of oligoclonal antigen-specific lymphocyte activation in microgravity. We utilized rotating wall vessel (RWV) bioreactors as an analog of microgravity for cell cultures to analyze three models of antigen-specific activation. A mixed-lymphocyte reaction, as a model for a primary immune response, a tetanus toxoid response and a Borrelia burgdorferi response, as models of a secondary immune response, were all suppressed in the RWV bioreactor. Our findings confirm that the suppression of activation observed with polyclonal models also encompasses oligoclonal antigen-specific activation.

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.

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

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

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

DOE PAGES

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; ...

2015-02-13

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

An Empirical Comparison of Different Models of Active Aging in Canada: The International Mobility in Aging Study

PubMed Central

Ahmed, Tamer; Filiatrault, Johanne; Yu, Hsiu-Ting; Zunzunegui, Maria Victoria

2017-01-01

Abstract Purpose: Active aging is a concept that lacks consensus. The WHO defines it as a holistic concept that encompasses the overall health, participation, and security of older adults. Fernández-Ballesteros and colleagues propose a similar concept but omit security and include mood and cognitive function. To date, researchers attempting to validate conceptual models of active aging have obtained mixed results. The goal of this study was to examine the validity of existing models of active aging with epidemiological data from Canada. Methods: The WHO model of active aging and the psychological model of active aging developed by Fernández-Ballesteros and colleagues were tested with confirmatory factor analysis. The data used included 799 community-dwelling older adults between 65 and 74 years old, recruited from the patient lists of family physicians in Saint-Hyacinthe, Quebec and Kingston, Ontario. Results: Neither model could be validated in the sample of Canadian older adults. Although a concept of healthy aging can be modeled adequately, social participation and security did not fit a latent factor model. A simple binary index indicated that 27% of older adults in the sample did not meet the active aging criteria proposed by the WHO. Implications: Our results suggest that active aging might represent a human rights policy orientation rather than an empirical measurement tool to guide research among older adult populations. Binary indexes of active aging may serve to highlight what remains to be improved about the health, participation, and security of growing populations of older adults. PMID:26350153

Modeling of the relationship between dipeptide structure and dipeptide stability, permeability, and ACE inhibitory activity.

PubMed

Foltz, Martin; van Buren, Leo; Klaffke, Werner; Duchateau, Guus S M J E

2009-09-01

Selected di- and tripeptides exhibit angiotensin-I converting enzyme (ACE) inhibitory activity in vitro. However, the efficacy in vivo is most likely limited for most peptides due to low bioavailability. The purpose of this study was to identify descriptors of intestinal stability, permeability, and ACE inhibitory activity of dipeptides. A total of 228 dipeptides were synthesized; intestinal stability was obtained by in vitro digestion, intestinal permeability using Caco-2 cells and ACE inhibitory activity by an in vitro assay. Databases were constructed to study the relationship between structure and activity, permeability, and stability. Quantitative structure-activity relationship (QSAR) modeling was performed based on computed models using partial least squares regression based on 400 molecular descriptors. QSAR modeling of dipeptide stability revealed high correlation coefficients (R > 0.65) for models based on Z and X scales. However, amino acid (AA) clustering showed the best results in describing stability of dipeptides. The N-terminal AA residues Asp, Gly, and Pro as well as the C-terminal residues Pro, Ser, Thr, and Asp stabilize dipeptides toward luminal enzymatic peptide hydrolysis. QSAR modeling did not reveal significant correlation models for intestinal permeability. 2D-fingerprint models were identified describing ACE inhibitory activity of dipeptides. The intestinal stability of 12 peptides was predicted. Peptides were synthesized and stability was confirmed in simulated digestion experiments. Based on the results, specific dipeptides can be designed to meet both stability and activity criteria. However, postabsorptive ACE inhibitory activities of dipeptides in vivo are most likely limited due to the very low intestinal permeability of dipeptides.

Associative memory model with spontaneous neural activity

NASA Astrophysics Data System (ADS)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

The ACTIVE conceptual framework as a structural equation model.

PubMed

Gross, Alden L; Payne, Brennan R; Casanova, Ramon; Davoudzadeh, Pega; Dzierzewski, Joseph M; Farias, Sarah; Giovannetti, Tania; Ip, Edward H; Marsiske, Michael; Rebok, George W; Schaie, K Warner; Thomas, Kelsey; Willis, Sherry; Jones, Richard N

2018-01-01

Background/Study Context: Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status. Preconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA < .05; all CFI > .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p < .005). Empirical data confirm the hypothesized ACTIVE conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from those with the greatest chance of transfer to real-world activities.

Mechanochemical pattern formation in simple models of active viscoelastic fluids and solids

NASA Astrophysics Data System (ADS)

Alonso, Sergio; Radszuweit, Markus; Engel, Harald; Bär, Markus

2017-11-01

The cytoskeleton of the organism Physarum polycephalum is a prominent example of a complex active viscoelastic material wherein stresses induce flows along the organism as a result of the action of molecular motors and their regulation by calcium ions. Experiments in Physarum polycephalum have revealed a rich variety of mechanochemical patterns including standing, traveling and rotating waves that arise from instabilities of spatially homogeneous states without gradients in stresses and resulting flows. Herein, we investigate simple models where an active stress induced by molecular motors is coupled to a model describing the passive viscoelastic properties of the cellular material. Specifically, two models for viscoelastic fluids (Maxwell and Jeffrey model) and two models for viscoelastic solids (Kelvin-Voigt and Standard model) are investigated. Our focus is on the analysis of the conditions that cause destabilization of spatially homogeneous states and the related onset of mechano-chemical waves and patterns. We carry out linear stability analyses and numerical simulations in one spatial dimension for different models. In general, sufficiently strong activity leads to waves and patterns. The primary instability is stationary for all active fluids considered, whereas all active solids have an oscillatory primary instability. All instabilities found are of long-wavelength nature reflecting the conservation of the total calcium concentration in the models studied.

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.

Modeling the Benchmark Active Control Technology Wind-Tunnel Model for Active Control Design Applications

NASA Technical Reports Server (NTRS)

Waszak, Martin R.

1998-01-01

This report describes the formulation of a model of the dynamic behavior of the Benchmark Active Controls Technology (BACT) wind tunnel model for active control design and analysis applications. The model is formed by combining the equations of motion for the BACT wind tunnel model with actuator models and a model of wind tunnel turbulence. The primary focus of this report is the development of the equations of motion from first principles by using Lagrange's equations and the principle of virtual work. A numerical form of the model is generated by making use of parameters obtained from both experiment and analysis. Comparisons between experimental and analytical data obtained from the numerical model show excellent agreement and suggest that simple coefficient-based aerodynamics are sufficient to accurately characterize the aeroelastic response of the BACT wind tunnel model. The equations of motion developed herein have been used to aid in the design and analysis of a number of flutter suppression controllers that have been successfully implemented.

Model of transcriptional activation by MarA in Escherichia coli.

PubMed

Wall, Michael E; Markowitz, David A; Rosner, Judah L; Martin, Robert G

2009-12-01

The AraC family transcription factor MarA activates approximately 40 genes (the marA/soxS/rob regulon) of the Escherichia coli chromosome resulting in different levels of resistance to a wide array of antibiotics and to superoxides. Activation of marA/soxS/rob regulon promoters occurs in a well-defined order with respect to the level of MarA; however, the order of activation does not parallel the strength of MarA binding to promoter sequences. To understand this lack of correspondence, we developed a computational model of transcriptional activation in which a transcription factor either increases or decreases RNA polymerase binding, and either accelerates or retards post-binding events associated with transcription initiation. We used the model to analyze data characterizing MarA regulation of promoter activity. The model clearly explains the lack of correspondence between the order of activation and the MarA-DNA affinity and indicates that the order of activation can only be predicted using information about the strength of the full MarA-polymerase-DNA interaction. The analysis further suggests that MarA can activate without increasing polymerase binding and that activation can even involve a decrease in polymerase binding, which is opposite to the textbook model of activation by recruitment. These findings are consistent with published chromatin immunoprecipitation assays of interactions between polymerase and the E. coli chromosome. We find that activation involving decreased polymerase binding yields lower latency in gene regulation and therefore might confer a competitive advantage to cells. Our model yields insights into requirements for predicting the order of activation of a regulon and enables us to suggest that activation might involve a decrease in polymerase binding which we expect to be an important theme of gene regulation in E. coli and beyond.

Mathematical model for the simulation of Dynamic Docking Test System (DDST) active table motion

NASA Technical Reports Server (NTRS)

Gates, R. M.; Graves, D. L.

1974-01-01

The mathematical model developed to describe the three-dimensional motion of the dynamic docking test system active table is described. The active table is modeled as a rigid body supported by six flexible hydraulic actuators which produce the commanded table motions.

A Model of Medical Countermeasures for Organophosphates

DTIC Science & Technology

2015-10-01

Animal Data ................................................................. 51 6.2.1. Verifying AChE Activity ...17 Figure 4-3. Model Output for AChE Activity and Free/Stimulated Receptor Fraction with No OP Exposure...Figure 6-1. Sarin Model Output Compared to Individual AChE Activity in Acute Phase Following Tokyo Sarin Attack

Developing Modelling Lenses among Practicing Teachers

ERIC Educational Resources Information Center

Shahbari, Juhaina Awawdeh; Tabach, Michal

2016-01-01

Growing awareness of the importance of modelling activities in mathematics education has raised the question of whether teachers are prepared to facilitate the engagement of students in such activities. The current study investigates the effects of how teachers cope with modelling activities in developing their abilities to identify modelling…

Virus elimination in activated sludge systems: from batch tests to mathematical modeling.

PubMed

Haun, Emma; Ulbricht, Katharina; Nogueira, Regina; Rosenwinkel, Karl-Heinz

2014-01-01

A virus tool based on Activated Sludge Model No. 3 for modeling virus elimination in activated sludge systems was developed and calibrated with the results from laboratory-scale batch tests and from measurements in a municipal wastewater treatment plant (WWTP). The somatic coliphages were used as an indicator for human pathogenic enteric viruses. The extended model was used to simulate the virus concentration in batch tests and in a municipal full-scale WWTP under steady-state and dynamic conditions. The experimental and modeling results suggest that both adsorption and inactivation processes, modeled as reversible first-order reactions, contribute to virus elimination in activated sludge systems. The model should be a useful tool to estimate the number of viruses entering water bodies from the discharge of treated effluents.

Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment.

PubMed

Berkes, Pietro; Orbán, Gergo; Lengyel, Máté; Fiser, József

2011-01-07

The brain maintains internal models of its environment to interpret sensory inputs and to prepare actions. Although behavioral studies have demonstrated that these internal models are optimally adapted to the statistics of the environment, the neural underpinning of this adaptation is unknown. Using a Bayesian model of sensory cortical processing, we related stimulus-evoked and spontaneous neural activities to inferences and prior expectations in an internal model and predicted that they should match if the model is statistically optimal. To test this prediction, we analyzed visual cortical activity of awake ferrets during development. Similarity between spontaneous and evoked activities increased with age and was specific to responses evoked by natural scenes. This demonstrates the progressive adaptation of internal models to the statistics of natural stimuli at the neural level.

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.

Lacosamide derivatives with anticonvulsant activity as carbonic anhydrase inhibitors. Molecular modeling, docking and QSAR analysis.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Duchowicz, Pablo R; Torrens, Francisco; Estrada, Mario R

2014-01-01

Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.

Teaching physical activities to students with significant disabilities using video modeling.

PubMed

Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

2013-06-01

The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

Stellar model chromospheres. IX - Chromospheric activity in dwarf stars

NASA Technical Reports Server (NTRS)

Kelch, W. L.; Worden, S. P.; Linsky, J. L.

1979-01-01

High-resolution Ca II K line profiles are used to model the upper photospheres and lower chromospheres of eight main-sequence stars ranging in spectral type from F0 to M0 and exhibiting different degrees of chromospheric activity. The model chromospheres are studied as a function of spectral type and activity for stars of similar spectral type in order to obtain evidence of enhanced nonradiative heating in the upper-photospheric models and in the ratio of minimum temperature at the base of the chromosphere to effective temperature, a correlation between activity and temperature in the lower chromospheres, and a correlation of the width at the base of the K-line emission core and at the K2 features with activity. Chromospheric radiative losses are estimated for the modelled stars and other previously analyzed main-sequence stars. The results obtained strengthen the argument that dMe flare stars exhibit fundamentally solar-type activity but on an increased scale.

Modeling Open-Set Spoken Word Recognition in Postlingually Deafened Adults after Cochlear Implantation: Some Preliminary Results with the Neighborhood Activation Model

PubMed Central

Meyer, Ted A.; Frisch, Stefan A.; Pisoni, David B.; Miyamoto, Richard T.; Svirsky, Mario A.

2012-01-01

Hypotheses Do cochlear implants provide enough information to allow adult cochlear implant users to understand words in ways that are similar to listeners with acoustic hearing? Can we use a computational model to gain insight into the underlying mechanisms used by cochlear implant users to recognize spoken words? Background The Neighborhood Activation Model has been shown to be a reasonable model of word recognition for listeners with normal hearing. The Neighborhood Activation Model assumes that words are recognized in relation to other similar-sounding words in a listener’s lexicon. The probability of correctly identifying a word is based on the phoneme perception probabilities from a listener’s closed-set consonant and vowel confusion matrices modified by the relative frequency of occurrence of the target word compared with similar-sounding words (neighbors). Common words with few similar-sounding neighbors are more likely to be selected as responses than less common words with many similar-sounding neighbors. Recent studies have shown that several of the assumptions of the Neighborhood Activation Model also hold true for cochlear implant users. Methods Closed-set consonant and vowel confusion matrices were obtained from 26 postlingually deafened adults who use cochlear implants. Confusion matrices were used to represent input errors to the Neighborhood Activation Model. Responses to the different stimuli were then generated by the Neighborhood Activation Model after incorporating the frequency of occurrence counts of the stimuli and their neighbors. Model outputs were compared with obtained performance measures on the Consonant-Vowel Nucleus-Consonant word test. Information transmission analysis was used to assess whether the Neighborhood Activation Model was able to successfully generate and predict word and individual phoneme recognition by cochlear implant users. Results The Neighborhood Activation Model predicted Consonant-Vowel Nucleus-Consonant test words at levels similar to those correctly identified by the cochlear implant users. The Neighborhood Activation Model also predicted phoneme feature information well. Conclusion The results obtained suggest that the Neighborhood Activation Model provides a reasonable explanation of word recognition by postlingually deafened adults after cochlear implantation. It appears that multichannel cochlear implants give cochlear implant users access to their mental lexicons in a manner that is similar to listeners with acoustic hearing. The lexical properties of the test stimuli used to assess performance are important to spoken-word recognition and should be included in further models of the word recognition process. PMID:12851554

Perceived sports competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment.

PubMed

Barnett, Lisa M; Morgan, Philip J; van Beurden, Eric; Beard, John R

2008-08-08

The purpose of this paper was to investigate whether perceived sports competence mediates the relationship between childhood motor skill proficiency and subsequent adolescent physical activity and fitness. In 2000, children's motor skill proficiency was assessed as part of a school-based physical activity intervention. In 2006/07, participants were followed up as part of the Physical Activity and Skills Study and completed assessments for perceived sports competence (Physical Self-Perception Profile), physical activity (Adolescent Physical Activity Recall Questionnaire) and cardiorespiratory fitness (Multistage Fitness Test). Structural equation modelling techniques were used to determine whether perceived sports competence mediated between childhood object control skill proficiency (composite score of kick, catch and overhand throw), and subsequent adolescent self-reported time in moderate-to-vigorous physical activity and cardiorespiratory fitness. Of 928 original intervention participants, 481 were located in 28 schools and 276 (57%) were assessed with at least one follow-up measure. Slightly more than half were female (52.4%) with a mean age of 16.4 years (range 14.2 to 18.3 yrs). Relevant assessments were completed by 250 (90.6%) students for the Physical Activity Model and 227 (82.3%) for the Fitness Model. Both hypothesised mediation models had a good fit to the observed data, with the Physical Activity Model accounting for 18% (R2 = 0.18) of physical activity variance and the Fitness Model accounting for 30% (R2 = 0.30) of fitness variance. Sex did not act as a moderator in either model. Developing a high perceived sports competence through object control skill development in childhood is important for both boys and girls in determining adolescent physical activity participation and fitness. Our findings highlight the need for interventions to target and improve the perceived sports competence of youth.

Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity

PubMed Central

Cheng, Leo K; Komuro, Rie; Austin, Travis M; Buist, Martin L; Pullan, Andrew J

2007-01-01

One of the major aims of the International Union of Physiological Sciences (IUPS) Physiome Project is to develop multiscale mathematical and computer models that can be used to help understand human health. We present here a small facet of this broad plan that applies to the gastrointestinal system. Specifically, we present an anatomically and physiologically based modelling framework that is capable of simulating normal and pathological electrical activity within the stomach and small intestine. The continuum models used within this framework have been created using anatomical information derived from common medical imaging modalities and data from the Visible Human Project. These models explicitly incorporate the various smooth muscle layers and networks of interstitial cells of Cajal (ICC) that are known to exist within the walls of the stomach and small bowel. Electrical activity within individual ICCs and smooth muscle cells is simulated using a previously published simplified representation of the cell level electrical activity. This simulated cell level activity is incorporated into a bidomain representation of the tissue, allowing electrical activity of the entire stomach or intestine to be simulated in the anatomically derived models. This electrical modelling framework successfully replicates many of the qualitative features of the slow wave activity within the stomach and intestine and has also been used to investigate activity associated with functional uncoupling of the stomach. PMID:17457969

Relating the bipolar spectrum to dysregulation of behavioural activation: a perspective from dynamical modelling.

PubMed

Steinacher, Arno; Wright, Kim A

2013-01-01

Bipolar Disorders affect a substantial minority of the population and result in significant personal, social and economic costs. Understanding of the causes of, and consequently the most effective interventions for, this condition is an area requiring development. Drawing upon theories of Bipolar Disorder that propose the condition to be underpinned by dysregulation of systems governing behavioural activation or approach motivation, we present a mathematical model of the regulation of behavioural activation. The model is informed by non-linear, dynamical principles and as such proposes that the transition from "non-bipolar" to "bipolar" diagnostic status corresponds to a switch from mono- to multistability of behavioural activation level, rather than an increase in oscillation of mood. Consistent with descriptions of the behavioural activation or approach system in the literature, auto-activation and auto-inhibitory feedback is inherent within our model. Comparison between our model and empirical, observational data reveals that by increasing the non-linearity dimension in our model, important features of Bipolar Spectrum disorders are reproduced. Analysis from stochastic simulation of the system reveals the role of noise in behavioural activation regulation and indicates that an increase of nonlinearity promotes noise to jump scales from small fluctuations of activation levels to longer lasting, but less variable episodes. We conclude that further research is required to relate parameters of our model to key behavioural and biological variables observed in Bipolar Disorder.

Multinomial model and zero-inflated gamma model to study time spent on leisure time physical activity: an example of ELSA-Brasil.

PubMed

Nobre, Aline Araújo; Carvalho, Marilia Sá; Griep, Rosane Härter; Fonseca, Maria de Jesus Mendes da; Melo, Enirtes Caetano Prates; Santos, Itamar de Souza; Chor, Dora

2017-08-17

To compare two methodological approaches: the multinomial model and the zero-inflated gamma model, evaluating the factors associated with the practice and amount of time spent on leisure time physical activity. Data collected from 14,823 baseline participants in the Longitudinal Study of Adult Health (ELSA-Brasil - Estudo Longitudinal de Saúde do Adulto ) have been analysed. Regular leisure time physical activity has been measured using the leisure time physical activity module of the International Physical Activity Questionnaire. The explanatory variables considered were gender, age, education level, and annual per capita family income. The main advantage of the zero-inflated gamma model over the multinomial model is that it estimates mean time (minutes per week) spent on leisure time physical activity. For example, on average, men spent 28 minutes/week longer on leisure time physical activity than women did. The most sedentary groups were young women with low education level and income. The zero-inflated gamma model, which is rarely used in epidemiological studies, can give more appropriate answers in several situations. In our case, we have obtained important information on the main determinants of the duration of leisure time physical activity. This information can help guide efforts towards the most vulnerable groups since physical inactivity is associated with different diseases and even premature death.

A kinetic model to explain the maximum in alpha-amylase activity measurements in the presence of small carbohydrates.

PubMed

Baks, Tim; Janssen, Anja E M; Boom, Remko M

2006-06-20

The effect of the presence of several small carbohydrates on the measurement of the alpha-amylase activity was determined over a broad concentration range. At low carbohydrate concentrations, a distinct maximum in the alpha-amylase activity versus concentration curves was observed in several cases. At higher concentrations, all carbohydrates show a decreasing alpha-amylase activity at increasing carbohydrate concentrations. A general kinetic model has been developed that can be used to describe and explain these phenomena. This model is based on the formation of a carbohydrate-enzyme complex that remains active. It is assumed that this complex is formed when a carbohydrate binds to alpha-amylase without blocking the catalytic site and its surrounding subsites. Furthermore, the kinetic model incorporates substrate inhibition and substrate competition. Depending on the carbohydrate type and concentration, the measured alpha-amylase activity can be 75% lower than the actual alpha-amylase activity. The model that has been developed can be used to correct for these effects in order to obtain the actual amount of active enzyme. 2006 Wiley Periodicals, Inc.

Physiological and neural correlates of worry and rumination: Support for the contrast avoidance model of worry.

PubMed

Steinfurth, Elisa C K; Alius, Manuela G; Wendt, Julia; Hamm, Alfons O

2017-02-01

The current experiments tested neural and physiological correlates of worry and rumination in comparison to thinking about neutral events. According to the avoidance model-stating that worry is a strategy to reduce intense emotions-physiological and neurobiological activity during worried thinking should not differ from activation during neutral thinking. According to the contrast avoidance model-stating that worry is a strategy to reduce abrupt shifts of emotions-activity should be increased. To test these competing models, we induced worry and neutral thinking in healthy participants using personal topics. A rumination condition was added to investigate the specificity of changes induced by the mental process. Two experiments were conducted assessing the effects on different response levels: (1) neural activation using fMRI, and (2) physiological response mobilization using startle and autonomic measures. During worry, participants showed a potentiated startle response and BOLD activity indicative of emotional network activation. These data partly support the contrast avoidance model of worry. Both mental processes showed elevated activity in a common network referred to as default network indicating self-referential activity. © 2016 Society for Psychophysiological Research.

Assessing herbivore foraging behavior with GPS collars in a semiarid grassland.

PubMed

Augustine, David J; Derner, Justin D

2013-03-15

Advances in global positioning system (GPS) technology have dramatically enhanced the ability to track and study distributions of free-ranging livestock. Understanding factors controlling the distribution of free-ranging livestock requires the ability to assess when and where they are foraging. For four years (2008-2011), we periodically collected GPS and activity sensor data together with direct observations of collared cattle grazing semiarid rangeland in eastern Colorado. From these data, we developed classification tree models that allowed us to discriminate between grazing and non-grazing activities. We evaluated: (1) which activity sensor measurements from the GPS collars were most valuable in predicting cattle foraging behavior, (2) the accuracy of binary (grazing, non-grazing) activity models vs. models with multiple activity categories (grazing, resting, traveling, mixed), and (3) the accuracy of models that are robust across years vs. models specific to a given year. A binary classification tree correctly removed 86.5% of the non-grazing locations, while correctly retaining 87.8% of the locations where the animal was grazing, for an overall misclassification rate of 12.9%. A classification tree that separated activity into four different categories yielded a greater misclassification rate of 16.0%. Distance travelled in a 5 minute interval and the proportion of the interval with the sensor indicating a head down position were the two most important variables predicting grazing activity. Fitting annual models of cattle foraging activity did not improve model accuracy compared to a single model based on all four years combined. This suggests that increased sample size was more valuable than accounting for interannual variation in foraging behavior associated with variation in forage production. Our models differ from previous assessments in semiarid rangeland of Israel and mesic pastures in the United States in terms of the value of different activity sensor measurements for identifying grazing activity, suggesting that the use of GPS collars to classify cattle grazing behavior will require calibrations specific to the environment and vegetation being studied.

Structural models for nickel electrode active mass

NASA Technical Reports Server (NTRS)

Cornilsen, Bahne C.; Karjala, P. J.; Loyselle, P. L.

1987-01-01

Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and x ray diffraction data are analyzed and shown to be consistent with this structural model.

Esterase Activity and Intracellular Localization in Reconstructed Human Epidermal Cultured Skin Models.

PubMed

Tokudome, Yoshihiro; Katayanagi, Mishina; Hashimoto, Fumie

2015-06-01

Reconstructed human epidermal culture skin models have been developed for cosmetic and pharmaceutical research. This study evaluated the total and carboxyl esterase activities (i.e., Km and Vmax , respectively) and localization in two reconstructed human epidermal culture skin models (LabCyte EPI-MODEL [Japan Tissue Engineering] and EpiDerm [MatTek/Kurabo]). The usefulness of the reconstruction cultured epidermis was also verified by comparison with human and rat epidermis. Homogenized epidermal samples were fractioned by centrifugation. p-nitrophenyl acetate and 4-methylumbelliferyl acetate were used as substrates of total esterase and carboxyl esterase, respectively. Total and carboxyl esterase activities were present in the reconstructed human epidermal culture skin models and were localized in the cytosol. Moreover, the activities and localization were the same as those in human and rat epidermis. LabCyte EPI-MODEL and EpiDerm are potentially useful for esterase activity prediction in human epidermis.

Esterase Activity and Intracellular Localization in Reconstructed Human Epidermal Cultured Skin Models

PubMed Central

Katayanagi, Mishina; Hashimoto, Fumie

2015-01-01

Background Reconstructed human epidermal culture skin models have been developed for cosmetic and pharmaceutical research. Objective This study evaluated the total and carboxyl esterase activities (i.e., Km and Vmax, respectively) and localization in two reconstructed human epidermal culture skin models (LabCyte EPI-MODEL [Japan Tissue Engineering] and EpiDerm [MatTek/Kurabo]). The usefulness of the reconstruction cultured epidermis was also verified by comparison with human and rat epidermis. Methods Homogenized epidermal samples were fractioned by centrifugation. p-nitrophenyl acetate and 4-methylumbelliferyl acetate were used as substrates of total esterase and carboxyl esterase, respectively. Results Total and carboxyl esterase activities were present in the reconstructed human epidermal culture skin models and were localized in the cytosol. Moreover, the activities and localization were the same as those in human and rat epidermis. Conclusion LabCyte EPI-MODEL and EpiDerm are potentially useful for esterase activity prediction in human epidermis. PMID:26082583

Experimental investigation of elastic mode control on a model of a transport aircraft

NASA Technical Reports Server (NTRS)

Abramovitz, M.; Heimbaugh, R. M.; Nomura, J. K.; Pearson, R. M.; Shirley, W. A.; Stringham, R. H.; Tescher, E. L.; Zoock, I. E.

1981-01-01

A 4.5 percent DC-10 derivative flexible model with active controls is fabricated, developed, and tested to investigate the ability to suppress flutter and reduce gust loads with active controlled surfaces. The model is analyzed and tested in both semispan and complete model configuration. Analytical methods are refined and control laws are developed and successfully tested on both versions of the model. A 15 to 25 percent increase in flutter speed due to the active system is demonstrated. The capability of an active control system to significantly reduce wing bending moments due to turbulence is demonstrated. Good correlation is obtained between test and analytical prediction.

Update on the Department of the Navy Systems Engineering Career Competency Model Acquisition Activities

DTIC Science & Technology

2016-04-30

Model Acquisition Activities Clifford Whitcomb, Systems Engineering Professor, NPS Corina White, Systems Engineering Research Associate, NPS...Engineering Acquisition Activities Karen Holness, Assistant Professor, NPS Update on the Department of the Navy Systems Engineering Career Competency Model ...Career Competency Model Clifford A. Whitcomb—is a Professor in the Systems Engineering Department at the Naval Postgraduate School, in Monterey, CA

An integrative review of in-class activities that enable active learning in college science classroom settings

NASA Astrophysics Data System (ADS)

Arthurs, Leilani A.; Kreager, Bailey Zo

2017-10-01

Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.

Human Activity Recognition by Combining a Small Number of Classifiers.

PubMed

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

2016-09-01

We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

Prediction of muscle activation for an eye movement with finite element modeling.

PubMed

Karami, Abbas; Eghtesad, Mohammad; Haghpanah, Seyyed Arash

2017-10-01

In this paper, a 3D finite element (FE) modeling is employed in order to predict extraocular muscles' activation and investigate force coordination in various motions of the eye orbit. A continuum constitutive hyperelastic model is employed for material description in dynamic modeling of the extraocular muscles (EOMs). Two significant features of this model are accurate mass modeling with FE method and stimulating EOMs for motion through muscle activation parameter. In order to validate the eye model, a forward dynamics simulation of the eye motion is carried out by variation of the muscle activation. Furthermore, to realize muscle activation prediction in various eye motions, two different tracking-based inverse controllers are proposed. The performance of these two inverse controllers is investigated according to their resulted muscle force magnitude and muscle force coordination. The simulation results are compared with the available experimental data and the well-known existing neurological laws. The comparison authenticates both the validation and the prediction results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bridging the gap between computation and clinical biology: validation of cable theory in humans

PubMed Central

Finlay, Malcolm C.; Xu, Lei; Taggart, Peter; Hanson, Ben; Lambiase, Pier D.

2013-01-01

Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S2 extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S3 were significantly different from those after an S2. Patient specific models demonstrated accurate prediction of the S3 activation wave, (Pearson's R2 = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R2 = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. PMID:24027527

Insights on activation enthalpy for non-Schmid slip in body-centered cubic metals

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

Hale, Lucas M.; Lim, Hojun; Zimmerman, Jonathan A.

2014-12-18

We use insights gained from atomistic simulation to develop an activation enthalpy model for dislocation slip in body-centered cubic iron. Furthermore, using a classical potential that predicts dislocation core stabilities consistent with ab initio predictions, we quantify the non-Schmid stress-dependent effects of slip. The kink-pair activation enthalpy is evaluated and a model is identified as a function of the general stress state. Thus, our model enlarges the applicability of the classic Kocks activation enthalpy model to materials with non-Schmid behavior.

Integrated Model of Chemical Perturbations of a Biological ...

EPA Pesticide Factsheets

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform (“”assay interference”). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 52 (2.8%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in v

Influence of Different Geometric Representations of the Volume Conductor on Nerve Activation during Electrical Stimulation

PubMed Central

Gómez-Tames, José; González, José; Yu, Wenwei

2014-01-01

Volume conductor models with different geometric representations, such as the parallel layer model (PM), the cylindrical layer model (CM), or the anatomically based model (AM), have been employed during the implementation of bioelectrical models for electrical stimulation (FES). Evaluating their strengths and limitations to predict nerve activation is fundamental to achieve a good trade-off between accuracy and computation time. However, there are no studies aimed at clarifying the following questions. (1) Does the nerve activation differ between CM and PM? (2) How well do CM and PM approximate an AM? (3) What is the effect of the presence of blood vessels and nerve trunk on nerve activation prediction? Therefore, in this study, we addressed these questions by comparing nerve activation between CM, PM, and AM models by FES. The activation threshold was used to evaluate the models under different configurations of superficial electrodes (size and distance), nerve depths, and stimulation sites. Additionally, the influences of the sciatic nerve, femoral artery, and femoral vein were inspected for a human thigh. The results showed that the CM and PM had a high error rate, but the variation of the activation threshold followed the same tendency for electrode size and interelectrode distance variation as AM. PMID:25276222

PLS modelling of structure—activity relationships of catechol O-methyltransferase inhibitors

NASA Astrophysics Data System (ADS)

Lotta, Timo; Taskinen, Jyrki; Bäckström, Reijo; Nissinen, Erkki

1992-06-01

Quantitative structure-activity analysis was carried out for in vitro inhibition of rat brain soluble catechol O-methyltransferase by a series (N=99) of 1,5-substituted-3,4-dihydroxybenzenes using computational chemistry and multivariate PLS modelling of data sets. The molecular structural descriptors (N=19) associated with the electronics of the catecholic ring and sizes of substituents were derived theoretically. For the whole set of molecules two separate PLS models have to be used. A PLS model with two significant (crossvalidated) model dimensions describing 82.2% of the variance in inhibition activity data was capable of predicting all molecules except those having the largest R1 substituent or having a large R5 substituent compared to the NO2 group. The other PLS model with three significant (crossvalidated) model dimensions described 83.3% of the variance in inhibition activity data. This model could not handle compounds having a small R5 substituent, compared to the NO2 group, or the largest R1 substituent. The predictive capability of these PLS models was good. The models reveal that inhibition activity is nonlinearly related to the size of the R5 substituent. The analysis of the PLS models also shows that the binding affinity is greatly dependent on the electronic nature of both R1 and R5 substituents. The electron-withdrawing nature of the substituents enhances inhibition activity. In addition, the size of the R1 substituent and its lipophilicity are important in the binding of inhibitors. The size of the R1 substituent has an upper limit. On the other hand, ionized R1 substituents decrease inhibition activity.

Antitumor activity of the investigational proteasome inhibitor MLN9708 in mouse models of B-cell and plasma cell malignancies.

PubMed

Lee, Edmund C; Fitzgerald, Michael; Bannerman, Bret; Donelan, Jill; Bano, Kristen; Terkelsen, Jennifer; Bradley, Daniel P; Subakan, Ozlem; Silva, Matthew D; Liu, Ray; Pickard, Michael; Li, Zhi; Tayber, Olga; Li, Ping; Hales, Paul; Carsillo, Mary; Neppalli, Vishala T; Berger, Allison J; Kupperman, Erik; Manfredi, Mark; Bolen, Joseph B; Van Ness, Brian; Janz, Siegfried

2011-12-01

The clinical success of the first-in-class proteasome inhibitor bortezomib (VELCADE) has validated the proteasome as a therapeutic target for treating human cancers. MLN9708 is an investigational proteasome inhibitor that, compared with bortezomib, has improved pharmacokinetics, pharmacodynamics, and antitumor activity in preclinical studies. Here, we focused on evaluating the in vivo activity of MLN2238 (the biologically active form of MLN9708) in a variety of mouse models of hematologic malignancies, including tumor xenograft models derived from a human lymphoma cell line and primary human lymphoma tissue, and genetically engineered mouse (GEM) models of plasma cell malignancies (PCM). Both cell line-derived OCI-Ly10 and primary human lymphoma-derived PHTX22L xenograft models of diffuse large B-cell lymphoma were used to evaluate the pharmacodynamics and antitumor effects of MLN2238 and bortezomib. The iMyc(Cα)/Bcl-X(L) GEM model was used to assess their effects on de novo PCM and overall survival. The newly developed DP54-Luc-disseminated model of iMyc(Cα)/Bcl-X(L) was used to determine antitumor activity and effects on osteolytic bone disease. MLN2238 has an improved pharmacodynamic profile and antitumor activity compared with bortezomib in both OCI-Ly10 and PHTX22L models. Although both MLN2238 and bortezomib prolonged overall survival, reduced splenomegaly, and attenuated IgG2a levels in the iMyc(Cα)/Bcl-X(L) GEM model, only MLN2238 alleviated osteolytic bone disease in the DP54-Luc model. Our results clearly showed the antitumor activity of MLN2238 in a variety of mouse models of B-cell lymphoma and PCM, supporting its clinical development. MLN9708 is being evaluated in multiple phase I and I/II trials. ©2011 AACR.

Temporal self-regulation theory: a neurobiologically informed model for physical activity behavior

PubMed Central

Hall, Peter A.; Fong, Geoffrey T.

2015-01-01

Dominant explanatory models for physical activity behavior are limited by the exclusion of several important components, including temporal dynamics, ecological forces, and neurobiological factors. The latter may be a critical omission, given the relevance of several aspects of cognitive function for the self-regulatory processes that are likely required for consistent implementation of physical activity behavior in everyday life. This narrative review introduces temporal self-regulation theory (TST; Hall and Fong, 2007, 2013) as a new explanatory model for physical activity behavior. Important features of the model include consideration of the default status of the physical activity behavior, as well as the disproportionate influence of temporally proximal behavioral contingencies. Most importantly, the TST model proposes positive feedback loops linking executive function (EF) and the performance of physical activity behavior. Specifically, those with relatively stronger executive control (and optimized brain structures supporting it, such as the dorsolateral prefrontal cortex (PFC)) are able to implement physical activity with more consistency than others, which in turn serves to strengthen the executive control network itself. The TST model has the potential to explain everyday variants of incidental physical activity, sport-related excellence via capacity for deliberate practice, and variability in the propensity to schedule and implement exercise routines. PMID:25859196

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity

NASA Astrophysics Data System (ADS)

Sadilek, Maximilian; Thurner, Stefan

2015-05-01

We derive a two-layer multiplex Kuramoto model from Wilson-Cowan type physiological equations that describe neural activity on a network of interconnected cortical regions. This is mathematically possible due to the existence of a unique, stable limit cycle, weak coupling, and inhibitory synaptic time delays. We study the phase diagram of this model numerically as a function of the inter-regional connection strength that is related to cerebral blood flow, and a phase shift parameter that is associated with synaptic GABA concentrations. We find three macroscopic phases of cortical activity: background activity (unsynchronized oscillations), epileptiform activity (highly synchronized oscillations) and resting-state activity (synchronized clusters/chaotic behaviour). Previous network models could hitherto not explain the existence of all three phases. We further observe a shift of the average oscillation frequency towards lower values together with the appearance of coherent slow oscillations at the transition from resting-state to epileptiform activity. This observation is fully in line with experimental data and could explain the influence of GABAergic drugs both on gamma oscillations and epileptic states. Compared to previous models for gamma oscillations and resting-state activity, the multiplex Kuramoto model not only provides a unifying framework, but also has a direct connection to measurable physiological parameters.

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity.

PubMed

Sadilek, Maximilian; Thurner, Stefan

2015-05-21

We derive a two-layer multiplex Kuramoto model from Wilson-Cowan type physiological equations that describe neural activity on a network of interconnected cortical regions. This is mathematically possible due to the existence of a unique, stable limit cycle, weak coupling, and inhibitory synaptic time delays. We study the phase diagram of this model numerically as a function of the inter-regional connection strength that is related to cerebral blood flow, and a phase shift parameter that is associated with synaptic GABA concentrations. We find three macroscopic phases of cortical activity: background activity (unsynchronized oscillations), epileptiform activity (highly synchronized oscillations) and resting-state activity (synchronized clusters/chaotic behaviour). Previous network models could hitherto not explain the existence of all three phases. We further observe a shift of the average oscillation frequency towards lower values together with the appearance of coherent slow oscillations at the transition from resting-state to epileptiform activity. This observation is fully in line with experimental data and could explain the influence of GABAergic drugs both on gamma oscillations and epileptic states. Compared to previous models for gamma oscillations and resting-state activity, the multiplex Kuramoto model not only provides a unifying framework, but also has a direct connection to measurable physiological parameters.

An Empirical Comparison of Different Models of Active Aging in Canada: The International Mobility in Aging Study.

PubMed

Bélanger, Emmanuelle; Ahmed, Tamer; Filiatrault, Johanne; Yu, Hsiu-Ting; Zunzunegui, Maria Victoria

2017-04-01

Active aging is a concept that lacks consensus. The WHO defines it as a holistic concept that encompasses the overall health, participation, and security of older adults. Fernández-Ballesteros and colleagues propose a similar concept but omit security and include mood and cognitive function. To date, researchers attempting to validate conceptual models of active aging have obtained mixed results. The goal of this study was to examine the validity of existing models of active aging with epidemiological data from Canada. The WHO model of active aging and the psychological model of active aging developed by Fernández-Ballesteros and colleagues were tested with confirmatory factor analysis. The data used included 799 community-dwelling older adults between 65 and 74 years old, recruited from the patient lists of family physicians in Saint-Hyacinthe, Quebec and Kingston, Ontario. Neither model could be validated in the sample of Canadian older adults. Although a concept of healthy aging can be modeled adequately, social participation and security did not fit a latent factor model. A simple binary index indicated that 27% of older adults in the sample did not meet the active aging criteria proposed by the WHO. Our results suggest that active aging might represent a human rights policy orientation rather than an empirical measurement tool to guide research among older adult populations. Binary indexes of active aging may serve to highlight what remains to be improved about the health, participation, and security of growing populations of older adults. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluating a Model of Youth Physical Activity

ERIC Educational Resources Information Center

Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary

2010-01-01

Objective: To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods: Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a…

Modeling the History of Astronomy: Ptolemy, Copernicus, and Tycho

NASA Astrophysics Data System (ADS)

Timberlake, Todd K.

This paper describes a series of activities in which students investigate and use the Ptolemaic, Copernican, and Tychonic models of planetary motion. The activities guide students through using open source software to discover important observational facts, learn the necessary vocabulary, understand the fundamental properties of different theoretical models, and relate the theoretical models to observational data. After completing these activities students can make observations of a fictitious solar system and use those observations to construct models for that system.

Does active ageing contribute to life satisfaction for older people? Testing a new model of active ageing.

PubMed

Marsillas, Sara; De Donder, Liesbeth; Kardol, Tinie; van Regenmortel, Sofie; Dury, Sarah; Brosens, Dorien; Smetcoren, An-Sofie; Braña, Teresa; Varela, Jesús

2017-09-01

Several debates have emerged across the literature about the conceptualisation of active ageing. The aim of this study is to develop a model of the construct that is focused on the individual, including different elements of people's lives that have the potential to be modified by intervention programs. Moreover, the paper examines the contributions of active ageing to life satisfaction, as well as the possible predictive role of coping styles on active ageing. For this purpose, a representative sample of 404 Galician (Spain) community-dwelling older adults (aged ≥60 years) were interviewed using a structured survey. The results demonstrate that the proposed model composed of two broad categories is valid. The model comprises status variables (related to physical, psychological, and social health) as well as different types of activities, called processual variables. This model is tested using partial least squares (PLS) regression. The findings show that active ageing is a fourth-order, formative construct. In addition, PLS analyses indicate that active ageing has a moderate and positive path on life satisfaction and that coping styles may predict active ageing. The discussion highlights the potential of active ageing as a relevant concept for people's lives, drawing out policy implications and suggestions for further research.

Material and physical model for evaluation of deep brain activity contribution to EEG recordings

NASA Astrophysics Data System (ADS)

Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

2015-12-01

Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.

USE OF TRANS-CONTEXTUAL MODEL-BASED PHYSICAL ACTIVITY COURSE IN DEVELOPING LEISURE-TIME PHYSICAL ACTIVITY BEHAVIOR OF UNIVERSITY STUDENTS.

PubMed

Müftüler, Mine; İnce, Mustafa Levent

2015-08-01

This study examined how a physical activity course based on the Trans-Contextual Model affected the variables of perceived autonomy support, autonomous motivation, determinants of leisure-time physical activity behavior, basic psychological needs satisfaction, and leisure-time physical activity behaviors. The participants were 70 Turkish university students (M age=23.3 yr., SD=3.2). A pre-test-post-test control group design was constructed. Initially, the participants were randomly assigned into an experimental (n=35) and a control (n=35) group. The experimental group followed a 12 wk. trans-contextual model-based intervention. The participants were pre- and post-tested in terms of Trans-Contextual Model constructs and of self-reported leisure-time physical activity behaviors. Multivariate analyses showed significant increases over the 12 wk. period for perceived autonomy support from instructor and peers, autonomous motivation in leisure-time physical activity setting, positive intention and perceived behavioral control over leisure-time physical activity behavior, more fulfillment of psychological needs, and more engagement in leisure-time physical activity behavior in the experimental group. These results indicated that the intervention was effective in developing leisure-time physical activity and indicated that the Trans-Contextual Model is a useful way to conceptualize these relationships.

Developing an active implementation model for a chronic disease management program.

PubMed

Smidth, Margrethe; Christensen, Morten Bondo; Olesen, Frede; Vedsted, Peter

2013-04-01

Introduction and diffusion of new disease management programs in healthcare is usually slow, but active theory-driven implementation seems to outperform other implementation strategies. However, we have only scarce evidence on the feasibility and real effect of such strategies in complex primary care settings where municipalities, general practitioners and hospitals should work together. The Central Denmark Region recently implemented a disease management program for chronic obstructive pulmonary disease (COPD) which presented an opportunity to test an active implementation model against the usual implementation model. The aim of the present paper is to describe the development of an active implementation model using the Medical Research Council's model for complex interventions and the Chronic Care Model. We used the Medical Research Council's five-stage model for developing complex interventions to design an implementation model for a disease management program for COPD. First, literature on implementing change in general practice was scrutinised and empirical knowledge was assessed for suitability. In phase I, the intervention was developed; and in phases II and III, it was tested in a block- and cluster-randomised study. In phase IV, we evaluated the feasibility for others to use our active implementation model. The Chronic Care Model was identified as a model for designing efficient implementation elements. These elements were combined into a multifaceted intervention, and a timeline for the trial in a randomised study was decided upon in accordance with the five stages in the Medical Research Council's model; this was captured in a PaTPlot, which allowed us to focus on the structure and the timing of the intervention. The implementation strategies identified as efficient were use of the Breakthrough Series, academic detailing, provision of patient material and meetings between providers. The active implementation model was tested in a randomised trial (results reported elsewhere). The combination of the theoretical model for complex interventions and the Chronic Care Model and the chosen specific implementation strategies proved feasible for a practice-based active implementation model for a chronic-disease-management-program for COPD. Using the Medical Research Council's model added transparency to the design phase which further facilitated the process of implementing the program. http://www.clinicaltrials.gov/(NCT01228708).

CFD Modeling Activities at the NASA Stennis Space Center

NASA Technical Reports Server (NTRS)

Allgood, Daniel

2007-01-01

A viewgraph presentation on NASA Stennis Space Center's Computational Fluid Dynamics (CFD) Modeling activities is shown. The topics include: 1) Overview of NASA Stennis Space Center; 2) Role of Computational Modeling at NASA-SSC; 3) Computational Modeling Tools and Resources; and 4) CFD Modeling Applications.

Spontaneous appetence for wheel-running: a model of dependency on physical activity in rat.

PubMed

Ferreira, Anthony; Lamarque, Stéphanie; Boyer, Patrice; Perez-Diaz, Fernando; Jouvent, Roland; Cohen-Salmon, Charles

2006-12-01

According to human observations of a syndrome of physical activity dependence and its consequences, we tried to examine if running activity in a free activity paradigm, where rats had a free access to activity wheel, may present a valuable animal model for physical activity dependence and most generally to behavioral dependence. The pertinence of reactivity to novelty, a well-known pharmacological dependence predictor was also tested. Given the close linkage observed in human between physical activity and drugs use and abuse, the influence of free activity in activity wheels on reactivity to amphetamine injection and reactivity to novelty were also assessed. It appeared that (1) free access to wheel may be used as a valuable model for physical activity addiction, (2) two populations differing in activity amount also differed in dependence to wheel-running. (3) Reactivity to novelty did not appeared as a predictive factor for physical activity dependence (4) activity modified novelty reactivity and (5) subjects who exhibited a high appetence to wheel-running, presented a strong reactivity to amphetamine. These results propose a model of dependency on physical activity without any pharmacological intervention, and demonstrate the existence of individual differences in the development of this addiction. In addition, these data highlight the development of a likely vulnerability to pharmacological addiction after intense and sustained physical activity, as also described in man. This model could therefore prove pertinent for studying behavioral dependencies and the underlying neurobiological mechanisms. These results may influence the way psychiatrists view behavioral dependencies and phenomena such as doping in sport or addiction to sport itself.

Application of the Human Activity Assistive Technology model for occupational therapy research.

PubMed

Giesbrecht, Ed

2013-08-01

Theoretical models provide a framework for describing practice and integrating evidence into systematic research. There are few models that relate specifically to the provision of assistive technology in occupational therapy practice. The Human Activity Assistive Technology model is an enduring example that has continued to develop by integrating a social model of disability, concepts from occupational therapy theory and principles of assistive technology adoption and abandonment. This study first describes the core concepts of the Human Activity Assistive Technology model and reviews its development over three successive published versions. A review of the research literature reflects application of the model to clinical practice, study design, outcome measure selection and interpretation of results, particularly among occupational therapists. An evaluative framework is used to critique the adequacy of the Human Activity Assistive Technology model for practice and research, exploring attributes of clarity, simplicity, generality, accessibility and importance. Finally, recommendations are proposed for continued development of the model and research applications. Most of the existing research literature employs the Human Activity Assistive Technology model for background and study design; there is emerging evidence to support the core concepts as predictive factors. Although the concepts are generally simple, clear and applicable to occupational therapy practice and research, evolving terminology and outcomes become more complex with the conflation of integrated theories. The development of the Human Activity Assistive Technology model offers enhanced access and application for occupational therapists, but poses challenges to clarity among concepts. Suggestions are made for further development and applications of the model. © 2013 Occupational Therapy Australia.

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.

Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism Phenotypes

DTIC Science & Technology

2014-09-01

AD_________________ Award Number: TITLE: Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...AUG 2013-7 Aug 2014 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...a genetic mouse model of autism -like phenotypes, the Grin1 knockdown mouse. The Grin1 gene encodes the NR1 subunit of the NMDA receptor . In the

Investigation on Quantitative Structure Activity Relationships and Pharmacophore Modeling of a Series of mGluR2 Antagonists

PubMed Central

Zhang, Meng-Qi; Zhang, Xiao-Le; Li, Yan; Fan, Wen-Jia; Wang, Yong-Hua; Hao, Ming; Zhang, Shu-Wei; Ai, Chun-Zhi

2011-01-01

MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson’s disease and schizophrenia. Herein, we report the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [3H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q2 of 0.513, R2 ncv of 0.868, R2 pred = 0.876, while the CoMSIA model yielded a Q2 of 0.450, R2 ncv = 0.899, R2 pred = 0.735. For activity II study, CoMFA model yielded statistics of Q2 = 0.5, R2 ncv = 0.715, R2 pred = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R7, R3 and position A benefit activity I of the antagonists, but decrease it when projected in R8 and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3D-QSAR modeling of these mGluR2 antagonists. All the conclusions may lead to a better understanding of the mechanism of antagonism and be helpful in the design of new potent mGluR2 antagonists. PMID:22016641

Investigation on quantitative structure activity relationships and pharmacophore modeling of a series of mGluR2 antagonists.

PubMed

Zhang, Meng-Qi; Zhang, Xiao-Le; Li, Yan; Fan, Wen-Jia; Wang, Yong-Hua; Hao, Ming; Zhang, Shu-Wei; Ai, Chun-Zhi

2011-01-01

MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson's disease and schizophrenia. Herein, we report the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [(3)H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q(2) of 0.513, R(2) (ncv) of 0.868, R(2) (pred) = 0.876, while the CoMSIA model yielded a Q(2) of 0.450, R(2) (ncv) = 0.899, R(2) (pred) = 0.735. For activity II study, CoMFA model yielded statistics of Q(2) = 0.5, R(2) (ncv) = 0.715, R(2) (pred) = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R(7), R(3) and position A benefit activity I of the antagonists, but decrease it when projected in R(8) and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3D-QSAR modeling of these mGluR2 antagonists. All the conclusions may lead to a better understanding of the mechanism of antagonism and be helpful in the design of new potent mGluR2 antagonists.

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.

How High Is It? An Educator's Guide with Activities Focused on Scale Models of Distances.

ERIC Educational Resources Information Center

Rosenberg, Carla B.; Rogers, Melissa J. B.

This guide focuses on scale models of distances. Activities also incorporate mathematics but can be used in science and technology grades 5-8 classes. The content of the book is divided into three sections: (1) Introductory Activities; (2) Core Activities; and (3) Activity/Assessment. Activities include: (1) KWL Chart; (2) Ball and String…

Modeling Interval Temporal Dependencies for Complex Activities Understanding

DTIC Science & Technology

2013-10-11

ORGANIZATION NAMES AND ADDRESSES U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Human activity modeling...computer vision applications: human activity recognition and facial activity recognition. The results demonstrate the superior performance of the

The Role of Various Curriculum Models on Physical Activity Levels

ERIC Educational Resources Information Center

Culpepper, Dean O.; Tarr, Susan J.; Killion, Lorraine E.

2011-01-01

Researchers have suggested that physical education curricula can be highly effective in increasing physical activity levels at school (Sallis & Owen, 1999). The purpose of this study was to investigate the impact of various curriculum models on physical activity. Total steps were measured on 1,111 subjects and three curriculum models were studied…

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...

Clarifications regarding the use of model-fitting methods of kinetic analysis for determining the activation energy from a single non-isothermal curve.

PubMed

Sánchez-Jiménez, Pedro E; Pérez-Maqueda, Luis A; Perejón, Antonio; Criado, José M

2013-02-05

This paper provides some clarifications regarding the use of model-fitting methods of kinetic analysis for estimating the activation energy of a process, in response to some results recently published in Chemistry Central journal. The model fitting methods of Arrhenius and Savata are used to determine the activation energy of a single simulated curve. It is shown that most kinetic models correctly fit the data, each providing a different value for the activation energy. Therefore it is not really possible to determine the correct activation energy from a single non-isothermal curve. On the other hand, when a set of curves are recorded under different heating schedules are used, the correct kinetic parameters can be clearly discerned. Here, it is shown that the activation energy and the kinetic model cannot be unambiguously determined from a single experimental curve recorded under non isothermal conditions. Thus, the use of a set of curves recorded under different heating schedules is mandatory if model-fitting methods are employed.

Quercetin protects against inflammation, MMP‑2 activation and apoptosis induction in rat model of cardiopulmonary resuscitation through modulating Bmi‑1 expression.

PubMed

Wang, Dawei; Lou, Xiaoqian; Jiang, Xiao-Ming; Yang, Chenxi; Liu, Xiao-Liang; Zhang, Nan

2018-05-08

With extensive pharmacological actions, quercetin has anti‑oxidant, free radical scavenging, anti‑tumor, anti‑inflammatory, anti‑bacterial and anti‑viral activity. Quercetin also reduces blood glucose and reduces high blood pressure, and has immunoregulation and cardiovascular protection functions. Additionally, it has been reported that it can reduce depression. The current study evaluated whether quercetin protects against inflammation, matrix metalloproteinase‑2 (MMP‑2) activation and apoptosis induction in a rat model of cardiopulmonary resuscitation (CPR), and whether Bmi‑1 expression was involved in the effects. In CPR model rats, treatment with quercetin significantly recovered left ventricular ejection fraction, left ventricular fractional shortening, ejection fraction (%), and left ventricle weight/body weight. Treatment with quercetin significantly inhibited ROS generation, inflammation and MMP‑2 protein expression in the rat model CPR. Finally, quercetin significantly suppressed caspase‑3 activity and activated Bmi‑1 protein expression in the rat model of CPR. The results demonstrated that quercetin protects against inflammation, MMP‑2 activation and apoptosis induction in a rat model of CPR, and that this may be mediated by modulating Bmi‑1 expression.

Modeling vocalization with ECoG cortical activity recorded during vocal production in the macaque monkey.

PubMed

Fukushima, Makoto; Saunders, Richard C; Fujii, Naotaka; Averbeck, Bruno B; Mishkin, Mortimer

2014-01-01

Vocal production is an example of controlled motor behavior with high temporal precision. Previous studies have decoded auditory evoked cortical activity while monkeys listened to vocalization sounds. On the other hand, there have been few attempts at decoding motor cortical activity during vocal production. Here we recorded cortical activity during vocal production in the macaque with a chronically implanted electrocorticographic (ECoG) electrode array. The array detected robust activity in motor cortex during vocal production. We used a nonlinear dynamical model of the vocal organ to reduce the dimensionality of `Coo' calls produced by the monkey. We then used linear regression to evaluate the information in motor cortical activity for this reduced representation of calls. This simple linear model accounted for circa 65% of the variance in the reduced sound representations, supporting the feasibility of using the dynamical model of the vocal organ for decoding motor cortical activity during vocal production.

3D-quantitative structure-activity relationship study for the design of novel enterovirus A71 3C protease inhibitors.

PubMed

Nie, Quandeng; Xu, Xiaoyi; Zhang, Qi; Ma, Yuying; Yin, Zheng; Shang, Luqing

2018-06-07

A three-dimensional quantitative structure-activity relationships model of enterovirus A71 3C protease inhibitors was constructed in this study. The protein-ligand interaction fingerprint was analyzed to generate a pharmacophore model. A predictive and reliable three-dimensional quantitative structure-activity relationships model was built based on the Flexible Alignment of AutoGPA. Moreover, three novel compounds (I-III) were designed and evaluated for their biochemical activity against 3C protease and anti-enterovirus A71 activity in vitro. III exhibited excellent inhibitory activity (IC 50 =0.031 ± 0.005 μM, EC 50 =0.036 ± 0.007 μM). Thus, this study provides a useful quantitative structure-activity relationships model to develop potent inhibitors for enterovirus A71 3C protease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

[Students' physical activity: an analysis according to Pender's health promotion model].

PubMed

Guedes, Nirla Gomes; Moreira, Rafaella Pessoa; Cavalcante, Tahissa Frota; de Araujo, Thelma Leite; Ximenes, Lorena Barbosa

2009-12-01

The objective of this study was to describe the everyday physical activity habits of students and analyze the practice of physical activity and its determinants, based on the first component of Pender's health promotion model. This cross-sectional study was performed from 2004 to 2005 with 79 students in a public school in Fortaleza, Ceará, Brazil. Data collection was performed by interviews and physical examinations. The data were analyzed according to the referred theoretical model. Most students (n=60) were physically active. Proportionally, adolescents were the most active (80.4%). Those with a sedentary lifestyle had higher rates for overweight and obesity (21.1%). Many students practiced outdoor physical activities, which did not require any physical structure and good financial conditions. The results show that it is possible to associate the first component of Pender's health promotion model with the everyday lives of students in terms of the physical activity practice.

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.

Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

PubMed

Weidlich, Iwona E; Pevzner, Yuri; Miller, Benjamin T; Filippov, Igor V; Woodcock, H Lee; Brooks, Bernard R

2015-01-05

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.

Advanced Performance Modeling with Combined Passive and Active Monitoring

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

Dovrolis, Constantine; Sim, Alex

2015-04-15

To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performancemore » information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.« less

Draft Forecasts from Real-Time Runs of Physics-Based Models - A Road to the Future

NASA Technical Reports Server (NTRS)

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

2008-01-01

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. After consultations with NOAA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Using multiple linear regression model to estimate thunderstorm activity

NASA Astrophysics Data System (ADS)

Suparta, W.; Putro, W. S.

2017-03-01

This paper is aimed to develop a numerical model with the use of a nonlinear model to estimate the thunderstorm activity. Meteorological data such as Pressure (P), Temperature (T), Relative Humidity (H), cloud (C), Precipitable Water Vapor (PWV), and precipitation on a daily basis were used in the proposed method. The model was constructed with six configurations of input and one target output. The output tested in this work is the thunderstorm event when one-year data is used. Results showed that the model works well in estimating thunderstorm activities with the maximum epoch reaching 1000 iterations and the percent error was found below 50%. The model also found that the thunderstorm activities in May and October are detected higher than the other months due to the inter-monsoon season.

Objectively-Measured Physical Activity and Cognitive Functioning in Breast Cancer Survivors

PubMed Central

Marinac, Catherine R.; Godbole, Suneeta; Kerr, Jacqueline; Natarajan, Loki; Patterson, Ruth E.; Hartman, Sheri J.

2015-01-01

Purpose To explore the relationship between objectively measured physical activity and cognitive functioning in breast cancer survivors. Methods Participants were 136 postmenopausal breast cancer survivors. Cognitive functioning was assessed using a comprehensive computerized neuropsychological test. 7-day physical activity was assessed using hip-worn accelerometers. Linear regression models examined associations of minutes per day of physical activity at various intensities on individual cognitive functioning domains. The partially adjusted model controlled for primary confounders (model 1), and subsequent adjustments were made for chemotherapy history (model 2), and BMI (model 3). Interaction and stratified models examined BMI as an effect modifier. Results Moderate-to-vigorous physical activity (MVPA) was associated with Information Processing Speed. Specifically, ten minutes of MVPA was associated with a 1.35-point higher score (out of 100) on the Information Processing Speed domain in the partially adjusted model, and a 1.29-point higher score when chemotherapy was added to the model (both p<.05). There was a significant BMI x MVPA interaction (p=.051). In models stratified by BMI (<25 vs. ≥25 kg/m2), the favorable association between MVPA and Information Processing Speed was stronger in the subsample of overweight and obese women (p<.05), but not statistically significant in the leaner subsample. Light-intensity physical activity was not significantly associated with any of the measured domains of cognitive function. Conclusions MVPA may have favorable effects on Information Processing Speed in breast cancer survivors, particularly among overweight or obese women. Implications for Cancer Survivors Interventions targeting increased physical activity may enhance aspects of cognitive function among breast cancer survivors. PMID:25304986

Measurement of Function Post Hip Fracture: Testing a Comprehensive Measurement Model of Physical Function

PubMed Central

Gruber-Baldini, Ann L.; Hicks, Gregory; Ostir, Glen; Klinedinst, N. Jennifer; Orwig, Denise; Magaziner, Jay

2015-01-01

Background Measurement of physical function post hip fracture has been conceptualized using multiple different measures. Purpose This study tested a comprehensive measurement model of physical function. Design This was a descriptive secondary data analysis including 168 men and 171 women post hip fracture. Methods Using structural equation modeling, a measurement model of physical function which included grip strength, activities of daily living, instrumental activities of daily living and performance was tested for fit at 2 and 12 months post hip fracture and among male and female participants and validity of the measurement model of physical function was evaluated based on how well the model explained physical activity, exercise and social activities post hip fracture. Findings The measurement model of physical function fit the data. The amount of variance the model or individual factors of the model explained varied depending on the activity. Conclusion Decisions about the ideal way in which to measure physical function should be based on outcomes considered and participant Clinical Implications The measurement model of physical function is a reliable and valid method to comprehensively measure physical function across the hip fracture recovery trajectory. Practical but useful assessment of function should be considered and monitored over the recovery trajectory post hip fracture. PMID:26492866

Mechanical perturbation control of cardiac alternans

NASA Astrophysics Data System (ADS)

Hazim, Azzam; Belhamadia, Youssef; Dubljevic, Stevan

2018-05-01

Cardiac alternans is a disturbance in heart rhythm that is linked to the onset of lethal cardiac arrhythmias. Mechanical perturbation control has been recently used to suppress alternans in cardiac tissue of relevant size. In this control strategy, cardiac tissue mechanics are perturbed via active tension generated by the heart's electrical activity, which alters the tissue's electric wave profile through mechanoelectric coupling. We analyze the effects of mechanical perturbation on the dynamics of a map model that couples the membrane voltage and active tension systems at the cellular level. Therefore, a two-dimensional iterative map of the heart beat-to-beat dynamics is introduced, and a stability analysis of the system of coupled maps is performed in the presence of a mechanical perturbation algorithm. To this end, a bidirectional coupling between the membrane voltage and active tension systems in a single cardiac cell is provided, and a discrete form of the proposed control algorithm, that can be incorporated in the coupled maps, is derived. In addition, a realistic electromechanical model of cardiac tissue is employed to explore the feasibility of suppressing alternans at cellular and tissue levels. Electrical activity is represented in two detailed ionic models, the Luo-Rudy 1 and the Fox models, while two active contractile tension models, namely a smooth variant of the Nash-Panfilov model and the Niederer-Hunter-Smith model, are used to represent mechanical activity in the heart. The Mooney-Rivlin passive elasticity model is employed to describe passive mechanical behavior of the myocardium.

Shaping Neuronal Network Activity by Presynaptic Mechanisms

PubMed Central

Ashery, Uri

2015-01-01

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048

Optimal treatment interruptions control of TB transmission model

NASA Astrophysics Data System (ADS)

Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.

2018-03-01

A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.

Brain regions engaged by part- and whole-task performance in a video game: a model-based test of the decomposition hypothesis.

PubMed

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Anderson, Abraham R; Poole, Ben; Qin, Yulin

2011-12-01

Part- and whole-task conditions were created by manipulating the presence of certain components of the Space Fortress video game. A cognitive model was created for two-part games that could be combined into a model that performed the whole game. The model generated predictions both for behavioral patterns and activation patterns in various brain regions. The activation predictions concerned both tonic activation that was constant in these regions during performance of the game and phasic activation that occurred when there was resource competition. The model's predictions were confirmed about how tonic and phasic activation in different regions would vary with condition. These results support the Decomposition Hypothesis that the execution of a complex task can be decomposed into a set of information-processing components and that these components combine unchanged in different task conditions. In addition, individual differences in learning gains were predicted by individual differences in phasic activation in those regions that displayed highest tonic activity. This individual difference pattern suggests that the rate of learning of a complex skill is determined by capacity limits.

Anti-diarrhoea and analgesic activities of the methanol extract and its fractions of Jasminum amplexicaule Buch.-Ham. (Oleaceae).

PubMed

Jia, Qiang; Su, Weiwei; Peng, Wei; Li, Peibo; Wang, Yonggang

2008-09-26

Jasminum amplexicaule Buch.-Ham. (Oleaceae) has been commonly used in the traditional medicine in dysentery, diarrhoea and bellyache in China. In the present work, the methanol extract of Jasminum amplexicaule and different fractions of this extract were studied for anti-diarrhoea and analgesic activities. The anti-diarrhoea activities were investigated using castor oil-induced, magnesium sulphate-induced diarrhoea models, antienteropooling assay and gastrointestinal motility models in mice. The analgesic activities were studied using hot-plate, writhing and formalin models in mice. At the doses of 100, 200 and 400mg/kg, the methanol extract (ME) showed significant and dose-dependent anti-diarrhoea and analgesic activity in these models. The chloroform fraction (CHF), ethyl acetate fraction (EAF) and the residual methanol fraction (RMF) exhibited similar activity using a dose of 200mg/kg in these models. The pharmacological activities of the n-butanol fraction (BUF) were lesser than the ME extract and other fractions. These results may support the fact that this plant is traditionally used to cure diarrhoea and pain.

ANALYSIS OF HUMAN ACTIVITY DATA FOR USE IN MODELING ENVIRONMENTAL EXPOSURES

EPA Science Inventory

Human activity data are a critical part of exposure models being developed by the US EPA's National Exposure Research Laboratory (NERL). An analysis of human activity data within NERL's Consolidated Human Activity Database (CHAD) was performed in two areas relevant to exposure ...

Capturing well-being in activity pattern models within activity-based travel demand models.

DOT National Transportation Integrated Search

2013-03-01

The activity-based approach which is based on the premise that the demand for travel is derived : from the demand for activities, currently constitutes the state of the art in metropolitan travel : demand forecasting and particularly in a form known ...

Capturing well-being in activity pattern models within activity-based travel demand models.

DOT National Transportation Integrated Search

2013-04-01

The activity-based approach which is based on the premise that the demand for travel is derived : from the demand for activities, currently constitutes the state of the art in metropolitan travel : demand forecasting and particularly in a form known ...

Modeling the Gratification-Seeking Process of Television Viewing.

ERIC Educational Resources Information Center

Lin, Carolyn A.

1993-01-01

Examines adolescents' television viewing motives, activities, and satisfaction, in an attempt to integrate the audience activity construct into the uses and gratifications model. Suggests that more strongly motivated viewers engage more actively in various audience activities throughout the viewing process and receive greater viewing satisfaction…

Development of community based model of Tawanchai Center: sufficiency economy principles for community Development an applicability at Bankhambong Community, Sa-ard Sub-district, Nampong District, Khon Kaen Province, Thailand.

PubMed

Kotrmaneetaweetong, Unchana; Choopen, Hhakuan; Chowchuen, Bowornsilp

2012-11-01

The objectives of the present study are 1) to study the application of sufficiency economy philosophy in community development as a model for future application of community health care program of Tawanchai Center, 2) study the administrative model for self sufficiency economy community in Bankhambong Community, Sa-ard Sub-district, Nampong District, Khon Kaen Province. The integrated study model included qualitative research by collecting data from documents, textbook, article, report, theory concept, researches and interviewing of relevant persons and the quantitative research by collecting data from questionnaires. The findings of study included objectives for development model of sufficiency economy for understanding of people, and use the philosophy of sufficiency economy model which compose of decrease expenditure, increase income activities, saving activities, learning activities and preservation of environment and sustainable natural resources activities. Decrease in expenditure activities included household gardening, and no allurements leading to ruin. Increase in income activities included supplement occupation and appropriate use of technology. Saving activities included creating saving group in household and community level. Learning activities included community use of local wisdom, and household learnt philosophy of sufficiency economy in daily living. Preservation of environment and sustainable natural resources activities included the use of sustainable raw materials in occupation. The generosity of one another activities included helping each other and solving problems for the poor and disable persons. The community development at in Bankhambong Community, Sa-ard Sub-district, Nampong District, Khon Kaen Province followed all of the above scope and guidelines and is the model for application of sufficiency community philosophy. We recommended method for successful implementation, including the starting from group process with capability of learning to create strong and adequate knowledge to apply sufficiency economy model and cover health care.

Developing a Degree-Day Model to Predict Billbug (Coleoptera: Curculionidae) Seasonal Activity in Utah and Idaho Turfgrass.

PubMed

Dupuy, Madeleine M; Powell, James A; Ramirez, Ricardo A

2017-10-01

Billbugs are native pests of turfgrass throughout North America, primarily managed with preventive, calendar-based insecticide applications. An existing degree-day model (lower development threshold of 10°C, biofix 1 March) developed in the eastern United States for bluegrass billbug, Sphenophorus parvulus (Gyllenhal; Coleoptera: Curculionidae), may not accurately predict adult billbug activity in the western United States, where billbugs occur as a species complex. The objectives of this study were 1) to track billbug phenology and species composition in managed Utah and Idaho turfgrass and 2) to evaluate model parameters that best predict billbug activity, including those of the existing bluegrass billbug model. Tracking billbugs with linear pitfall traps at two sites each in Utah and Idaho, we confirmed a complex of three univoltine species damaging turfgrass consisting of (in descending order of abundance) bluegrass billbug, hunting billbug (Sphenophorus venatus vestitus Chittenden; Coleoptera: Curculionidae), and Rocky Mountain billbug (Sphenophorus cicatristriatus Fabraeus; Coleoptera: Curculionidae). This complex was active from February through mid-October, with peak activity in mid-June. Based on linear regression analysis, we found that the existing bluegrass billbug model was not robust in predicting billbug activity in Utah and Idaho. Instead, the model that best predicts adult activity of the billbug complex accumulates degree-days above 3°C after 13 January. This model predicts adult activity levels important for management within 11 d of observed activity at 77% of sites. In conjunction with outreach and cooperative networking, this predictive degree-day model may assist end users to better time monitoring efforts and insecticide applications against billbug pests in Utah and Idaho by predicting adult activity. © The Author 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Interactive activation and mutual constraint satisfaction in perception and cognition.

PubMed

McClelland, James L; Mirman, Daniel; Bolger, Donald J; Khaitan, Pranav

2014-08-01

In a seminal 1977 article, Rumelhart argued that perception required the simultaneous use of multiple sources of information, allowing perceivers to optimally interpret sensory information at many levels of representation in real time as information arrives. Building on Rumelhart's arguments, we present the Interactive Activation hypothesis-the idea that the mechanism used in perception and comprehension to achieve these feats exploits an interactive activation process implemented through the bidirectional propagation of activation among simple processing units. We then examine the interactive activation model of letter and word perception and the TRACE model of speech perception, as early attempts to explore this hypothesis, and review the experimental evidence relevant to their assumptions and predictions. We consider how well these models address the computational challenge posed by the problem of perception, and we consider how consistent they are with evidence from behavioral experiments. We examine empirical and theoretical controversies surrounding the idea of interactive processing, including a controversy that swirls around the relationship between interactive computation and optimal Bayesian inference. Some of the implementation details of early versions of interactive activation models caused deviation from optimality and from aspects of human performance data. More recent versions of these models, however, overcome these deficiencies. Among these is a model called the multinomial interactive activation model, which explicitly links interactive activation and Bayesian computations. We also review evidence from neurophysiological and neuroimaging studies supporting the view that interactive processing is a characteristic of the perceptual processing machinery in the brain. In sum, we argue that a computational analysis, as well as behavioral and neuroscience evidence, all support the Interactive Activation hypothesis. The evidence suggests that contemporary versions of models based on the idea of interactive activation continue to provide a basis for efforts to achieve a fuller understanding of the process of perception. Copyright © 2014 Cognitive Science Society, Inc.

Memory-induced mechanism for self-sustaining activity in networks

NASA Astrophysics Data System (ADS)

Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

2015-12-01

We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

Quantitative structure–activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods

PubMed Central

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure–activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7−7−1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure–activity relationship model suggested is robust and satisfactory. PMID:26600858

Utilization of oil palm biodiesel solid residue as renewable sources for preparation of granular activated carbon by microwave induced KOH activation.

PubMed

Foo, K Y; Hameed, B H

2013-02-01

In this work, preparation of granular activated carbon from oil palm biodiesel solid residue, oil palm shell (PSAC) by microwave assisted KOH activation has been attempted. The physical and chemical properties of PSAC were characterized using scanning electron microscopy, volumetric adsorption analyzer and elemental analysis. The adsorption behavior was examined by performing batch adsorption experiments using methylene blue as dye model compound. Equilibrium data were simulated using the Langmuir, Freundlich and Temkin isotherm models. Kinetic modeling was fitted to the pseudo-first-order, pseudo-second-order and Elovich kinetic models, while the adsorption mechanism was determined using the intraparticle diffusion and Boyd equations. The result was satisfactory fitted to the Langmuir isotherm model with a monolayer adsorption capacity of 343.94mg/g at 30°C. The findings support the potential of oil palm shell for preparation of high surface area activated carbon by microwave assisted KOH activation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Active bio-based food-packaging: Diffusion and release of active substances through and from cellulose nanofiber coating toward food-packaging design.

PubMed

Lavoine, Nathalie; Guillard, Valérie; Desloges, Isabelle; Gontard, Nathalie; Bras, Julien

2016-09-20

Cellulose nanofibers (CNFs) were recently investigated for the elaboration of new functional food-packaging materials. Their nanoporous network was especially of interest for controlling the release of active species. Qualitative release studies were conducted, but quantification of the diffusion phenomenon observed when the active species are released from and through CNF coating has not yet been studied. Therefore, this work aims to model CNF-coated paper substrates as controlled release system for food-packaging using release data obtained for two model molecules, namely caffeine and chlorhexidine digluconate. The applied mathematical model - derived from Fickian diffusion - was validated for caffeine only. When the active species chemically interacts with the release device, another model is required as a non-predominantly diffusion-controlled release was observed. From caffeine modeling data, a theoretical active food-packaging material was designed. The use of CNFs as barrier coating was proved to be the ideal material configuration that best meets specifications. Copyright © 2016. Published by Elsevier Ltd.

Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

2016-02-01

Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.

The ACTIVE conceptual framework as a structural equation model

PubMed Central

Gross, Alden L.; Payne, Brennan R.; Casanova, Ramon; Davoudzadeh, Pega; Dzierzewski, Joseph M.; Farias, Sarah; Giovannetti, Tania; Ip, Edward H.; Marsiske, Michael; Rebok, George W.; Schaie, K. Warner; Thomas, Kelsey; Willis, Sherry; Jones, Richard N.

2018-01-01

Background/Study Context Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations. Methods The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status. Results Preconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA < .05; all CFI > .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p < .005). Conclusions Empirical data confirm the hypothesized ACTIVE conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from those with the greatest chance of transfer to real-world activities. PMID:29303475

Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

NASA Astrophysics Data System (ADS)

Wang, G.; Mayes, M. A.; Gu, L.; Schadt, C. W.

2013-12-01

Experimental observations and modeling efforts have shown that dormancy is likely a common strategy for microorganisms to contend with environmental stress. We review the state-of-the-art in modeling approaches for microbial dormancy and discuss the rationales of these models. We proved that the physiological state index model is not appropriate for describing transformation between active and dormant states. Based on the generally accepted assumptions summarized from ten existing models, we postulated a new synthetic microbial physiology component within the Microbial-ENzyme-mediated Decomposition (MEND) model. Both the steady state active fraction (rss) and substrate saturation level (Øss) positively depend on two physiological indices: α and β. The index α = mR /(μG+ mR), where μG and mR represent the maximum specific growth and maintenance rates, respectively, for active microbes. β denotes the ratio of dormant to active maintenance rate. The rss equals to Øss only under the condition of β→0, and they are identical to α. When substrate availability is the only limiting factor, the maximum rss is ca. 0.5 with α≤0.5 and β ≤0.01. This threshold value (0.5) of rss (not dynamic r) can explain the low active microbial fractions observed in undisturbed soils. The applications of the improved model to a 14C-labeled glucose induced respiration dataset and a batch experimental dataset show satisfactory model performance. We found that the exponential growth respiration rates can only be used to determine μG and initial active microbial biomass (Ba0), thus we suggest using respiration data representing both exponential growth and non-accelerating phases to robustly determine other important parameters such as initial total live microbial biomass (B0), initial active fraction (r0), μG, α, and the half-saturation constant (Ks). Similar improved representations of microbial physiology should be incorporated into existing ecosystem models in order to account for the significance of dormancy in microbially-mediated processes.

A musculoskeletal foot model for clinical gait analysis.

PubMed

Saraswat, Prabhav; Andersen, Michael S; Macwilliams, Bruce A

2010-06-18

Several full body musculoskeletal models have been developed for research applications and these models may potentially be developed into useful clinical tools to assess gait pathologies. Existing full-body musculoskeletal models treat the foot as a single segment and ignore the motions of the intrinsic joints of the foot. This assumption limits the use of such models in clinical cases with significant foot deformities. Therefore, a three-segment musculoskeletal model of the foot was developed to match the segmentation of a recently developed multi-segment kinematic foot model. All the muscles and ligaments of the foot spanning the modeled joints were included. Muscle pathways were adjusted with an optimization routine to minimize the difference between the muscle flexion-extension moment arms from the model and moment arms reported in literature. The model was driven by walking data from five normal pediatric subjects (aged 10.6+/-1.57 years) and muscle forces and activation levels required to produce joint motions were calculated using an inverse dynamic analysis approach. Due to the close proximity of markers on the foot, small marker placement error during motion data collection may lead to significant differences in musculoskeletal model outcomes. Therefore, an optimization routine was developed to enforce joint constraints, optimally scale each segment length and adjust marker positions. To evaluate the model outcomes, the muscle activation patterns during walking were compared with electromyography (EMG) activation patterns reported in the literature. Model-generated muscle activation patterns were observed to be similar to the EMG activation patterns. Published by Elsevier Ltd.

Comparing Computer-Supported Dynamic Modeling and "Paper & Pencil" Concept Mapping Technique in Students' Collaborative Activity

ERIC Educational Resources Information Center

Komis, Vassilis; Ergazaki, Marida; Zogza, Vassiliki

2007-01-01

This study aims at highlighting the collaborative activity of two high school students (age 14) in the cases of modeling the complex biological process of plant growth with two different tools: the "paper & pencil" concept mapping technique and the computer-supported educational environment "ModelsCreator". Students' shared activity in both cases…

Examining of Model Eliciting Activities Developed by Mathematics Student Teachers

ERIC Educational Resources Information Center

Dede, Ayse Tekin; Hidiroglu, Çaglar Naci; Güzel, Esra Bukova

2017-01-01

The purpose of this study is to examine the model eliciting activities developed by the mathematics student teachers in the context of the principles of the model eliciting activities. The participants of the study conducted as a case study design were twenty one mathematics student teachers working on seven groups. The data collection tools were…

Dithiolato-bridged nickel-iron complexes as models for the active site of [NiFe]-hydrogenases.

PubMed

Song, Li-Cheng; Yang, Xi-Yue; Cao, Meng; Gao, Xiu-Yun; Liu, Bei-Bei; Zhu, Liang; Jiang, Feng

2017-03-30

The structural and functional modeling of the active site of [NiFe]-hydrogenases has been proved to be challenging to a great extent. Herein, we report the synthesis, structures, and some properties of the NiFe-based dicarbonyl, terminal hydride, and μ-hydroxo models for the active site of [NiFe]-hydrogenases.

The Scholarly Activity Predictor Model among Counseling Psychology Doctoral Students: A Modification and Extension

ERIC Educational Resources Information Center

Huber, Daniel M.

2010-01-01

The purpose of the current study was to help understand scholarly activity better among counseling psychology doctoral students. Two new variables were added to the previously created predictor model of scholarly activity: advisory working alliance and research competence. Three path analytic models were designed in the current study: (1) a…

Periodic Properties and Inquiry: Student Mental Models Observed during a Periodic Table Puzzle Activity

ERIC Educational Resources Information Center

Larson, Kathleen G.; Long, George R.; Briggs, Michael W.

2012-01-01

The mental models of both novice and advanced chemistry students were observed while the students performed a periodic table activity. The mental model framework seems to be an effective way of analyzing student behavior during learning activities. The analysis suggests that students do not recognize periodic trends through the examination of…

Integrating Social Activity Theory and Critical Discourse Analysis: A Multilayered Methodological Model for Examining Knowledge Mediation in Mentoring

ERIC Educational Resources Information Center

Becher, Ayelet; Orland-Barak, Lily

2016-01-01

This study suggests an integrative qualitative methodological framework for capturing complexity in mentoring activity. Specifically, the model examines how historical developments of a discipline direct mentors' mediation of professional knowledge through the language that they use. The model integrates social activity theory and a framework of…

Large memory capacity in chaotic artificial neural networks: a view of the anti-integrable limit.

PubMed

Lin, Wei; Chen, Guanrong

2009-08-01

In the literature, it was reported that the chaotic artificial neural network model with sinusoidal activation functions possesses a large memory capacity as well as a remarkable ability of retrieving the stored patterns, better than the conventional chaotic model with only monotonic activation functions such as sigmoidal functions. This paper, from the viewpoint of the anti-integrable limit, elucidates the mechanism inducing the superiority of the model with periodic activation functions that includes sinusoidal functions. Particularly, by virtue of the anti-integrable limit technique, this paper shows that any finite-dimensional neural network model with periodic activation functions and properly selected parameters has much more abundant chaotic dynamics that truly determine the model's memory capacity and pattern-retrieval ability. To some extent, this paper mathematically and numerically demonstrates that an appropriate choice of the activation functions and control scheme can lead to a large memory capacity and better pattern-retrieval ability of the artificial neural network models.

Biofidelic Human Activity Modeling and Simulation with Large Variability

DTIC Science & Technology

2014-11-25

A systematic approach was developed for biofidelic human activity modeling and simulation by using body scan data and motion capture data to...replicate a human activity in 3D space. Since technologies for simultaneously capturing human motion and dynamic shapes are not yet ready for practical use, a...that can replicate a human activity in 3D space with the true shape and true motion of a human. Using this approach, a model library was built to

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

Testing a Longitudinal Integrated Self-Efficacy and Self-Determination Theory Model for Physical Activity Post-Cardiac Rehabilitation

PubMed Central

Sweet, Shane N.; Fortier, Michelle S.; Strachan, Shaelyn M.; Blanchard, Chris M.; Boulay, Pierre

2014-01-01

Self-determination theory and self-efficacy theory are prominent theories in the physical activity literature, and studies have begun integrating their concepts. Sweet, Fortier, Strachan and Blanchard (2012) have integrated these two theories in a cross-sectional study. Therefore, this study sought to test a longitudinal integrated model to predict physical activity at the end of a 4-month cardiac rehabilitation program based on theory, research and Sweet et al.’s cross-sectional model. Participants from two cardiac rehabilitation programs (N=109) answered validated self-report questionnaires at baseline, two and four months. Data were analyzed using Amos to assess the path analysis and model fit. Prior to integration, perceived competence and self-efficacy were combined, and labeled as confidence. After controlling for 2-month physical activity and cardiac rehabilitation site, no motivational variables significantly predicted residual change in 4-month physical activity. Although confidence at two months did not predict residual change in 4-month physical activity, it had a strong positive relationship with 2-month physical activity (β=0.30, P<0.001). The overall model retained good fit indices. In conclusion, results diverged from theoretical predictions of physical activity, but self-determination and self-efficacy theory were still partially supported. Because the model had good fit, this study demonstrated that theoretical integration is feasible. PMID:26973926

An Evaluation of the My ParticipACTION Campaign to Increase Self-Efficacy for Being More Physically Active.

PubMed

Craig, Cora Lynn; Bauman, Adrian; Latimer-Cheung, Amy; Rhodes, Ryan E; Faulkner, Guy; Berry, Tanya R; Tremblay, Mark S; Spence, John C

2015-01-01

The objective of the My ParticipACTION campaign was to inspire Canadian adults to increase their physical activity through messaging that was relevant, engaging, and designed to build self-efficacy to be more active. This research examined the communication effects of the campaign according to the a priori Hierarchy of Effects Model (saliency → cognitive engagement → self-efficacy to become more active → trial behavior) and investigated how these effects related to overall self-efficacy for physical activity, intention to be active, and current activity level. Participants (N = 1,110) were recruited from an existing panel of Canadian adults 18 years and older and completed a short online questionnaire about the potential communication effects. Logistic regression models were constructed to test the communication effects adjusting for age, gender, and education. The relations were consistent with those hypothesized in the model. In addition, some earlier outcomes in the sequence of effects were associated with other outcomes further down the progression. When intention to be active was included, the initial relation between ad-specific self-efficacy and current physical activity disappeared. This analysis suggested that the campaign was successful in increasing self-efficacy to be more active and that using the Hierarchy of Effects Model was useful in guiding the design of campaign messages and assessing communication effects. Given the limited amount of theoretical testing of the Hierarchy of Effects Model, future research employing longitudinal designs is required to further confirm the communication effects of such an intervention and further test the model.

Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations.

PubMed

Jopp, Daniela; Hertzog, Christopher

2007-12-01

In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns. PsycINFO Database Record (c) 2008 APA, all rights reserved.

[Leisure activities, resilience and mental stress in adolescents].

PubMed

Karpinski, Norbert; Popal, Narges; Plück, Julia; Petermann, Franz; Lehmkuhl, Gerd

2017-01-01

To date, the factors contributing to emergence of resilience in different stages of adolescence have yet to be sufficiently examined. This study looks at the influence of extracurricular activities on resilience. The sample consists of 413 adolescents (f = 14.8) reporting personal problems (mood, concentration problems, behavior). The effect of extracurricular activities on resilience (gathered by the RS25) was analyzed by linear regression models. Predictor variables in these models were extracurricular activities (sport, hobbies, club memberships, household duties) and the subscales of the SDQ (Strengths and Difficulties Questionnaire). Because of the lack of homoscedasticity, two different regression models (model A: Realschule and Grammar School. Model B: Hauptschule) were specified. The explained variance of both models (model A: R = .516; model B: R = .643) is satisfactory. In both models “prosocial behavior” (SDQ) turns out to be a significant positive predictor for resilience (model A: b = 2.815; model B; b = 3.577) and emotional symptoms (model A: b = -1.697; model B: b = -2.596) are significant negative predictors for resilience. In addition, model A presents significant positive influences of sport (b = 16,314) and significant negative influences of “hyperactivity” (SDQ). In contrast, in model B “club memberships” (b = 15.775) and” peer relationship problems” (b = 1.508) are additional positive predictors. The results of the study demonstrate the important role of prosocial behavior and emotional competence in the manifestation of resilience. The effect of extracurricular activities proves to depend on the social environment (type of school). Thus, these results could form the basis for further more specific developmental programs.

Learning Setting-Generalized Activity Models for Smart Spaces

PubMed Central

Cook, Diane J.

2011-01-01

The data mining and pervasive computing technologies found in smart homes offer unprecedented opportunities for providing context-aware services, including health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to provide these services, smart environment algorithms need to recognize and track activities that people normally perform as part of their daily routines. However, activity recognition has typically involved gathering and labeling large amounts of data in each setting to learn a model for activities in that setting. We hypothesize that generalized models can be learned for common activities that span multiple environment settings and resident types. We describe our approach to learning these models and demonstrate the approach using eleven CASAS datasets collected in seven environments. PMID:21461133

Activity of convective coupled equatorial wave in tropical Tropopause layer in reanalysis and high-top CMIP5 models

NASA Astrophysics Data System (ADS)

Harza, Alia; Lubis, Sandro W.; Setiawan, Sonni

2018-05-01

The activity of convectively coupled equatorial waves (CCEWs), including Kelvin waves, Mixed Rossby-Gravity (MRG), and Equatorial Rossby (ER), in the tropical tropopause layer (TTL) is investigated in the Reanalysis and nine high-top CMIP5 models using the zonal wave number-frequency spectral analysis with equatorially symmetric-antisymmetric decomposition. We found that the TTL activities in the high-top CMIP5 models show significant difference among the high-top CMIP5 models with respect to the observation. The MIROC and HadGEM2-CC models work best in simulating Kelvin wave in the TTL, while the HadGEM2-CC and MPI-ESM-LR models work best in simulating MRG waves. The ER waves in TTL are best simulated in the MRI-CGCM model. None of the models are good in simulating all waves at once. It is concluded that the broad range of wave activity found in the different CMIP5 models depend on the convective parameterization used by each model and the representation of the tropical stratosphere variability, including the QBO.

Deriving Tools from Real-time Runs: A New CCMC Support for SEC and AFWA

NASA Technical Reports Server (NTRS)

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

2008-01-01

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. After consultations with NOA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

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.

Demand Activated Manufacturing Architecture (DAMA) model for supply chain collaboration

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

CHAPMAN,LEON D.; PETERSEN,MARJORIE B.

The Demand Activated Manufacturing Architecture (DAMA) project during the last five years of work with the U.S. Integrated Textile Complex (retail, apparel, textile, and fiber sectors) has developed an inter-enterprise architecture and collaborative model for supply chains. This model will enable improved collaborative business across any supply chain. The DAMA Model for Supply Chain Collaboration is a high-level model for collaboration to achieve Demand Activated Manufacturing. The five major elements of the architecture to support collaboration are (1) activity or process, (2) information, (3) application, (4) data, and (5) infrastructure. These five elements are tied to the application of themore » DAMA architecture to three phases of collaboration - prepare, pilot, and scale. There are six collaborative activities that may be employed in this model: (1) Develop Business Planning Agreements, (2) Define Products, (3) Forecast and Plan Capacity Commitments, (4) Schedule Product and Product Delivery, (5) Expedite Production and Delivery Exceptions, and (6) Populate Supply Chain Utility. The Supply Chain Utility is a set of applications implemented to support collaborative product definition, forecast visibility, planning, scheduling, and execution. The DAMA architecture and model will be presented along with the process for implementing this DAMA model.« less

Antibacterial Activity of Imidazolium-Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies.

PubMed

Hodyna, Diana; Kovalishyn, Vasyl; Rogalsky, Sergiy; Blagodatnyi, Volodymyr; Petko, Kirill; Metelytsia, Larisa

2016-09-01

Predictive QSAR models for the inhibitors of B. subtilis and Ps. aeruginosa among imidazolium-based ionic liquids were developed using literary data. The regression QSAR models were created through Artificial Neural Network and k-nearest neighbor procedures. The classification QSAR models were constructed using WEKA-RF (random forest) method. The predictive ability of the models was tested by fivefold cross-validation; giving q(2) = 0.77-0.92 for regression models and accuracy 83-88% for classification models. Twenty synthesized samples of 1,3-dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3-dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3-dialkylimidazolium salts was found to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3-dioctylimidazolium cation. The obtained experimental results suggested that the application of classification QSAR models is more accurate for the prediction of activity of new imidazolium-based ILs as potential antibacterials. © 2016 John Wiley & Sons A/S.

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

Semi-analytical Model for Estimating Absorption Coefficients of Optically Active Constituents in Coastal Waters

NASA Astrophysics Data System (ADS)

Wang, D.; Cui, Y.

2015-12-01

The objectives of this paper are to validate the applicability of a multi-band quasi-analytical algorithm (QAA) in retrieval absorption coefficients of optically active constituents in turbid coastal waters, and to further improve the model using a proposed semi-analytical model (SAA). The ap(531) and ag(531) semi-analytically derived using SAA model are quite different from the retrievals procedures of QAA model that ap(531) and ag(531) are semi-analytically derived from the empirical retrievals results of a(531) and a(551). The two models are calibrated and evaluated against datasets taken from 19 independent cruises in West Florida Shelf in 1999-2003, provided by SeaBASS. The results indicate that the SAA model produces a superior performance to QAA model in absorption retrieval. Using of the SAA model in retrieving absorption coefficients of optically active constituents from West Florida Shelf decreases the random uncertainty of estimation by >23.05% from the QAA model. This study demonstrates the potential of the SAA model in absorption coefficients of optically active constituents estimating even in turbid coastal waters. Keywords: Remote sensing; Coastal Water; Absorption Coefficient; Semi-analytical Model

Perceived sports competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment

PubMed Central

Barnett, Lisa M; Morgan, Philip J; van Beurden, Eric; Beard, John R

2008-01-01

Background The purpose of this paper was to investigate whether perceived sports competence mediates the relationship between childhood motor skill proficiency and subsequent adolescent physical activity and fitness. Methods In 2000, children's motor skill proficiency was assessed as part of a school-based physical activity intervention. In 2006/07, participants were followed up as part of the Physical Activity and Skills Study and completed assessments for perceived sports competence (Physical Self-Perception Profile), physical activity (Adolescent Physical Activity Recall Questionnaire) and cardiorespiratory fitness (Multistage Fitness Test). Structural equation modelling techniques were used to determine whether perceived sports competence mediated between childhood object control skill proficiency (composite score of kick, catch and overhand throw), and subsequent adolescent self-reported time in moderate-to-vigorous physical activity and cardiorespiratory fitness. Results Of 928 original intervention participants, 481 were located in 28 schools and 276 (57%) were assessed with at least one follow-up measure. Slightly more than half were female (52.4%) with a mean age of 16.4 years (range 14.2 to 18.3 yrs). Relevant assessments were completed by 250 (90.6%) students for the Physical Activity Model and 227 (82.3%) for the Fitness Model. Both hypothesised mediation models had a good fit to the observed data, with the Physical Activity Model accounting for 18% (R2 = 0.18) of physical activity variance and the Fitness Model accounting for 30% (R2 = 0.30) of fitness variance. Sex did not act as a moderator in either model. Conclusion Developing a high perceived sports competence through object control skill development in childhood is important for both boys and girls in determining adolescent physical activity participation and fitness. Our findings highlight the need for interventions to target and improve the perceived sports competence of youth. PMID:18687148

A simple mathematical model based on biomarkers in stress-resistant catfish species, Sciades herzbergii (Pisces, Ariidae), in São Marcos Bay, Brazil.

PubMed

Carvalho Neta, Raimunda Nonata Fortes; Torres Junior, Audalio Rebelo; Silva, Dilson; Cortez, Célia Martins

2014-12-01

We present a refinement of our model describing the association between enzyme activity and histopathological lesions in the catfish, Sciades herzbergii from a polluted port. The fish were sampled from a port known to be contaminated with heavy metals and organic compounds and from a natural reserve in São Marcos Bay, Brazil. Two biomarkers, hepatic glutathione S-transferase (GST) activity and histopathological lesions, in gills and liver tissue were measured. The values for GST activity were modeled with the occurrence of branchial and hepatic lesions by fitting a third-order polynomial. Results from the mathematical model indicate that GST activity has a strong polynomial relationship with the occurrence of branchial and hepatic lesions in both wet and the dry seasons but only at the polluted port site. The model developed in this study indicates that branchial and hepatic lesions are initiated when GST activity reaches 2.17 μmol min(-1) mg protein(-1). Beyond this limit, GST activity decreased to very low levels and irreversible histopathological lesions occurred. This mathematical model based on two biomarkers (histopathological lesions and enzyme activity) in catfish provides a realistic approach to analyze stress induced by contaminants.

Biological activity of aldose reductase and lipophilicity of pyrrolyl-acetic acid derivatives

NASA Astrophysics Data System (ADS)

Kumari, A.; Kumari, R.; Kumar, R.; Gupta, M.

2011-12-01

Quantitative Structure-Activity Relationship modeling is a powerful approach for correlating an organic compound to its lipophilicity. In this paper QSAR models are established for estimation of correlation of the lipophilicity of a series of pyrrolyl-acetic acid derivatives, inhibitors of the aldose reductase enzyme, in the n-octanol-water system with biological activity of aldose reductase. Lipophilicity, expressed by the logarithm of n-octnol-water partition coefficient log P and biological activity of aldose reductase inhibitory activity by log it. Result obtained by QSAR modeling of compound series reveal a definite trend in biological activity and a further improvement in quantitative relationships are established if, beside log P, Hammett electronic constant σ and connectivity index chi-3 (3 χ) term included in the regression equation. The tri-parametric model with log P, 3 χ and σ as correlating parameters have been found to be the best which gives a variance of 87% ( R 2 = 0.8743). A compound has been found to be serious outlier and when the same has been excluded the model explains about 94% variance of the data set ( R 2 = 0.9447). The topological index (3 χ) has been found to be a good parameter for modeling the biological activity.

Reducing Societal Obesity: Establishing a Separate Exercise Model through Studies of Group Behavior.

PubMed

Puterbaugh, J S

2016-01-01

The past 50 years has brought attention to high and increasing levels of human obesity in most of the industrialized world. The medical profession has noticed, has evaluated, and has developed models for studying, preventing, and reversing obesity. The current model prescribes activity in specific quantities such as days, minutes, heart rates, and footfalls. Although decreased levels of activity have come from changes revolving around built environments and social networks, the existing medical model to lower body weights by increasing activity remains individually prescriptive. It is not working. The study of societal obesity precludes the individual and must involve group behavioral studies. Such studies necessitate acquiring separate tools and, therefore, require a significant change in the evaluation and treatment of obesity. Finding groups with common activities and lower levels of obesity would allow the development of new models of land use and encourage active lifestyles through shared interests.

The Effects of the Activities of Current Textbook and 5 E Model on the Attitude of the Students: Sample of "The Global Effects of Natural Resources Unit"

ERIC Educational Resources Information Center

Uzunoz, Abdulkadir

2011-01-01

This study aimed to determine the effects of the activities of current textbook and 5 E Model on the attitude of the students. This study is a research as an experimental model. For testing the effects of geography education supported by 5 E model and geography education based on activities of current textbook attitude of students, controlled…

Modeling the Magnetic and Thermal Structure of Active Regions: 1st Year 1st Semi-Annual Progress Report

NASA Technical Reports Server (NTRS)

Mikic, Zoran

2003-01-01

This report covers technical progress during the first six months of the first year of NASA SR&T contract "Modeling the Magnetic and Thermal Structure of Active Regions", NASW-03008, between NASA and Science Applications International Corporation, and covers the period January 14, 2003 to July 13, 2003. Under this contract SAIC has conducted research into theoretical modeling of the properties of active regions using the MHD model.

In silico study of in vitro GPCR assays by QSAR modeling ...

EPA Pesticide Factsheets

The U.S. EPA is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays (the ToxCast program). One goal is to prioritize chemicals for more detailed analyses based on activity in molecular initiating events (MIE) of adverse outcome pathways (AOPs). However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in silico methods, and quantitative structure-activity relationships (QSARs) are a proven and cost effective approach to predict biological activity. ToxCast in turn provides relatively large datasets that are ideal for training and testing QSAR models. The overall goal of the study described here was to develop QSAR models to fill the data gaps in a larger environmental database of ~32k structures. The specific aim of the current work was to build QSAR models for 18 G-Protein Coupled Receptor (GPCR) assays, part of the aminergic category. Two QSAR modeling strategies were adopted: classification models were developed to separate chemicals into active/non-active classes, and then regression models were built to predict the potency values of the bioassays for the active chemicals. Multiple software programs were used to calculate constitutional, topological and substructural molecular descriptors from two-dimensional (2D) chemical structures. Model-fitting methods included PLSDA (partial least squares d

Determinants of physical activity in middle-aged woman in Isfahan using the health belief model.

PubMed

Hosseini, Habibollah; Moradi, Razieh; Kazemi, Ashraf; Shahshahani, Maryam Sadat

2017-01-01

Nowadays with respect to the automation of the lifestyle, immobility statistics in middle-aged women has increased and they are at risk for complications of immobility. One of the models used to identify factors associated with physical activity is Health Belief Model utilized in different age and different cultural backgrounds and different results have been obtained from those studies. The purpose of this study was to investigate the factors affecting on physical activity in middle-aged women using Health Belief Model. This descriptive-correlation study was conducted on 224 middle-aged women referring to health centers in Isfahan. Health Belief Model structures including perceived susceptibility and severity, perceived barriers and benefits, and self-efficacy were measured by questionnaire and physical activity was assessed using the international physical activity questionnaire. Collected data were analyzed using descriptive statistics and Pearson correlation coefficient test and regression analysis. There wasn't significant correlation between perceived susceptibility ( P = 0.263, r = 0.075) and perceived severity with physical activity duration ( P = 0.127, r = 0.058) but there was positive and weak correlation between physical activity duration with perceived benefits ( P = 0.001 and r = 0.26) and perceived self-efficacy ( P = 0.001, r = 0.54) and had weak and inverse correlation with perceived barriers ( P = 0.001, r = -0.25). Regression analysis also showed that from among all the Health Belief Model structures just self-efficacy structure has influenced on behavior independently and other structures are affected by it. The obtained results implied on a correlation between benefits, barriers and perceived self-efficacy with and moderate physical activity. Therefore it is necessary to develop appropriate educational programs with emphasis on structures of Health Belief Model that has the maximum impact on physical activity in middle-aged women.

Comparison of the active-site design of molybdenum oxo-transfer enzymes by quantum mechanical calculations.

PubMed

Li, Jilai; Ryde, Ulf

2014-11-17

There are three families of mononuclear molybdenum enzymes that catalyze oxygen atom transfer (OAT) reactions, named after a typical example from each family, viz., dimethyl sulfoxide reductase (DMSOR), sulfite oxidase (SO), and xanthine oxidase (XO). These families differ in the construction of their active sites, with two molybdopterin groups in the DMSOR family, two oxy groups in the SO family, and a sulfido group in the XO family. We have employed density functional theory calculations on cluster models of the active sites to understand the selection of molybdenum ligands in the three enzyme families. Our calculations show that the DMSOR active site has a much stronger oxidative power than the other two sites, owing to the extra molybdopterin ligand. However, the active sites do not seem to have been constructed to make the OAT reaction as exergonic as possible, but instead to keep the reaction free energy close to zero (to avoid excessive loss of energy), thereby making the reoxidation (SO and XO) or rereduction of the active sites (DMSOR) after the OAT reaction facile. We also show that active-site models of the three enzyme families can all catalyze the reduction of DMSO and that the DMSOR model does not give the lowest activation barrier. Likewise, all three models can catalyze the oxidation of sulfite, provided that the Coulombic repulsion between the substrate and the enzyme model can be overcome, but for this harder reaction, the SO model gives the lowest activation barrier, although the differences are not large. However, only the XO model can catalyze the oxidation of xanthine, owing to its sulfido ligand.

Impact of very low physical activity, BMI, and comorbidities on mortality among breast cancer survivors

PubMed Central

Nelson, Sandahl H; Marinac, Catherine R; Patterson, Ruth E; Nechuta, Sarah J; Flatt, Shirley W; Caan, Bette J; Kwan, Marilyn L; Poole, Elizabeth M.; Chen, Wendy Y; Shu, Xiao-ou; Pierce, John P

2016-01-01

Purpose To examine post diagnosis BMI, very low physical activity, and comorbidities, as predictors of breast cancer specific and all-cause mortality. Methods Data from three female US breast cancer survivor cohorts were harmonized in the After Breast Cancer Pooling Project (n=9513). Delayed entry Cox proportional hazards models were used to examine the impact of three post-diagnosis lifestyle factors; body mass index (BMI), select comorbidities (diabetes only, hypertension only, or both) and very low physical activity (defined as physical activity <1.5 MET hrs/wk) in individual models and together in multivariate models for breast cancer and all-cause mortality. Results For breast cancer mortality, the individual lifestyle models demonstrated a significant association with very low physical activity but not with the selected comorbidities or BMI. In the model that included all three lifestyle variables, very low physical activity was associated with a 22% increased risk of breast cancer mortality (HR=1.22, 95% CI= 1.05, 1.42). For all-cause mortality, the three individual models demonstrated significant associations for all three lifestyle predictors. In the combined model, the strength and significance of the association of comorbidities (both hypertension and diabetes vs. neither: HR=2.16, 95% CI= 1.79, 2.60) and very low physical activity (HR=1.35, 95% CI= 1.22, 1.51) remained unchanged, but the association with obesity was completely attenuated. Conclusion These data indicate that after active treatment, very low physical activity, consistent with a sedentary lifestyle (and comorbidities for all-cause mortality), may account for the increased risk of mortality, with higher BMI, that is seen in other studies. PMID:26861056

[Active ageing and success: A brief history of conceptual models].

PubMed

Petretto, Donatella Rita; Pili, Roberto; Gaviano, Luca; Matos López, Cristina; Zuddas, Carlo

2016-01-01

The aim of this paper is to analyse and describe different conceptual models of successful ageing, active and healthy ageing developed in Europe and in America in the 20° century, starting from Rowe and Kahn's original model (1987, 1997). A narrative review was conducted on the literature on successful ageing. Our review included definition of successful ageing from European and American scholars. Models were found that aimed to describe indexes of active and healthy ageing, models devoted to describe processes involved in successful ageing, and additional views that emphasise subjective and objective perception of successful ageing. A description is also given of critiques on previous models and remedies according to Martin et al. (2014) and strategies for successful ageing according to Jeste and Depp (2014). The need is discussed for the enhancement of Rowe and Kahn's model and other models with a more inclusive, universal description of ageing, incorporating scientific evidence regarding active ageing. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

Human Activity Modeling and Simulation with High Biofidelity

DTIC Science & Technology

2013-01-01

Human activity Modeling and Simulation (M&S) plays an important role in simulation-based training and Virtual Reality (VR). However, human activity M...kinematics and motion mapping/creation; and (e) creation and replication of human activity in 3-D space with true shape and motion. A brief review is

Marshmallow Meiosis.

ERIC Educational Resources Information Center

Soderberg, Patti

1992-01-01

Presents an activity in which students model the processes of meiosis, fertilization, development, and birth using model creatures called reebops. Students breed reebops to analyze chromosome combinations. Makes recommendations for activity utilization and identifies the strengths of the activity. (MDH)

A framework for the use of agent based modeling to simulate ...

EPA Pesticide Factsheets

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 agent-based model (ABM) is used to simulate population distributions of longitudinal patterns of four macro activities (sleeping, eating, working, and commuting) in populations of adults over a period of one year. In this ABM, an individual is modeled as an agent whose movement through time and space is determined by a set of decision rules. The rules are based on the agent having time-varying “needs” that are satisfied by performing actions. Needs are modeled as increasing over time, and taking an action reduces the need. Need-satisfying actions include sleeping (meeting the need for rest), eating (meeting the need for food), and commuting/working (meeting the need for income). Every time an action is completed, the model determines the next action the agent will take based on the magnitude of each of the agent’s needs at that point in time. Different activities advertise their ability to satisfy various needs of the agent (such as food to eat or sleeping in a bed or on a couch). The model then chooses the activity that satisfies the greatest of the agent’s needs. When multiple actions could address a need, the model will choose the most effective of the actions (bed over the couc

Patterns of Activity in A Global Model of A Solar Active Region

NASA Technical Reports Server (NTRS)

Bradshaw, S. J.; Viall, N. M.

2016-01-01

In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.

Active Player Modeling in the Iterated Prisoner's Dilemma

PubMed Central

Park, Hyunsoo; Kim, Kyung-Joong

2016-01-01

The iterated prisoner's dilemma (IPD) is well known within the domain of game theory. Although it is relatively simple, it can also elucidate important problems related to cooperation and trust. Generally, players can predict their opponents' actions when they are able to build a precise model of their behavior based on their game playing experience. However, it is difficult to make such predictions based on a limited number of games. The creation of a precise model requires the use of not only an appropriate learning algorithm and framework but also a good dataset. Active learning approaches have recently been introduced to machine learning communities. The approach can usually produce informative datasets with relatively little effort. Therefore, we have proposed an active modeling technique to predict the behavior of IPD players. The proposed method can model the opponent player's behavior while taking advantage of interactive game environments. This experiment used twelve representative types of players as opponents, and an observer used an active modeling algorithm to model these opponents. This observer actively collected data and modeled the opponent's behavior online. Most of our data showed that the observer was able to build, through direct actions, a more accurate model of an opponent's behavior than when the data were collected through random actions. PMID:26989405

Active Player Modeling in the Iterated Prisoner's Dilemma.

PubMed

Park, Hyunsoo; Kim, Kyung-Joong

2016-01-01

The iterated prisoner's dilemma (IPD) is well known within the domain of game theory. Although it is relatively simple, it can also elucidate important problems related to cooperation and trust. Generally, players can predict their opponents' actions when they are able to build a precise model of their behavior based on their game playing experience. However, it is difficult to make such predictions based on a limited number of games. The creation of a precise model requires the use of not only an appropriate learning algorithm and framework but also a good dataset. Active learning approaches have recently been introduced to machine learning communities. The approach can usually produce informative datasets with relatively little effort. Therefore, we have proposed an active modeling technique to predict the behavior of IPD players. The proposed method can model the opponent player's behavior while taking advantage of interactive game environments. This experiment used twelve representative types of players as opponents, and an observer used an active modeling algorithm to model these opponents. This observer actively collected data and modeled the opponent's behavior online. Most of our data showed that the observer was able to build, through direct actions, a more accurate model of an opponent's behavior than when the data were collected through random actions.

PlayDoh and Toothpicks and Gummy Bears... OH MY, They're Models!

NASA Astrophysics Data System (ADS)

Kolandaivelu, K. P.; Wilson, M. W.; Glesener, G. B.

2017-12-01

Simple, everyday items found around the house are often used in geoscience lab activities. Gummy bears and silly putty can model the bending and breaking behaviour of rocks; shaking buildings during an earthquake can be modeled with some Jello, toothpicks, and marshmallows; PlayDoh can be used to demonstrate layers of sedimentary rocks; and even plumbing pipes filled with pebbles and playground sand become miniature physical models of aquifers. When performed correctly, these activities can help students visualize geoscience phenomena or increase students' motivation to pay attention in class, but how do these activities help students develop ways to think like a scientist? "Developing and using models" is one of the important science and engineering practices recommended in the Next Generation Science Standards (NGSS). In this presentation, we will demonstrate a variety of common geoscience lab activities using simple, everyday household items in order to describe ways instructors can help their students develop model-based reasoning skills. Specific areas of interest will be on identifying positive and negative attributes of a model, ways to evaluate the reliability of a model, and how a model can be revised to improve its outcome. We will also outline other kinds of models that can be generated from these lab activities, such as mathematical, graphical, and verbal models. Our goal is to encourage educators to focus more time on helping students develop model-based reasoning skills, which can be used in almost all aspects of everyday life.

Thermodynamics-Based Models of Transcriptional Regulation by Enhancers: The Roles of Synergistic Activation, Cooperative Binding and Short-Range Repression

PubMed Central

He, Xin; Samee, Md. Abul Hassan; Blatti, Charles; Sinha, Saurabh

2010-01-01

Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences. PMID:20862354

Controlling Nuclear Jaks and Stats for Specific Gene Activation by Ifn γ and Other Cytokines: A Possible Steroid-like Connection

PubMed Central

Johnson, Howard M.; Noon-Song, Ezra; Ahmed, Chulbul M.

2011-01-01

The mechanism of specific gene activation by cytokines that use JAK/STAT signalling pathway is unknown. There are four different types of JAKs and seven different types of STATs. In the classical model of signaling, ligand interacts solely with the receptor extracellular domain, which triggers JAK activation at the receptor cytoplasmic domain. Activated STATs are then said to carry out nuclear events of specific gene activation, including associated epigenetic changes that cause heterochromatin destabilization. Ligand, receptor, and JAKs play no further role in the classical model. Given the limited number of STATs and the activation of the same STATs by cytokines with different functions, the mechanism of the specificity of their signalling is not obvious. Focusing on gamma interferon (IFNγ), we have shown that ligand, receptor, and activated JAKs are involved in nuclear events that are associated with specific gene activation. In this model, receptor subunit IFNGR1 functions as a transcription/cotranscription factor and the JAKs are involved in key epigenetic events that are required for specific gene activation. The model has implications for gene activation in cancer as well as stem cell differentiation. PMID:22924155

Controlling Nuclear Jaks and Stats for Specific Gene Activation by Ifn γ and Other Cytokines: A Possible Steroid-like Connection.

PubMed

Johnson, Howard M; Noon-Song, Ezra; Ahmed, Chulbul M

2011-09-03

The mechanism of specific gene activation by cytokines that use JAK/STAT signalling pathway is unknown. There are four different types of JAKs and seven different types of STATs. In the classical model of signaling, ligand interacts solely with the receptor extracellular domain, which triggers JAK activation at the receptor cytoplasmic domain. Activated STATs are then said to carry out nuclear events of specific gene activation, including associated epigenetic changes that cause heterochromatin destabilization. Ligand, receptor, and JAKs play no further role in the classical model. Given the limited number of STATs and the activation of the same STATs by cytokines with different functions, the mechanism of the specificity of their signalling is not obvious. Focusing on gamma interferon (IFNγ), we have shown that ligand, receptor, and activated JAKs are involved in nuclear events that are associated with specific gene activation. In this model, receptor subunit IFNGR1 functions as a transcription/cotranscription factor and the JAKs are involved in key epigenetic events that are required for specific gene activation. The model has implications for gene activation in cancer as well as stem cell differentiation.

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

PubMed Central

Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.

2015-01-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367

Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

PubMed

Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J

2015-02-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

Reconstruction of 137Cs activity in the ocean following the Fukushima Daiichi Nuclear Power Plant Accident

NASA Astrophysics Data System (ADS)

Tsumune, Daisuke; Aoyama, Michio; Tsubono, Takaki; Tateda, Yutaka; Misumi, Kazuhiro; Hayami, Hiroshi; Toyoda, Yasuhiro; Maeda, Yoshiaki; Yoshida, Yoshikatsu; Uematsu, Mitsuo

2014-05-01

A series of accidents at the Fukushima Dai-ichi Nuclear Power Plant following the earthquake and tsunami of 11 March 2011 resulted in the release of radioactive materials to the ocean by two major pathways, direct release from the accident site and atmospheric deposition. We reconstructed spatiotemporal variability of 137Cs activity in the ocean by the comparison model simulations and observed data. We employed a regional scale and the North Pacific scale oceanic dispersion models, an atmospheric transport model, a sediment transport model, a dynamic biological compartment model for marine biota and river runoff model to investigate the oceanic contamination. Direct releases of 137Cs were estimated for more than 2 years after the accident by comparing simulated results and observed activities very close to the site. The estimated total amounts of directly released 137Cs was 3.6±0.7 PBq. Directly release rate of 137Cs decreased exponentially with time by the end of December 2012 and then, was almost constant. The daily release rate of 137Cs was estimated to be 3.0 x 1010 Bq day-1 by the end of September 2013. The activity of directly released 137Cs was detectable only in the coastal zone after December 2012. Simulated 137Cs activities attributable to direct release were in good agreement with observed activities, a result that implies the estimated direct release rate was reasonable, while simulated 137Cs activities attributable to atmospheric deposition were low compared to measured activities. The rate of atmospheric deposition onto the ocean was underestimated because of a lack of measurements of dose rate and air activity of 137Cs over the ocean when atmospheric deposition rates were being estimated. Observed 137Cs activities attributable to atmospheric deposition in the ocean helped to improve the accuracy of simulated atmospheric deposition rates. Although there is no observed data of 137Cs activity in the ocean from 11 to 21 March 2011, observed data of marine biota should reflect the history of 137Cs activity in this early period. The comparisons between simulated 137Cs activity of marine biota by a dynamic biological compartment and observed data also suggest that simulated 137Cs activity attributable to atmospheric deposition was underestimated in this early period. In addition, river runoff model simulations suggest that the river flux of 137Cs to the ocean was effective to the 137Cs activity in the ocean in this early period. The sediment transport model simulations suggests that the inventory of 137Cs in sediment was less than 10

Developing an active implementation model for a chronic disease management program

PubMed Central

Smidth, Margrethe; Christensen, Morten Bondo; Olesen, Frede; Vedsted, Peter

2013-01-01

Background Introduction and diffusion of new disease management programs in healthcare is usually slow, but active theory-driven implementation seems to outperform other implementation strategies. However, we have only scarce evidence on the feasibility and real effect of such strategies in complex primary care settings where municipalities, general practitioners and hospitals should work together. The Central Denmark Region recently implemented a disease management program for chronic obstructive pulmonary disease (COPD) which presented an opportunity to test an active implementation model against the usual implementation model. The aim of the present paper is to describe the development of an active implementation model using the Medical Research Council’s model for complex interventions and the Chronic Care Model. Methods We used the Medical Research Council’s five-stage model for developing complex interventions to design an implementation model for a disease management program for COPD. First, literature on implementing change in general practice was scrutinised and empirical knowledge was assessed for suitability. In phase I, the intervention was developed; and in phases II and III, it was tested in a block- and cluster-randomised study. In phase IV, we evaluated the feasibility for others to use our active implementation model. Results The Chronic Care Model was identified as a model for designing efficient implementation elements. These elements were combined into a multifaceted intervention, and a timeline for the trial in a randomised study was decided upon in accordance with the five stages in the Medical Research Council’s model; this was captured in a PaTPlot, which allowed us to focus on the structure and the timing of the intervention. The implementation strategies identified as efficient were use of the Breakthrough Series, academic detailing, provision of patient material and meetings between providers. The active implementation model was tested in a randomised trial (results reported elsewhere). Conclusion The combination of the theoretical model for complex interventions and the Chronic Care Model and the chosen specific implementation strategies proved feasible for a practice-based active implementation model for a chronic-disease-management-program for COPD. Using the Medical Research Council’s model added transparency to the design phase which further facilitated the process of implementing the program. Trial registration: http://www.clinicaltrials.gov/(NCT01228708). PMID:23882169

Evaluation of the Klobuchar model in TaiWan

NASA Astrophysics Data System (ADS)

Li, Jinghua; Wan, Qingtao; Ma, Guanyi; Zhang, Jie; Wang, Xiaolan; Fan, Jiangtao

2017-09-01

Ionospheric delay is the mainly error source in Global Navigation Satellite System (GNSS). Ionospheric model is one of the ways to correct the ionospheric delay. The single-frequency GNSS users modify the ionospheric delay by receiving the correction parameters broadcasted by satellites. Klobuchar model is widely used in Global Positioning System (GPS) and COMPASS because it is simple and convenient for real-time calculation. This model is established on the observations mainly from Europe and USA. It does not describe the equatorial anomaly region. South of China is located near the north crest of the equatorial anomaly, where the ionosphere has complex spatial and temporal variation. The assessment on the validation of Klobuchar model in this area is important to improve this model. Eleven years (2003-2014) data from one GPS receiver located at Taoyuan Taiwan (121°E, 25°N) are used to assess the validation of Klobuchar model in Taiwan. Total electron content (TEC) from the dual-frequency GPS observations is calculated and used as the reference, and TEC based on the Klobuchar model is compared with the reference. The residual is defined as the difference between the TEC from Klobuchar model and the reference. It is a parameter to reflect the absolute correction of the model. RMS correction percentage presents the validation of the model relative to the observations. The residuals' long-term variation, the RMS correction percentage, and their changes with the latitudes are analyzed respectively to access the model. In some months the RMS correction did not reach the goal of 50% purposed by Klobuchar, especially in the winter of the low solar activity years and at nighttime. RMS correction did not depend on the 11-years solar activity, neither the latitudes. Different from RMS correction, the residuals changed with the solar activity, similar to the variation of TEC. The residuals were large in the daytime, during the equinox seasons and in the high solar activity years; they are small at night, during the solstice seasons, and in the low activity years. During 1300-1500 BJT in the high solar activity years, the mean bias was negative, implying the model underestimated TEC on average. The maximum mean bias was 33TECU in April 2014, and the maximum underestimation reached 97TECU in October 2011. During 0000-0200 BJT, the residuals had small mean bias, small variation range and small standard deviation. It suggested that the model could describe the TEC of the ionosphere better than that in the daytime. Besides the variation with the solar activity, the residuals also vary with the latitudes. The means bias reached the maximum at 20-22°N, corresponding to the north crest of the equatorial anomaly. At this latitude, the maximum mean bias was 47TECU lower than the observation in the high activity years, and 12TECU lower in the low activity years. The minimum variation range appeared at 30-32°N in high and low activity years. But the minimum mean bias was at different latitudes in the high and low activity years. In the high activity years, it appeared at 30-32°N, and in the low years it was at 24-26°N. For an ideal model, the residuals should have small mean bias and small variation range. Further study is needed to learn the distribution of the residuals and to improve the model.

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

Dmitriev, Alexander S.; Yemelyanov, Ruslan Yu.; Moscow Institute of Physics and Technology

The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

Teaching Tip: Using Activity Diagrams to Model Systems Analysis Techniques: Teaching What We Preach

ERIC Educational Resources Information Center

Lending, Diane; May, Jeffrey

2013-01-01

Activity diagrams are used in Systems Analysis and Design classes as a visual tool to model the business processes of "as-is" and "to-be" systems. This paper presents the idea of using these same activity diagrams in the classroom to model the actual processes (practices and techniques) of Systems Analysis and Design. This tip…

Analysis and synthesis of distributed-lumped-active networks by digital computer

NASA Technical Reports Server (NTRS)

1973-01-01

The use of digital computational techniques in the analysis and synthesis of DLA (distributed lumped active) networks is considered. This class of networks consists of three distinct types of elements, namely, distributed elements (modeled by partial differential equations), lumped elements (modeled by algebraic relations and ordinary differential equations), and active elements (modeled by algebraic relations). Such a characterization is applicable to a broad class of circuits, especially including those usually referred to as linear integrated circuits, since the fabrication techniques for such circuits readily produce elements which may be modeled as distributed, as well as the more conventional lumped and active ones.

Dynamic modeling of nitrogen removal for a three-stage integrated fixed-film activated sludge process treating municipal wastewater.

PubMed

Moretti, Paul; Choubert, Jean-Marc; Canler, Jean-Pierre; Buffière, Pierre; Pétrimaux, Olivier; Lessard, Paul

2018-02-01

The integrated fixed-film activated sludge (IFAS) process is being increasingly used to enhance nitrogen removal for former activated sludge systems. The aim of this work is to evaluate a numerical model of a new nitrifying/denitrifying IFAS configuration. It consists of two carrier-free reactors (anoxic and aerobic) and one IFAS reactor with a filling ratio of 43% of carriers, followed by a clarifier. Simulations were carried out with GPS-X involving the nitrification reaction combined with a 1D heterogeneous biofilm model, including attachment/detachment processes. An original iterative calibration protocol was created comprising four steps and nine actions. Experimental campaigns were carried out to collect data on the pilot in operation, specifically for modelling purpose. The model used was able to predict properly the variations of the activated sludge (bulk) and the biofilm masses, the nitrification rates of both the activated sludge and the biofilm, and the nitrogen concentration in the effluent for short (4-10 days) and long (300 days) simulation runs. A calibrated parameter set is proposed (biokinetics, detachment, diffusion) related to the activated sludge, the biofilm and the effluent variables to enhance the model prediction on hourly and daily data sets.

Application of a rat hindlimb model: a prediction of force spaces reachable through stimulation of nerve fascicles.

PubMed

Johnson, Will L; Jindrich, Devin L; Zhong, Hui; Roy, Roland R; Edgerton, V Reggie

2011-12-01

A device to generate standing or locomotion through chronically placed electrodes has not been fully developed due in part to limitations of clinical experimentation and the high number of muscle activation inputs of the leg. We investigated the feasibility of functional electrical stimulation paradigms that minimize the input dimensions for controlling the limbs by stimulating at nerve fascicles, utilizing a model of the rat hindlimb, which combined previously collected morphological data with muscle physiological parameters presented herein. As validation of the model, we investigated the suitability of a lumped-parameter model for the prediction of muscle activation during dynamic tasks. Using the validated model, we found that the space of forces producible through activation of muscle groups sharing common nerve fascicles was nonlinearly dependent on the number of discrete muscle groups that could be individually activated (equivalently, the neuroanatomical level of activation). Seven commonly innervated muscle groups were sufficient to produce 78% of the force space producible through individual activation of the 42 modeled hindlimb muscles. This novel, neuroanatomically derived reduction in input dimension emphasizes the potential to simplify controllers for functional electrical stimulation to improve functional recovery after a neuromuscular injury.

Application of a Rat Hindlimb Model: A Prediction of Force Spaces Reachable Through Stimulation of Nerve Fascicles

PubMed Central

Johnson, Will L.; Jindrich, Devin L.; Zhong, Hui; Roy, Roland R.

2011-01-01

A device to generate standing or locomotion through chronically placed electrodes has not been fully developed due in part to limitations of clinical experimentation and the high number of muscle activation inputs of the leg. We investigated the feasibility of functional electrical stimulation paradigms that minimize the input dimensions for controlling the limbs by stimulating at nerve fascicles, utilizing a model of the rat hindlimb which combined previously collected morphological data with muscle physiological parameters presented herein. As validation of the model we investigated the suitability of a lumped-parameter model for prediction of muscle activation during dynamic tasks. Using the validated model we found that the space of forces producible through activation of muscle groups sharing common nerve fascicles was nonlinearly dependent on the number of discrete muscle groups that could be individually activated (equivalently, the neuroanatomical level of activation). Seven commonly innervated muscle groups were sufficient to produce 78% of the force space producible through individual activation of the 42 modeled hindlimb muscles. This novel, neuroanatomically derived reduction in input dimension emphasizes the potential to simplify controllers for functional electrical stimulation to improve functional recovery after a neuromuscular injury. PMID:21244999

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

Antitumor Activity of the Investigational Proteasome Inhibitor MLN9708 in Mouse Models of B-cell and Plasma Cell Malignancies

PubMed Central

Lee, Edmund C.; Fitzgerald, Michael; Bannerman, Bret; Donelan, Jill; Bano, Kristen; Terkelsen, Jennifer; Bradley, Daniel P.; Subakan, Ozlem; Silva, Matthew D.; Liu, Ray; Pickard, Michael; Li, Zhi; Tayber, Olga; Li, Ping; Hales, Paul; Carsillo, Mary; Neppalli, Vishala T.; Berger, Allison J.; Kupperman, Erik; Manfredi, Mark; Bolen, Joseph B.; Van Ness, Brian; Janz, Siegfried

2012-01-01

Purpose The clinical success of the first-in-class proteasome inhibitor bortezomib (VELCADE) has validated the proteasome as a therapeutic target for treating human cancers. MLN9708 is an investigational proteasome inhibitor that, compared with bortezomib, has improved pharmacokinetics, pharmacodynamics, and antitumor activity in preclinical studies. Here, we focused on evaluating the in vivo activity of MLN2238 (the biologically active form of MLN9708) in a variety of mouse models of hematologic malignancies, including tumor xenograft models derived from a human lymphoma cell line and primary human lymphoma tissue, and genetically engineered mouse (GEM) models of plasma cell malignancies (PCM). Experimental Design Both cell line–derived OCI-Ly10 and primary human lymphoma–derived PHTX22L xenograft models of diffuse large B-cell lymphoma were used to evaluate the pharmacodynamics and antitumor effects of MLN2238 and bortezomib. The iMycCα/Bcl-XL GEM model was used to assess their effects on de novo PCM and overall survival. The newly developed DP54-Luc–disseminated model of iMycCα/ Bcl-XL was used to determine antitumor activity and effects on osteolytic bone disease. Results MLN2238 has an improved pharmacodynamic profile and antitumor activity compared with bortezomib in both OCI-Ly10 and PHTX22L models. Although both MLN2238 and bortezomib prolonged overall survival, reduced splenomegaly, and attenuated IgG2a levels in the iMycCα/Bcl-XL GEM model, only MLN2238 alleviated osteolytic bone disease in the DP54-Luc model. Conclusions Our results clearly showed the antitumor activity of MLN2238 in a variety of mouse models of B-cell lymphoma and PCM, supporting its clinical development. MLN9708 is being evaluated in multiple phase I and I/II trials. PMID:21903769

Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High-Throughput Screening Assays for the Estrogen Receptor

PubMed Central

Judson, Richard S.; Magpantay, Felicia Maria; Chickarmane, Vijay; Haskell, Cymra; Tania, Nessy; Taylor, Jean; Xia, Menghang; Huang, Ruili; Rotroff, Daniel M.; Filer, Dayne L.; Houck, Keith A.; Martin, Matthew T.; Sipes, Nisha; Richard, Ann M.; Mansouri, Kamel; Setzer, R. Woodrow; Knudsen, Thomas B.; Crofton, Kevin M.; Thomas, Russell S.

2015-01-01

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation, and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform (“assay interference”). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 111 (6.1%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in vivo endocrine testing. Finally, this model is generalizable to any molecular pathway for which there are multiple upstream and downstream assays available. PMID:26272952

ADVANCED UTILITY SIMULATION MODEL, REPORT OF SENSITIVITY TESTING, CALIBRATION, AND MODEL OUTPUT COMPARISONS (VERSION 3.0)

EPA Science Inventory

The report gives results of activities relating to the Advanced Utility Simulation Model (AUSM): sensitivity testing. comparison with a mature electric utility model, and calibration to historical emissions. The activities were aimed at demonstrating AUSM's validity over input va...

A measurement error model for physical activity level as measured by a questionnaire with application to the 1999-2006 NHANES questionnaire.

PubMed

Tooze, Janet A; Troiano, Richard P; Carroll, Raymond J; Moshfegh, Alanna J; Freedman, Laurence S

2013-06-01

Systematic investigations into the structure of measurement error of physical activity questionnaires are lacking. We propose a measurement error model for a physical activity questionnaire that uses physical activity level (the ratio of total energy expenditure to basal energy expenditure) to relate questionnaire-based reports of physical activity level to true physical activity levels. The 1999-2006 National Health and Nutrition Examination Survey physical activity questionnaire was administered to 433 participants aged 40-69 years in the Observing Protein and Energy Nutrition (OPEN) Study (Maryland, 1999-2000). Valid estimates of participants' total energy expenditure were also available from doubly labeled water, and basal energy expenditure was estimated from an equation; the ratio of those measures estimated true physical activity level ("truth"). We present a measurement error model that accommodates the mixture of errors that arise from assuming a classical measurement error model for doubly labeled water and a Berkson error model for the equation used to estimate basal energy expenditure. The method was then applied to the OPEN Study. Correlations between the questionnaire-based physical activity level and truth were modest (r = 0.32-0.41); attenuation factors (0.43-0.73) indicate that the use of questionnaire-based physical activity level would lead to attenuated estimates of effect size. Results suggest that sample sizes for estimating relationships between physical activity level and disease should be inflated, and that regression calibration can be used to provide measurement error-adjusted estimates of relationships between physical activity and disease.

Face-to-face comparison of the predictive validity of two models of neuropathic pain in the rat: analgesic activity of pregabalin, tramadol and duloxetine.

PubMed

Le Cudennec, Camille; Castagné, Vincent

2014-07-15

We compared the preclinical analgesic activity of three marketed drugs with different pharmacological properties, pregabalin, tramadol and duloxetine, described as effective against neuropathic pain in the clinic. These drugs were tested against evoked pain in two different neuropathic models in the rat, the Bennett (CCI) and the Chung (SNL) models. The selected endpoints were tactile allodynia, tactile hyperalgesia, heat hyperalgesia and cold allodynia. Although all three drugs displayed analgesic activity, the effects observed varied according to the behavioral evaluation. Pregabalin showed clear analgesic effects against cold allodynia and tactile hyperalgesia in both the CCI and Chung models. Tramadol was active against all four endpoints in the Chung model with similar effects in the CCI model, apart from tactile allodynia. Duloxetine inhibited tactile allodynia and heat hyperalgesia in both neuropathic pain models. It also displayed efficacy against tactile hyperalgesia in the CCI model and against cold allodynia in the Chung model. These data confirm that the CCI and the Chung models of neuropathic pain do not detect the activity of analgesics with the same sensitivity. Furthermore, the mode of stimulation (tactile or thermal) and the type of endpoint (allodynia or hyperalgesia) can further influence the observed efficacy of gold standards as well as novel compounds developed for treating neuropathic pain symptoms. Copyright © 2014. Published by Elsevier B.V.

Spiking and bursting patterns of fractional-order Izhikevich model

NASA Astrophysics Data System (ADS)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Estimation of ice activation parameters within a particle tracking Lagrangian cloud model using the ensemble Kalman filter to match ISCDAC golden case observations

NASA Astrophysics Data System (ADS)

Reisner, J. M.; Dubey, M. K.

2010-12-01

To both quantify and reduce uncertainty in ice activation parameterizations for stratus clouds occurring in the temperature range between -5 to -10 C ensemble simulations of an ISDAC golden case have been conducted. To formulate the ensemble, three parameters found within an ice activation model have been sampled using a Latin hypercube technique over a parameter range that induces large variability in both number and mass of ice. The ice activation model is contained within a Lagrangian cloud model that simulates particle number as a function of radius for cloud ice, snow, graupel, cloud, and rain particles. A unique aspect of this model is that it produces very low levels of numerical diffusion that enable the model to accurately resolve the sharp cloud edges associated with the ISDAC stratus deck. Another important aspect of the model is that near the cloud edges the number of particles can be significantly increased to reduce sampling errors and accurately resolve physical processes such as collision-coalescence that occur in this region. Thus, given these relatively low numerical errors, as compared to traditional bin models, the sensitivity of a stratus deck to changes in parameters found within the activation model can be examined without fear of numerical contamination. Likewise, once the ensemble has been completed, ISDAC observations can be incorporated into a Kalman filter to optimally estimate the ice activation parameters and reduce overall model uncertainty. Hence, this work will highlight the ability of an ensemble Kalman filter system coupled to a highly accurate numerical model to estimate important parameters found within microphysical parameterizations containing high uncertainty.

Comparative Sensitivity Analysis of Muscle Activation Dynamics

PubMed Central

Günther, Michael; Götz, Thomas

2015-01-01

We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Modelling of active layer thickness evolution on James Ross Island in 2006-2015

NASA Astrophysics Data System (ADS)

Hrbáček, Filip; Uxa, Tomáš

2017-04-01

Antarctic Peninsula region has been considered as one of the most rapidly warming areas on the Earth. However, the recent studies (Turner et al., 2016; Oliva et al., 2017) showed that significant air temperature cooling began around 2000 and has continued until present days. The climate cooling led to reduction of active layer thickness in several parts of Antarctic Peninsula region during decade 2006-2015, but the information about spatiotemporal variability of active layer thickness across the region remains largely incoherent due to lack of active layer temperature data from deeper profiles. Valuable insights into active layer thickness evolution in Antarctic Peninsula region can be, however, provided by thermal modelling techniques. These have been widely used to study the active layer dynamics in different regions of Arctic since 1990s. By contrast, they have been employed much less in Antarctica. In this study, we present our first results from two equilibrium models, the Stefan and Kudryavtsev equations, that were applied to calculate the annual active layer thickness based on ground temperature data from depth of 5 cm on one site on James Ross Island, Eastern Antarctic Peninsula, in period 2006/07 to 2014/15. Study site (Abernethy Flats) is located in the central part of the major ice-free area of James Ross Island called Ulu Peninsula. Monitoring of air temperature 2 m above ground surface and ground temperature in 50 cm profile began on January 2006. The profile was extended under the permafrost table down to 75 cm in February 2012, which allowed precise determination of active layer thickness, defined as a depth of 0°C isotherm, in period 2012 to 2015. The active layer thickness in the entire observation period was reconstructed using the Stefan and Kudryavtsev models, which were driven by ground temperature data from depth of 5 cm and physical parameters of the ground obtained by laboratory analyses (moisture content and bulk density) and calculations from ground heat flux measurement (thermal conductivity and thermal capacity). Model results were validated using the reference active layer thicknesses from the summer seasons of 2012/13 to 2014/15 with very good accuracy of 0 to 4 cm and -4 to 1 cm for the Stefan and the Kudryavtsev models, respectively. Average active layer thickness on Abernethy Flats varied between 62 cm (Stefan model) and 60 cm (Kudryavtsev model) in period 2006/07-2014/15. Both models showed average active layer thinning of -1.3 cm.year-1 (Stefan model) and -2.3 cm.year-1 (Kudryavtsev model). Maximum active layer thickness was predicted in summer season 2008/09, reaching 75 cm (Stefan model) and 83 cm (Kudryavtsev model), while the minimum active layer thickness was observed in summer season 2009/10 when both models predicted 36 cm. Our results show that both models are well suited for conditions of Antarctica because their accuracy is in the order of the first centimetres. The nine-year series confirmed thinning of active layer in this part of Antarctic Peninsula region, which was mainly related to variability of summer air temperature. References: Turner, J., Lu, H., White, I., King, J. C., Phillips, T., Scott Hosking, J. Bracegirdle, T. J.,Marshall, G. J., Mulvaney, R., Deb, P., 2016. Absence of 21st century warming on Antarctic Peninsula consistent with natural variability. Nature 535, doi: 10.1038/nature18645 Oliva, M., Navarro, F., Hrbáček, F., Hernandéz, A., Nývlt, D., Perreira, P., Ruiz-Fernandéz, J., Trigo, R., in press. Recent regional climate cooling on the Antarctic Peninsula and associated impacts on the cryosphere. Science of Total Environment. dx.doi.org/10.1016/j.scitotenv.2016.12.030

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.

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.

Two-state model of light induced activation and thermal bleaching of photochromic glasses: theory and experiments

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

Ferrari, Jose A.; Perciante, Cesar D

2008-07-10

The behavior of photochromic glasses during activation and bleaching is investigated. A two-state phenomenological model describing light-induced activation (darkening) and thermal bleaching is presented. The proposed model is based on first-order kinetics. We demonstrate that the time behavior in the activation process (acting simultaneously with the thermal fading) can be characterized by two relaxation times that depend on the intensity of the activating light. These characteristic times are lower than the decay times of the pure thermal bleaching process. We study the temporal evolution of the glass optical density and its dependence on the activating intensity. We also present amore » series of activation and bleaching experiments that validate the proposed model. Our approach may be used to gain more insight into the transmittance behavior of photosensitive glasses, which could be potentially relevant in a broad range of applications, e.g., real-time holography and reconfigurable optical memories.« less

Modeling financial markets by the multiplicative sequence of trades

NASA Astrophysics Data System (ADS)

Gontis, V.; Kaulakys, B.

2004-12-01

We introduce the stochastic multiplicative point process modeling trading activity of financial markets. Such a model system exhibits power-law spectral density S(f)∝1/fβ, scaled as power of frequency for various values of β between 0.5 and 2. Furthermore, we analyze the relation between the power-law autocorrelations and the origin of the power-law probability distribution of the trading activity. The model reproduces the spectral properties of trading activity and explains the mechanism of power-law distribution in real markets.

Building chemistry one atom at a time: An investigation of the effects of two curricula in students' understanding of covalent bonding and atomic size

NASA Astrophysics Data System (ADS)

Bull, Barbara Jeanne

Chemists have to rely on models to aid in the explanation of phenomena they experience. Instruction of atomic theory has been used as the introduction and primary model for many concepts in chemistry. Therefore, it is important for students to have a robust understanding of the different atomic models, their relationships and their limitations. Previous research has shown that students have alternative conceptions concerning their interpretation of atomic models, but there is less exploration into how students apply their understanding of atomic structure to other chemical concepts. Therefore, this research concentrated on the development of three Model Eliciting Activities to investigate the most fundamental topic of the atom and how students applied their atomic model to covalent bonding and atomic size. Along with the investigation into students' use of their atomic models, a comparison was included between a traditional chemistry curriculum using an Atoms First approach and Chemistry, Life, the Universe and Everything (CLUE), a NSF-funded general chemistry curriculum. Treatment and Control groups were employed to determine the effectiveness of the curricula in conveying the relationship between atoms, covalent bonds and atomic size. The CLUE students developed a Cloud representation on the Atomic Model Eliciting Activity and maintained this depiction through the Covalent Bonding Model Eliciting Activity. The traditional students more often illustrated the atom using a Bohr representation and continued to apply the same model to their portrayal of covalent bonding. During the analysis of the Atomic Size Model Eliciting Activity, students had difficulty fully supporting their explanation of the atomic size trend. Utilizing the beSocratic platform, an activity was designed to aid students' construction of explanations using Toulmin's Argumentation Pattern. In order to study the effectiveness of the activity, the students were asked questions relating to a four-week long investigation into the identity of an inorganic salt during their laboratory class. Students who completed the activity exhibited an improvement in their explanation of the identity of their salt's cation. After completing the activity, another question was posed about the identity of their anion. Both groups saw a decrease in the percentage of students who included reasoning in their answer; however, the activity group maintained a significantly higher percentage of responses with a reasoning than the control group.

Modelling the vicious circle between obesity and physical activity in children and adolescents using a bivariate probit model with endogenous regressors.

PubMed

Yeh, C-Y; Chen, L-J; Ku, P-W; Chen, C-M

2015-01-01

The increasing prevalence of obesity in children and adolescents has become one of the most important public health issues around the world. Lack of physical activity is a risk factor for obesity, while being obese could reduce the likelihood of participating in physical activity. Failing to account for the endogeneity between obesity and physical activity would result in biased estimation. This study investigates the relationship between overweight and physical activity by taking endogeneity into consideration. It develops an endogenous bivariate probit model estimated by the maximum likelihood method. The data included 4008 boys and 4197 girls in the 5th-9th grades in Taiwan in 2007-2008. The relationship between overweight and physical activity is significantly negative in the endogenous model, but insignificant in the comparative exogenous model. This endogenous relationship presents a vicious circle in which lower levels of physical activity lead to overweight, while those who are already overweight engage in less physical activity. The results not only reveal the importance of endogenous treatment, but also demonstrate the robust negative relationship between these two factors. An emphasis should be put on overweight and obese children and adolescents in order to break the vicious circle. Promotion of physical activity by appropriate counselling programmes and peer support could be effective in reducing the prevalence of obesity in children and adolescents.

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…

Seizures, refractory status epilepticus, and depolarization block as endogenous brain activities

NASA Astrophysics Data System (ADS)

El Houssaini, Kenza; Ivanov, Anton I.; Bernard, Christophe; Jirsa, Viktor K.

2015-01-01

Epilepsy, refractory status epilepticus, and depolarization block are pathological brain activities whose mechanisms are poorly understood. Using a generic mathematical model of seizure activity, we show that these activities coexist under certain conditions spanning the range of possible brain activities. We perform a detailed bifurcation analysis and predict strategies to escape from some of the pathological states. Experimental results using rodent data provide support of the model, highlighting the concept that these pathological activities belong to the endogenous repertoire of brain activities.

GEANT4 benchmark with MCNPX and PHITS for activation of concrete

NASA Astrophysics Data System (ADS)

Tesse, Robin; Stichelbaut, Frédéric; Pauly, Nicolas; Dubus, Alain; Derrien, Jonathan

2018-02-01

The activation of concrete is a real problem from the point of view of waste management. Because of the complexity of the issue, Monte Carlo (MC) codes have become an essential tool to its study. But various codes or even nuclear models exist in MC. MCNPX and PHITS have already been validated for shielding studies but GEANT4 is also a suitable solution. In these codes, different models can be considered for a concrete activation study. The Bertini model is not the best model for spallation while BIC and INCL model agrees well with previous results in literature.

Selecting university undergraduate student activities via compromised-analytical hierarchy process and 0-1 integer programming to maximize SETARA points

NASA Astrophysics Data System (ADS)

Nazri, Engku Muhammad; Yusof, Nur Ai'Syah; Ahmad, Norazura; Shariffuddin, Mohd Dino Khairri; Khan, Shazida Jan Mohd

2017-11-01

Prioritizing and making decisions on what student activities to be selected and conducted to fulfill the aspiration of a university as translated in its strategic plan must be executed with transparency and accountability. It is becoming even more crucial, particularly for universities in Malaysia with the recent budget cut imposed by the Malaysian government. In this paper, we illustrated how 0-1 integer programming (0-1 IP) model was implemented to select which activities among the forty activities proposed by the student body of Universiti Utara Malaysia (UUM) to be implemented for the 2017/2018 academic year. Two different models were constructed. The first model was developed to determine the minimum total budget that should be given to the student body by the UUM management to conduct all the activities that can fulfill the minimum targeted number of activities as stated in its strategic plan. On the other hand, the second model was developed to determine which activities to be selected based on the total budget already allocated beforehand by the UUM management towards fulfilling the requirements as set in its strategic plan. The selection of activities for the second model, was also based on the preference of the members of the student body whereby the preference value for each activity was determined using Compromised-Analytical Hierarchy Process. The outputs from both models were compared and discussed. The technique used in this study will be useful and suitable to be implemented by organizations with key performance indicator-oriented programs and having limited budget allocation issues.

The associations between increasing degrees of homeostatic model assessment for insulin resistance and muscular strengthening activities among euglycaemic US adults.

PubMed

Boyer, William R; Johnson, Tammie M; Fitzhugh, Eugene C; Richardson, Michael R; Churilla, James R

2015-11-01

To examine the associations between the homeostatic model assessment for insulin resistance and self-reported muscular strengthening activity in a nationally representative sample of euglycaemic US adults. Sample included euglycaemic adults (⩾20 years of age (n = 2009)) from the 1999 to 2004 National Health and Nutrition Examination Survey. Homeostatic model assessment for insulin resistance was categorized into quartiles and was the primary independent variable of interest. No reported muscular strengthening activity was the dependent variable. Following adjustment for covariates, those with homeostatic model assessment for insulin resistance values in fourth (odds ratio: 2.04, 95% confidence interval: 1.35-3.06, p < 0.001) quartile were found to have significantly greater odds of reporting no muscular strengthening activity. Following further adjustment for non-muscular strengthening activity specific aerobic leisure-time physical activity, results remained significant for the fourth (odds ratio: 2.30, 95% confidence interval: 1.50-3.52, p < 0.001) quartile. A significant trend was seen across quartiles of homeostatic model assessment for insulin resistance for increasing prevalence of no muscular strengthening activity (p < 0.001). Having a higher homeostatic model assessment for insulin resistance value is associated with greater odds of reporting no muscular strengthening activity among euglycaemic US adults. This implies that subjects with an increasing degree of insulin resistance are more likely to not engage in muscular strengthening activity, an exercise modality that has been shown to reduce the risk of several cardiometabolic diseases and improve glycaemic status. © The Author(s) 2015.

Modelling the maximum voluntary joint torque/angular velocity relationship in human movement.

PubMed

Yeadon, Maurice R; King, Mark A; Wilson, Cassie

2006-01-01

The force exerted by a muscle is a function of the activation level and the maximum (tetanic) muscle force. In "maximum" voluntary knee extensions muscle activation is lower for eccentric muscle velocities than for concentric velocities. The aim of this study was to model this "differential activation" in order to calculate the maximum voluntary knee extensor torque as a function of knee angular velocity. Torque data were collected on two subjects during maximal eccentric-concentric knee extensions using an isovelocity dynamometer with crank angular velocities ranging from 50 to 450 degrees s(-1). The theoretical tetanic torque/angular velocity relationship was modelled using a four parameter function comprising two rectangular hyperbolas while the activation/angular velocity relationship was modelled using a three parameter function that rose from submaximal activation for eccentric velocities to full activation for high concentric velocities. The product of these two functions gave a seven parameter function which was fitted to the joint torque/angular velocity data, giving unbiased root mean square differences of 1.9% and 3.3% of the maximum torques achieved. Differential activation accounts for the non-hyperbolic behaviour of the torque/angular velocity data for low concentric velocities. The maximum voluntary knee extensor torque that can be exerted may be modelled accurately as the product of functions defining the maximum torque and the maximum voluntary activation level. Failure to include differential activation considerations when modelling maximal movements will lead to errors in the estimation of joint torque in the eccentric phase and low velocity concentric phase.

Testing a self-determination theory model of children's physical activity motivation: a cross-sectional study.

PubMed

Sebire, Simon J; Jago, Russell; Fox, Kenneth R; Edwards, Mark J; Thompson, Janice L

2013-09-26

Understanding children's physical activity motivation, its antecedents and associations with behavior is important and can be advanced by using self-determination theory. However, research among youth is largely restricted to adolescents and studies of motivation within certain contexts (e.g., physical education). There are no measures of self-determination theory constructs (physical activity motivation or psychological need satisfaction) for use among children and no previous studies have tested a self-determination theory-based model of children's physical activity motivation. The purpose of this study was to test the reliability and validity of scores derived from scales adapted to measure self-determination theory constructs among children and test a motivational model predicting accelerometer-derived physical activity. Cross-sectional data from 462 children aged 7 to 11 years from 20 primary schools in Bristol, UK were analysed. Confirmatory factor analysis was used to examine the construct validity of adapted behavioral regulation and psychological need satisfaction scales. Structural equation modelling was used to test cross-sectional associations between psychological need satisfaction, motivation types and physical activity assessed by accelerometer. The construct validity and reliability of the motivation and psychological need satisfaction measures were supported. Structural equation modelling provided evidence for a motivational model in which psychological need satisfaction was positively associated with intrinsic and identified motivation types and intrinsic motivation was positively associated with children's minutes in moderate-to-vigorous physical activity. The study provides evidence for the psychometric properties of measures of motivation aligned with self-determination theory among children. Children's motivation that is based on enjoyment and inherent satisfaction of physical activity is associated with their objectively-assessed physical activity and such motivation is positively associated with perceptions of psychological need satisfaction. These psychological factors represent potential malleable targets for interventions to increase children's physical activity.

Modelling Typical Online Language Learning Activity

ERIC Educational Resources Information Center

Montoro, Carlos; Hampel, Regine; Stickler, Ursula

2014-01-01

This article presents the methods and results of a four-year-long research project focusing on the language learning activity of individual learners using online tasks conducted at the University of Guanajuato (Mexico) in 2009-2013. An activity-theoretical model (Blin, 2010; Engeström, 1987) of the typical language learning activity was used to…

Intentional Development: A Model to Guide Lifelong Physical Activity

ERIC Educational Resources Information Center

Cherubini, Jeffrey M.

2009-01-01

Framed in the context of researching influences on physical activity and actually working with individuals and groups seeking to initiate, increase or maintain physical activity, the purpose of this review is to present the model of Intentional Development as a multi-theoretical approach to guide research and applied work in physical activity.…

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

Incorporating learning goals about modeling into an upper-division physics laboratory experiment

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin M.; Finkelstein, Noah; Lewandowski, H. J.

2014-09-01

Implementing a laboratory activity involves a complex interplay among learning goals, available resources, feedback about the existing course, best practices for teaching, and an overall philosophy about teaching labs. Building on our previous work, which described a process of transforming an entire lab course, we now turn our attention to how an individual lab activity on the polarization of light was redesigned to include a renewed emphasis on one broad learning goal: modeling. By using this common optics lab as a concrete case study of a broadly applicable approach, we highlight many aspects of the activity development and show how modeling is used to integrate sophisticated conceptual and quantitative reasoning into the experimental process through the various aspects of modeling: constructing models, making predictions, interpreting data, comparing measurements with predictions, and refining models. One significant outcome is a natural way to integrate an analysis and discussion of systematic error into a lab activity.

Modelling carbon oxidation in pulp mill activated sludge systems: calibration of Activated Sludge Model No 3.

PubMed

Barañao, P A; Hall, E R

2004-01-01

Activated Sludge Model No 3 (ASM3) was chosen to model an activated sludge system treating effluents from a mechanical pulp and paper mill. The high COD concentration and the high content of readily biodegradable substrates of the wastewater make this model appropriate for this system. ASM3 was calibrated based on batch respirometric tests using fresh wastewater and sludge from the treatment plant, and on analytical measurements of COD, TSS and VSS. The model, developed for municipal wastewater, was found suitable for fitting a variety of respirometric batch tests, performed at different temperatures and food to microorganism ratios (F/M). Therefore, a set of calibrated parameters, as well as the wastewater COD fractions, was estimated for this industrial wastewater. The majority of the calibrated parameters were in the range of those found in the literature.

A passive and active microwave-vector radiative transfer (PAM-VRT) model

NASA Astrophysics Data System (ADS)

Yang, Jun; Min, Qilong

2015-11-01

A passive and active microwave vector radiative transfer (PAM-VRT) package has been developed. This fast and accurate forward microwave model, with flexible and versatile input and output components, self-consistently and realistically simulates measurements/radiation of passive and active microwave sensors. The core PAM-VRT, microwave radiative transfer model, consists of five modules: gas absorption (two line-by-line databases and four fast models); hydrometeor property of water droplets and ice (spherical and nonspherical) particles; surface emissivity (from Community Radiative Transfer Model (CRTM)); vector radiative transfer of successive order of scattering (VSOS); and passive and active microwave simulation. The PAM-VRT package has been validated against other existing models, demonstrating good accuracy. The PAM-VRT not only can be used to simulate or assimilate measurements of existing microwave sensors, but also can be used to simulate observation results at some new microwave sensors.

Space Weather Products at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse, Michael; Kuznetsova, M.; Pulkkinen, A.; Maddox, M.; Rastaetter, L.; Berrios, D.; MacNeice, P.

2010-01-01

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 CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of space weather forecasting tools. Owing to the pace of development in the science community, new model capabilities emerge frequently. Consequently, space weather products and tools involve not only increased validity, but often entirely new capabilities. This presentation will review the present state of space weather tools as well as point out emerging future capabilities.

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

QSAR modeling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines

NASA Astrophysics Data System (ADS)

Masand, Vijay H.; El-Sayed, Nahed N. E.; Mahajan, Devidas T.; Mercader, Andrew G.; Alafeefy, Ahmed M.; Shibi, I. G.

2017-02-01

In the present work, sixty substituted 2-Phenylimidazopyridines previously reported with potent anti-human African trypanosomiasis (HAT) activity were selected to build genetic algorithm (GA) based QSAR models to determine the structural features that have significant correlation with the activity. Multiple QSAR models were built using easily interpretable descriptors that are directly associated with the presence or the absence of a structural scaffold, or a specific atom. All the QSAR models have been thoroughly validated according to the OECD principles. All the QSAR models are statistically very robust (R2 = 0.80-0.87) with high external predictive ability (CCCex = 0.81-0.92). The QSAR analysis reveals that the HAT activity has good correlation with the presence of five membered rings in the molecule.

Preterm labor--modeling the uterine electrical activity from cellular level to surface recording.

PubMed

Rihana, S; Marque, C

2008-01-01

Uterine electrical activity is correlated to the appearance of uterine contractions. forceful contractions appear at the end of term. Therefore, understanding the genesis and the propagation of uterine electrical activity may provide an efficient tool to diagnose preterm labor. Moreover, the control of uterine excitability seems to have important consequences in the control of preterm labor. Modeling the electrical activity in uterine tissue is thus an important step in understanding physiological uterine contractile mechanisms and to permit uterine EMG simulation. Our model presented in this paper, incorporates ion channel models at the cell level, the reaction diffusion equations at the tissue level and the spatiotemporal integration at the uterine EMG reconstructed level. This model validates some key physiological observation hypotheses concerning uterine excitability and propagation.

Predicting physical activity and fruit and vegetable intake in adolescents: a test of the information, motivation, behavioral skills model.

PubMed

Kelly, Stephanie; Melnyk, Bernadette Mazurek; Belyea, Michael

2012-04-01

Most adolescents do not meet national recommendations regarding physical activity and/or the intake of fruits and vegetables. The purpose of this study was to explore whether variables in the information, motivation, behavioral skills (IMB) model of health promotion predicted physical activity and fruit and vegetable intake in 404 adolescents from 2 high schools in the Southwest United States using structural equation modeling (SEM). The SEM models included theoretical constructs, contextual variables, and moderators. The theoretical relationships in the IMB model were confirmed and were moderated by gender and race. Interventions that incorporate cognitive-behavioral skills building may be a key factor for promoting physical activity as well as fruit and vegetable intake in adolescents. Copyright © 2012 Wiley Periodicals, Inc.

The Health Action Process Approach as a motivational model for physical activity self-management for people with multiple sclerosis: a path analysis.

PubMed

Chiu, Chung-Yi; Lynch, Ruth T; Chan, Fong; Berven, Norman L

2011-08-01

To evaluate the Health Action Process Approach (HAPA) as a motivational model for physical activity self-management for people with multiple sclerosis (MS). Quantitative descriptive research design using path analysis. One hundred ninety-five individuals with MS were recruited from the National Multiple Sclerosis Society and a neurology clinic at a university teaching hospital in the Midwest. Outcome was measured by the Physical Activity Stages of Change Instrument, along with measures for nine predictors (severity, action self-efficacy, outcome expectancy, risk perception, perceived barriers, intention, maintenance self-efficacy, action and coping planning, and recovery self-efficacy). The respecified HAPA physical activity model fit the data relatively well (goodness-of-fit index = .92, normed fit index = .91, and comparative fit index = .93) explaining 38% of the variance in physical activity. Recovery self-efficacy, action and coping planning, and perceived barriers directly contributed to the prediction of physical activity. Outcome expectancy significantly influenced intention and the relationship between intention and physical activity is mediated by action and coping planning. Action self-efficacy, maintenance self-efficacy, and recovery self-efficacy directly or indirectly affected physical activity. Severity of MS and action self-efficacy had an inverse relationship with perceived barriers and perceived barriers influenced physical activity. Empirical support was found for the proposed HAPA model of physical activity for people with MS. The HAPA model appears to provide useful information for clinical rehabilitation and health promotion interventions.

Activated carbon from pyrolysis of brewer's spent grain: Production and adsorption properties.

PubMed

Vanreppelen, Kenny; Vanderheyden, Sara; Kuppens, Tom; Schreurs, Sonja; Yperman, Jan; Carleer, Robert

2014-07-01

Brewer's spent grain is a low cost residue generated by the brewing industry. Its chemical composition (high nitrogen content 4.35 wt.%, fibres, etc.) makes it very useful for the production of added value in situ nitrogenised activated carbon. The composition of brewer's spent grain revealed high amounts of cellulose (20.8 wt.%), hemicellulose (48.78 wt.%) and lignin (11.3 wt.%). The fat, ethanol extractives and ash accounted for 8.17 wt.%, 4.7 wt.% and 3.2 wt.%, respectively. Different activated carbons were produced in a lab-scale pyrolysis/activation reactor by applying several heat and steam activation profiles on brewer's spent grain. Activated carbon yields from 16.1 to 23.6 wt.% with high N-contents (> 2 wt.%) were obtained. The efficiency of the prepared activated carbons for phenol adsorption was studied as a function of different parameters: pH, contact time and carbon dosage relative to two commercial activated carbons. The equilibrium isotherms were described by the non-linear Langmuir and Freundlich models, and the kinetic results were fitted using the pseudo-first-order model and the pseudo-second-order model. The feasibility of an activated carbon production facility (onsite and offsite) that processes brewer's spent grain for different input feeds is evaluated based on a techno-economic model for estimating the net present value. Even though the model assumptions start from a rather pessimistic scenario, encouraging results for a profitable production of activated carbon using brewer's spent grain are obtained. © The Author(s) 2014.

Influence of the piezoelectric parameters on the dynamics of an active rotor

NASA Astrophysics Data System (ADS)

Gawryluk, Jarosław; Mitura, Andrzej; Teter, Andrzej

2018-01-01

The main aim of this paper is an experimental and numerical analysis of the dynamic behavior of an active rotor with three composite blades. The study focuses on developing an effective FE modeling technique of a macro fiber composite element (denoted as MFC or active element) for the dynamic tests of active structures. The active rotor under consideration consists of a hub with a drive shaft, three grips and three glass-epoxy laminate blades with embedded active elements. A simplified FE model of the macro fiber composite element exhibiting the d33 piezoelectric effect is developed using the Abaqus software package. The discussed transducer is modeled as quasi-homogeneous piezoelectric material, and voltage is applied to the opposite faces of the element. In this case, the effective (equivalent) piezoelectric constant d33* is specified. Both static and dynamic tests are performed to verify the proposed model. First, static deflections of the active blade caused by the voltage signal are determined by numerical and experimental analyses. Next, a numerical modal analysis of the active rotor is performed. The eigenmodes and corresponding eigenfrequencies are determined by the Lanczos method. The influence of the model parameters (i.e., the effective piezoelectric constant d33 *, voltage signal, angular velocity) on the dynamics of the active rotor is examined. Finally, selected numerical results are validated in experimental tests. The experimental findings demonstrate that the structural stiffening effect caused by the active element strongly depends on the value of the effective piezoelectric constant.

Between the Rock and a Hard Place: The CCMC as a Transit Station Between Modelers and Forecasters

NASA Technical Reports Server (NTRS)

Hesse, Michael

2009-01-01

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 CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involved model evaluations, model transitions to operations, and the development of draft Space Weather forecasting tools. This presentation will focus on the latter element. Specifically, we will discuss the process of transition research models, or information generated by research models, to Space Weather Forecasting organizations. We will analyze successes as well as obstacles to further progress, and we will suggest avenues for increased transitioning success.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates

NASA Astrophysics Data System (ADS)

Barberis, Lucas; Peruani, Fernando

2016-12-01

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit—due to the VC that breaks Newton's third law—various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving—locally polar—files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates.

PubMed

Barberis, Lucas; Peruani, Fernando

2016-12-09

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit-due to the VC that breaks Newton's third law-various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving-locally polar-files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Active Subspaces for Wind Plant Surrogate Modeling

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

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

QSAR models for anti-malarial activity of 4-aminoquinolines.

PubMed

Masand, Vijay H; Toropov, Andrey A; Toropova, Alla P; Mahajan, Devidas T

2014-03-01

In the present study, predictive quantitative structure - activity relationship (QSAR) models for anti-malarial activity of 4-aminoquinolines have been developed. CORAL, which is freely available on internet (http://www.insilico.eu/coral), has been used as a tool of QSAR analysis to establish statistically robust QSAR model of anti-malarial activity of 4-aminoquinolines. Six random splits into the visible sub-system of the training and invisible subsystem of validation were examined. Statistical qualities for these splits vary, but in all these cases, statistical quality of prediction for anti-malarial activity was quite good. The optimal SMILES-based descriptor was used to derive the single descriptor based QSAR model for a data set of 112 aminoquinolones. All the splits had r(2)> 0.85 and r(2)> 0.78 for subtraining and validation sets, respectively. The three parametric multilinear regression (MLR) QSAR model has Q(2) = 0.83, R(2) = 0.84 and F = 190.39. The anti-malarial activity has strong correlation with presence/absence of nitrogen and oxygen at a topological distance of six.

The road plan model: Information model for planning road building activities

NASA Technical Reports Server (NTRS)

Azinhal, Rafaela K.; Moura-Pires, Fernando

1994-01-01

The general building contractor is presented with an information model as an approach for deriving a high-level work plan of construction activities applied to road building. Road construction activities are represented in a Road Plan Model (RPM), which is modeled in the ISO standard STEP/EXPRESS and adopts various concepts from the GARM notation. The integration with the preceding road design stage and the succeeding phase of resource scheduling is discussed within the framework of a Road Construction Model. Construction knowledge is applied to the road design and the terrain model of the surrounding road infrastructure for the instantiation of the RPM. Issues regarding the implementation of a road planner application supporting the RPM are discussed.

Role Models of Australian Female Adolescents: A Longitudinal Study to Inform Programmes Designed to Increase Physical Activity and Sport Participation

ERIC Educational Resources Information Center

Young, Janet A.; Symons, Caroline M.; Pain, Michelle D.; Harvey, Jack T.; Eime, Rochelle M.; Craike, Melinda J.; Payne, Warren R.

2015-01-01

In light of the importance attributed to the presence of positive role models in promoting physical activity during adolescence, this study examined role models of adolescent girls and their influence on physical activity. Seven hundred and thirty two girls in Years 7 and 11 from metropolitan and non-metropolitan regions of Victoria, Australia,…

Robust Active Portfolio Management

DTIC Science & Technology

2006-11-27

the Markowitz mean-variance model led to development of the Capital Asset Pricing Model ( CAPM ) for asset pricing [35, 29, 23] which remains one of the...active portfolio management. Our model uses historical returns and equilibrium expected returns predicted by the CAPM to identify assets that are...incorrectly priced in the market. There is a fundamental inconsistency between the CAPM and active portfolio management. The CAPM assumes that markets are

A redefinition of the representation of mammary cells and enzyme activities in a lactating dairy cow model.

PubMed

Hanigan, M D; Rius, A G; Kolver, E S; Palliser, C C

2007-08-01

The Molly model predicts various aspects of digestion and metabolism in the cow, including nutrient partitioning between milk and body stores. It has been observed previously that the model underpredicts milk component yield responses to nutrition and consequently overpredicts body energy store responses. In Molly, mammary enzyme activity is represented as an aggregate of mammary cell numbers and activity per cell with minimal endocrine regulation. Work by others suggests that mammary cells can cycle between active and quiescent states in response to various stimuli. Simple models of milk production have demonstrated the utility of this representation when using the model to simulate variable milking and nutrient restriction. It was hypothesized that replacing the current representation of mammary cells and enzyme activity in Molly with a representation of active and quiescent cells and improving the representation of endocrine control of cell activity would improve predictions of milk component yield. The static representation of cell numbers was replaced with a representation of cell growth during gestation and early lactation periods and first-order cell death. Enzyme capacity for fat and protein synthesis was assumed to be proportional to cell numbers. Enzyme capacity for lactose synthesis was represented with the same equation form as for cell numbers. Data used for parameter estimation were collected as part of an extended lactation trial. Cows with North American or New Zealand genotypes were fed 0, 3, or 6 kg of concentrate dry matter daily during a 600-d lactation. The original model had root mean square prediction errors of 17.7, 22.3, and 19.8% for lactose, protein, and fat yield, respectively, as compared with values of 8.3, 9.4, and 11.7% for the revised model, respectively. The original model predicted body weight with an error of 19.7% vs. 5.7% for the revised model. Based on these observations, it was concluded that representing mammary synthetic capacity as a function of active cell numbers and revisions to endocrine control of cell activity was meritorious.

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.

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.

Attributing runoff changes to climate variability and human activities: uncertainty analysis using four monthly water balance models

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

Li, Shuai; Xiong, Lihua; Li, Hong-Yi

2015-05-26

Hydrological simulations to delineate the impacts of climate variability and human activities are subjected to uncertainties related to both parameter and structure of the hydrological models. To analyze the impact of these uncertainties on the model performance and to yield more reliable simulation results, a global calibration and multimodel combination method that integrates the Shuffled Complex Evolution Metropolis (SCEM) and Bayesian Model Averaging (BMA) of four monthly water balance models was proposed. The method was applied to the Weihe River Basin (WRB), the largest tributary of the Yellow River, to determine the contribution of climate variability and human activities tomore » runoff changes. The change point, which was used to determine the baseline period (1956-1990) and human-impacted period (1991-2009), was derived using both cumulative curve and Pettitt’s test. Results show that the combination method from SCEM provides more skillful deterministic predictions than the best calibrated individual model, resulting in the smallest uncertainty interval of runoff changes attributed to climate variability and human activities. This combination methodology provides a practical and flexible tool for attribution of runoff changes to climate variability and human activities by hydrological models.« less

Beneficial effect of daidzin in dry eye rat model through the suppression of inflammation and oxidative stress in the cornea.

PubMed

Xiao, Fan; Cui, Hua; Zhong, Xiao

2018-05-01

Present investigation evaluates the effect of daidzin in dry eye rat model through the suppression of inflammation and oxidative stress in the cornea. Briefly, electron spine resonance was used for the estimation of radical scavenging activity of daidzin and COX Fluorescent Activity Assay Kit was used for the estimation of PGS activity. Dry eye rat model was developed by removing the lacrimal gland and effect of daidzin was evaluated in dry eye rat model by estimating the fluorescein score, tear volume and expressions of heme oxigenase (HO-1), TNF α, Interlukin 6 (IL-6), matrix metallopeptidase 9 (MMP-9) and PGS-2. Result of the present study suggested that daidzin possess tyrosyl radical scavenging activity and thereby decreases the oxidative stress. Activity of PGS significantly increases in dry eye which was inhibited by daidzin treatment due to competitive inhibition of PGS. It also recovers the tear volume in dry eye rat model in which lacrimal gland was removed. Thus corneal erosion was improved by daidzin in dry eye rat model. Thus present study concludes that treatment with daidzin protects the cornea in dry eye rat model by suppression inflammation and oxidative stress.

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.

A Lower Limb-Pelvis Finite Element Model with 3D Active Muscles.

PubMed

Mo, Fuhao; Li, Fan; Behr, Michel; Xiao, Zhi; Zhang, Guanjun; Du, Xianping

2018-01-01

A lower limb-pelvis finite element (FE) model with active three-dimensional (3D) muscles was developed in this study for biomechanical analysis of human body. The model geometry was mainly reconstructed from a male volunteer close to the anthropometry of a 50th percentile Chinese male. Tissue materials and structural features were established based on the literature and new implemented experimental tests. In particular, the muscle was modeled with a combination of truss and hexahedral elements to define its passive and active properties as well as to follow the detailed anatomy structure. Both passive and active properties of the model were validated against the experiments of Post-Mortem Human Surrogate (PMHS) and volunteers, respectively. The model was then used to simulate driver's emergency braking during frontal crashes and investigate Knee-Thigh-Hip (KTH) injury mechanisms and tolerances of the human body. A significant force and bending moment variance was noted for the driver's femur due to the effects of active muscle forces during emergency braking. In summary, the present lower limb-pelvis model can be applied in various research fields to support expensive and complex physical tests or corresponding device design.

Inference evaluation in a finite evidence domain

NASA Astrophysics Data System (ADS)

Ratway, Michael J.; Bellomo, Carryn

2000-08-01

Modeling of a target starts with a subject matter expert (SME) analysis of the available sensor(s) data. The SME then forms relationships between the data and known target attributes, called evidence, to support modeling of different types of targets or target activity. Speeds in the interval 10 to 30 knots and ranges less than 30 nautical miles are two samples of target evidence derived from sensor data. Evidence is then organized into sets to define the activities of a target and/or to distinguish different types of targets. For example, near an airport, target activities of takeoff, landing, and holding need to be evaluated in addition to target classification of civilian or commercial aircraft. This paper discusses a method for evaluation of the inferred activities over the finite evidence domain formed from the collection of models under consideration. The methodology accounts for repeated use of evidence in different models. For example, 'near an airport' is a required piece of evidence used repeatedly in the takeoff, landing, and holding models of a wide area sensor. Properties of the activity model evaluator methodology are discussed in terms of model construction and informal results are presented in a Boolean evidence type of problem domain.

The transcription factor p53: Not a repressor, solely an activator

PubMed Central

Fischer, Martin; Steiner, Lydia; Engeland, Kurt

2014-01-01

The predominant function of the tumor suppressor p53 is transcriptional regulation. It is generally accepted that p53-dependent transcriptional activation occurs by binding to a specific recognition site in promoters of target genes. Additionally, several models for p53-dependent transcriptional repression have been postulated. Here, we evaluate these models based on a computational meta-analysis of genome-wide data. Surprisingly, several major models of p53-dependent gene regulation are implausible. Meta-analysis of large-scale data is unable to confirm reports on directly repressed p53 target genes and falsifies models of direct repression. This notion is supported by experimental re-analysis of representative genes reported as directly repressed by p53. Therefore, p53 is not a direct repressor of transcription, but solely activates its target genes. Moreover, models based on interference of p53 with activating transcription factors as well as models based on the function of ncRNAs are also not supported by the meta-analysis. As an alternative to models of direct repression, the meta-analysis leads to the conclusion that p53 represses transcription indirectly by activation of the p53-p21-DREAM/RB pathway. PMID:25486564

Hybrid active contour model for inhomogeneous image segmentation with background estimation

NASA Astrophysics Data System (ADS)

Sun, Kaiqiong; Li, Yaqin; Zeng, Shan; Wang, Jun

2018-03-01

This paper proposes a hybrid active contour model for inhomogeneous image segmentation. The data term of the energy function in the active contour consists of a global region fitting term in a difference image and a local region fitting term in the original image. The difference image is obtained by subtracting the background from the original image. The background image is dynamically estimated from a linear filtered result of the original image on the basis of the varying curve locations during the active contour evolution process. As in existing local models, fitting the image to local region information makes the proposed model robust against an inhomogeneous background and maintains the accuracy of the segmentation result. Furthermore, fitting the difference image to the global region information makes the proposed model robust against the initial contour location, unlike existing local models. Experimental results show that the proposed model can obtain improved segmentation results compared with related methods in terms of both segmentation accuracy and initial contour sensitivity.

QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

PubMed Central

Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

2009-01-01

A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

Activated sludge pilot plant: comparison between experimental and predicted concentration profiles using three different modelling approaches.

PubMed

Le Moullec, Y; Potier, O; Gentric, C; Leclerc, J P

2011-05-01

This paper presents an experimental and numerical study of an activated sludge channel pilot plant. Concentration profiles of oxygen, COD, NO(3) and NH(4) have been measured for several operating conditions. These profiles have been compared to the simulated ones with three different modelling approaches, namely a systemic approach, CFD and compartmental modelling. For these three approaches, the kinetics model was the ASM-1 model (Henze et al., 2001). The three approaches allowed a reasonable simulation of all the concentration profiles except for ammonium for which the simulations results were far from the experimental ones. The analysis of the results showed that the role of the kinetics model is of primary importance for the prediction of activated sludge reactors performance. The fact that existing kinetics parameters in the literature have been determined by parametric optimisation using a systemic model limits the reliability of the prediction of local concentrations and of the local design of activated sludge reactors. Copyright © 2011 Elsevier Ltd. All rights reserved.

CERAPP: Collaborative Estrogen Receptor Activity Prediction ...

EPA Pesticide Factsheets

Humans potentially are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Many of these chemicals never have been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for assessment in costly in vivo tests, for instance, within the EPA Endocrine Disruptor Screening Program. Here, we describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating the efficacy of using predictive computational models on high-throughput screening data to screen thousands of chemicals against the ER. CERAPP combined multiple models developed in collaboration among 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1677 compounds provided by EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were tested using an evaluation set of 7522 chemicals collected from the literature. To overcome the limitations of single models, a consensus was built weighting models using a scoring function (0 to 1) based on their accuracies. Individual model scores ranged from 0.69 to 0.85, showing

Cuatro Modelos para Disenar Actividades de Capacitacion de Docentes (Four Models to Design In-Service Teacher Training Activities).

ERIC Educational Resources Information Center

Valle, Victor M.

In designing inservice teacher training activities, it is necessary to apply educational principles and teaching and learning techniques which are suitable for adult education programs. Four models for designing inservice teacher training programs are the Malcom Knowles Model, the Leonard Nadler Model, the Cyril O. Houle Model, and the William R.…

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

NASA Astrophysics Data System (ADS)

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; de Zeeuw, Chris I.

2016-11-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity.

Development of a Conceptual Model for Smoking Cessation: Physical Activity, Neurocognition, and Executive Functioning.

PubMed

Loprinzi, Paul D; Herod, Skyla M; Walker, Jerome F; Cardinal, Bradley J; Mahoney, Sara E; Kane, Christy

2015-01-01

Considerable research has shown adverse neurobiological effects of chronic alcohol use, including long-term and potentially permanent changes in the structure and function of the brain; however, much less is known about the neurobiological consequences of chronic smoking, as it has largely been ignored until recently. In this article, we present a conceptual model proposing the effects of smoking on neurocognition and the role that physical activity may play in this relationship as well as its role in smoking cessation. Pertinent published peer-reviewed articles deposited in PubMed delineating the pathways in the proposed model were reviewed. The proposed model, which is supported by emerging research, demonstrates a bidirectional relationship between smoking and executive functioning. In support of our conceptual model, physical activity may moderate this relationship and indirectly influence smoking behavior through physical activity-induced changes in executive functioning. Our model may have implications for aiding smoking cessation efforts through the promotion of physical activity as a mechanism for preventing smoking-induced deficits in neurocognition and executive function.

A comparative study of two communication models in HIV/AIDS coverage in selected Nigerian newspapers

PubMed Central

Okidu, Onjefu

2013-01-01

The current overriding thought in HIV/AIDS communication in developing countries is the need for a shift from the cognitive model, which emphasises the decision-making of the individual, to the activity model, which emphasises the context of the individual. In spite of the acknowledged media shift from the cognitive to the activity model in some developing countries, some HIV/AIDS communication scholars have felt otherwise. It was against this background that this study examined the content of some selected Nigerian newspapers to ascertain the attention paid to HIV/AIDS cognitive and activity information. Generally, the study found that Nigerian newspapers had shifted from the cognitive to the activity model of communication in their coverage of HIV/AIDS issues. The findings of the study seem inconsistent with the theoretical argument of some scholars that insufficient attention has been paid by mass media in developing countries to the activity model of HIV/AIDS communication. It is suggested that future research replicate the study for Nigerian and other developing countries’ mass media. PMID:23394854

A comparative study of two communication models in HIV/AIDS coverage in selected Nigerian newspapers.

PubMed

Okidu, Onjefu

2013-01-30

The current overriding thought in HIV/AIDS communication in developing countries is the need for a shift from the cognitive model, which emphasises the decision-making of the individual, to the activity model, which emphasises the context of the individual. In spite of the acknowledged media shift from the cognitive to the activity model in some developing countries, some HIV/AIDS communication scholars have felt otherwise. It was against this background that this study examined the content of some selected Nigerian newspapers to ascertain the attention paid to HIV/AIDS cognitive and activity information. Generally, the study found that Nigerian newspapers had shifted from the cognitive to the activity model of communication in their coverage of HIV/AIDS issues. The findings of the study seem inconsistent with the theoretical argument of some scholars that insufficient attention has been paid by mass media in developing countries to the activity model of HIV/AIDS communication. It is suggested that future research replicate the study for Nigerian and other developing countries' mass media.

Abnormal patterns of displacement activities: a review and reinterpretation.

PubMed

Anselme, Patrick

2008-09-01

A series of important theoretical contributions flourished in the years 1950-1970 about displacement activities -- those 'out-of-context' actions expressed by organisms in stressful situations. Nothing really new has appeared thereafter. Although the models address different issues, such as causal factors of displacement, it appears obvious that they do not provide a unified (coherent) approach; they often explain the same phenomena using very different means and turn out to be contradictory on several points. In addition, some problems currently remain unsolved, especially concerning the fact that displacement activities exhibit 'abnormalities' of expression in comparison with the same activities performed in usual context. Each model is here described and criticized in order to evaluate its explanatory power and allow the identification of specific limits. A new, integrative model -- the Anticipatory Dynamics Model (or ADM) -- then attempts to overcome the failures of previous models. The ADM suggests that abnormal patterns of displacement activities result from attentional interference caused by a thwarting experience or conflicting motivations. At least one theoretical prediction of the ADM can be differentiated from that of any other model.

A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA.

PubMed

Zhang, Tao; Wei, Dong-Qing; Chou, Kuo-Chen

2012-03-01

Comparative molecular field analysis (CoMFA) is a widely used 3D-QSAR method by which we can investigate the potential relation between biological activity of compounds and their structural features. In this study, a new application of this approach is presented by combining the molecular modeling with a new developed pharmacophore model specific to CYP1A2 active site. During constructing the model, we used the molecular dynamics simulation and molecular docking method to select the sensible binding conformations for 17 CYP1A2 substrates based on the experimental data. Subsequently, the results obtained via the alignment of binding conformations of substrates were projected onto the active- site residues, upon which a simple blueprint of active site was produced. It was validated by the experimental and computational results that the model did exhibit the high degree of rationality and provide useful insights into the substrate binding. It is anticipated that our approach can be extended to investigate the protein-ligand interactions for many other enzyme-catalyzed systems as well.

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

PubMed Central

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; De Zeeuw, Chris I.

2016-01-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity. PMID:27805050

Modeling Cytoskeletal Active Matter Systems

NASA Astrophysics Data System (ADS)

Blackwell, Robert

Active networks of filamentous proteins and crosslinking motor proteins play a critical role in many important cellular processes. One of the most important microtubule-motor protein assemblies is the mitotic spindle, a self-organized active liquid-crystalline structure that forms during cell division and that ultimately separates chromosomes into two daughter cells. Although the spindle has been intensively studied for decades, the physical principles that govern its self-organization and function remain mysterious. To evolve a better understanding of spindle formation, structure, and dynamics, I investigate course-grained models of active liquid-crystalline networks composed of microtubules, modeled as hard spherocylinders, in diffusive equilibrium with a reservoir of active crosslinks, modeled as hookean springs that can adsorb to microtubules and and translocate at finite velocity along the microtubule axis. This model is investigated using a combination of brownian dynamics and kinetic monte carlo simulation. I have further refined this model to simulate spindle formation and kinetochore capture in the fission yeast S. pombe. I then make predictions for experimentally realizable perturbations in motor protein presence and function in S. pombe.

Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

PubMed

Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

2018-06-01

A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model

USGS Publications Warehouse

Madenjian, Charles P.; David, Solomon R.; Pothoven, Steven A.

2012-01-01

We evaluated the performance of the Wisconsin bioenergetics model for lake trout Salvelinus namaycush that were fed ad libitum in laboratory tanks under regimes of low activity and high activity. In addition, we compared model performance under two different model algorithms: (1) balancing the lake trout energy budget on day t based on lake trout energy density on day t and (2) balancing the lake trout energy budget on day t based on lake trout energy density on day t + 1. Results indicated that the model significantly underestimated consumption for both inactive and active lake trout when algorithm 1 was used and that the degree of underestimation was similar for the two activity levels. In contrast, model performance substantially improved when using algorithm 2, as no detectable bias was found in model predictions of consumption for inactive fish and only a slight degree of overestimation was detected for active fish. The energy budget was accurately balanced by using algorithm 2 but not by using algorithm 1. Based on the results of this study, we recommend the use of algorithm 2 to estimate food consumption by fish in the field. Our study results highlight the importance of accurately accounting for changes in fish energy density when balancing the energy budget; furthermore, these results have implications for the science of evaluating fish bioenergetics model performance and for more accurate estimation of food consumption by fish in the field when fish energy density undergoes relatively rapid changes.

A robust and fast active contour model for image segmentation with intensity inhomogeneity

NASA Astrophysics Data System (ADS)

Ding, Keyan; Weng, Guirong

2018-04-01

In this paper, a robust and fast active contour model is proposed for image segmentation in the presence of intensity inhomogeneity. By introducing the local image intensities fitting functions before the evolution of curve, the proposed model can effectively segment images with intensity inhomogeneity. And the computation cost is low because the fitting functions do not need to be updated in each iteration. Experiments have shown that the proposed model has a higher segmentation efficiency compared to some well-known active contour models based on local region fitting energy. In addition, the proposed model is robust to initialization, which allows the initial level set function to be a small constant function.

Highly dispersed buckybowls as model carbocatalysts for C–H bond activation

DOE PAGES

Soykal, I. Ilgaz; Wang, Hui; Park, Jewook; ...

2015-03-19

Buckybowl fractions dispersed on mesoporous silica constitute an ideal model for studying the catalysis of graphitic forms of carbon since the dispersed carbon nanostructures contain a high ratio of edge defects and curvature induced by non-six-membered rings. Dispersion of the active centers on an easily accessible high surface area material allowed for high density of surface active sites associated with oxygenated structures. This report illustrates a facile method of creating model polycyclic aromatic nano-structures that are not only active for alkane C-H bond activation and oxidative dehydrogenation but also can be practical catalysts to be eventually used in industry.

Social modeling of eating mediated by mirror neuron activity: A causal model moderated by frontal asymmetry and BMI.

PubMed

McGeown, Laura; Davis, Ron

2018-02-15

The social modeling of eating effect refers to the consistently demonstrated phenomenon that individuals tend to match their quantity of food intake to their eating companion. The current study sought to explore whether activity within the mirror neuron system (MNS) mediates the social modeling of eating effect as a function of EEG frontal asymmetry and body mass index (BMI). Under the guise of rating empathy, 93 female undergraduates viewed a female video confederate "incidentally" consume either a low or high intake of chips while electroencephalogram (EEG) activity was recorded. Subsequent ad libitum chip consumption was quantified. A first- and second-stage dual moderation model revealed that frontal asymmetry and BMI moderated an indirect effect of model consumption on participants' food consumption as mediated by MNS activity at electrode site C3, a 3 b 3 =-0.718, SE=0.365, 95% CI [-1.632, -0.161]. Left frontal asymmetry was associated with greater mu activity and a positive association between model and participant chip consumption, while right frontal asymmetry was associated with less mu activity and a negative association between model and participant consumption. Across all levels of frontal asymmetry, the effect was only significant among those with a BMI at the 50th percentile or lower. Thus, among leaner individuals, the MNS was demonstrated to mediate social modeling of eating, as moderated by frontal asymmetry. These findings are integrated within the normative account of social modeling of eating. It is proposed that the normative framework may benefit from consideration of both conscious and unconscious operation of intake norms. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular design and structure--activity relationships leading to the potent, selective, and orally active thrombin active site inhibitor BMS-189664.

PubMed

Das, Jagabandhu; Kimball, S David; Hall, Steven E; Han, Wen Ching; Iwanowicz, Edwin; Lin, James; Moquin, Robert V; Reid, Joyce A; Sack, John S; Malley, Mary F; Chang, Chiehying Y; Chong, Saeho; Wang-Iverson, David B; Roberts, Daniel G M; Seiler, Steven M; Schumacher, William A; Ogletree, Martin L

2002-01-07

A series of structurally novel small molecule inhibitors of human alpha-thrombin was prepared to elucidate their structure-activity relationships (SARs), selectivity and activity in vivo. BMS-189664 (3) is identified as a potent, selective, and orally active reversible inhibitor of human alpha-thrombin which is efficacious in vivo in a mouse lethality model, and at inhibiting both arterial and venous thrombosis in cynomolgus monkey models.

Accurate prediction of energy expenditure using a shoe-based activity monitor.

PubMed

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

2011-07-01

The aim of this study was to develop and validate a method for predicting energy expenditure (EE) using a footwear-based system with integrated accelerometer and pressure sensors. We developed a footwear-based device with an embedded accelerometer and insole pressure sensors for the prediction of EE. The data from the device can be used to perform accurate recognition of major postures and activities and to estimate EE using the acceleration, pressure, and posture/activity classification information in a branched algorithm without the need for individual calibration. We measured EE via indirect calorimetry as 16 adults (body mass index=19-39 kg·m) performed various low- to moderate-intensity activities and compared measured versus predicted EE using several models based on the acceleration and pressure signals. Inclusion of pressure data resulted in better accuracy of EE prediction during static postures such as sitting and standing. The activity-based branched model that included predictors from accelerometer and pressure sensors (BACC-PS) achieved the lowest error (e.g., root mean squared error (RMSE)=0.69 METs) compared with the accelerometer-only-based branched model BACC (RMSE=0.77 METs) and nonbranched model (RMSE=0.94-0.99 METs). Comparison of EE prediction models using data from both legs versus models using data from a single leg indicates that only one shoe needs to be equipped with sensors. These results suggest that foot acceleration combined with insole pressure measurement, when used in an activity-specific branched model, can accurately estimate the EE associated with common daily postures and activities. The accuracy and unobtrusiveness of a footwear-based device may make it an effective physical activity monitoring tool.

A model for the electronic support of practice-based research networks.

PubMed

Peterson, Kevin A; Delaney, Brendan C; Arvanitis, Theodoros N; Taweel, Adel; Sandberg, Elisabeth A; Speedie, Stuart; Richard Hobbs, F D

2012-01-01

The principal goal of the electronic Primary Care Research Network (ePCRN) is to enable the development of an electronic infrastructure to support clinical research activities in primary care practice-based research networks (PBRNs). We describe the model that the ePCRN developed to enhance the growth and to expand the reach of PBRN research. Use cases and activity diagrams were developed from interviews with key informants from 11 PBRNs from the United States and United Kingdom. Discrete functions were identified and aggregated into logical components. Interaction diagrams were created, and an overall composite diagram was constructed describing the proposed software behavior. Software for each component was written and aggregated, and the resulting prototype application was pilot tested for feasibility. A practical model was then created by separating application activities into distinct software packages based on existing PBRN business rules, hardware requirements, network requirements, and security concerns. We present an information architecture that provides for essential interactions, activities, data flows, and structural elements necessary for providing support for PBRN translational research activities. The model describes research information exchange between investigators and clusters of independent data sites supported by a contracted research director. The model was designed to support recruitment for clinical trials, collection of aggregated anonymous data, and retrieval of identifiable data from previously consented patients across hundreds of practices. The proposed model advances our understanding of the fundamental roles and activities of PBRNs and defines the information exchange commonly used by PBRNs to successfully engage community health care clinicians in translational research activities. By describing the network architecture in a language familiar to that used by software developers, the model provides an important foundation for the development of electronic support for essential PBRN research activities.

Topological pattern for the search of new active drugs against methicillin resistant Staphylococcus aureus.

PubMed

Bueso-Bordils, Jose I; Perez-Gracia, Maria T; Suay-Garcia, Beatriz; Duart, Maria J; Martin Algarra, Rafael V; Lahuerta Zamora, Luis; Anton-Fos, Gerardo M; Aleman Lopez, Pedro A

2017-09-29

Molecular topology was used to develop a mathematical model capable of classifying compounds according to antimicrobial activity against methicillin resistant Staphylococcus aureus (MRSA). Topological indices were used as structural descriptors and their relation to antimicrobial activity was determined by using linear discriminant analysis. This topological model establishes new structure activity relationships which show that the presence of cyclopropyl, chlorine and ramification pairs at a distance of two bonds favor this activity, while the presence of tertiary amines decreases it. This model was applied to a combinatorial library of a thousand and one 6-fluoroquinolones, from which 117 theoretical active molecules were obtained. The compound 10 and five new quinolones were tested against MRSA. They all showed some activity against MRSA, although compounds 6, 8 and 9 showed anti-MRSA activity similar to ciprofloxacin. This model was also applied to 263 theoretical antibacterial agents described by us in a previous work, from which 34 were predicted as theoretically active. Anti-MRSA activity was found bibliographically in 9 of them (ensuring at least 26% of success), and from the rest, 3 compounds were randomly chosen and tested, finding mitomycin C to be more active than ciprofloxacin. The results demonstrate the utility of the molecular topology approaches for identifying new drugs active against MRSA. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Chromatin as active matter

NASA Astrophysics Data System (ADS)

Agrawal, Ankit; Ganai, Nirmalendu; Sengupta, Surajit; Menon, Gautam I.

2017-01-01

Active matter models describe a number of biophysical phenomena at the cell and tissue scale. Such models explore the macroscopic consequences of driving specific soft condensed matter systems of biological relevance out of equilibrium through ‘active’ processes. Here, we describe how active matter models can be used to study the large-scale properties of chromosomes contained within the nuclei of human cells in interphase. We show that polymer models for chromosomes that incorporate inhomogeneous activity reproduce many general, yet little understood, features of large-scale nuclear architecture. These include: (i) the spatial separation of gene-rich, low-density euchromatin, predominantly found towards the centre of the nucleus, vis a vis. gene-poor, denser heterochromatin, typically enriched in proximity to the nuclear periphery, (ii) the differential positioning of individual gene-rich and gene-poor chromosomes, (iii) the formation of chromosome territories, as well as (iv), the weak size-dependence of the positions of individual chromosome centres-of-mass relative to the nuclear centre that is seen in some cell types. Such structuring is induced purely by the combination of activity and confinement and is absent in thermal equilibrium. We systematically explore active matter models for chromosomes, discussing how our model can be generalized to study variations in chromosome positioning across different cell types. The approach and model we outline here represent a preliminary attempt towards a quantitative, first-principles description of the large-scale architecture of the cell nucleus.

Adsorption and biodegradation of 2-chlorophenol by mixed culture using activated carbon as a supporting medium-reactor performance and model verification

NASA Astrophysics Data System (ADS)

Lin, Yen-Hui

2017-11-01

A non-steady-state mathematical model system for the kinetics of adsorption and biodegradation of 2-chlorophenol (2-CP) by attached and suspended biomass on activated carbon process was derived. The mechanisms in the model system included 2-CP adsorption by activated carbon, 2-CP mass transport diffusion in biofilm, and biodegradation by attached and suspended biomass. Batch kinetic tests were performed to determine surface diffusivity of 2-CP, adsorption parameters for 2-CP, and biokinetic parameters of biomass. Experiments were conducted using a biological activated carbon (BAC) reactor system with high recycled rate to approximate a completely mixed flow reactor for model verification. Concentration profiles of 2-CP by model predictions indicated that biofilm bioregenerated the activated carbon by lowering the 2-CP concentration at the biofilm-activated carbon interface as the biofilm grew thicker. The removal efficiency of 2-CP by biomass was approximately 98.5% when 2-CP concentration in the influent was around 190.5 mg L-1 at a steady-state condition. The concentration of suspended biomass reached up to about 25.3 mg L-1 while the thickness of attached biomass was estimated to be 636 μm at a steady-state condition by model prediction. The experimental results agree closely with the results of the model predictions.

Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome.

PubMed

Schuecker, Jannis; Schmidt, Maximilian; van Albada, Sacha J; Diesmann, Markus; Helias, Moritz

2017-02-01

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to experimental observations. Nevertheless, structurally realistic network models of spiking neurons are necessarily underconstrained even if experimental data on brain connectivity are incorporated to the best of our knowledge. Guided by physiological observations, any model must therefore explore the parameter ranges within the uncertainty of the data. Based on simulation results alone, however, the mechanisms underlying stable and physiologically realistic activity often remain obscure. We here employ a mean-field reduction of the dynamics, which allows us to include activity constraints into the process of model construction. We shape the phase space of a multi-scale network model of the vision-related areas of macaque cortex by systematically refining its connectivity. Fundamental constraints on the activity, i.e., prohibiting quiescence and requiring global stability, prove sufficient to obtain realistic layer- and area-specific activity. Only small adaptations of the structure are required, showing that the network operates close to an instability. The procedure identifies components of the network critical to its collective dynamics and creates hypotheses for structural data and future experiments. The method can be applied to networks involving any neuron model with a known gain function.

A Statistical Comparison of Coupled Thermosphere-Ionosphere Models

NASA Astrophysics Data System (ADS)

Liuzzo, L. R.

2014-12-01

The thermosphere-ionosphere system is a highly dynamic, non-linearly coupled interaction that fluctuates on a daily basis. Many models exist to attempt to quantify the relationship between the two atmospheric layers, and each approaches the problem differently. Because these models differ in the implementation of the equations that govern the dynamics of the thermosphere-ionosphere system, it is important to understand under which conditions each model performs best, and under which conditions each model may have limitations in accuracy. With this in consideration, this study examines the ability of two of the leading coupled thermosphere-ionosphere models in the community, TIE-GCM and GITM, to reproduce thermospheric and ionospheric quantities observed by the CHAMP satellite during times of differing geomagnetic activity. Neutral and electron densities are studied for three geomagnetic activity levels, ranging form high to minimal activity. Metrics used to quantify differences between the two models include root-mean-square error and prediction efficiency, and qualitative differences between a model and observed data is also considered. The metrics are separated into the high- mid- and low-latitude region to depict any latitudinal dependencies of the models during the various events. Despite solving for the same parameters, the models are shown to be highly dependent on the amount of activity level that occurs and can be significantly different from each other. In addition, in comparing previous statistical studies that use the models, a clear improvement is observed in the evolution of each model as thermospheric and ionosphericconstituents during the differing levels of activity are solved.

An Additional Approach to Model Current Followers and Amplifiers with Electronically Controllable Parameters from Commercially Available ICs

NASA Astrophysics Data System (ADS)

Sotner, R.; Kartci, A.; Jerabek, J.; Herencsar, N.; Dostal, T.; Vrba, K.

2012-12-01

Several behavioral models of current active elements for experimental purposes are introduced in this paper. These models are based on commercially available devices. They are suitable for experimental tests of current- and mixed-mode filters, oscillators, and other circuits (employing current-mode active elements) frequently used in analog signal processing without necessity of onchip fabrication of proper active element. Several methods of electronic control of intrinsic resistance in the proposed behavioral models are discussed. All predictions and theoretical assumptions are supported by simulations and experiments. This contribution helps to find a cheaper and more effective way to preliminary laboratory tests without expensive on-chip fabrication of special active elements.

Modeling the target acquisition performance of active imaging systems

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Jacobs, Eddie L.; Halford, Carl E.; Vollmerhausen, Richard; Tofsted, David H.

2007-04-01

Recent development of active imaging system technology in the defense and security community have driven the need for a theoretical understanding of its operation and performance in military applications such as target acquisition. In this paper, the modeling of active imaging systems, developed at the U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors Directorate, is presented with particular emphasis on the impact of coherent effects such as speckle and atmospheric scintillation. Experimental results from human perception tests are in good agreement with the model results, validating the modeling of coherent effects as additional noise sources. Example trade studies on the design of a conceptual active imaging system to mitigate deleterious coherent effects are shown.

Modeling the target acquisition performance of active imaging systems.

PubMed

Espinola, Richard L; Jacobs, Eddie L; Halford, Carl E; Vollmerhausen, Richard; Tofsted, David H

2007-04-02

Recent development of active imaging system technology in the defense and security community have driven the need for a theoretical understanding of its operation and performance in military applications such as target acquisition. In this paper, the modeling of active imaging systems, developed at the U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors Directorate, is presented with particular emphasis on the impact of coherent effects such as speckle and atmospheric scintillation. Experimental results from human perception tests are in good agreement with the model results, validating the modeling of coherent effects as additional noise sources. Example trade studies on the design of a conceptual active imaging system to mitigate deleterious coherent effects are shown.

A Novel Higher Order Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Xu, Shuxiang

2010-05-01

In this paper a new Higher Order Neural Network (HONN) model is introduced and applied in several data mining tasks. Data Mining extracts hidden patterns and valuable information from large databases. A hyperbolic tangent function is used as the neuron activation function for the new HONN model. Experiments are conducted to demonstrate the advantages and disadvantages of the new HONN model, when compared with several conventional Artificial Neural Network (ANN) models: Feedforward ANN with the sigmoid activation function; Feedforward ANN with the hyperbolic tangent activation function; and Radial Basis Function (RBF) ANN with the Gaussian activation function. The experimental results seem to suggest that the new HONN holds higher generalization capability as well as abilities in handling missing data.

Modeled Microgravity Inhibits Apoptosis in Peripheral Blood Lymphocytes

NASA Technical Reports Server (NTRS)

Risin, Diana; Pellis, Neal R.

2000-01-01

Microgravity interferes with numerous lymphocyte functions (expression of cell surface molecules, locomotion, polyclonal and antigen-specific activation, and the protein kinase C activity in signal transduction). The latter suggests that gravity may also affect programmed cell death (PCD) in lymphocyte populations. To test this hypothesis, we investigated spontaneous, activation- and radiation-induced PCD in peripheral blood mononuclear cells (PBMC) exposed to modeled microgravity using a rotating cell culture system. The results showed significant inhibition of radiation- and activation-induced apoptosis in modeled microgravity and provide insights into the potential mechanisms of this phenomenon.

Reducing Disease Activity in Animal Models of MS by Activation of the Protective Arm of the Renin-Angiotensin System

DTIC Science & Technology

2015-10-01

patients, there is little evidence for a role of ACE2/A( 1 -7)/Mas axis, only a solitary assessment showing decreased ACE2 levels in the CSF of MS...project? Major Goals (Year 1 ): 1 : Measure levels of RAS components in the spinal cord of mice with EAE (animal model of MS) prior to, and at multiple...AWARD NUMBER: W81XWH-14- 1 -0523 TITLE: Reducing Disease Activity in Animal Models of MS by Activation of the Protective Arm of the Renin

Reconstructing liver shape and position from MR image slices using an active shape model

NASA Astrophysics Data System (ADS)

Fenchel, Matthias; Thesen, Stefan; Schilling, Andreas

2008-03-01

We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of n 2D MR slice images. Reconstructing the shape of an organ from slice images can be used for scan planning, for surgical planning or other purposes where 3D anatomical knowledge has to be inferred from sparse slices. The algorithm is based on adapting an active shape model of the liver surface to a given set of slice images. The active shape model is created from a training set of liver segmentations from a group of volunteers. The training set is set up with semi-manual segmentations of T1-weighted volumetric MR images. Searching for the optimal shape model that best fits to the image data is done by maximizing a similarity measure based on local appearance at the surface. Two different algorithms for the active shape model search are proposed and compared: both algorithms seek to maximize the a-posteriori probability of the grey level appearance around the surface while constraining the surface to the space of valid shapes. The first algorithm works by using grey value profile statistics in normal direction. The second algorithm uses average and variance images to calculate the local surface appearance on the fly. Both algorithms are validated by fitting the active shape model to abdominal 2D slice images and comparing the shapes, which have been reconstructed, to the manual segmentations and to the results of active shape model searches from 3D image data. The results turn out to be promising and competitive to active shape model segmentations from 3D data.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High-Throughput Screening Assays for the Estrogen Receptor.

PubMed

Judson, Richard S; Magpantay, Felicia Maria; Chickarmane, Vijay; Haskell, Cymra; Tania, Nessy; Taylor, Jean; Xia, Menghang; Huang, Ruili; Rotroff, Daniel M; Filer, Dayne L; Houck, Keith A; Martin, Matthew T; Sipes, Nisha; Richard, Ann M; Mansouri, Kamel; Setzer, R Woodrow; Knudsen, Thomas B; Crofton, Kevin M; Thomas, Russell S

2015-11-01

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation, and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform ("assay interference"). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 111 (6.1%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in vivo endocrine testing. Finally, this model is generalizable to any molecular pathway for which there are multiple upstream and downstream assays available. Published by Oxford University Press on behalf of the Society of Toxicology 2015. This work is written by US Government employees and is in the public domain in the US.

Assessment method for epithermal gold deposits in Northeast Washington State using weights-of-evidence GIS modeling

USGS Publications Warehouse

Boleneus, D.E.; Raines, G.L.; Causey, J.D.; Bookstrom, A.A.; Frost, T.P.; Hyndman, P.C.

2001-01-01

The weights-of-evidence analysis, a quantitative mineral resource mapping tool, is used to delineate favorable areas for epithermal gold deposits and to predict future exploration activity of the mineral industry for similar deposits in a four-county area (222 x 277 km), including the Okanogan and Colville National Forests of northeastern Washington. Modeling is applied in six steps: (1) building a spatial digital database, (2) extracting predictive evidence for a particular deposit, based on an exploration model, (3) calculating relative weights for each predictive map, (4) combining the geologic evidence maps to predict the location of undiscovered mineral resources and (5) measuring the intensity of recent exploration activity by use of mining claims on federal lands, and (6) combining mineral resource and exploration activity into an assessment model of future mining activity. The analysis is accomplished on a personal computer using ArcView GIS platform with Spatial Analyst and Weights-of-Evidence software. In accord with the descriptive model for epithermal gold deposits, digital geologic evidential themes assembled include lithologic map units, thrust faults, normal faults, and igneous dikes. Similarly, geochemical evidential themes include placer gold deposits and gold and silver analyses from stream sediment (silt) samples from National Forest lands. Fifty mines, prospects, or occurrences of epithermal gold deposits, the training set, define the appropriate a really-associated terrane. The areal (or spatial) correlation of each evidential theme with the training set yield predictor theme maps for lithology, placer sites and normal faults. The weights-of-evidence analysis disqualified the thrust fault, dike, and gold and silver silt analyses evidential themes because they lacked spatial correlation with the training set. The decision to accept or reject evidential themes as predictors is assisted by considering probabilistic data consisting of weights and contrast values calculated for themes according to areal correlation with the training sites. Predictor themes having acceptable weights and contrast values are combined into a preliminary model to predict the locations of undiscovered epithermal gold deposits. This model facilitates ranking of tracts as non-permissive, permissive or favorable categories based on exclusionary, passive, and active criteria through evaluation of probabilistic data provided by interaction of predictor themes. The method is very similar to the visual inspection method of drawing conclusions from anomalies on a manually overlain system of maps. This method serves as a model for future mineral assessment procedures because of its objective nature. To develop a model to predict future exploration activity, the locations of lode mining claims were summarized for 1980, 1985, 1990, and 1996. Land parcels containing historic claims were identified either as those with mining claims present in 1980 or valid claims present in 1985. Current claim parcels were identified as those containing valid lode claims in either 1990 or 1996. A consistent parcel contains both historic and current claims. The epithermal gold and mining claim activity models were combined into an assessment (or mineral resource-activity) model to assist in land use decisions by providing a prediction of mineral exploration activity on federal land in the next decade. Ranks in the assessment model are: (1) no activity, (2) low activity, (3) low to moderate activity, (4) moderate activity and (5) high activity.

Developing the Practising Model in Physical Education: An Expository Outline Focusing on Movement Capability

ERIC Educational Resources Information Center

Barker, D. M.; Aggerholm, K.; Standal, O.; Larsson, H.

2018-01-01

Background: Physical educators currently have a number of pedagogical (or curricular) models at their disposal. While existing models have been well-received in educational contexts, these models seek to extend students' capacities within a limited number of "human activities" (Arendt, 1958). The activity of "human practising,"…

Using Modeling Tasks to Facilitate the Development of Percentages

ERIC Educational Resources Information Center

Shahbari, Juhaina Awawdeh; Peled, Irit

2016-01-01

This study analyzes the development of percentages knowledge by seventh graders given a sequence of activities starting with a realistic modeling task, in which students were expected to create a model that would facilitate the reinvention of percentages. In the first two activities, students constructed their own pricing model using fractions and…

Emergent Feature Structures: Harmony Systems in Exemplar Models of Phonology

ERIC Educational Resources Information Center

Cole, Jennifer

2009-01-01

In exemplar models of phonology, phonotactic constraints are modeled as emergent from patterns of high activation between units that co-occur with statistical regularity, or as patterns of low activation or inhibition between units that co-occur less frequently or not at all. Exemplar models posit no a "priori" formal or representational…

Primary School Pre-Service Mathematics Teachers' Views on Mathematical Modeling

ERIC Educational Resources Information Center

Karali, Diren; Durmus, Soner

2015-01-01

The current study aimed to identify the views of pre-service teachers, who attended a primary school mathematics teaching department but did not take mathematical modeling courses. The mathematical modeling activity used by the pre-service teachers was developed with regards to the modeling activities utilized by Lesh and Doerr (2003) in their…

Use of the Flipped Classroom Instructional Model in Higher Education: Instructors' Perspectives

ERIC Educational Resources Information Center

Long, Taotao; Cummins, John; Waugh, Michael

2017-01-01

The flipped classroom model is an instructional model in which students learn basic subject matter knowledge prior to in-class meetings, then come to the classroom for active learning experiences. Previous research has shown that the flipped classroom model can motivate students towards active learning, can improve their higher-order thinking…

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.

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.

"When Mathematical Activity Moves You": An Exploration of the Design and Use of Purposefully Embodied Mathematical Activities, Models, Contexts, and Environments

ERIC Educational Resources Information Center

Campbell, William James

2017-01-01

This dissertation describes a mathematics curriculum and instruction design experiment involving a series of embodied mathematical activities conducted in two Colorado elementary schools Activities designed for this experiment include multi-scalar number line models focused on supporting students' understanding of elementary mathematics. Realistic…

Gender and School-Level Differences in Students' Moderate and Vigorous Physical Activity Levels When Taught Basketball through the Tactical Games Model

ERIC Educational Resources Information Center

Harvey, Stephen; Smith, Megan L.; Song, Yang; Robertson, David; Brown, Renee; Smith, Lindsey R.

2016-01-01

The Tactical Games Model (TGM) prefaces the cognitive components of physical education (PE), which has implications for physical activity (PA) accumulation. PA recommendations suggest students reach 50% moderate-vigorous physical activity (MVPA). However, this criterion does not indicate the contribution from vigorous physical activity (VPA).…

Modeling microbial products in activated sludge under feast-famine conditions.

PubMed

Ni, Bing-Jie; Fang, Fang; Rittmann, Bruce E; Yu, Han-Qing

2009-04-01

We develop an expanded unified model that integrates production and consumption of internal storage products (X(STO)) into a unified model for extracellular polymeric substances (EPS), soluble microbial products (SMP), and active and inert biomass in activated sludge. We also conducted independent experiments to find needed parameter values and to test the ability of the expanded unified model to describe all the microbial products, along with original substrate and oxygen uptake. The model simulations match all experimental measurements and provide insights into the dynamics of soluble and solid components in activated sludge exposed to dynamic feast-and-famine conditions in two batch experiments and in one cycle of a sequencing batch reactor. In particular, the model illustrates how X(STO) cycles up and down rapidly during feast and famine periods, while EPS and biomass components are relatively stable despite feast and famine. The agreement between model outputs and experimental EPS, SMP, and X(STO) data from distinctly different experiments supports that the expanded unified model properly captures the relationships among the forms of microbial products.

Generic instabilities in a fluid membrane coupled to a thin layer of ordered active polar fluid.

PubMed

Sarkar, Niladri; Basu, Abhik

2013-08-01

We develop an effective two-dimensional coarse-grained description for the coupled system of a planar fluid membrane anchored to a thin layer of polar ordered active fluid below. The macroscopic orientation of the active fluid layer is assumed to be perpendicular to the attached membrane. We demonstrate that activity or nonequilibrium drive of the active fluid makes such a system generically linearly unstable for either signature of a model parameter [Formula: see text] [Formula: see text] that characterises the strength of activity. Depending upon boundary conditions and within a range of the model parameters, underdamped propagating waves may be present in our model. We discuss the phenomenological significance of our results.

Unspoken Playground Rules Discourage Adolescent Physical Activity in School: A Focus Group Study of Constructs in the Prototype Willingness Model.

PubMed

Wheatley, Catherine M; Davies, Emma L; Dawes, Helen

2018-03-01

The health benefits of exercise in school are recognized, yet physical activity continues to decline during early adolescence despite numerous interventions. In this study, we investigated whether the prototype willingness model, an account of adolescent decision making that includes both reasoned behavioral choices and unplanned responses to social environments, might improve understanding of physical activity in school. We conducted focus groups with British pupils aged 12 to 13 years and used deductive thematic analysis to search for themes relating to the model. Participants described reasoned decisions about physical activity outside school and unplanned choices to be inactive during break, in response to social contexts described as more "judgmental" than in primary school. Social contexts appeared characterized by anxiety about competence, negative peer evaluation, and inactive playground norms. The prototype willingness model might more fully explain physical activity in school than reasoned behavioral models alone, indicating potential for interventions targeting anxieties about playground social environments.

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.

Applications of active adaptive noise control to jet engines

NASA Technical Reports Server (NTRS)

Shoureshi, Rahmat; Brackney, Larry

1993-01-01

During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

Comparative study on kinetic adsorption of Cu(II), Cd(II) and Ni(II) ions from aqueous solutions using activated sludge and dried sludge

NASA Astrophysics Data System (ADS)

Ong, Soon-An; Toorisaka, Eiichi; Hirata, Makoto; Hano, Tadashi

2013-03-01

The adsorption of Cu(II), Cd(II) and Ni(II) ions from aqueous solutions by activated sludge and dried sludge was investigated under laboratory conditions to assess its potential in removing metal ions. The adsorption behavior of metal ions onto activated sludge and dried sludge was analyzed with Weber-Morris intra-particle diffusion model, Lagergren first-order model and pseudo second-order model. The rate constant of intra-particle diffusion on activated sludge and dried sludge increased in the sequence of Cu(II) > Ni(II) > Cd(II). According to the regression coefficients, it was observed that the kinetic adsorption data can fit better by the pseudo second-order model compared to the first-order Lagergren model with R 2 > 0.997. The adsorption capacities of metal ions onto activated sludge and dried sludge followed the sequence Ni(II) ≈ Cu(II) > Cd(II) and Cu(II) > Ni(II) > Cd(II).

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

Mean ionic activity coefficients in aqueous NaCl solutions from molecular dynamics simulations

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

Mester, Zoltan; Panagiotopoulos, Athanassios Z., E-mail: azp@princeton.edu

The mean ionic activity coefficients of aqueous NaCl solutions of varying concentrations at 298.15 K and 1 bar have been obtained from molecular dynamics simulations by gradually turning on the interactions of an ion pair inserted into the solution. Several common non-polarizable water and ion models have been used in the simulations. Gibbs-Duhem equation calculations of the thermodynamic activity of water are used to confirm the thermodynamic consistency of the mean ionic activity coefficients. While the majority of model combinations predict the correct trends in mean ionic activity coefficients, they overestimate their values at high salt concentrations. The solubility predictionsmore » also suffer from inaccuracies, with all models underpredicting the experimental values, some by large factors. These results point to the need for further ion and water model development.« less

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. PMID:22506020

Prediction of p38 map kinase inhibitory activity of 3, 4-dihydropyrido [3, 2-d] pyrimidone derivatives using an expert system based on principal component analysis and least square support vector machine

PubMed Central

Shahlaei, M.; Saghaie, L.

2014-01-01

A quantitative structure–activity relationship (QSAR) study is suggested for the prediction of biological activity (pIC50) of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors. Modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (PCA) and least square support vector machine (LS-SVM) methods. The results showed that the pIC50 values calculated by LS-SVM are in good agreement with the experimental data, and the performance of the LS-SVM regression model is superior to the PCA-based model. The developed LS-SVM model was applied for the prediction of the biological activities of pyrimidone derivatives, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.460 for LS-SVM. The study provided a novel and effective approach for predicting biological activities of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors and disclosed that LS-SVM can be used as a powerful chemometrics tool for QSAR studies. PMID:26339262

Population Modelling with M&M's[R

ERIC Educational Resources Information Center

Winkel, Brian

2009-01-01

Several activities in which population dynamics can be modelled by tossing M&M's[R] candy are presented. Physical activities involving M&M's[R] can be modelled by difference equations and several population phenomena, including death and immigration, are studied. (Contains 1 note.)

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.

[Acceleration of Jingui Shenqi Pill on the testis telomerase activity in mice of Shen-yang deficiency].

PubMed

Xu, Cui-Ping; Zhu, Qing-Jun; Song, Jie; Li, Zhen; Zhang, Dan

2013-02-01

To explore the effects of Jingui Shenqi Pill (JSP) on the testis telomerase activity in mice of Shen-yang deficiency syndrome (SYDS). The SYDS model was prepared in 30 mice by over-fatigue and sexual overstrain. They were randomly divided into the model group and the JSP group, 15 in each group. Another 15 normal male mice were selected as the normal group. Mice in the normal group were fed routinely, with distilled water administered intragastrically at the daily dose of 0.1 mL/10 g. Mice in the model group were also administered intragastrically with distilled water at the daily dose of 0.1 mL/10 g while modeling establishment. Mice in the treatment group were administered intragastrically with JSP suspension at 0.1 mL/10 g (the concentration was 0.241 g/mL). The intervention lasted for 4 weeks. Four weeks later, the testis telomerase activity was detected in the three groups by ELISA. The SYDS model was replicated successfully by over-fatigue and sexual overstrain. JSP could improve the signs of mice of SYDS. Compared with the normal group, the activity of testis telomerase decreased in the model group (P < 0.01). Compared with the model group, the testis telomerase activity markedly increased in the treatment group (P < 0.01). The testis telomerase activity in mice of SYDS caused by over-fatigue and sexual overstrain obviously decreased, when compared with that in mice of the normal group. JSP could recover its activity.

A visual model for object detection based on active contours and level-set method.

PubMed

Satoh, Shunji

2006-09-01

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

Active imaging system performance model for target acquisition

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Teaney, Brian; Nguyen, Quang; Jacobs, Eddie L.; Halford, Carl E.; Tofsted, David H.

2007-04-01

The U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors Directorate has developed a laser-range-gated imaging system performance model for the detection, recognition, and identification of vehicle targets. The model is based on the established US Army RDECOM CERDEC NVESD sensor performance models of the human system response through an imaging system. The Java-based model, called NVLRG, accounts for the effect of active illumination, atmospheric attenuation, and turbulence effects relevant to LRG imagers, such as speckle and scintillation, and for the critical sensor and display components. This model can be used to assess the performance of recently proposed active SWIR systems through various trade studies. This paper will describe the NVLRG model in detail, discuss the validation of recent model components, present initial trade study results, and outline plans to validate and calibrate the end-to-end model with field data through human perception testing.

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.

Refining Time-Activity Classification of Human Subjects Using the Global Positioning System.

PubMed

Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun

2016-01-01

Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations.

Effects of atmospheric composition on apparent activation energy of silicate weathering: I. Model formulation

NASA Astrophysics Data System (ADS)

Kanzaki, Yoshiki; Murakami, Takashi

2018-07-01

We have developed a weathering model to comprehensively understand the determining factors of the apparent activation energy of silicate weathering in order to better estimate the silicate-weathering flux in the Precambrian. The model formulates the reaction rate of a mineral as a basis, then the elemental loss by summing the reaction rates of whole minerals, and finally the weathering flux from a given weathering profile by integrating the elemental losses along the depth of the profile. The rate expressions are formulated with physicochemical parameters relevant to weathering, including solution and atmospheric compositions. The apparent activation energies of silicate weathering are then represented by the temperature dependences of the physicochemical parameters based on the rate expressions. It was found that the interactions between individual mineral-reactions and the compositions of solution and atmosphere are necessarily accompanied by those of temperature-dependence counterparts. Indeed, the model calculates the apparent activation energy of silicate weathering as a function of the temperature dependence of atmospheric CO2 (Δ HCO2‧) . The dependence of the apparent activation energy of silicate weathering on Δ HCO2‧ may explain the empirical dependence of silicate weathering on the atmospheric composition. We further introduce a compensation law between the apparent activation energy and the pre-exponential factor to obtain the relationship between the silicate-weathering flux (FCO2), temperature and the apparent activation energy. The model calculation and the compensation law enable us to predict FCO2 as a function of temperature, once Δ HCO2‧ is given. The validity of the model is supported by agreements between the model prediction and observations of the apparent activation energy and FCO2 in the modern weathering systems. The present weathering model will be useful for the estimation of FCO2 in the Precambrian, for which Δ HCO2‧ can be deduced from the greenhouse effect of atmospheric CO2.

Inhibitory control in mind and brain 2.0: Blocked-input models of saccadic countermanding

PubMed Central

Logan, Gordon D.; Yamaguchi, Motonori; Schall, Jeffrey D.; Palmeri, Thomas J.

2015-01-01

The interactive race model of saccadic countermanding assumes that response inhibition results from an interaction between a go unit, identified with gaze-shifting neurons, and a stop unit, identified with gaze-holding neurons, in which activation of the stop unit inhibits the growth of activation in the go unit to prevent it from reaching threshold. The interactive race model accounts for behavioral data and predicts physiological data in monkeys performing the stop-signal task. We propose an alternative model that assumes that response inhibition results from blocking the input to the go unit. We show that the blocked-input model accounts for behavioral data as accurately as the original interactive race model and predicts aspects of the physiological data more accurately. We extend the models to address the steady-state fixation period before the go stimulus is presented and find that the blocked-input model fits better than the interactive race model. We consider a model in which fixation activity is boosted when a stop signal occurs and find that it fits as well as the blocked input model but predicts very high steady-state fixation activity after the response is inhibited. We discuss the alternative linking propositions that connect computational models to neural mechanisms, the lessons to be learned from model mimicry, and generalization from countermanding saccades to countermanding other kinds of responses. PMID:25706403

Modelling the Active Hearing Process in Mosquitoes

NASA Astrophysics Data System (ADS)

Avitabile, Daniele; Homer, Martin; Jackson, Joe; Robert, Daniel; Champneys, Alan

2011-11-01

A simple microscopic mechanistic model is described of the active amplification within the Johnston's organ of the mosquito species Toxorhynchites brevipalpis. The model is based on the description of the antenna as a forced-damped oscillator coupled to a set of active threads (ensembles of scolopidia) that provide an impulsive force when they twitch. This twitching is in turn controlled by channels that are opened and closed if the antennal oscillation reaches a critical amplitude. The model matches both qualitatively and quantitatively with recent experiments. New results are presented using mathematical homogenization techniques to derive a mesoscopic model as a simple oscillator with nonlinear force and damping characteristics. It is shown how the results from this new model closely resemble those from the microscopic model as the number of threads approach physiologically correct values.

Future missions studies: Combining Schatten's solar activity prediction model with a chaotic prediction model

NASA Technical Reports Server (NTRS)

Ashrafi, S.

1991-01-01

K. Schatten (1991) recently developed a method for combining his prediction model with our chaotic model. The philosophy behind this combined model and his method of combination is explained. Because the Schatten solar prediction model (KS) uses a dynamo to mimic solar dynamics, accurate prediction is limited to long-term solar behavior (10 to 20 years). The Chaotic prediction model (SA) uses the recently developed techniques of nonlinear dynamics to predict solar activity. It can be used to predict activity only up to the horizon. In theory, the chaotic prediction should be several orders of magnitude better than statistical predictions up to that horizon; beyond the horizon, chaotic predictions would theoretically be just as good as statistical predictions. Therefore, chaos theory puts a fundamental limit on predictability.

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Reed, Erik; Cavanagh, Peter

2011-01-01

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

Analyzing Reaction Rates with the Distortion/Interaction‐Activation Strain Model

PubMed Central

2017-01-01

Abstract The activation strain or distortion/interaction model is a tool to analyze activation barriers that determine reaction rates. For bimolecular reactions, the activation energies are the sum of the energies to distort the reactants into geometries they have in transition states plus the interaction energies between the two distorted molecules. The energy required to distort the molecules is called the activation strain or distortion energy. This energy is the principal contributor to the activation barrier. The transition state occurs when this activation strain is overcome by the stabilizing interaction energy. Following the changes in these energies along the reaction coordinate gives insights into the factors controlling reactivity. This model has been applied to reactions of all types in both organic and inorganic chemistry, including substitutions and eliminations, cycloadditions, and several types of organometallic reactions. PMID:28447369

Constrained Total Energy Expenditure and Metabolic Adaptation to Physical Activity in Adult Humans.

PubMed

Pontzer, Herman; Durazo-Arvizu, Ramon; Dugas, Lara R; Plange-Rhule, Jacob; Bovet, Pascal; Forrester, Terrence E; Lambert, Estelle V; Cooper, Richard S; Schoeller, Dale A; Luke, Amy

2016-02-08

Current obesity prevention strategies recommend increasing daily physical activity, assuming that increased activity will lead to corresponding increases in total energy expenditure and prevent or reverse energy imbalance and weight gain [1-3]. Such Additive total energy expenditure models are supported by exercise intervention and accelerometry studies reporting positive correlations between physical activity and total energy expenditure [4] but are challenged by ecological studies in humans and other species showing that more active populations do not have higher total energy expenditure [5-8]. Here we tested a Constrained total energy expenditure model, in which total energy expenditure increases with physical activity at low activity levels but plateaus at higher activity levels as the body adapts to maintain total energy expenditure within a narrow range. We compared total energy expenditure, measured using doubly labeled water, against physical activity, measured using accelerometry, for a large (n = 332) sample of adults living in five populations [9]. After adjusting for body size and composition, total energy expenditure was positively correlated with physical activity, but the relationship was markedly stronger over the lower range of physical activity. For subjects in the upper range of physical activity, total energy expenditure plateaued, supporting a Constrained total energy expenditure model. Body fat percentage and activity intensity appear to modulate the metabolic response to physical activity. Models of energy balance employed in public health [1-3] should be revised to better reflect the constrained nature of total energy expenditure and the complex effects of physical activity on metabolic physiology. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Discovering Anti-platelet Drug Combinations with an Integrated Model of Activator-Inhibitor Relationships, Activator-Activator Synergies and Inhibitor-Inhibitor Synergies

PubMed Central

Lombardi, Federica; Golla, Kalyan; Fitzpatrick, Darren J.; Casey, Fergal P.; Moran, Niamh; Shields, Denis C.

2015-01-01

Identifying effective therapeutic drug combinations that modulate complex signaling pathways in platelets is central to the advancement of effective anti-thrombotic therapies. However, there is no systems model of the platelet that predicts responses to different inhibitor combinations. We developed an approach which goes beyond current inhibitor-inhibitor combination screening to efficiently consider other signaling aspects that may give insights into the behaviour of the platelet as a system. We investigated combinations of platelet inhibitors and activators. We evaluated three distinct strands of information, namely: activator-inhibitor combination screens (testing a panel of inhibitors against a panel of activators); inhibitor-inhibitor synergy screens; and activator-activator synergy screens. We demonstrated how these analyses may be efficiently performed, both experimentally and computationally, to identify particular combinations of most interest. Robust tests of activator-activator synergy and of inhibitor-inhibitor synergy required combinations to show significant excesses over the double doses of each component. Modeling identified multiple effects of an inhibitor of the P2Y12 ADP receptor, and complementarity between inhibitor-inhibitor synergy effects and activator-inhibitor combination effects. This approach accelerates the mapping of combination effects of compounds to develop combinations that may be therapeutically beneficial. We integrated the three information sources into a unified model that predicted the benefits of a triple drug combination targeting ADP, thromboxane and thrombin signaling. PMID:25875950

Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum

PubMed Central

Hasselmo, Michael E.

2008-01-01

The spiking activity of hippocampal neurons during REM sleep exhibits temporally structured replay of spiking occurring during previously experienced trajectories (Louie and Wilson, 2001). Here, temporally structured replay of place cell activity during REM sleep is modeled in a large-scale network simulation of grid cells, place cells and head direction cells. During simulated waking behavior, the movement of the simulated rat drives activity of a population of head direction cells that updates the activity of a population of entorhinal grid cells. The population of grid cells drives the activity of place cells coding individual locations. Associations between location and movement direction are encoded by modification of excitatory synaptic connections from place cells to speed modulated head direction cells. During simulated REM sleep, the population of place cells coding an experienced location activates the head direction cells coding the associated movement direction. Spiking of head direction cells then causes frequency shifts within the population of entorhinal grid cells to update a phase representation of location. Spiking grid cells then activate new place cells that drive new head direction activity. In contrast to models that perform temporally compressed sequence retrieval similar to sharp wave activity, this model can simulate data on temporally structured replay of hippocampal place cell activity during REM sleep at time scales similar to those observed during waking. These mechanisms could be important for episodic memory of trajectories. PMID:18973557

A closed-loop model of the respiratory system: focus on hypercapnia and active expiration.

PubMed

Molkov, Yaroslav I; Shevtsova, Natalia A; Park, Choongseok; Ben-Tal, Alona; Smith, Jeffrey C; Rubin, Jonathan E; Rybak, Ilya A

2014-01-01

Breathing is a vital process providing the exchange of gases between the lungs and atmosphere. During quiet breathing, pumping air from the lungs is mostly performed by contraction of the diaphragm during inspiration, and muscle contraction during expiration does not play a significant role in ventilation. In contrast, during intense exercise or severe hypercapnia forced or active expiration occurs in which the abdominal "expiratory" muscles become actively involved in breathing. The mechanisms of this transition remain unknown. To study these mechanisms, we developed a computational model of the closed-loop respiratory system that describes the brainstem respiratory network controlling the pulmonary subsystem representing lung biomechanics and gas (O2 and CO2) exchange and transport. The lung subsystem provides two types of feedback to the neural subsystem: a mechanical one from pulmonary stretch receptors and a chemical one from central chemoreceptors. The neural component of the model simulates the respiratory network that includes several interacting respiratory neuron types within the Bötzinger and pre-Bötzinger complexes, as well as the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG) representing the central chemoreception module targeted by chemical feedback. The RTN/pFRG compartment contains an independent neural generator that is activated at an increased CO2 level and controls the abdominal motor output. The lung volume is controlled by two pumps, a major one driven by the diaphragm and an additional one activated by abdominal muscles and involved in active expiration. The model represents the first attempt to model the transition from quiet breathing to breathing with active expiration. The model suggests that the closed-loop respiratory control system switches to active expiration via a quantal acceleration of expiratory activity, when increases in breathing rate and phrenic amplitude no longer provide sufficient ventilation. The model can be used for simulation of closed-loop control of breathing under different conditions including respiratory disorders.

A model of metastable dynamics during ongoing and evoked cortical activity

NASA Astrophysics Data System (ADS)

La Camera, Giancarlo

The dynamics of simultaneously recorded spike trains in alert animals often evolve through temporal sequences of metastable states. Little is known about the network mechanisms responsible for the genesis of such sequences, or their potential role in neural coding. In the gustatory cortex of alert rates, state sequences can be observed also in the absence of overt sensory stimulation, and thus form the basis of the so-called `ongoing activity'. This activity is characterized by a partial degree of coordination among neurons, sharp transitions among states, and multi-stability of single neurons' firing rates. A recurrent spiking network model with clustered topology can account for both the spontaneous generation of state sequences and the (network-generated) multi-stability. In the model, each network state results from the activation of specific neural clusters with potentiated intra-cluster connections. A mean field solution of the model shows a large number of stable states, each characterized by a subset of simultaneously active clusters. The firing rate in each cluster during ongoing activity depends on the number of active clusters, so that the same neuron can have different firing rates depending on the state of the network. Because of dense intra-cluster connectivity and recurrent inhibition, in finite networks the stable states lose stability due to finite size effects. Simulations of the dynamics show that the model ensemble activity continuously hops among the different states, reproducing the ongoing dynamics observed in the data. Moreover, when probed with external stimuli, the model correctly predicts the quenching of single neuron multi-stability into bi-stability, the reduction of dimensionality of the population activity, the reduction of trial-to-trial variability, and a potential role for metastable states in the anticipation of expected events. Altogether, these results provide a unified mechanistic model of ongoing and evoked cortical dynamics. NSF IIS-1161852, NIDCD K25-DC013557, NIDCD R01-DC010389.

A fully resolved active musculo-mechanical model for esophageal transport

NASA Astrophysics Data System (ADS)

Kou, Wenjun; Bhalla, Amneet Pal Singh; Griffith, Boyce E.; Pandolfino, John E.; Kahrilas, Peter J.; Patankar, Neelesh A.

2015-10-01

Esophageal transport is a physiological process that mechanically transports an ingested food bolus from the pharynx to the stomach via the esophagus, a multi-layered muscular tube. This process involves interactions between the bolus, the esophagus, and the neurally coordinated activation of the esophageal muscles. In this work, we use an immersed boundary (IB) approach to simulate peristaltic transport in the esophagus. The bolus is treated as a viscous fluid that is actively transported by the muscular esophagus, and the esophagus is modeled as an actively contracting, fiber-reinforced tube. Before considering the full model of the esophagus, however, we first consider a standard benchmark problem of flow past a cylinder. Next a simplified version of our model is verified by comparison to an analytic solution to the tube dilation problem. Finally, three different complex models of the multi-layered esophagus, which differ in their activation patterns and the layouts of the mucosal layers, are extensively tested. To our knowledge, these simulations are the first of their kind to incorporate the bolus, the multi-layered esophagus tube, and muscle activation into an integrated model. Consistent with experimental observations, our simulations capture the pressure peak generated by the muscle activation pulse that travels along the bolus tail. These fully resolved simulations provide new insights into roles of the mucosal layers during bolus transport. In addition, the information on pressure and the kinematics of the esophageal wall resulting from the coordination of muscle activation is provided, which may help relate clinical data from manometry and ultrasound images to the underlying esophageal motor function.

A fully resolved active musculo-mechanical model for esophageal transport

PubMed Central

Kou, Wenjun; Bhalla, Amneet Pal Singh; Griffith, Boyce E.; Pandolfino, John E.; Kahrilas, Peter J.; Patankar, Neelesh A.

2015-01-01

Esophageal transport is a physiological process that mechanically transports an ingested food bolus from the pharynx to the stomach via the esophagus, a multilayered muscular tube. This process involves interactions between the bolus, the esophagus, and the neurally coordinated activation of the esophageal muscles. In this work, we use an immersed boundary (IB) approach to simulate peristaltic transport in the esophagus. The bolus is treated as a viscous fluid that is actively transported by the muscular esophagus, and the esophagus is modeled as an actively contracting, fiber-reinforced tube. Before considering the full model of the esophagus, however, we first consider a standard benchmark problem of flow past a cylinder. Next a simplified version of our model is verified by comparison to an analytic solution to the tube dilation problem. Finally, three different complex models of the multi-layered esophagus, which differ in their activation patterns and the layouts of the mucosal layers, are extensively tested. To our knowledge, these simulations are the first of their kind to incorporate the bolus, the multi-layered esophagus tube, and muscle activation into an integrated model. Consistent with experimental observations, our simulations capture the pressure peak generated by the muscle activation pulse that travels along the bolus tail. These fully resolved simulations provide new insights into roles of the mucosal layers during bolus transport. In addition, the information on pressure and the kinematics of the esophageal wall resulting from the coordination of muscle activation is provided, which may help relate clinical data from manometry and ultrasound images to the underlying esophageal motor function. PMID:26190859

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

PubMed

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

Mechanistic modeling of microbial interactions at pore to profile scale resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-05-01

The sensitivity of polar regions to raising global temperatures is reflected in rapidly changing hydrological processes associated with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and stimulation of other soil-borne greenhouse gas emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and other environmental factors. Soil structural elements such as aggregates and layering affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hot spots). We developed a mechanistic individual-based model to quantify microbial activity dynamics in soil pore networks considering transport processes and enzymatic activity associated with methane production in soil. The model was upscaled from single aggregates to the soil profile where freezing/thawing provides macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged profile) for resolving methane production and oxidation rates. Methane transport pathways by diffusion and ebullition of bubbles vary with hydration dynamics. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability and enzyme activity) on long-term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Derivation of low flow frequency distributions under human activities and its implications

NASA Astrophysics Data System (ADS)

Gao, Shida; Liu, Pan; Pan, Zhengke; Ming, Bo; Guo, Shenglian; Xiong, Lihua

2017-06-01

Low flow, refers to a minimum streamflow in dry seasons, is crucial to water supply, agricultural irrigation and navigation. Human activities, such as groundwater pumping, influence low flow severely. In order to derive the low flow frequency distribution functions under human activities, this study incorporates groundwater pumping and return flow as variables in the recession process. Steps are as follows: (1) the original low flow without human activities is assumed to follow a Pearson type three distribution, (2) the probability distribution of climatic dry spell periods is derived based on a base flow recession model, (3) the base flow recession model is updated under human activities, and (4) the low flow distribution under human activities is obtained based on the derived probability distribution of dry spell periods and the updated base flow recession model. Linear and nonlinear reservoir models are used to describe the base flow recession, respectively. The Wudinghe basin is chosen for the case study, with daily streamflow observations during 1958-2000. Results show that human activities change the location parameter of the low flow frequency curve for the linear reservoir model, while alter the frequency distribution function for the nonlinear one. It is indicated that alter the parameters of the low flow frequency distribution is not always feasible to tackle the changing environment.

Spatial and Activities Models of Airport Based on GIS and Dynamic Model

NASA Astrophysics Data System (ADS)

Masri, R. M.; Purwaamijaya, I. M.

2017-02-01

The purpose of research were (1) a conceptual, functional model designed and implementation for spatial airports, (2) a causal, flow diagrams and mathematical equations made for airport activity, (3) obtained information on the conditions of space and activities at airports assessment, (4) the space and activities evaluation at airports based on national and international airport services standards, (5) options provided to improve the spatial and airport activities performance become the international standards airport. Descriptive method is used for the research. Husein Sastranegara Airport in Bandung, West Java, Indonesia was study location. The research was conducted on September 2015 to April 2016. A spatial analysis is used to obtain runway, taxiway and building airport geometric information. A system analysis is used to obtain the relationship between components in airports, dynamic simulation activity at airports and information on the results tables and graphs of dynamic model. Airport national and international standard could not be fulfilled by spatial and activity existing condition of Husein Sastranegara. Idea of re-location program is proposed as problem solving for constructing new airport which could be serving international air transportation.

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.

[Emergencies and continuous care: overload of the current on-call system and search for new models].

PubMed

Enríquez-Navascués, Jose M

2008-04-01

Emergency surgical care is still provided by means of an 24 hours physical presence "on-call" model (encompassing a normal day followed by "on call"), and is obligatory for all staff. This defective organisation of work has become unsustainable with the acceptance of the European 48 hours Directive, and is gruelling due to the excessive night work and feeling of being locked in that it entails. Emergency general and digestive system surgery care cannot be provided by a single organisational model, but has to be adapted to local circumstances. It is important to separate scheduled activity from urgent, and whereas increasingly more resources are dedicated to scheduled care, sufficient resources are also required for urgent activities, that cannot be considered as simply an "on call" or a fleeting stop in scheduled activity. Core subjects in residency, creating different levels of provision and activities, the analysis of urgent activity per work period and the identification of foreseeable activity, to maintain a pro-active mentality, and the disappearance of the "overtime" concept, should help provide another care model and method of remuneration.

Autonomous Learner Model Resource Book

ERIC Educational Resources Information Center

Betts, George T.; Carey, Robin J.; Kapushion, Blanche M.

2016-01-01

"Autonomous Learner Model Resource Book" includes activities and strategies to support the development of autonomous learners. More than 40 activities are included, all geared to the emotional, social, cognitive, and physical development of students. Teachers may use these activities and strategies with the entire class, small groups, or…

Mathematical Model Of Nerve/Muscle Interaction

NASA Technical Reports Server (NTRS)

Hannaford, Blake

1990-01-01

Phasic Excitation/Activation (PEA) mathematical model simulates short-term nonlinear dynamics of activation and control of muscle by nerve. Includes electronic and mechanical elements. Is homeomorphic at level of its three major building blocks, which represent motoneuron, dynamics of activation of muscle, and mechanics of muscle.

Environmental Education Activities & Programs 1998-1999.

ERIC Educational Resources Information Center

Bureau of Reclamation (Dept. of Interior), Denver, CO.

This document features descriptions of interactive learning models and presentations in environmental education concerning groundwater, geology, the environment, weather, water activities, and interactive games. Activities include: (1) GW-Standard; (2) GW-w/no Leaky Underground Storage Tank (No UST); (3) GW-Karst; (4) GW-Landfill Models--Standard…

Investigating Nitrogen Pollution: Activities and Models.

ERIC Educational Resources Information Center

Green Teacher, 2000

2000-01-01

Introduces activities on nitrogen, nitrogen pollution from school commuters, nitrogen response in native and introduced species, and nutrient loading models. These activities help students determine the nitrogen contribution from their parents' cars, test native plant responses to nitrogen, and experiment with the results of removing water from…

Promote Physical Activity--It's Proactive Guidance

ERIC Educational Resources Information Center

Gartrell, Dan; Sonsteng, Kathleen

2008-01-01

Healthy child development relies on physical activity. New curriculum models are effectively integrating physical activity in education programs. The authors describe three such models: S.M.A.R.T. (Stimulating Maturity through Accelerated Readiness Training); Kids in Action, incorporating cardiovascular endurance, muscle strength and endurance,…

Sexual risk behavior among youth: modeling the influence of prosocial activities and socioeconomic factors.

PubMed

Ramirez-Valles, J; Zimmerman, M A; Newcomb, M D

1998-09-01

Sexual activity among high-school-aged youths has steadily increased since the 1970s, emerging as a significant public health concern. Yet, patterns of youth sexual risk behavior are shaped by social class, race, and gender. Based on sociological theories of financial deprivation and collective socialization, we develop and test a model of the relationships among neighborhood poverty; family structure and social class position; parental involvement; prosocial activities; race; and gender as they predict youth sexual risk behavior. We employ structural equation modeling to test this model on a cross-sectional sample of 370 sexually active high-school students from a midwestern city; 57 percent (n = 209) are males and 86 percent are African American. We find that family structure indirectly predicts sexual risk behavior through neighborhood poverty, parental involvement, and prosocial activities. In addition, family class position indirectly predicts sexual risk behavior through neighborhood poverty and prosocial activities. We address implications for theory and health promotion.

Renewable Molecular Flasks with NADH Models: Combination of Light-Driven Proton Reduction and Biomimetic Hydrogenation of Benzoxazinones.

PubMed

Zhao, Liang; Wei, Jianwei; Lu, Junhua; He, Cheng; Duan, Chunying

2017-07-17

Using small molecules with defined pockets to catalyze chemical transformations resulted in attractive catalytic syntheses that echo the remarkable properties of enzymes. By modulating the active site of a nicotinamide adenine dinucleotide (NADH) model in a redox-active molecular flask, we combined biomimetic hydrogenation with in situ regeneration of the active site in a one-pot transformation using light as a clean energy source. This molecular flask facilitates the encapsulation of benzoxazinones for biomimetic hydrogenation of the substrates within the inner space of the flask using the active sites of the NADH models. The redox-active metal centers provide an active hydrogen source by light-driven proton reduction outside the pocket, allowing the in situ regeneration of the NADH models under irradiation. This new synthetic platform, which offers control over the location of the redox events, provides a regenerating system that exhibits high selectivity and efficiency and is extendable to benzoxazinone and quinoxalinone systems. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Approaching an experimental electron density model of the biologically active trans -epoxysuccinyl amide group-Substituent effects vs. crystal packing

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

Shi, Ming W.; Stewart, Scott G.; Sobolev, Alexandre N.

The trans-epoxysuccinyl amide group as a biologically active moiety in cysteine protease inhibitors such as loxistatin acid E64c has been used as a benchmark system for theoretical studies of environmental effects on the electron density of small active ingredients in relation to their biological activity. Here, the synthesis and the electronic properties of the smallest possible active site model compound are reported to close the gap between the unknown experimental electron density of trans-epoxysuccinyl amides and the well-known function of related drugs. Intramolecular substituent effects are separated from intermolecular crystal packing effects on the electron density, which allows us tomore » predict the conditions under which an experimental electron density investigation on trans-epoxysuccinyl amides will be possible. In this context, the special importance of the carboxylic acid function in the model compound for both crystal packing and biological activity is revealed through the novel tool of model energy analysis.« less

Quantitative Structure--Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Background: Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. Objective: In this study, a combinatorial QSAR approach has been employed for the creation of robust and predictive models of acute toxi...

Modeling Water Filtration

ERIC Educational Resources Information Center

Parks, Melissa

2014-01-01

Model-eliciting activities (MEAs) are not new to those in engineering or mathematics, but they were new to Melissa Parks. Model-eliciting activities are simulated real-world problems that integrate engineering, mathematical, and scientific thinking as students find solutions for specific scenarios. During this process, students generate solutions…

Comparing microscopic activity-based and traditional models of travel demand : an Austin area case study

DOT National Transportation Integrated Search

2007-09-01

Two competing approaches to travel demand modeling exist today. The more traditional 4-step travel demand models rely on aggregate demographic data at a traffic analysis zone (TAZ) level. Activity-based microsimulation methods employ more robus...

Integrated Modeling for the James Webb Space Telescope (JWST) Project: Structural Analysis Activities

NASA Technical Reports Server (NTRS)

Johnston, John; Mosier, Mark; Howard, Joe; Hyde, Tupper; Parrish, Keith; Ha, Kong; Liu, Frank; McGinnis, Mark

2004-01-01

This paper presents viewgraphs about structural analysis activities and integrated modeling for the James Webb Space Telescope (JWST). The topics include: 1) JWST Overview; 2) Observatory Structural Models; 3) Integrated Performance Analysis; and 4) Future Work and Challenges.

Improving the Students' Activity and Learning Outcomes on Social Sciences Subject Using Round Table and Rally Coach of Cooperative Learning Model

ERIC Educational Resources Information Center

Ningsih; Soetjipto, Budi Eko; Sumarmi

2017-01-01

The purpose of this study was: (1) to analyze increasing students' learning activity and learning outcomes. Student activities which were observed include the visual, verbal, listening, writing and mental visual activity; (2) to analyze the improvement of student learning outcomes using "Round Table" and "Rally Coach" Model of…

Creating Stimulating Learning and Thinking Using New Models of Activity-Based Learning and Metacognitive-Based Activities

ERIC Educational Resources Information Center

Pang, Katherine

2010-01-01

The purpose of this paper is to present a novel way to stimulate learning, creativity, and thinking based on a new understanding of activity-based learning (ABL) and two methods for developing metacognitive-based activities for the classroom. ABL, in this model, is based on the premise that teachers are distillers and facilitators of information…

Exact solutions to a spatially extended model of kinase-receptor interaction.

PubMed

Szopa, Piotr; Lipniacki, Tomasz; Kazmierczak, Bogdan

2011-10-01

B and Mast cells are activated by the aggregation of the immune receptors. Motivated by this phenomena we consider a simple spatially extended model of mutual interaction of kinases and membrane receptors. It is assumed that kinase activates membrane receptors and in turn the kinase molecules bound to the active receptors are activated by transphosphorylation. Such a type of interaction implies positive feedback and may lead to bistability. In this study we apply the Steklov eigenproblem theory to analyze the linearized model and find exact solutions in the case of non-uniformly distributed membrane receptors. This approach allows us to determine the critical value of receptor dephosphorylation rate at which cell activation (by arbitrary small perturbation of the inactive state) is possible. We found that cell sensitivity grows with decreasing kinase diffusion and increasing anisotropy of the receptor distribution. Moreover, these two effects are cooperating. We showed that the cell activity can be abruptly triggered by the formation of the receptor aggregate. Since the considered activation mechanism is not based on receptor crosslinking by polyvalent antigens, the proposed model can also explain B cell activation due to receptor aggregation following binding of monovalent antigens presented on the antigen presenting cell.

Differentiability of simulated MEG hippocampal, medial temporal and neocortical temporal epileptic spike activity.

PubMed

Stephen, Julia M; Ranken, Doug M; Aine, Cheryl J; Weisend, Michael P; Shih, Jerry J

2005-12-01

Previous studies have shown that magnetoencephalography (MEG) can measure hippocampal activity, despite the cylindrical shape and deep location in the brain. The current study extended this work by examining the ability to differentiate the hippocampal subfields, parahippocampal cortex, and neocortical temporal sources using simulated interictal epileptic activity. A model of the hippocampus was generated on the MRIs of five subjects. CA1, CA3, and dentate gyrus of the hippocampus were activated as well as entorhinal cortex, presubiculum, and neocortical temporal cortex. In addition, pairs of sources were activated sequentially to emulate various hypotheses of mesial temporal lobe seizure generation. The simulated MEG activity was added to real background brain activity from the five subjects and modeled using a multidipole spatiotemporal modeling technique. The waveforms and source locations/orientations for hippocampal and parahippocampal sources were differentiable from neocortical temporal sources. In addition, hippocampal and parahippocampal sources were differentiated to varying degrees depending on source. The sequential activation of hippocampal and parahippocampal sources was adequately modeled by a single source; however, these sources were not resolvable when they overlapped in time. These results suggest that MEG has the sensitivity to distinguish parahippocampal and hippocampal spike generators in mesial temporal lobe epilepsy.

Exploring Behavioral Markers of Long-Term Physical Activity Maintenance: A Case Study of System Identification Modeling within a Behavioral Intervention

ERIC Educational Resources Information Center

Hekler, Eric B.; Buman, Matthew P.; Poothakandiyil, Nikhil; Rivera, Daniel E.; Dzierzewski, Joseph M.; Aiken Morgan, Adrienne; McCrae, Christina S.; Roberts, Beverly L.; Marsiske, Michael; Giacobbi, Peter R., Jr.

2013-01-01

Efficacious interventions to promote long-term maintenance of physical activity are not well understood. Engineers have developed methods to create dynamical system models for modeling idiographic (i.e., within-person) relationships within systems. In behavioral research, dynamical systems modeling may assist in decomposing intervention effects…

Adapting the Sport Education Model for Children with Disabilities

ERIC Educational Resources Information Center

Presse, Cindy; Block, Martin E.; Horton, Mel; Harvey, William J.

2011-01-01

The sport education model (SEM) has been widely used as a curriculum and instructional model to provide children with authentic and active sport experiences in physical education. In this model, students are assigned various roles to gain a deeper understanding of the sport or activity. This article provides a brief overview of the SEM and…

Evolution of Forms of Representation in a Modelling Activity: A Case Study

ERIC Educational Resources Information Center

Garuti, Rossella; Dapueto, Carlo; Boero, Paolo

2003-01-01

The report describes a mathematical modelling activity of a natural phenomenon (transmission of hereditary characters in a codominance case) using the concept of model as a theoretical instrument. The chosen tool enables us to show how the construction of a link between reality and a model is related to the evolution of the graphical…

When does 1/2 = 1/3?: Modelling with Wet Fractions

ERIC Educational Resources Information Center

Fitzallen, Noleine

2015-01-01

Many fraction activities rely on the use of area models for developing partitioning skills. These models, however, are limited in their ability to assist students to visualise a fraction of an object when the whole changes. This article describes a fraction modelling activity that requires the transfer of water from one container to another. The…

A dynamical systems model of progesterone receptor interactions with inflammation in human parturition.

PubMed

Brubaker, Douglas; Barbaro, Alethea; R Chance, Mark; Mesiano, Sam

2016-08-19

Progesterone promotes uterine relaxation and is essential for the maintenance of pregnancy. Withdrawal of progesterone activity and increased inflammation within the uterine tissues are key triggers for parturition. Progesterone actions in myometrial cells are mediated by two progesterone receptor (PR) isoforms, PR-A and PR-B, that function as ligand-activated transcription factors. PR-B mediates relaxatory actions of progesterone, in part, by decreasing myometrial cell responsiveness to pro-inflammatory stimuli. These same pro-inflammatory stimuli promote the expression of PR-A which inhibits the anti-inflammatory activity of PR-B. Competitive interaction between the progesterone receptors then augments myometrial responsiveness to pro-inflammatory stimuli. The interaction between PR-B transcriptional activity and inflammation in the pregnancy myometrium is examined using a dynamical systems model in which quiescence and labor are represented as phase-space equilibrium points. Our model shows that PR-B transcriptional activity and the inflammatory load determine the stability of the quiescent and laboring phenotypes. The model is tested using published transcriptome datasets describing the mRNA abundances in the myometrium before and after the onset of labor at term. Surrogate transcripts were selected to reflect PR-B transcriptional activity and inflammation status. The model coupling PR-B activity and inflammation predicts contractile status (i.e., laboring or quiescent) with high precision and recall and outperforms uncoupled single and two-gene classifiers. Linear stability analysis shows that phase space bifurcations exist in our model that may reflect the phenotypic states of the pregnancy uterus. The model describes a possible tipping point for the transition of the quiescent to the contractile laboring phenotype. Our model describes the functional interaction between the PR-A:PR-B hypothesis and tissue level inflammation in the pregnancy uterus and is a first step in more sophisticated dynamical systems modeling of human partition. The model explains observed biochemical dynamics and as such will be useful for the development of a range of systems-based models using emerging data to predict preterm birth and identify strategies for its prevention.

Design, synthesis of allosteric peptide activator for human SIRT1 and its biological evaluation in cellular model of Alzheimer's disease.

PubMed

Kumar, Rahul; Nigam, Lokesh; Singh, Amrendra Pratap; Singh, Kusum; Subbarao, Naidu; Dey, Sharmistha

2017-02-15

Sirtuin 1 (SIRT1) is one of the member of the mammalian proteins of the Sirtuin family of NAD + dependent deacetylases, has recently been shown to attenuate amyloidogenic processing of amyloid protein precursor (APP) in in-vitro cell culture studies and transgenic mouse models of Alzheimer's disease (AD). SIRT1 has been shown to have a protective role against (AD). It has been reported earlier that increasing SIRT1 activity can prevent AD in mice model. Tripeptide as an activator of SIRT1 were screened on the basis of structural information by molecular docking and synthesized by solid phase method. The enhancement of biochemical activity of pure recombinant SIRT1 as well as SIRT1 in serum of AD patients in presence of tripeptide was done by Fluorescent Activity Assay. The activity of SIRT1 by peptide was assessed in IMR-32 cell line by measuring acetylated p53 level. Further the protective effect of SIRT1 activator in cellular model of AD was analyzed by MTT assay. We find CWR tripeptide as a SIRT1 activator by molecular docking, enhanced the activity of SIRT1 protein by lowering the Michaelis constant, Km by allosteric mechanism. The activity of serum SIRT1 of AD was also increases by CWR. It also decreased the acetylation of p53 in IMR32 neuroblastoma cells and protected the cell death caused by Aβ amyloid fragments in cell line model of AD. Thus, it can be concluded that CWR may serve as platform to elucidate further small molecule activator as a therapeutic agent for AD targeting SIRT1. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

A neuro-immune model of Myalgic Encephalomyelitis/Chronic fatigue syndrome.

PubMed

Morris, Gerwyn; Maes, Michael

2013-12-01

This paper proposes a neuro-immune model for Myalgic Encephalomyelitis/Chronic fatigue syndrome (ME/CFS). A wide range of immunological and neurological abnormalities have been reported in people suffering from ME/CFS. They include abnormalities in proinflammatory cytokines, raised production of nuclear factor-κB, mitochondrial dysfunctions, autoimmune responses, autonomic disturbances and brain pathology. Raised levels of oxidative and nitrosative stress (O&NS), together with reduced levels of antioxidants are indicative of an immuno-inflammatory pathology. A number of different pathogens have been reported either as triggering or maintaining factors. Our model proposes that initial infection and immune activation caused by a number of possible pathogens leads to a state of chronic peripheral immune activation driven by activated O&NS pathways that lead to progressive damage of self epitopes even when the initial infection has been cleared. Subsequent activation of autoreactive T cells conspiring with O&NS pathways cause further damage and provoke chronic activation of immuno-inflammatory pathways. The subsequent upregulation of proinflammatory compounds may activate microglia via the vagus nerve. Elevated proinflammatory cytokines together with raised O&NS conspire to produce mitochondrial damage. The subsequent ATP deficit together with inflammation and O&NS are responsible for the landmark symptoms of ME/CFS, including post-exertional malaise. Raised levels of O&NS subsequently cause progressive elevation of autoimmune activity facilitated by molecular mimicry, bystander activation or epitope spreading. These processes provoke central nervous system (CNS) activation in an attempt to restore immune homeostatsis. This model proposes that the antagonistic activities of the CNS response to peripheral inflammation, O&NS and chronic immune activation are responsible for the remitting-relapsing nature of ME/CFS. Leads for future research are suggested based on this neuro-immune model.

A Discrete Electromechanical Model for Human Cardiac Tissue: Effects of Stretch-Activated Currents and Stretch Conditions on Restitution Properties and Spiral Wave Dynamics

PubMed Central

Weise, Louis D.; Panfilov, Alexander V.

2013-01-01

We introduce an electromechanical model for human cardiac tissue which couples a biophysical model of cardiac excitation (Tusscher, Noble, Noble, Panfilov, 2006) and tension development (adjusted Niederer, Hunter, Smith, 2006 model) with a discrete elastic mass-lattice model. The equations for the excitation processes are solved with a finite difference approach, and the equations of the mass-lattice model are solved using Verlet integration. This allows the coupled problem to be solved with high numerical resolution. Passive mechanical properties of the mass-lattice model are described by a generalized Hooke's law for finite deformations (Seth material). Active mechanical contraction is initiated by changes of the intracellular calcium concentration, which is a variable of the electrical model. Mechanical deformation feeds back on the electrophysiology via stretch-activated ion channels whose conductivity is controlled by the local stretch of the medium. We apply the model to study how stretch-activated currents affect the action potential shape, restitution properties, and dynamics of spiral waves, under constant stretch, and dynamic stretch caused by active mechanical contraction. We find that stretch conditions substantially affect these properties via stretch-activated currents. In constantly stretched medium, we observe a substantial decrease in conduction velocity, and an increase of action potential duration; whereas, with dynamic stretch, action potential duration is increased only slightly, and the conduction velocity restitution curve becomes biphasic. Moreover, in constantly stretched medium, we find an increase of the core size and period of a spiral wave, but no change in rotation dynamics; in contrast, in the dynamically stretching medium, we observe spiral drift. Our results may be important to understand how altered stretch conditions affect the heart's functioning. PMID:23527160

A discrete electromechanical model for human cardiac tissue: effects of stretch-activated currents and stretch conditions on restitution properties and spiral wave dynamics.

PubMed

Weise, Louis D; Panfilov, Alexander V

2013-01-01

We introduce an electromechanical model for human cardiac tissue which couples a biophysical model of cardiac excitation (Tusscher, Noble, Noble, Panfilov, 2006) and tension development (adjusted Niederer, Hunter, Smith, 2006 model) with a discrete elastic mass-lattice model. The equations for the excitation processes are solved with a finite difference approach, and the equations of the mass-lattice model are solved using Verlet integration. This allows the coupled problem to be solved with high numerical resolution. Passive mechanical properties of the mass-lattice model are described by a generalized Hooke's law for finite deformations (Seth material). Active mechanical contraction is initiated by changes of the intracellular calcium concentration, which is a variable of the electrical model. Mechanical deformation feeds back on the electrophysiology via stretch-activated ion channels whose conductivity is controlled by the local stretch of the medium. We apply the model to study how stretch-activated currents affect the action potential shape, restitution properties, and dynamics of spiral waves, under constant stretch, and dynamic stretch caused by active mechanical contraction. We find that stretch conditions substantially affect these properties via stretch-activated currents. In constantly stretched medium, we observe a substantial decrease in conduction velocity, and an increase of action potential duration; whereas, with dynamic stretch, action potential duration is increased only slightly, and the conduction velocity restitution curve becomes biphasic. Moreover, in constantly stretched medium, we find an increase of the core size and period of a spiral wave, but no change in rotation dynamics; in contrast, in the dynamically stretching medium, we observe spiral drift. Our results may be important to understand how altered stretch conditions affect the heart's functioning.

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.

Developing high-resolution urban scale heavy-duty truck emission inventory using the data-driven truck activity model output

NASA Astrophysics Data System (ADS)

Perugu, Harikishan; Wei, Heng; Yao, Zhuo

2017-04-01

Air quality modelers often rely on regional travel demand models to estimate the vehicle activity data for emission models, however, most of the current travel demand models can only output reliable person travel activity rather than goods/service specific travel activity. This paper presents the successful application of data-driven, Spatial Regression and output optimization Truck model (SPARE-Truck) to develop truck-related activity inputs for the mobile emission model, and eventually to produce truck specific gridded emissions. To validate the proposed methodology, the Cincinnati metropolitan area in United States was selected as a case study site. From the results, it is found that the truck miles traveled predicted using traditional methods tend to underestimate - overall 32% less than proposed model- truck miles traveled. The coefficient of determination values for different truck types range between 0.82 and 0.97, except the motor homes which showed least model fit with 0.51. Consequently, the emission inventories calculated from the traditional methods were also underestimated i.e. -37% for NOx, -35% for SO2, -43% for VOC, -43% for BC, -47% for OC and - 49% for PM2.5. Further, the proposed method also predicted within ∼7% of the national emission inventory for all pollutants. The bottom-up gridding methodology used in this paper could allocate the emissions to grid cell where more truck activity is expected, and it is verified against regional land-use data. Most importantly, using proposed method it is easy to segregate gridded emission inventory by truck type, which is of particular interest for decision makers, since currently there is no reliable method to test different truck-category specific travel-demand management strategies for air pollution control.

Extracurricular activity participation moderates impact of family and school factors on adolescents' disruptive behavioural problems.

PubMed

Driessens, Corine M E F

2015-11-11

The prevalence of problem behaviours among British adolescents has increased in the past decades. Following Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model, it was hypothesized that youth problem behaviour is shaped in part by social environment. The aim of this project was to explore potential protective factors within the social environment of British youth's for the presentation of disruptive behavioural problems. This study used secondary data from the Longitudinal Study of Young People in England, a cohort study of secondary school students. These data were analysed with generalized estimation equations to take the correlation between the longitudinal observations into account. Three models were built. The first model determined the effect of family, school, and extracurricular setting on presentation of disruptive behavioural problems. The second model expanded the first model by assuming extracurricular activities as protective factors that moderated the interaction between family and school factors with disruptive behavioural problems. The third model described the effect of prior disruptive behaviour on current disruptive behaviour. Associations were found between school factors, family factors, involvement in extracurricular activities and presence of disruptive behavioural problems. Results from the second generalized estimating equation (GEE) logistic regression models indicated that extracurricular activities buffered the impact of school and family factors on the presence of disruptive behavioural problems. For instance, participation in sports activities decreased the effect of bullying on psychological distress. Results from the third model indicated that prior acts of disruptive behaviour reinforced current disruptive behaviour. This study supports Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model; social environment did influence the presence of disruptive behavioural problems for British adolescents. The potential of extracurricular activities to intervention strategies addressing disruptive behavioural problems of adolescents is discussed.

Structural investigation of protein kinase C inhibitors

NASA Technical Reports Server (NTRS)

Barak, D.; Shibata, M.; Rein, R.

1991-01-01

The phospholipid and Ca2+ dependent protein kinase (PKC) plays an essential role in a variety of cellular events. Inhibition of PKC was shown to arrest growth in tumor cell cultures making it a target for possible antitumor therapy. Calphostins are potent inhibitors of PKC with high affinity for the enzyme regulatory site. Structural characteristics of calphostins, which confer the inhibitory activity, are investigated by comparing their optimized structures with the existing models for PKC activation. The resulting model of inhibitory activity assumes interaction with two out of the three electrostatic interaction sites postulated for activators. The model shows two sites of hydrophobic interaction and enables the inhibitory activity of gossypol to be accounted for.

[Changes in proline-specific peptidase activity in experimental model of retrograde amnesia].

PubMed

Nazarova, G A; Zolotov, N N; Krupina, N A; Kraĭneva, V A; Garibova, T L; Voronina, T A

2007-01-01

Changes in proline-specific peptidase activity in the frontal cortex and hippocampus were studied using the experimental model of retrograde amnesia in rats. In one group, the amnesia was produced by a single injection of M-cholinergic antagonist scopolamine and the other group received the maximal electroconvulsive stimulation (MES). The amnesic effect was evaluated in passive avoidance test. In the amnesia models under consideration, the activity of prolylendopeptidase was significantly increased in both frontal cortex and hippocampus. The activity of dipeptidyl peptidase IV was significantly decreased in the cortex, whereas in the hippocampus it remained unchanged. Pyracetam inhibited prolylendopeptidase in the cortex and hippocampus, whereas dipeptidyl peptidase IV activity remained unchanged.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

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

Kinetics versus thermodynamics in materials modeling: The case of the di-vacancy in iron

NASA Astrophysics Data System (ADS)

Djurabekova, F.; Malerba, L.; Pasianot, R. C.; Olsson, P.; Nordlund, K.

2010-07-01

Monte Carlo models are widely used for the study of microstructural and microchemical evolution of materials under irradiation. However, they often link explicitly the relevant activation energies to the energy difference between local equilibrium states. We provide a simple example (di-vacancy migration in iron) in which a rigorous activation energy calculation, by means of both empirical interatomic potentials and density functional theory methods, clearly shows that such a link is not granted, revealing a migration mechanism that a thermodynamics-linked activation energy model cannot predict. Such a mechanism is, however, fully consistent with thermodynamics. This example emphasizes the importance of basing Monte Carlo methods on models where the activation energies are rigorously calculated, rather than deduced from widespread heuristic equations.

The Built Environment and Active Travel: Evidence from Nanjing, China.

PubMed

Feng, Jianxi

2016-03-08

An established relationship exists between the built environment and active travel. Nevertheless, the literature examining the impacts of different components of the built environment is limited. In addition, most existing studies are based on data from cities in the U.S. and Western Europe. The situation in Chinese cities remains largely unknown. Based on data from Nanjing, China, this study explicitly examines the influences of two components of the built environment--the neighborhood form and street form--on residents' active travel. Binary logistic regression analyses examined the effects of the neighborhood form and street form on subsistence, maintenance and discretionary travel, respectively. For each travel purpose, three models are explored: a model with only socio-demographics, a model with variables of the neighborhood form and a complete model with all variables. The model fit indicator, Nagelkerke's ρ², increased by 0.024 when neighborhood form variables are included and increased by 0.070 when street form variables are taken into account. A similar situation can be found in the models of maintenance activities and discretionary activities. Regarding specific variables, very limited significant impacts of the neighborhood form variables are observed, while almost all of the characteristics of the street form show significant influences on active transport. In Nanjing, street form factors have a more profound influence on active travel than neighborhood form factors. The focal point of the land use regulations and policy of local governments should shift from the neighborhood form to the street form to maximize the effects of policy interventions.

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.

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models.

PubMed

Kleinbach, Christian; Martynenko, Oleksandr; Promies, Janik; Haeufle, Daniel F B; Fehr, Jörg; Schmitt, Syn

2017-09-02

In the state of the art finite element AHBMs for car crash analysis in the LS-DYNA software material named *MAT_MUSCLE (*MAT_156) is used for active muscles modeling. It has three elements in parallel configuration, which has several major drawbacks: restraint approximation of the physical reality, complicated parameterization and absence of the integrated activation dynamics. This study presents implementation of the extended four element Hill-type muscle model with serial damping and eccentric force-velocity relation including [Formula: see text] dependent activation dynamics and internal method for physiological muscle routing. Proposed model was implemented into the general-purpose finite element (FE) simulation software LSDYNA as a user material for truss elements. This material model is verified and validated with three different sets of mammalian experimental data, taken from the literature. It is compared to the *MAT_MUSCLE (*MAT_156) Hill-type muscle model already existing in LS-DYNA, which is currently used in finite element human body models (HBMs). An application example with an arm model extracted from the FE ViVA OpenHBM is given, taking into account physiological muscle paths. The simulation results show better material model accuracy, calculation robustness and improved muscle routing capability compared to *MAT_156. The FORTRAN source code for the user material subroutine dyn21.f and the muscle parameters for all simulations, conducted in the study, are given at https://zenodo.org/record/826209 under an open source license. This enables a quick application of the proposed material model in LS-DYNA, especially in active human body models (AHBMs) for applications in automotive safety.

Quantitative structure activity relationship studies of piperazinyl phenylalanine derivatives as VLA-4/VCAM-1 inhibitors.

PubMed

Bhargava, Dinesh; Karthikeyan, C; Moorthy, N S H N; Trivedi, Piyush

2009-09-01

QSAR study was carried out for a series of piperazinyl phenylalanine derivatives exhibiting VLA-4/VCAM-1 inhibitory activity to find out the structural features responsible for the biological activity. The QSAR study was carried out on V-life Molecular Design Suite software and the derived best QSAR model by partial least square (forward) regression method showed 85.67% variation in biological activity. The statistically significant model with high correlation coefficient (r2=0.85) was selected for further study and the resulted validation parameters of the model, crossed squared correlation coefficient (q2=0.76 and pred_r2=0.42) show the model has good predictive ability. The model showed that the parameters SaaNEindex, SsClcount slogP,and 4PathCount are highly correlated with VLA-4/VCAM-1 inhibitory activity of piperazinyl phenylalanine derivatives. The result of the study suggests that the chlorine atoms in the molecule and fourth order fragmentation patterns in the molecular skeleton favour VLA-4/VCAM-1 inhibition shown by the title compounds whereas lipophilicity and nitrogen bonded to aromatic bond are not conducive for VLA-4/VCAM-1 inhibitory activity.

Synergistic effects in threshold models on networks.

PubMed

Juul, Jonas S; Porter, Mason A

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can-depending on a parameter-either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Synergistic effects in threshold models on networks

NASA Astrophysics Data System (ADS)

Juul, Jonas S.; Porter, Mason A.

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Hippocampal Morphology in a Rat Model of Depression: The Effects of Physical Activity

PubMed Central

Sierakowiak, Adam; Mattsson, Anna; Gómez-Galán, Marta; Feminía, Teresa; Graae, Lisette; Aski, Sahar Nikkhou; Damberg, Peter; Lindskog, Mia; Brené, Stefan; Åberg, Elin

2015-01-01

Accumulating in vivo and ex vivo evidences show that humans suffering from depression have decreased hippocampal volume and altered spine density. Moreover, physical activity has an antidepressant effect in humans and in animal models, but to what extent physical activity can affect hippocampal volume and spine numbers in a model for depression is not known. In this study we analyzed whether physical activity affects hippocampal volume and spine density by analyzing a rodent genetic model of depression, Flinders Sensitive Line Rats (FSL), with Magnetic Resonance Imaging (MRI) and ex vivo Golgi staining. We found that physical activity in the form of voluntary wheel running during 5 weeks increased hippocampal volume. Moreover, runners also had larger numbers of thin spines in the dentate gyrus. Our findings support that voluntary wheel running, which is antidepressive in FSL rats, is associated with increased hippocampal volume and spine numbers. PMID:25674191

Hippocampal morphology in a rat model of depression: the effects of physical activity.

PubMed

Sierakowiak, Adam; Mattsson, Anna; Gómez-Galán, Marta; Feminía, Teresa; Graae, Lisette; Aski, Sahar Nikkhou; Damberg, Peter; Lindskog, Mia; Brené, Stefan; Åberg, Elin

2014-01-01

Accumulating in vivo and ex vivo evidences show that humans suffering from depression have decreased hippocampal volume and altered spine density. Moreover, physical activity has an antidepressant effect in humans and in animal models, but to what extent physical activity can affect hippocampal volume and spine numbers in a model for depression is not known. In this study we analyzed whether physical activity affects hippocampal volume and spine density by analyzing a rodent genetic model of depression, Flinders Sensitive Line Rats (FSL), with Magnetic Resonance Imaging (MRI) and ex vivo Golgi staining. We found that physical activity in the form of voluntary wheel running during 5 weeks increased hippocampal volume. Moreover, runners also had larger numbers of thin spines in the dentate gyrus. Our findings support that voluntary wheel running, which is antidepressive in FSL rats, is associated with increased hippocampal volume and spine numbers.

Design, synthesis, molecular modeling and biological evaluation of novel 2,3-dihydrophthalazine-1,4-dione derivatives as potential anticonvulsant agents

NASA Astrophysics Data System (ADS)

El-Helby, Abdel Ghany A.; Ayyad, Rezk R.; Sakr, Helmy M.; Abdelrahim, Adel S.; El-Adl, K.; Sherbiny, Farag S.; Eissa, Ibrahim H.; Khalifa, Mohamed M.

2017-02-01

In view of their expected anticonvulsant activity, some novel derivatives of 2,3-dihydrophthalazine-1,4-dione 4-22 were designed, synthesized and evaluated using pentylenetetrazole (PTZ) and picrotoxin as convulsion-inducing models. Moreover, the most active compounds were tested against electrical induced convulsion using maximal electroshock (MES) models of seizures. Most of the tested compounds showed considerable anticonvulsant activity in at least one of the anticonvulsant tests. Compounds 13 and 14g were proved to be the most potent compounds of this series with relatively low toxicity in the median lethal dose test when compared with the reference drug. Molecular modeling studies were done to verify the biological activity. The obtained results showed that the most potent compounds could be useful as a template for future design, optimization, and investigation to produce more active analogues.

Predicting the Activity Coefficients of Free-Solvent for Concentrated Globular Protein Solutions Using Independently Determined Physical Parameters

PubMed Central

McBride, Devin W.; Rodgers, Victor G. J.

2013-01-01

The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations. PMID:24324733

Development of Novel Repellents Using Structure - Activity Modeling of Compounds in the USDA Archival Database

DTIC Science & Technology

2011-01-01

used in efforts to develop QSAR models. Measurement of Repellent Efficacy Screening for Repellency of Compounds with Unknown Toxicology In screening...CPT) were used to develop Quantitative Structure Activity Relationship ( QSAR ) models to predict repellency. Successful prediction of novel...acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not

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.

Modelling in Action. Examining How Students Approach Modelling Real Life Situations. Three Case Studies. Model of the Movement of an Elevator

ERIC Educational Resources Information Center

Rivas, Eugenia Marmolejo

2015-01-01

By means of three case studies, we will present two mathematical modelling activities that are suitable for students enrolled in senior high school and the first year of mathematics at university level. The activities have been designed to enrich the learning process and promote the formation of vital modelling skills. In case studies one and two,…

Chronic inhibition of Ca(2+)/calmodulin kinase II activity in the pilocarpine model of epilepsy.

PubMed

Churn, S B; Kochan, L D; DeLorenzo, R J

2000-09-01

The development of symptomatic epilepsy is a model of long-term plasticity changes in the central nervous system. The rat pilocarpine model of epilepsy was utilized to study persistent alterations in calcium/calmodulin-dependent kinase II (CaM kinase II) activity associated with epileptogenesis. CaM kinase II-dependent substrate phosphorylation and autophosphorylation were significantly inhibited for up to 6 weeks following epileptogenesis in both the cortex and hippocampus, but not in the cerebellum. The net decrease in CaM kinase II autophosphorylation and substrate phosphorylation was shown to be due to decreased kinase activity and not due to increased phosphatase activity. The inhibition in CaM kinase II activity and the development of epilepsy were blocked by pretreating seizure rats with MK-801 indicating that the long-lasting decrease in CaM kinase II activity was dependent on N-methyl-D-aspartate receptor activation. In addition, the inhibition of CaM kinase II activity was associated in time and regional localization with the development of spontaneous recurrent seizure activity. The decrease in enzyme activity was not attributed to a decrease in the alpha or beta kinase subunit protein expression level. Thus, the significant inhibition of the enzyme occurred without changes in kinase protein expression, suggesting a long-lasting, post-translational modification of the enzyme. This is the first published report of a persistent, post-translational alteration of CaM kinase II activity in a model of epilepsy characterized by spontaneous recurrent seizure activity.

Integrating Motivational Activities into Instruction: A Developmental Model.

ERIC Educational Resources Information Center

Brawer, Michael P.

A model for integrating motivational activities into instruction and the problem with motivational activities in the classroom for the disadvantaged learner are examined. Eight basic learning processes are identified that the teacher should understand in preparation for presenting information to students: attention/reception, selective perception,…

Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

EPA Science Inventory

In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

10 CFR 110.50 - Terms.

Code of Federal Regulations, 2011 CFR

2011-01-01

... and activity level in TBq, both for single and aggregate shipments; (E) Make, model and serial number... exporting facility; (D) Radionuclides and activity level in TBq, both for single and aggregate shipments; (E) Make, model and serial number, radionuclide, and activity level for any Category 1 and 2 sealed sources...

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…

Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires.

PubMed

Gupta, Nidhi; Heiden, Marina; Mathiassen, Svend Erik; Holtermann, Andreas

2016-05-01

We aimed at developing and evaluating statistical models predicting objectively measured occupational time spent sedentary or in physical activity from self-reported information available in large epidemiological studies and surveys. Two-hundred-and-fourteen blue-collar workers responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time. Least-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire. A full prediction model based on age, gender, body mass index, job group, self-reported occupational physical activity (OPA), and self-reported occupational sedentary time (OST) explained 63% (R (2)adjusted) of the variance of both objectively measured time spent sedentary and in physical activity since these two exposures were complementary. Single-predictor models based only on self-reported information about either OPA or OST explained 21% and 38%, respectively, of the variance of the objectively measured exposures. Internal validation using bootstrapping suggested that the full and single-predictor models would show almost the same performance in new datasets as in that used for modelling. Both full and single-predictor models based on self-reported information typically available in most large epidemiological studies and surveys were able to predict objectively measured occupational time spent sedentary or in physical activity, with explained variances ranging from 21-63%.

Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

PubMed

Nargotra, Amit; Sharma, Sujata; Koul, Jawahir Lal; Sangwan, Pyare Lal; Khan, Inshad Ali; Kumar, Ashwani; Taneja, Subhash Chander; Koul, Surrinder

2009-10-01

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.

Shoulder model validation and joint contact forces during wheelchair activities.

PubMed

Morrow, Melissa M B; Kaufman, Kenton R; An, Kai-Nan

2010-09-17

Chronic shoulder impingement is a common problem for manual wheelchair users. The loading associated with performing manual wheelchair activities of daily living is substantial and often at a high frequency. Musculoskeletal modeling and optimization techniques can be used to estimate the joint contact forces occurring at the shoulder to assess the soft tissue loading during an activity and to possibly identify activities and strategies that place manual wheelchair users at risk for shoulder injuries. The purpose of this study was to validate an upper extremity musculoskeletal model and apply the model to wheelchair activities for analysis of the estimated joint contact forces. Upper extremity kinematics and handrim wheelchair kinetics were measured over three conditions: level propulsion, ramp propulsion, and a weight relief lift. The experimental data were used as input to a subject-specific musculoskeletal model utilizing optimization to predict joint contact forces of the shoulder during all conditions. The model was validated using a mean absolute error calculation. Model results confirmed that ramp propulsion and weight relief lifts place the shoulder under significantly higher joint contact loading than level propulsion. In addition, they exhibit large superior contact forces that could contribute to impingement. This study highlights the potential impingement risk associated with both the ramp and weight relief lift activities. Level propulsion was shown to have a low relative risk of causing injury, but with consideration of the frequency with which propulsion is performed, this observation is not conclusive.

Active and Reactive Power Optimal Dispatch Associated with Load and DG Uncertainties in Active Distribution Network

NASA Astrophysics Data System (ADS)

Gao, F.; Song, X. H.; Zhang, Y.; Li, J. F.; Zhao, S. S.; Ma, W. Q.; Jia, Z. Y.

2017-05-01

In order to reduce the adverse effects of uncertainty on optimal dispatch in active distribution network, an optimal dispatch model based on chance-constrained programming is proposed in this paper. In this model, the active and reactive power of DG can be dispatched at the aim of reducing the operating cost. The effect of operation strategy on the cost can be reflected in the objective which contains the cost of network loss, DG curtailment, DG reactive power ancillary service, and power quality compensation. At the same time, the probabilistic constraints can reflect the operation risk degree. Then the optimal dispatch model is simplified as a series of single stage model which can avoid large variable dimension and improve the convergence speed. And the single stage model is solved using a combination of particle swarm optimization (PSO) and point estimate method (PEM). Finally, the proposed optimal dispatch model and method is verified by the IEEE33 test system.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

A Novel Model for the Entire Settling-Thickening Process in a Secondary Settling Tank.

PubMed

He, Zhijiang; Zhang, Yuankai; Wang, Hongchen; Qi, Lu; Yin, Xunfei; Zhang, Xiaojun; Wen, Yang

2016-12-01

  Sludge settling and thickening occur simultaneously in secondary settling tanks (SSTs). The ability to accurately calculate the settling and thickening capacity of activated sludge was of great importance. Despite extensive studies on the development of settling velocity models for use with SSTs, these models have not been applied due to the difficulty in calibrating the related parameters. Additionally, there have been some studies of the thickening behavior of the activated sludge in SSTs. In this study, a novel settling and thickening model for activated sludge was developed, and the model was validated using experimental data (R2 = 0.830 to 0.963, p < 0.001), which is more reasonable for the characterization of the settling and thickening behavior of the activated sludge in an SST. The application of these models requires only one critical parameter, namely, the stirred sludge volume index SSVI3.5, which is readily available in a water resource recovery facility.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

PubMed Central

Angelaki, Dora E

2017-01-01

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. PMID:29043978

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.

The spatiotemporal MEG covariance matrix modeled as a sum of Kronecker products.

PubMed

Bijma, Fetsje; de Munck, Jan C; Heethaar, Rob M

2005-08-15

The single Kronecker product (KP) model for the spatiotemporal covariance of MEG residuals is extended to a sum of Kronecker products. This sum of KP is estimated such that it approximates the spatiotemporal sample covariance best in matrix norm. Contrary to the single KP, this extension allows for describing multiple, independent phenomena in the ongoing background activity. Whereas the single KP model can be interpreted by assuming that background activity is generated by randomly distributed dipoles with certain spatial and temporal characteristics, the sum model can be physiologically interpreted by assuming a composite of such processes. Taking enough terms into account, the spatiotemporal sample covariance matrix can be described exactly by this extended model. In the estimation of the sum of KP model, it appears that the sum of the first 2 KP describes between 67% and 93%. Moreover, these first two terms describe two physiological processes in the background activity: focal, frequency-specific alpha activity, and more widespread non-frequency-specific activity. Furthermore, temporal nonstationarities due to trial-to-trial variations are not clearly visible in the first two terms, and, hence, play only a minor role in the sample covariance matrix in terms of matrix power. Considering the dipole localization, the single KP model appears to describe around 80% of the noise and seems therefore adequate. The emphasis of further improvement of localization accuracy should be on improving the source model rather than the covariance model.

An ocular biomechanic model for dynamic simulation of different eye movements.

PubMed

Iskander, J; Hossny, M; Nahavandi, S; Del Porto, L

2018-04-11

Simulating and analysing eye movement is useful for assessing visual system contribution to discomfort with respect to body movements, especially in virtual environments where simulation sickness might occur. It can also be used in the design of eye prosthesis or humanoid robot eye. In this paper, we present two biomechanic ocular models that are easily integrated into the available musculoskeletal models. The model was previously used to simulate eye-head coordination. The models are used to simulate and analyse eye movements. The proposed models are based on physiological and kinematic properties of the human eye. They incorporate an eye-globe, orbital suspension tissues and six muscles with their connective tissues (pulleys). Pulleys were incorporated in rectus and inferior oblique muscles. The two proposed models are the passive pulleys and the active pulleys models. Dynamic simulations of different eye movements, including fixation, saccade and smooth pursuit, are performed to validate both models. The resultant force-length curves of the models were similar to the experimental data. The simulation results show that the proposed models are suitable to generate eye movement simulations with results comparable to other musculoskeletal models. The maximum kinematic root mean square error (RMSE) is 5.68° and 4.35° for the passive and active pulley models, respectively. The analysis of the muscle forces showed realistic muscle activation with increased muscle synergy in the active pulley model. Copyright © 2018 Elsevier Ltd. All rights reserved.

A New Activity-Based Financial Cost Management Method

NASA Astrophysics Data System (ADS)

Qingge, Zhang

The standard activity-based financial cost management model is a new model of financial cost management, which is on the basis of the standard cost system and the activity-based cost and integrates the advantages of the two. It is a new model of financial cost management with more accurate and more adequate cost information by taking the R&D expenses as the accounting starting point and after-sale service expenses as the terminal point and covering the whole producing and operating process and the whole activities chain and value chain aiming at serving the internal management and decision.

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.

Thermal models for basaltic volcanism on Io

USGS Publications Warehouse

Keszthelyil, L.; McEwen, A.

1997-01-01

We present a new model for the thermal emissions from active basaltic eruptions on Io. While our methodology shares many similarities with previous work, it is significantly different in that (1) it uses a field tested cooling model and (2) the model is more applicable to pahoehoe flows and lava lakes than fountain-fed, channelized, 'a'a flows. This model demonstrates the large effect lava porosity has on the surface cooling rate (with denser flows cooling more slowly) and provides a preliminary tool for examining some of the hot spots on Io. The model infrared signature of a basaltic eruption is largely controlled by a single parameter, ??, the average survival time for a lava surface. During an active eruption surfaces are quickly covered or otherwise destroyed and typical values of ?? for a basaltic eruption are expected to be on the order of 10 seconds to 10 minutes. Our model suggests that the Galileo SSI eclipse data are consistent with moderately active to quiescent basaltic lava lakes but are not diagnostic of such activity. Copyright 1997 by the American Geophysical Union.

Validating proposed migration equation and parameters' values as a tool to reproduce and predict 137Cs vertical migration activity in Spanish soils.

PubMed

Olondo, C; Legarda, F; Herranz, M; Idoeta, R

2017-04-01

This paper shows the procedure performed to validate the migration equation and the migration parameters' values presented in a previous paper (Legarda et al., 2011) regarding the migration of 137 Cs in Spanish mainland soils. In this paper, this model validation has been carried out checking experimentally obtained activity concentration values against those predicted by the model. This experimental data come from the measured vertical activity profiles of 8 new sampling points which are located in northern Spain. Before testing predicted values of the model, the uncertainty of those values has been assessed with the appropriate uncertainty analysis. Once establishing the uncertainty of the model, both activity concentration values, experimental versus model predicted ones, have been compared. Model validation has been performed analyzing its accuracy, studying it as a whole and also at different depth intervals. As a result, this model has been validated as a tool to predict 137 Cs behaviour in a Mediterranean environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physical Modeling of Activation Energy in Organic Semiconductor Devices based on Energy and Momentum Conservations

PubMed Central

Mao, Ling-Feng; Ning, H.; Hu, Changjun; Lu, Zhaolin; Wang, Gaofeng

2016-01-01

Field effect mobility in an organic device is determined by the activation energy. A new physical model of the activation energy is proposed by virtue of the energy and momentum conservation equations. The dependencies of the activation energy on the gate voltage and the drain voltage, which were observed in the experiments in the previous independent literature, can be well explained using the proposed model. Moreover, the expression in the proposed model, which has clear physical meanings in all parameters, can have the same mathematical form as the well-known Meyer-Neldel relation, which lacks of clear physical meanings in some of its parameters since it is a phenomenological model. Thus it not only describes a physical mechanism but also offers a possibility to design the next generation of high-performance optoelectronics and integrated flexible circuits by optimizing device physical parameter. PMID:27103586

Dynamical Properties of a Living Nematic

NASA Astrophysics Data System (ADS)

Genkin, Mikhail

The systems, which are made of a large number or interacting particles, or agents that convert the energy stored in the environment into mechanical motion, are called active systems, or active matter. The examples of active matter include both living and synthetic systems. The size of agents varies significantly: bird flocks and fish schools represent macroscopic active systems, while suspensions of living organisms or artificial colloidal particles are examples of microscopic ones. In this work, I studied one of the simplest realization of active matter termed living (or active) nematics, that can be conceived by mixing swimming bacteria and nematic liquid crystal. Using modeling, numerical simulations and experiments I studied various dynamical properties of active nematics. This work hints into new methods of control and manipulation of active matter. Active nematic exhibits complex spatiotemporal behavior manifested by formation, proliferation, and annihilation of topological defects. A new computational 2D model coupling nematic liquid crystal and swimming bacteria dynamics have been proposed. We investigated the developed system of partial differential equations analytically and integrated it numerically using the highly efficient parallel GPU code. The integration results are in a very good agreement with other theoretical and experimental studies. In addition, our model revealed a number of testable phenomena. The major model prediction (bacteria accumulation in positive and depletion in negative topological defects) was tested by a dedicated experiment. We extended our model to study active nematics in a biphasic state, where nematic and isotropic phases coexist. Typically this coexistence is manifested by formation of tactoids - isotropic elongated regions surrounded by nematic phase, or nematic regions surrounded by isotropic phase. Using numerical integration, we revealed fundamental properties of such systems. Our main model outcome - spontaneous negative charging of isotropic-nematic interfaces - was confirmed by the experiment. The provided modeling and experimental results are in a very good qualitative and quantitative agreement. At last, we studied living nematics experimentally. We worked with swimming bacteria Bacillus subtilis suspended in disodium cromoglycate (DSCG) liquid crystal. Using cylindrical confinement, we were able to observe quantization of nematics' bending instability. Our experimental results revealed a complex interplay between bacteria self-propulsion and nematics' elasticity in the presence of cylindrical confinements of different sizes.

Applying the Transtheoretical Model to Physical Activity Behavior in Individuals With Non-Cystic Fibrosis Bronchiectasis.

PubMed

Wilson, Jason J; Kirk, Alison; Hayes, Kate; Bradbury, Ian; McDonough, Suzanne; Tully, Mark A; O'Neill, Brenda; Bradley, Judy M

2016-01-01

The transtheoretical model has been successful in promoting health behavior change in general and clinical populations. However, there is little knowledge about the application of the transtheoretical model to explain physical activity behavior in individuals with non-cystic fibrosis bronchiectasis. The aim was to examine patterns of (1) physical activity and (2) mediators of behavior change (self-efficacy, decisional balance, and processes of change) across stages of change in individuals with non-cystic fibrosis bronchiectasis. Fifty-five subjects with non-cystic fibrosis bronchiectasis (mean age ± SD = 63 ± 10 y) had physical activity assessed over 7 d using an accelerometer. Each component of the transtheoretical model was assessed using validated questionnaires. Subjects were divided into groups depending on stage of change: Group 1 (pre-contemplation and contemplation; n = 10), Group 2 (preparation; n = 20), and Group 3 (action and maintenance; n = 25). Statistical analyses included one-way analysis of variance and Tukey-Kramer post hoc tests. Physical activity variables were significantly (P < .05) higher in Group 3 (action and maintenance) compared with Group 2 (preparation) and Group 1 (pre-contemplation and contemplation). For self-efficacy, there were no significant differences between groups for mean scores (P = .14). Decisional balance cons (barriers to being physically active) were significantly lower in Group 3 versus Group 2 (P = .032). For processes of change, substituting alternatives (substituting inactive options for active options) was significantly higher in Group 3 versus Group 1 (P = .01), and enlisting social support (seeking out social support to increase and maintain physical activity) was significantly lower in Group 3 versus Group 2 (P = .038). The pattern of physical activity across stages of change is consistent with the theoretical predictions of the transtheoretical model. Constructs of the transtheoretical model that appear to be important at different stages of change include decisional balance cons, substituting alternatives, and enlisting social support. This study provides support to explore transtheoretical model-based physical activity interventions in individuals with non-cystic fibrosis bronchiectasis. (ClinicalTrials.gov registration NCT01569009.). Copyright © 2016 by Daedalus Enterprises.

Rural Active Living: A Call to Action.

PubMed

Umstattd Meyer, M Renée; Moore, Justin B; Abildso, Christiaan; Edwards, Michael B; Gamble, Abigail; Baskin, Monica L

2016-01-01

Rural residents are less physically active than their urban counterparts and disproportionately affected by chronic diseases and conditions associated with insufficient activity. While the ecological model has been successful in promoting and translating active living research in urban settings, relatively little research has been conducted in rural settings. The resulting research gap prohibits a comprehensive understanding and application of solutions for active living in rural America. Therefore, the purpose of this article was to assess the evidence base for an ecological model of active living for rural populations and outline key scientific gaps that inhibit the development and application of solutions. Specifically, we reexamined the 4 domains conceptualized by the model and suggest that there is a dearth of research specific to rural communities across all areas of the framework. Considering the limited rural-specific efforts, we propose areas that need addressing to mobilize rural active living researchers and practitioners into action.

Electrochemical modelling of QD-phospholipid interactions.

PubMed

Zhang, Shengwen; Chen, Rongjun; Malhotra, Girish; Critchley, Kevin; Vakurov, Alexander; Nelson, Andrew

2014-04-15

The aggregation of quantum dots (QDs) and capping of individual QDs affects their activity towards biomembrane models. Electrochemical methods using a phospholipid layer on mercury (Hg) membrane model have been used to determine the phospholipid monolayer activity of thioglycollic acid (TGA) coated quantum dots (QDs) as an indicator of biomembrane activity. The particles were characterised for size and charge. The activity of the QDs towards dioleoyl phosphatidylcholine (DOPC) monolayers is pH dependent, and is most active at pH 8.2 within the pH range 8.2-6.5 examined in this work. This pH dependent activity is the result of increased particle aggregation coupled to decreasing surface charge emanating from the TGA carboxylic groups employed to stabilize the QD dispersion in aqueous media. Capping the QDs with CdS/ZnS lowers the particles' activity to phospholipid monolayers. Copyright © 2014 Elsevier Inc. All rights reserved.

Rural Active Living: A Call to Action

PubMed Central

Meyer, M. Renée Umstattd; Moore, Justin B.; Abildso, Christiaan; Edwards, Michael B.; Gamble, Abigail; Baskin, Monica L.

2015-01-01

Rural residents are less physically active than their urban counterparts and disproportionately affected by chronic diseases and conditions associated with insufficient activity. While the ecological model has been successful in promoting and translating active living research in urban settings, relatively little research has been conducted in rural settings. The resulting research gap prohibits a comprehensive understanding and application of solutions for active living in rural America. Therefore, the purpose of this paper was to assess the evidence-base for an ecological model of active living for rural populations and outline key scientific gaps that inhibit the development and application of solutions. Specifically, we reexamined the four domains conceptualized by the model and suggest there is a dearth of research specific to rural communities across all areas of the framework. Considering the limited rural-specific efforts, we propose areas that need addressing in order to mobilize rural active living researchers and practitioners into action. PMID:26327514

Antidepressant Activity of Brahmi in Albino Mice

PubMed Central

Kadali, SLDV Ramana Murty; M.C., Das; Rao A.S.R., Srinivasa; Sri G, Karuna

2014-01-01

Context: In traditional system of medicine brahmi has been used to enhance memory. Recently it has been reported to have action in psychiatric disorders. With these backgrounds the work has been undertaken to study antidepressant activity of brahmi in albino mice. Aim: To evaluate antidepressant activity of brahmi in experimental models. Materials and Methods: The antidepressant activity was studied in albino mice using forced swimming test (FST), tail suspension test (TST) and shock induced depression (SID). Imipramine (10mg/kg), fluoxetine (30mg/kg) were used as standard drugs and brahmi (10, 20, 30mg/kg) was used as test drug. Results: Brahmi exhibited significant decrease in duration of immobility in FST and reduced the shock induced decrease in activity in SID models. It didn’t show any activity in the TST model. Conclusion: Brahmi has shown antidepressant activity in FST and SID. PMID:24783074

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

PubMed

Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

2015-12-21

Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

Use of the Pyrithiamine-Induced Thiamine Deficient Animal Model of Korsakoff’s Syndrome for Exploratory Research Activities in Undergraduate Physiological Psychology

PubMed Central

Flint, Robert W.; Hill, Jonathan E.; Sandusky, Leslie A.; Marino, Christina L.

2007-01-01

Undergraduate neuroscience laboratory activities frequently focus on exercises that build student’s wet/dry laboratory skills, foster critical thinking, and provide opportunities for hands-on experiences. Such activities are, without a doubt, extremely important, but sometimes fall short of modeling actual research and often lack the ‘unknown’ hypothetical nature accompanying empirical studies. In this article we report a series of research activities using an animal model of Korsakoff’s syndrome in a Physiological Psychology course. The activities involve testing hypotheses regarding performance of animals with experimentally-induced Korsakoff’s syndrome and the effectiveness of glucose as a memory-enhancer in this model. Students were given a set of 24 articles for use in answering a series of laboratory report questions regarding the activities. At the conclusion of the course, students were asked to complete a questionnaire designed to assess the effectiveness of the laboratory activities. Results of the laboratory exercises indicated that locomotor activity, environmental habituation, and anxiety were unaffected in the Korsakoff condition, and glucose had no effect. Results of performance in the T-maze indicated that Korsakoff animals had significantly fewer spontaneous alternations than controls, but Korsakoff animals given glucose did not reveal this difference. Results of the student assessments indicated that the activities were considered educational, challenging, and more interesting than standard laboratory activities designed to reproduce reliable phenomena. PMID:23494173

Modeling activated states of GPCRs: the rhodopsin template.

PubMed

Niv, Masha Y; Skrabanek, Lucy; Filizola, Marta; Weinstein, Harel

2006-01-01

Activation of G Protein-Coupled Receptors (GPCRs) is an allosteric mechanism triggered by ligand binding and resulting in conformational changes transduced by the transmembrane domain. Models of the activated forms of GPCRs have become increasingly necessary for the development of a clear understanding of signal propagation into the cell. Experimental evidence points to a multiplicity of conformations related to the activation of the receptor, rendered important physiologically by the suggestion that different conformations may be responsible for coupling to different signaling pathways. In contrast to the inactive state of rhodopsin (RHO) for which several high quality X-ray structures are available, the structure-related information for the active states of rhodopsin and all other GPCRs is indirect. We have collected and stored such information in a repository we maintain for activation-specific structural data available for rhodopsin-like GPCRs, http://www.physiology.med.cornell.edu/GPCRactivation/gpcrindex.html . Using these data as structural constraints, we have applied Simulated Annealing Molecular Dynamics to construct a number of different active state models of RHO starting from the known inactive structure. The common features of the models indicate that TM3 and TM5 play an important role in activation, in addition to the well-established rearrangement of TM6. Some of the structural changes observed in these models occur in regions that were not involved in the constraints, and have not been previously tested experimentally; they emerge as interesting candidates for further experimental exploration of the conformational space of activated GPCRs. We show that none of the normal modes calculated from the inactive structure has a dominant contribution along the path of conformational rearrangement from inactive to the active forms of RHO in the models. This result may differentiate rhodopsin from other GPCRs, and the reasons for this difference are discussed in the context of the structural properties and the physiological function of the protein.

Testing a self-determination theory model of children’s physical activity motivation: a cross-sectional study

PubMed Central

2013-01-01

Background Understanding children’s physical activity motivation, its antecedents and associations with behavior is important and can be advanced by using self-determination theory. However, research among youth is largely restricted to adolescents and studies of motivation within certain contexts (e.g., physical education). There are no measures of self-determination theory constructs (physical activity motivation or psychological need satisfaction) for use among children and no previous studies have tested a self-determination theory-based model of children’s physical activity motivation. The purpose of this study was to test the reliability and validity of scores derived from scales adapted to measure self-determination theory constructs among children and test a motivational model predicting accelerometer-derived physical activity. Methods Cross-sectional data from 462 children aged 7 to 11 years from 20 primary schools in Bristol, UK were analysed. Confirmatory factor analysis was used to examine the construct validity of adapted behavioral regulation and psychological need satisfaction scales. Structural equation modelling was used to test cross-sectional associations between psychological need satisfaction, motivation types and physical activity assessed by accelerometer. Results The construct validity and reliability of the motivation and psychological need satisfaction measures were supported. Structural equation modelling provided evidence for a motivational model in which psychological need satisfaction was positively associated with intrinsic and identified motivation types and intrinsic motivation was positively associated with children’s minutes in moderate-to-vigorous physical activity. Conclusions The study provides evidence for the psychometric properties of measures of motivation aligned with self-determination theory among children. Children’s motivation that is based on enjoyment and inherent satisfaction of physical activity is associated with their objectively-assessed physical activity and such motivation is positively associated with perceptions of psychological need satisfaction. These psychological factors represent potential malleable targets for interventions to increase children’s physical activity. PMID:24067078

Active Learning with Statistical Models.

DTIC Science & Technology

1995-01-01

Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

A Hypermedia Model for Teaching Technology.

ERIC Educational Resources Information Center

Savage, Ernest N.

Ohio's Model Industrial Technology Systems (MITS) project was initiated in 1987 to achieve the following: identify good activities in the areas of physical, communication, and bio-related technology; standardize the activities' format; and provide a coding system for their eventual use in a hypermedia system. To date, 220 activities have been…

The Relation between Employee Organizational and Professional Development Activities

ERIC Educational Resources Information Center

Blau, Gary; Andersson, Lynne; Davis, Kathleen; Daymont, Tom; Hochner, Arthur; Koziara, Karen; Portwood, Jim; Holladay, Blair

2008-01-01

A model is presented showing hypothesized common and parallel antecedents of employee organizational development activity (ODA) versus professional development activity (PDA). A common antecedent is expected to affect both ODA and PDA, while a parallel antecedent is expected to affect its corresponding work referent. This model was tested using a…

Fractional models of seismoacoustic and electromagnetic activity

NASA Astrophysics Data System (ADS)

Shevtsov, Boris; Sheremetyeva, Olga

2017-10-01

Statistical models of the seismoacoustic and electromagnetic activity caused by deformation disturbances are considered on the basis of compound Poisson process and its fractional generalizations. Wave representations of these processes are used too. It is discussed five regimes of deformation activity and their role in understanding of the earthquakes precursors nature.

Development of new physical activity and sedentary behavior change self-efficacy questionnaires using item response modeling

USDA-ARS?s Scientific Manuscript database

Theoretically, increased levels of physical activity self-efficacy (PASE) should lead to increased physical activity, but few studies have reported this effect among youth. This failure may be at least partially attributable to measurement limitations. In this study, Item Response Modeling (IRM) was...

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.

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…

Contributions of the Model of Modelling Diagram to the Learning of Ionic Bonding: Analysis of a Case Study

ERIC Educational Resources Information Center

Mendonca, Paula Cristina Cardoso; Justi, Rosaria

2011-01-01

Current proposals for science education recognise the importance of students' involvement in activities aimed at favouring the understanding of science as a human, dynamic and non-linear construct. Modelling-based teaching is one of the alternatives through which to address such issues. Modelling-based teaching activities for ionic bonding were…

In silico modelling of thiazolidine derivatives with antioxidant potency: Models quantify the degree of contribution of molecular fragments towards the free radical scavenging ability

NASA Astrophysics Data System (ADS)

De, Biplab; Adhikari, Indrani; Nandy, Ashis; Saha, Achintya; Goswami, Binoy Behari

2017-06-01

Design and development of antioxidant supplements constitute an essential aspect of research in order to derive molecules that would help to combat the free radical invasion to the human body and curb oxidative stress related diseases. The present work deals with the development of in silico models for a series of thiazolidine derivatives having antioxidant potential. The objective of the work is to obtain models that would help to design new thazolidine derivatives based on substituent modification and thereby predict their activity profile. The QSAR model thus developed helps in quantification of the extent of contribution of the various molecular fragments towards the activity of the molecules, while the 3D pharmacophore model provides a brief idea of the essential molecular features that help the molecules to interact with the neighbouring free radicals. Both the models have been extensively validated which ensures their predictive ability as well the potential to search molecular databases for selection of thiazolidine derivatives with potent antioxidant activity. The models can thus be utilised effectively for database searching with the aim to isolate active antioxidants belonging to the thiazolidine group.

Prediction of enzyme activity with neural network models based on electronic and geometrical features of substrates.

PubMed

Szaleniec, Maciej

2012-01-01

Artificial Neural Networks (ANNs) are introduced as robust and versatile tools in quantitative structure-activity relationship (QSAR) modeling. Their application to the modeling of enzyme reactivity is discussed, along with methodological issues. Methods of input variable selection, optimization of network internal structure, data set division and model validation are discussed. The application of ANNs in the modeling of enzyme activity over the last 20 years is briefly recounted. The discussed methodology is exemplified by the case of ethylbenzene dehydrogenase (EBDH). Intelligent Problem Solver and genetic algorithms are applied for input vector selection, whereas k-means clustering is used to partition the data into training and test cases. The obtained models exhibit high correlation between the predicted and experimental values (R(2) > 0.9). Sensitivity analyses and study of the response curves are used as tools for the physicochemical interpretation of the models in terms of the EBDH reaction mechanism. Neural networks are shown to be a versatile tool for the construction of robust QSAR models that can be applied to a range of aspects important in drug design and the prediction of biological activity.

From good ideas to actions: a model-driven community collaborative to prevent childhood obesity.

PubMed

Huberty, Jennifer L; Balluff, Mary; O'Dell, Molly; Peterson, Kerri

2010-01-01

Activate Omaha Kids, a community collaborative, was designed, implemented, and evaluated with the aim of preventing childhood obesity in the Omaha community. Activate Omaha Kids brought together key stakeholders and community leaders to create a community coalition. The coalition's aim was to oversee a long-term sustainable approach to preventing obesity. Following a planning phase, a business plan was developed that prioritized best practices to be implemented in Omaha. The business plan was developed using the Ecological Model, Health Policy Model, and Robert Wood Johnson Foundation Active Living by Design 5P model. The three models helped the community identify target populations and activities that then created a single model for sustainable change. Twenty-four initiatives were identified, over one million dollars in funding was secured, and evaluation strategies were identified. By using the models from the initial steps through evaluation, a clear facilitation of the process was possible, and the result was a comprehensive, feasible plan. The use of the models to design a strategic plan was pivotal in building a sustainable coalition to achieve measurable improvements in the health of children and prove replicable over time.

Premarital Contraceptive Use: A Test of Two Models

ERIC Educational Resources Information Center

Delamater, John; Maccorquodale, Patricia

1978-01-01

Tests the utility of two models for explaining contraceptive use by sexually active women (N=391). Significant relationships were found between use and permissive premarital standards and standard-behavior consistency. Neither model is particularly applicable to the contraceptive reports of sexually active males (N=354). (Author)

78 FR 4186 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-18

... business models, activities and operations. Further, the requested information will inform FINRA's ongoing... business relationships, business model and compensation. FINRA will accord confidential treatment to the... familiar with the proposed business models, activities and operations of funding portals. Further, the...

Learning through Intermediate Problems in Creating Cognitive Models

ERIC Educational Resources Information Center

Miwa, Kazuhisa; Morita, Junya; Nakaike, Ryuichi; Terai, Hitoshi

2014-01-01

Cognitive modelling is one of the representative research methods in cognitive science. It is believed that creating cognitive models promotes learners' meta-cognitive activities such as self-monitoring and reflecting on their own cognitive processing. Preceding studies have confirmed that such meta-cognitive activities actually promote learning…

Influence of perceived sport competence and body attractiveness on physical activity and other healthy lifestyle habits in adolescents.

PubMed

Moreno-Murcia, Juan Antonio; Hellín, Pedro; González-Cutre, David; Martínez-Galindo, Celestina

2011-05-01

The purpose of this study was to test an explanatory model of the relationships between physical self-concept and some healthy habits. A sample of 472 adolescents aged 16 to 20 answered different questionnaires assessing physical self-concept, physical activity, intention to be physically active and consumption of alcohol and tobacco. The results of the structural equation model showed that perceived sport competence positively correlated with current physical activity. Body attractiveness positively correlated with physical activity in boys and negatively in girls. Current physical activity positively correlated with the intention to be physically active in the future and negatively with the consumption of alcohol and tobacco. Nevertheless, this last relationship was only significant in boys. The results are discussed in connection with the promotion of healthy lifestyle guidelines among adolescents. This model shows the importance of physical self-concept for engaging in physical activity in adolescence. It also suggests that physical activity is associated with the intention to continue being physically active and with healthy lifestyle habits.

Long-Term Global Morphology of Gravity Wave Activity Using UARS Data

NASA Technical Reports Server (NTRS)

Eckermann, Stephen D.; Bacmeister, Julio T.; Wu, Dong L.

1998-01-01

Progress in research into the global morphology of gravity wave activity using UARS data is described for the period March-June, 1998. Highlights this quarter include further progress in the analysis and interpretation of CRISTA temperature variances; model-generated climatologies of mesospheric gravity wave activity using the HWM-93 wind and temperature model; and modeling of gravity wave detection from space-based platforms. Preliminary interpretations and recommended avenues for further analysis are also described.

MIQSTURE: An Experimental Online Language for Army Tactical Intelligence Information Processing

DTIC Science & Technology

1978-07-01

algorithms. The most critical component of an active information processing model for Army tactical intelligence is the user interface, which must be based on...1976)** defined some preliminary notions of an active information model centered around a data base that can introspect about its contents and...34An Introspective Data Base for an Active Information Model." OSI Technical Note N76-017, 17 November 1976 1-4 L4 beyond optimistic expectations and

Active surface model improvement by energy function optimization for 3D segmentation.

PubMed

Azimifar, Zohreh; Mohaddesi, Mahsa

2015-04-01

This paper proposes an optimized and efficient active surface model by improving the energy functions, searching method, neighborhood definition and resampling criterion. Extracting an accurate surface of the desired object from a number of 3D images using active surface and deformable models plays an important role in computer vision especially medical image processing. Different powerful segmentation algorithms have been suggested to address the limitations associated with the model initialization, poor convergence to surface concavities and slow convergence rate. This paper proposes a method to improve one of the strongest and recent segmentation algorithms, namely the Decoupled Active Surface (DAS) method. We consider a gradient of wavelet edge extracted image and local phase coherence as external energy to extract more information from images and we use curvature integral as internal energy to focus on high curvature region extraction. Similarly, we use resampling of points and a line search for point selection to improve the accuracy of the algorithm. We further employ an estimation of the desired object as an initialization for the active surface model. A number of tests and experiments have been done and the results show the improvements with regards to the extracted surface accuracy and computational time of the presented algorithm compared with the best and recent active surface models. Copyright © 2015 Elsevier Ltd. All rights reserved.

In-vehicle group activity modeling and simulation in sensor-based virtual environment

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Telagamsetti, Durga; Poshtyar, Azin; Chan, Alex; Hu, Shuowen

2016-05-01

Human group activity recognition is a very complex and challenging task, especially for Partially Observable Group Activities (POGA) that occur in confined spaces with limited visual observability and often under severe occultation. In this paper, we present IRIS Virtual Environment Simulation Model (VESM) for the modeling and simulation of dynamic POGA. More specifically, we address sensor-based modeling and simulation of a specific category of POGA, called In-Vehicle Group Activities (IVGA). In VESM, human-alike animated characters, called humanoids, are employed to simulate complex in-vehicle group activities within the confined space of a modeled vehicle. Each articulated humanoid is kinematically modeled with comparable physical attributes and appearances that are linkable to its human counterpart. Each humanoid exhibits harmonious full-body motion - simulating human-like gestures and postures, facial impressions, and hands motions for coordinated dexterity. VESM facilitates the creation of interactive scenarios consisting of multiple humanoids with different personalities and intentions, which are capable of performing complicated human activities within the confined space inside a typical vehicle. In this paper, we demonstrate the efficiency and effectiveness of VESM in terms of its capabilities to seamlessly generate time-synchronized, multi-source, and correlated imagery datasets of IVGA, which are useful for the training and testing of multi-source full-motion video processing and annotation. Furthermore, we demonstrate full-motion video processing of such simulated scenarios under different operational contextual constraints.

Predictive Factors of Regular Physical Activity among Middle-Aged Women in the West of Iran, Hamadan: Application of PRECEDE Model.

PubMed

Emdadi, Shohreh; Hazavehie, Seyed Mohammad Mehdi; Soltanian, Alireza; Bashirian, Saeed; Heidari Moghadam, Rashid

2015-01-01

Regular physical activity is important for midlife women. Models and theories help better understanding this behavior among middle-aged women and better planning for change behavior in target group. This study aimed to investigate predictive factors of regular physical activity among middle-aged women based on PRECEDE model as a theoretical framework. This descriptive-analytical study was performed on 866 middle-aged women of Hamadan City western Iran, recruited with a proportional stratified sampling method in 2015. The participants completed a self-administered questionnaire including questions on demographic characteristics and PRECEDE model constructs and IPAQ questionnaire. Data were then analyzed by SPSS-16 and AMOS-16 using the Pearson correlation test and the pathway analysis method. Overall, 57% of middle-aged women were inactive (light level) or not sufficiently active. With SEM (Structural Equation Modeling) analysis, knowledge b=0.84, P<0.001, attitude b=0.799, P<0.001, self-efficacy b=0.633, P<0.001 as predisposing factor and social support as reinforcing factor b=0.2, P<0.001 were the most important predictors for physical activity among middle-aged women in Hamadan. The framework of the PRECEDE model is useful in understanding regular physical activity among middle-aged women. Furthermore, results showed the importance of predisposing and reinforcing factors when planning educational interventions.

Inter-comparison of dynamic models for radionuclide transfer to marine biota in a Fukushima accident scenario

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

Vives i Batlle, J.; Beresford, N. A.; Beaugelin-Seiller, K.

We report an inter-comparison of eight models designed to predict the radiological exposure of radionuclides in marine biota. The models were required to simulate dynamically the uptake and turnover of radionuclides by marine organisms. Model predictions of radionuclide uptake and turnover using kinetic calculations based on biological half-life (TB1/2) and/or more complex metabolic modelling approaches were used to predict activity concentrations and, consequently, dose rates of 90Sr, 131I and 137Cs to fish, crustaceans, macroalgae and molluscs under circumstances where the water concentrations are changing with time. For comparison, the ERICA Tool, a model commonly used in environmental assessment, and whichmore » uses equilibrium concentration ratios, was also used. As input to the models we used hydrodynamic forecasts of water and sediment activity concentrations using a simulated scenario reflecting the Fukushima accident releases. Although model variability is important, the intercomparison gives logical results, in that the dynamic models predict consistently a pattern of delayed rise of activity concentration in biota and slow decline instead of the instantaneous equilibrium with the activity concentration in seawater predicted by the ERICA Tool. The differences between ERICA and the dynamic models increase the shorter the TB1/2 becomes; however, there is significant variability between models, underpinned by parameter and methodological differences between them. The need to validate the dynamic models used in this intercomparison has been highlighted, particularly in regards to optimisation of the model biokinetic parameters.« less

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

NASA Technical Reports Server (NTRS)

Wang, Hui; Long, Lindsey; Kumar, Arun; Wang, Wanqiu; Schemm, Jae-Kyung E.; Zhao, Ming; Vecchi, Gabriel A.; LaRow, Timorhy E.; Lim, Young-Kwon; Schubert, Siegfried D.;

College Students' Physical Activity and Health-Related Quality of Life: An Achievement Goal Perspective.

PubMed

Zhang, Tao; Xiang, Ping; Gu, Xiangli; Rose, Melanie

2016-06-01

The 2 × 2 achievement goal model, including the mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance goal orientations, has recently been used to explain motivational outcomes in physical activity. This study attempted to examine the relationships among 2 × 2 achievement goal orientations, physical activity, and health-related quality of life (HRQOL) in college students. Participants were 325 students (130 men and 195 women; Mage = 21.4 years) enrolled in physical activity classes at a Southern university. They completed surveys validated in previous research assessing achievement goal orientations, physical activity, and HRQOL. Path analyses revealed a good fit between the model and data (root mean square error of approximation = .06; Comparative Fit Index = .99; Bentler-Bonett Nonnormed Fit Index = .98; Incremental Fit Index = .99), but the model explained small variances in the current study. Mastery-approach and performance-approach goal orientations only had low or no relationships with physical activity. Mastery-approach goal orientation and physical activity also had low positive relationships with HRQOL, but mastery-avoidance and performance-avoidance goal orientations had low negative relationships with HRQOL. The hypothesized mediational role of physical activity in the relationship between mastery-approach and performance-approach goal orientations and HRQOL was not supported in this study. Although the data fit the proposed model well, only small variance was explained by the model. The relationship between physical activity and HRQOL of the college students and other related correlates should be further studied.

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.

Analysis of Family Structures Reveals Robustness or Sensitivity of Bursting Activity to Parameter Variations in a Half-Center Oscillator (HCO) Model.

PubMed

Doloc-Mihu, Anca; Calabrese, Ronald L

2016-01-01

The underlying mechanisms that support robustness in neuronal networks are as yet unknown. However, recent studies provide evidence that neuronal networks are robust to natural variations, modulation, and environmental perturbations of parameters, such as maximal conductances of intrinsic membrane and synaptic currents. Here we sought a method for assessing robustness, which might easily be applied to large brute-force databases of model instances. Starting with groups of instances with appropriate activity (e.g., tonic spiking), our method classifies instances into much smaller subgroups, called families, in which all members vary only by the one parameter that defines the family. By analyzing the structures of families, we developed measures of robustness for activity type. Then, we applied these measures to our previously developed model database, HCO-db, of a two-neuron half-center oscillator (HCO), a neuronal microcircuit from the leech heartbeat central pattern generator where the appropriate activity type is alternating bursting. In HCO-db, the maximal conductances of five intrinsic and two synaptic currents were varied over eight values (leak reversal potential also varied, five values). We focused on how variations of particular conductance parameters maintain normal alternating bursting activity while still allowing for functional modulation of period and spike frequency. We explored the trade-off between robustness of activity type and desirable change in activity characteristics when intrinsic conductances are altered and identified the hyperpolarization-activated (h) current as an ideal target for modulation. We also identified ensembles of model instances that closely approximate physiological activity and can be used in future modeling studies.

Understanding disease mechanisms with models of signaling pathway activities.

PubMed

Sebastian-Leon, Patricia; Vidal, Enrique; Minguez, Pablo; Conesa, Ana; Tarazona, Sonia; Amadoz, Alicia; Armero, Carmen; Salavert, Francisco; Vidal-Puig, Antonio; Montaner, David; Dopazo, Joaquín

2014-10-25

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine. Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation statuses can be interpreted as biomarkers that discriminate among the compared conditions. This type of mechanism-based biomarkers accounts for cell functional activities and can easily be associated to disease or drug action mechanisms. The accuracy of the proposed model is demonstrated with simulations and real datasets. The proposed model provides detailed information that enables the interpretation disease mechanisms as a consequence of the complex combinations of altered gene expression values. Moreover, it offers a framework for suggesting possible ways of therapeutic intervention in a pathologically perturbed system.

A battery model that enables consideration of realistic anisotropic environment surrounding an active material particle and its application

NASA Astrophysics Data System (ADS)

Lin, Xianke; Lu, Wei

2017-07-01

This paper proposes a model that enables consideration of the realistic anisotropic environment surrounding an active material particle by incorporating both diffusion and migration of lithium ions and electrons in the particle. This model makes it possible to quantitatively evaluate effects such as fracture on capacity degradation. In contrast, the conventional model assumes isotropic environment and only considers diffusion in the active particle, which cannot capture the effect of fracture since it would predict results contradictory to experimental observations. With the developed model we have investigated the effects of active material electronic conductivity, particle size, and State of Charge (SOC) swing window when fracture exists. The study shows that the low electronic conductivity of active material has a significant impact on the lithium ion pattern. Fracture increases the resistance for electron transport and therefore reduces lithium intercalation/deintercalation. Particle size plays an important role in lithium ion transport. Smaller particle size is preferable for mitigating capacity loss when fracture happens. The study also shows that operating at high SOC reduces the impact of fracture.

Is running away right? The behavioral activation-behavioral inhibition model of anterior asymmetry.

PubMed

Wacker, Jan; Chavanon, Mira-Lynn; Leue, Anja; Stemmler, Gerhard

2008-04-01

The measurement of anterior electroencephalograph (EEG) asymmetries has become an important standard paradigm for the investigation of affective states and traits. Findings in this area are typically interpreted within the motivational direction model, which suggests a lateralization of approach and withdrawal motivational systems to the left and right anterior region, respectively. However, efforts to compare this widely adopted model with an alternative account-which relates the left anterior region to behavioral activation independent of the direction of behavior (approach or withdrawal) and the right anterior region to goal conflict-induced behavioral inhibition-are rare and inconclusive. Therefore, the authors measured the EEG in a sample of 93 young men during emotional imagery designed to provide a critical test between the 2 models. The results (e.g., a correlation between left anterior activation and withdrawal motivation) favor the alternative model on the basis of the concepts of behavioral activation and behavioral inhibition. In addition, the present study also supports an association of right parietal activation with physiological arousal and the conceptualization of parietal EEG asymmetry as a mediator of emotion-related physiological arousal. (Copyright) 2008 APA.

The Right to Move: A Multidisciplinary Lifespan Conceptual Framework

PubMed Central

Antonucci, Toni C.; Ashton-Miller, James A.; Brant, Jennifer; Falk, Emily B.; Halter, Jeffrey B.; Hamdemir, Levent; Konrath, Sara H.; Lee, Joyce M.; McCullough, Wayne R.; Persad, Carol C.; Seydel, Roland; Smith, Jacqui; Webster, Noah J.

2012-01-01

This paper addresses the health problems and opportunities that society will face in 2030. We propose a proactive model to combat the trend towards declining levels of physical activity and increasing obesity. The model emphasizes the need to increase physical activity among individuals of all ages. We focus on the right to move and the benefits of physical activity. The paper introduces a seven-level model that includes cells, creature (individual), clan (family), community, corporation, country, and culture. At each level the model delineates how increased or decreased physical activity influences health and well-being across the life span. It emphasizes the importance of combining multiple disciplines and corporate partners to produce a multifaceted cost-effective program that increases physical activity at all levels. The goal of this paper is to recognize exercise as a powerful, low-cost solution with positive benefits to cognitive, emotional, and physical health. Further, the model proposes that people of all ages should incorporate the “right to move” into their life style, thereby maximizing the potential to maintain health and well-being in a cost-effective, optimally influential manner. PMID:23251148

Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

PubMed Central

Jhin, Changho; Hwang, Keum Taek

2014-01-01

Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

Modelling and Vibration Control of Beams with Partially Debonded Active Constrained Layer Damping Patch

NASA Astrophysics Data System (ADS)

SUN, D.; TONG, L.

2002-05-01

A detailed model for the beams with partially debonded active constraining damping (ACLD) treatment is presented. In this model, the transverse displacement of the constraining layer is considered to be non-identical to that of the host structure. In the perfect bonding region, the viscoelastic core is modelled to carry both peel and shear stresses, while in the debonding area, it is assumed that no peel and shear stresses be transferred between the host beam and the constraining layer. The adhesive layer between the piezoelectric sensor and the host beam is also considered in this model. In active control, the positive position feedback control is employed to control the first mode of the beam. Based on this model, the incompatibility of the transverse displacements of the active constraining layer and the host beam is investigated. The passive and active damping behaviors of the ACLD patch with different thicknesses, locations and lengths are examined. Moreover, the effects of debonding of the damping layer on both passive and active control are examined via a simulation example. The results show that the incompatibility of the transverse displacements is remarkable in the regions near the ends of the ACLD patch especially for the high order vibration modes. It is found that a thinner damping layer may lead to larger shear strain and consequently results in a larger passive and active damping. In addition to the thickness of the damping layer, its length and location are also key factors to the hybrid control. The numerical results unveil that edge debonding can lead to a reduction of both passive and active damping, and the hybrid damping may be more sensitive to the debonding of the damping layer than the passive damping.

A physically-based approach of treating dust-water cloud interactions in climate models

NASA Astrophysics Data System (ADS)

Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-12-01

All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532

Energetic Assessment of the Nonexercise Activities under Free-Living Conditions.

PubMed

Sun, Shijie; Tang, Qiang; Quan, Haiying; Lu, Qi; Sun, Ming; Zhang, Kuan

2016-01-01

Nonexercise activities (NAs) are common types of physical activity in daily life and critical component in energy expenditure. However, energetic assessment of NA, particularly in free-living subjects, is a technical challenge. In this study, mechanical modeling and portable device were used to evaluate five common types of NA in daily life: sit to stand, lie to sit, bowing while standing, squat, and right leg over left. A human indirect calorimeter was used to measure the activity energy expenditure of NA. Mechanical work and mechanical efficiency of NA were calculated for mechanical modeling. Thirty-two male subjects were recruited for the study (20 subjects for the development of models and 12 subjects for evaluation of models). The average (mean ± SD) mechanical work of 5 NAs was 2.31 ± 0.50, 2.88 ± 0.57, 1.75 ± 0.55, 3.96 ± 1.25, and 1.25 ± 0.51 J/kg·m, respectively. The mean mechanical efficiencies of those activities were 22.0 ± 3.3%, 26.5 ± 5.1%, 19.8 ± 3.7%, 24.0 ± 5.5%, and 26.3 ± 5.5%. The activity energy expenditure estimated by the models was not significantly different from the measurements by the calorimeter (p > 0.05) with accuracies of 102.2 ± 20.7%, 103.7 ± 25.8%, 105.6 ± 14.6%, 101.1 ± 28.0%, and 95.8 ± 20.7%, respectively, for those activities. These findings suggest that the mechanical models combined with a portable device can provide an alternative method for the energetic analysis of nonexercise activities under free-living condition.

Mechanistic modeling of thermo-hydrological processes and microbial interactions at pore to profile scales resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-04-01

The sensitivity of the Earth's polar regions to raising global temperatures is reflected in rapidly changing hydrological processes with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and the stimulation of other soil-borne GHG emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and a host of other environmental factors. Soil structural elements such as aggregates and layering and hydration status affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hotspots or hot-layers). We developed a mechanistic individual based model to quantify microbial activity dynamics within soil pore networks considering, hydration, temperature, transport processes and enzymatic activity associated with methane production in soil. The model was the upscaled from single aggregates (or hotspots) to quantifying emissions from soil profiles in which freezing/thawing processes provide macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged parts of the profile) for resolving methane production and oxidation rates. Methane transport pathways through soil by diffusion and ebullition of bubbles vary with hydration dynamics and affect emission patterns. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability, enzyme activity, PH) on long term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Early-onset sleep defects in Drosophila models of Huntington's disease reflect alterations of PKA/CREB signaling

PubMed Central

Gonzales, Erin D.; Tanenhaus, Anne K.; Zhang, Jiabin; Chaffee, Ryan P.; Yin, Jerry C.P.

2016-01-01

Huntington's disease (HD) is a progressive neurological disorder whose non-motor symptoms include sleep disturbances. Whether sleep and activity abnormalities are primary molecular disruptions of mutant Huntingtin (mutHtt) expression or result from neurodegeneration is unclear. Here, we report Drosophila models of HD exhibit sleep and activity disruptions very early in adulthood, as soon as sleep patterns have developed. Pan-neuronal expression of full-length or N-terminally truncated mutHtt recapitulates sleep phenotypes of HD patients: impaired sleep initiation, fragmented and diminished sleep, and nighttime hyperactivity. Sleep deprivation of HD model flies results in exacerbated sleep deficits, indicating that homeostatic regulation of sleep is impaired. Elevated PKA/CREB activity in healthy flies produces patterns of sleep and activity similar to those in our HD models. We were curious whether aberrations in PKA/CREB signaling were responsible for our early-onset sleep/activity phenotypes. Decreasing signaling through the cAMP/PKA pathway suppresses mutHtt-induced developmental lethality. Genetically reducing PKA abolishes sleep/activity deficits in HD model flies, restores the homeostatic response and extends median lifespan. In vivo reporters, however, show dCREB2 activity is unchanged, or decreased when sleep/activity patterns are abnormal, suggesting dissociation of PKA and dCREB2 occurs early in pathogenesis. Collectively, our data suggest that sleep defects may reflect a primary pathological process in HD, and that measurements of sleep and cAMP/PKA could be prodromal indicators of disease, and serve as therapeutic targets for intervention. PMID:26604145

Anticancer agent ABT-737 possesses anti-atopic dermatitis activity via blockade of caspase-1 in atopic dermatitis in vitro and in vivo models.

PubMed

Jeong, Hyun-Ja; Ryu, Ka-Jung; Kim, Hyung-Min

2018-06-29

Previous studies reported that depletion of Bcl-2 has a protective effect against allergic diseases. Furthermore, recently our study showed that anticancer drug has antiallergic inflammatory effect. An anticancer agent ABT-737 is an inhibitor of Bcl-2 and has an anti-inflammatory effect. However, the antiallergic inflammatory activity of ABT-737 is still unknown. Here, we aimed to explore the anti-atopic dermatitis (AD) activity and the mechanism of ABT-737 in AD models. HaCaT cells were used for in vitro experiments. To evaluate the effect of ABT-737 in vivo model, BalB/c mice were orally administered ABT-737 for 6 weeks in 2,4-dinitrofluorobenzene (DNFB)-induced AD-like murine model. Major assays were enzyme-linked immunosorbent assay, reverse transcription-PCR, caspase-1 assay, histamine assay, and H&E staining. ABT-737 significantly decreased thymic stromal lymphopoietin (TSLP) secretion and caspase-1 activity in activated HaCaT cells. In DNFB-induced AD mice, oral administration of ABT-737 alleviated clinical severity and scratching behavior. ABT-737 decreased levels of AD-related biomarkers including IgE, histamine, TSLP, and inflammatory cytokines. In addition, ABT significantly reduced caspase-1 activity in skin lesions of AD mice. ABT-737 elicited an anti-AD activity via suppression of caspase-1 activation in AD in vitro and in vivo models. Therefore, this study provides important information regarding the use of anticancer drugs for controlling allergic inflammatory diseases.

Examining a conceptual model of parental nurturance, parenting practices and physical activity among 5-6 year olds.

PubMed

Sebire, Simon J; Jago, Russell; Wood, Lesley; Thompson, Janice L; Zahra, Jezmond; Lawlor, Deborah A

2016-01-01

Parenting is an often-studied correlate of children's physical activity, however there is little research examining the associations between parenting styles, practices and the physical activity of younger children. This study aimed to investigate whether physical activity-based parenting practices mediate the association between parenting styles and 5-6 year-old children's objectively-assessed physical activity. 770 parents self-reported parenting style (nurturance and control) and physical activity-based parenting practices (logistic and modeling support). Their 5-6 year old child wore an accelerometer for five days to measure moderate-to-vigorous physical activity (MVPA). Linear regression was used to examine direct and indirect (mediation) associations. Data were collected in the United Kingdom in 2012/13 and analyzed in 2014. Parent nurturance was positively associated with provision of modeling (adjusted unstandardized coefficient, β = 0.11; 95% CI = 0.02, 0.21) and logistic support (β = 0.14; 0.07, 0.21). Modeling support was associated with greater child MVPA (β = 2.41; 0.23, 4.60) and a small indirect path from parent nurturance to child's MVPA was identified (β = 0.27; 0.04, 0.70). Physical activity-based parenting practices are more strongly associated with 5-6 year old children's MVPA than parenting styles. Further research examining conceptual models of parenting is needed to understand in more depth the possible antecedents to adaptive parenting practices beyond parenting styles. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.