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

Modeling four occurred debris flow events in the Dolomites area (North-Eastern Italian Alps)

NASA Astrophysics Data System (ADS)

Boreggio, Mauro; Gregoretti, Carlo; Degetto, Massimo; Bernard, Martino

2016-04-01

Four occurred debris flows in the Dolomites area (North-Eastern Italian Alps) are modeled by back-analysis. The four debris flows events are those occurred at Rio Lazer (Trento) on the 4th of November 1966, at Fiames (Belluno) on the 5th of July 2006, at Rovina di Cancia (Belluno) on the 18th of July 2009 and at Rio Val Molinara (Trento) on the 15th of August 2010. In all the events, runoff entrained sediments present on natural channels and formed a solid-liquid wave that routed downstream. The first event concerns the routing of debris flow on an inhabited fan. The second event the deviation of debris flow from the usual path due to an obstruction with the excavation of a channel in the scree and the downstream spreading in a wood. The third event concerns the routing of debris flow in a channel with an ending the reservoir, its overtopping and final spreading in the inhabited area. The fourth event concerns the routing of debris flow along the main channel downstream the initiation area until spreading just upstream a village. All the four occurred debris flows are simulated by modeling runoff that entrained debris flow for determining the solid-liquid hydrograph. The routing of the solid-liquid hydrograph is simulated by a bi-phase cell model based on the kinematic approach. The comparison between simulated and measured erosion and deposition depths is satisfactory. Nearly the same parameters for computing erosion and deposition were used for all the four occurred events. The maps of erosion and deposition depths are obtained by comparing the results of post-event surveys with the pre-event DEM. The post-event surveys were conducted by using different instruments (LiDAR and GPS) or the combination photos-single points depth measurements (in this last case it is possible obtaining the deposition/erosion depths by means of stereoscopy techniques).

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 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

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.

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.

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

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.

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.

Activity of a social dynamics model

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Neves, Ubiraci P. C.

2015-10-01

Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.

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.

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…

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.

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.

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.

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.

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…

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.

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…

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

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.

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.

Travelling waves in a model of quasi-active dendrites with active spines

NASA Astrophysics Data System (ADS)

Timofeeva, Y.

2010-05-01

Dendrites, the major components of neurons, have many different types of branching structures and are involved in receiving and integrating thousands of synaptic inputs from other neurons. Dendritic spines with excitable channels can be present in large densities on the dendrites of many cells. The recently proposed Spike-Diffuse-Spike (SDS) model that is described by a system of point hot-spots (with an integrate-and-fire process) embedded throughout a passive tree has been shown to provide a reasonable caricature of a dendritic tree with supra-threshold dynamics. Interestingly, real dendrites equipped with voltage-gated ion channels can exhibit not only supra-threshold responses, but also sub-threshold dynamics. This sub-threshold resonant-like oscillatory behaviour has already been shown to be adequately described by a quasi-active membrane. In this paper we introduce a mathematical model of a branched dendritic tree based upon a generalisation of the SDS model where the active spines are assumed to be distributed along a quasi-active dendritic structure. We demonstrate how solitary and periodic travelling wave solutions can be constructed for both continuous and discrete spine distributions. In both cases the speed of such waves is calculated as a function of system parameters. We also illustrate that the model can be naturally generalised to an arbitrary branched dendritic geometry whilst remaining computationally simple. The spatio-temporal patterns of neuronal activity are shown to be significantly influenced by the properties of the quasi-active membrane. Active (sub- and supra-threshold) properties of dendrites are known to vary considerably among cell types and animal species, and this theoretical framework can be used in studying the combined role of complex dendritic morphologies and active conductances in rich neuronal dynamics.

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

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

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

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.

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

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.

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.

The hydrological response of a rocky head water basin to convective rainfalls

NASA Astrophysics Data System (ADS)

Gregoretti, Carlo; Bernard, Martino; Degetto, Massimo; Matteo, Berti; Alessandro, Simoni; Stefano, Lanzoni

2015-04-01

A sharp-crested weir is installed at the outlet (altitude 1770 m a.s.l) of a rocky channel incised on the walls of Dimai Peak in the area of Fiames (Cortina d'Ampezzo, Dolomites-North Eastern Italian Alps) at the purpose of measuring runoff discharges. The area of the headwater basin is just 0.032 km2 but sub-vertical cliffs are capable to generate notable discharge during severe rainstorms. Due to the severe environment only five runoff events were measured (two times the facility was destroyed by rock falls and avalanches; other times failure of sensors stopped the measurements). Hydrological response is characterized by peaked hydrographs with very high rising limb. A kinematic distributed hydrological model was used to simulate the response of the basin to the convective rainfalls with the help of two rain gauges placed upstream the basin head and downstream the outlet respectively. The hydrological model uses an hortonian simplified law for determining excess rainfall and satisfactorily simulates the measured hydrographs. Such measurements are important for the understanding the hydrological response of a rocky basin to a convective rainfall. Their modeling are important as well when focused on predicting both flash floods in mountain torrents and the triggering conditions and magnitude of runoff generated debris flows.

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

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

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.

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

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.

Group-Based Active Learning of Classification Models.

PubMed

Luo, Zhipeng; Hauskrecht, Milos

2017-05-01

Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

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.

Phase Transitions in Model Active Systems

NASA Astrophysics Data System (ADS)

Redner, Gabriel S.

The amazing collective behaviors of active systems such as bird flocks, schools of fish, and colonies of microorganisms have long amazed scientists and laypeople alike. Understanding the physics of such systems is challenging due to their far-from-equilibrium dynamics, as well as the extreme diversity in their ingredients, relevant time- and length-scales, and emergent phenomenology. To make progress, one can categorize active systems by the symmetries of their constituent particles, as well as how activity is expressed. In this work, we examine two categories of active systems, and explore their phase behavior in detail. First, we study systems of self-propelled spherical particles moving in two dimensions. Despite the absence of an aligning interaction, this system displays complex emergent dynamics, including phase separation into a dense active solid and dilute gas. Using simulations and analytic modeling, we quantify the phase diagram and separation kinetics. We show that this nonequilibrium phase transition is analogous to an equilibrium vapor-liquid system, with binodal and spinodal curves and a critical point. We also characterize the dense active solid phase, a unique material which exhibits the structural signatures of a crystalline solid near the crystal-hexatic transition point, as well as anomalous dynamics including superdiffusive motion on intermediate timescales. We also explore the role of interparticle attraction in this system. We demonstrate that attraction drastically changes the phase diagram, which contains two distinct phase-separated regions and is reentrant as a function of propulsion speed. We interpret this complex situation with a simple kinetic model, which builds from the observed microdynamics of individual particles to a full description of the macroscopic phase behavior. We also study active nematics, liquid crystals driven out of equilibrium by energy-dissipating active stresses. The equilibrium nematic state is unstable in these

Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

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

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.

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.

Parametrization in models of subcritical glass fracture: Activation offset and concerted activation

NASA Astrophysics Data System (ADS)

Rodrigues, Bruno Poletto; Hühn, Carolin; Erlebach, Andreas; Mey, Dorothea; Sierka, Marek; Wondraczek, Lothar

2017-08-01

There are two established but fundamentally different empirical approaches to parametrize the rate of subcritical fracture in brittle materials. While both are relying on a thermally activated reaction of bond rupture, the difference lies in the way as to how the externally applied stresses affect the local energy landscape. In the consideration of inorganic glasses, the strain energy is typically taken as an off-set on the activation barrier. As an alternative interpretation, the system’s volumetric strain-energy is added to its thermal energy. Such an interpretation is consistent with the democratic fiber bundle model. Here, we test this approach of concerted activation against macroscopic data of bond cleavage activation energy, and also against ab initio quantum chemical simulation of the energy barrier for cracking in silica. The fact that both models are able to reproduce experimental observation to a remarkable degree highlights the importance of a holistic consideration towards non-empirical understanding.

Aeroelastic modeling of the active flexible wing wind-tunnel model

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Heeg, Jennifer; Bennett, Robert M.

1991-01-01

The primary issues involved in the generation of linear, state-space equations of motion of a flexible wind tunnel model, the Active Flexible Wing (AFW), are discussed. The codes that were used and their inherent assumptions and limitations are also briefly discussed. The application of the CAP-TSD code to the AFW for determination of the model's transonic flutter boundary is included as well.

Kinetic model of excess activated sludge thermohydrolysis.

PubMed

Imbierowicz, Mirosław; Chacuk, Andrzej

2012-11-01

Thermal hydrolysis of excess activated sludge suspensions was carried at temperatures ranging from 423 K to 523 K and under pressure 0.2-4.0 MPa. Changes of total organic carbon (TOC) concentration in a solid and liquid phase were measured during these studies. At the temperature 423 K, after 2 h of the process, TOC concentration in the reaction mixture decreased by 15-18% of the initial value. At 473 K total organic carbon removal from activated sludge suspension increased to 30%. It was also found that the solubilisation of particulate organic matter strongly depended on the process temperature. At 423 K the transfer of TOC from solid particles into liquid phase after 1 h of the process reached 25% of the initial value, however, at the temperature of 523 K the conversion degree of 'solid' TOC attained 50% just after 15 min of the process. In the article a lumped kinetic model of the process of activated sludge thermohydrolysis has been proposed. It was assumed that during heating of the activated sludge suspension to a temperature in the range of 423-523 K two parallel reactions occurred. One, connected with thermal destruction of activated sludge particles, caused solubilisation of organic carbon and an increase of dissolved organic carbon concentration in the liquid phase (hydrolysate). The parallel reaction led to a new kind of unsolvable solid phase, which was further decomposed into gaseous products (CO(2)). The collected experimental data were used to identify unknown parameters of the model, i.e. activation energies and pre-exponential factors of elementary reactions. The mathematical model of activated sludge thermohydrolysis appropriately describes the kinetics of reactions occurring in the studied system. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.…

Active shape models unleashed

NASA Astrophysics Data System (ADS)

Kirschner, Matthias; Wesarg, Stefan

2011-03-01

Active Shape Models (ASMs) are a popular family of segmentation algorithms which combine local appearance models for boundary detection with a statistical shape model (SSM). They are especially popular in medical imaging due to their ability for fast and accurate segmentation of anatomical structures even in large and noisy 3D images. A well-known limitation of ASMs is that the shape constraints are over-restrictive, because the segmentations are bounded by the Principal Component Analysis (PCA) subspace learned from the training data. To overcome this limitation, we propose a new energy minimization approach which combines an external image energy with an internal shape model energy. Our shape energy uses the Distance From Feature Space (DFFS) concept to allow deviations from the PCA subspace in a theoretically sound and computationally fast way. In contrast to previous approaches, our model does not rely on post-processing with constrained free-form deformation or additional complex local energy models. In addition to the energy minimization approach, we propose a new method for liver detection, a new method for initializing an SSM and an improved k-Nearest Neighbour (kNN)-classifier for boundary detection. Our ASM is evaluated with leave-one-out tests on a data set with 34 tomographic CT scans of the liver and is compared to an ASM with standard shape constraints. The quantitative results of our experiments show that we achieve higher segmentation accuracy with our energy minimization approach than with standard shape constraints.nym

A model of differential amygdala activation in psychopathy.

PubMed

Moul, Caroline; Killcross, Simon; Dadds, Mark R

2012-10-01

This article introduces a novel hypothesis regarding amygdala function in psychopathy. The first part of this article introduces the concept of psychopathy and describes the main cognitive and affective impairments demonstrated by this population; that is, a deficit in fear-recognition, lower conditioned fear responses and poor performance in passive avoidance, and response-reversal learning tasks. Evidence for amygdala dysfunction in psychopathy is considered with regard to these deficits; however, the idea of unified amygdala function is untenable. A model of differential amygdala activation in which the basolateral amygdala (BLA) is underactive while the activity of the central amygdala (CeA) is of average to above average levels is proposed to provide a more accurate and up-to-date account for the specific cognitive and emotional deficits found in psychopathy. In addition, the model provides a mechanism by which attentional-based models and emotion-based models of psychopathy can coexist. Data to support the differential amygdala activation model are provided from studies from both human and animal research. Supporting evidence concerning some of the neurochemicals implicated in psychopathy is then reviewed. Implications of the model and areas of future research are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

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.

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…

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.

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

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.

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

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.

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

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…

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

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…

A Case Study of Teachers' Development of Well-Structured Mathematical Modelling Activities

ERIC Educational Resources Information Center

Stohlmann, Micah; Maiorca, Cathrine; Allen, Charlie

2017-01-01

This case study investigated how three teachers developed mathematical modelling activities integrated with content standards through participation in a course on mathematical modelling. The class activities involved experiencing a mathematical modelling activity, reading and rating example mathematical modelling activities, reading articles about…

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

PubMed

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

2004-06-12

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

Oriented active shape models.

PubMed

Liu, Jiamin; Udupa, Jayaram K

2009-04-01

Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks

The activation strain model and molecular orbital theory

PubMed Central

Wolters, Lando P; Bickelhaupt, F Matthias

2015-01-01

The activation strain model is a powerful tool for understanding reactivity, or inertness, of molecular species. This is done by relating the relative energy of a molecular complex along the reaction energy profile to the structural rigidity of the reactants and the strength of their mutual interactions: ΔE(ζ) = ΔEstrain(ζ) + ΔEint(ζ). We provide a detailed discussion of the model, and elaborate on its strong connection with molecular orbital theory. Using these approaches, a causal relationship is revealed between the properties of the reactants and their reactivity, e.g., reaction barriers and plausible reaction mechanisms. This methodology may reveal intriguing parallels between completely different types of chemical transformations. Thus, the activation strain model constitutes a unifying framework that furthers the development of cross-disciplinary concepts throughout various fields of chemistry. We illustrate the activation strain model in action with selected examples from literature. These examples demonstrate how the methodology is applied to different research questions, how results are interpreted, and how insights into one chemical phenomenon can lead to an improved understanding of another, seemingly completely different chemical process. WIREs Comput Mol Sci 2015, 5:324–343. doi: 10.1002/wcms.1221 PMID:26753009

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.

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

A multi-physics model for ultrasonically activated soft tissue.

PubMed

Suvranu De, Rahul

2017-02-01

A multi-physics model has been developed to investigate the effects of cellular level mechanisms on the thermomechanical response of ultrasonically activated soft tissue. Cellular level cavitation effects have been incorporated in the tissue level continuum model to accurately determine the thermodynamic states such as temperature and pressure. A viscoelastic material model is assumed for the macromechanical response of the tissue. The cavitation model based equation-of-state provides the additional pressure arising from evaporation of intracellular and cellular water by absorbing heat due to structural and viscoelastic heating in the tissue, and temperature to the continuum level thermomechanical model. The thermomechanical response of soft tissue is studied for the operational range of frequencies of oscillations and applied loads for typical ultrasonically activated surgical instruments. The model is shown to capture characteristics of ultrasonically activated soft tissue deformation and temperature evolution. At the cellular level, evaporation of water below the boiling temperature under ambient conditions is indicative of protein denaturation around the temperature threshold for coagulation of tissues. Further, with increasing operating frequency (or loading), the temperature rises faster leading to rapid evaporation of tissue cavity water, which may lead to accelerated protein denaturation and coagulation.

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.

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.

Active Exploration of Large 3D Model Repositories.

PubMed

Gao, Lin; Cao, Yan-Pei; Lai, Yu-Kun; Huang, Hao-Zhi; Kobbelt, Leif; Hu, Shi-Min

2015-12-01

With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100 K models.

Global empirical model of TEC response to geomagnetic activity

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

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.

Models for H₃ receptor antagonist activity of sulfonylurea derivatives.

PubMed

Khatri, Naveen; Madan, A K

2014-03-01

The histamine H₃ receptor has been perceived as an auspicious target for the treatment of various central and peripheral nervous system diseases. In present study, a wide variety of 60 2D and 3D molecular descriptors (MDs) were successfully utilized for the development of models for the prediction of antagonist activity of sulfonylurea derivatives for histamine H₃ receptors. Models were developed through decision tree (DT), random forest (RF) and moving average analysis (MAA). Dragon software version 6.0.28 was employed for calculation of values of diverse MDs of each analogue involved in the data set. The DT classified and correctly predicted the input data with an impressive non-error rate of 94% in the training set and 82.5% during cross validation. RF correctly classified the analogues into active and inactive with a non-error rate of 79.3%. The MAA based models predicted the antagonist histamine H₃ receptor activity with non-error rate up to 90%. Active ranges of the proposed MAA based models not only exhibited high potency but also showed improved safety as indicated by relatively high values of selectivity index. The statistical significance of the models was assessed through sensitivity, specificity, non-error rate, Matthew's correlation coefficient and intercorrelation analysis. Proposed models offer vast potential for providing lead structures for development of potent but safe H₃ receptor antagonist sulfonylurea derivatives. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

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.

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

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

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.

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

Inferring brain-computational mechanisms with models of activity measurements

PubMed Central

Diedrichsen, Jörn

2016-01-01

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574316

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

Modeling the Benchmark Active Control Technology Wind-Tunnel Model for Application to Flutter Suppression

NASA Technical Reports Server (NTRS)

Waszak, Martin R.

1996-01-01

This paper describes the formulation of a model of the dynamic behavior of the Benchmark Active Controls Technology (BACT) wind-tunnel model for application to design and analysis of flutter suppression controllers. 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 paper is the development of the equations of motion from first principles using Lagrange's equations and the principle of virtual work. A numerical form of the model is generated using values for parameters obtained from both experiment and analysis. A unique aspect of the BACT wind-tunnel model is that it has upper- and lower-surface spoilers for active control. Comparisons with experimental frequency responses and other data 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 assist the design and analysis of a number of flutter suppression controllers that have been successfully implemented.

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.

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,…

Modeling Mitigation Activities in North Carolina Watersheds

NASA Astrophysics Data System (ADS)

Garcia, A. M.

2017-12-01

Nutrient enrichment and excessive sediment loadings have contributed to the degradation of rivers, lakes and estuaries in North Carolina. The North Carolina Department of Environmental Quality (NCDEQ) has implemented several basin-wide nutrient and sediment management strategies, yet gaps remain in understanding the impact of these strategies given the complexities in quantifying the processes that govern the transport of nutrient and sediment. In particular, improved assessment of the status of nutrient and sediment loadings to lakes and estuaries throughout the state is needed, including characterizing their sources and describing the relative contributions of different areas. The NCDEQ Division of Mitigation Services (DMS) uses watershed planning to identify and prioritize the best locations to implement stream, wetland, and riparian-buffer restoration to improve water quality. To support better decision-making for watershed restoration activities we are developing a SPARROW (SPAtially Referenced Regressions On Watershed attributes) model framework specifically for North Carolina. The SPARROW analysis (developed by the U.S. Geological Survey) relates water-quality monitoring data to better understand the effects of human activities and natural processes on surface-water quality. The core of the model consists of using a nonlinear-regression equation to describe the non-conservative transport of contaminants from point and nonpoint sources on land to rivers, lakes and estuaries through the stream and river network. In this presentation, preliminary total Nitrogen, total Phosphorus, and Total Suspended Solids (TSS) NC-SPARROW models are described that illustrate the SPARROW modeling framework incorporating specific restoration datasets and activity metrics, such as extent of riparian buffer and easements.

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.

[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.

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.

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.

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.

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.

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.

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

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

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.

An improved active contour model for glacial lake extraction

NASA Astrophysics Data System (ADS)

Zhao, H.; Chen, F.; Zhang, M.

2017-12-01

Active contour model is a widely used method in visual tracking and image segmentation. Under the driven of objective function, the initial curve defined in active contour model will evolve to a stable condition - a desired result in given image. As a typical region-based active contour model, C-V model has a good effect on weak boundaries detection and anti noise ability which shows great potential in glacial lake extraction. Glacial lake is a sensitive indicator for reflecting global climate change, therefore accurate delineate glacial lake boundaries is essential to evaluate hydrologic environment and living environment. However, the current method in glacial lake extraction mainly contains water index method and recognition classification method are diffcult to directly applied in large scale glacial lake extraction due to the diversity of glacial lakes and masses impacted factors in the image, such as image noise, shadows, snow and ice, etc. Regarding the abovementioned advantanges of C-V model and diffcults in glacial lake extraction, we introduce the signed pressure force function to improve the C-V model for adapting to processing of glacial lake extraction. To inspect the effect of glacial lake extraction results, three typical glacial lake development sites were selected, include Altai mountains, Centre Himalayas, South-eastern Tibet, and Landsat8 OLI imagery was conducted as experiment data source, Google earth imagery as reference data for varifying the results. The experiment consequence suggests that improved active contour model we proposed can effectively discriminate the glacial lakes from complex backgound with a higher Kappa Coefficient - 0.895, especially in some small glacial lakes which belongs to weak information in the image. Our finding provide a new approach to improved accuracy under the condition of large proportion of small glacial lakes and the possibility for automated glacial lake mapping in large-scale area.

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…

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...

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…

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.…

Mathematical modeling of electrical activity of uterine muscle cells.

PubMed

Rihana, Sandy; Terrien, Jeremy; Germain, Guy; Marque, Catherine

2009-06-01

The uterine electrical activity is an efficient parameter to study the uterine contractility. In order to understand the ionic mechanisms responsible for its generation, we aimed at building a mathematical model of the uterine cell electrical activity based upon the physiological mechanisms. First, based on the voltage clamp experiments found in the literature, we focus on the principal ionic channels and their cognate currents involved in the generation of this electrical activity. Second, we provide the methodology of formulations of uterine ionic currents derived from a wide range of electrophysiological data. The model is validated step by step by comparing simulated voltage-clamp results with the experimental ones. The model reproduces successfully the generation of single spikes or trains of action potentials that fit with the experimental data. It allows analyzing ionic channels implications. Likewise, the calcium-dependent conductance influences significantly the cellular oscillatory behavior.

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.

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

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

Cometary activity and nucleus modelling: a new approach

NASA Astrophysics Data System (ADS)

Möhlmann, D.

1996-06-01

The phenomena of comet splittings with an average frequency of about one splitting per 100 years and comet (Chen and Jewitt, Icarus108, 265-271, 1994), and the restriction of cometary activity to well-defined small areas at the almost passive and mantle covered surface (Keller et al., ESA SP-250, Vol. II, pp. 363-364, 1986) are at present driving challenges to models of structure and evolution of comet nuclei. Extending the presently discussed models by incorporating lateral subsurface transport of sublimed volatiles, there appears the possibility that the places of sublimation are different from those of activity (the so-called active areas). Then, there is no necessity to distinguish between different surface properties at active and passive areas, assuming, e.g. an uncovered icy surface at active areas. Active areas are simply the very local "source sites" where the accumulated subsurface flows from distant regions reach the surface. The pressure driven subsurface flows of volatiles may not only leave the comet at its surface, they may penetrate via cracks, etc. also deeply into the nucleus. There they can cause a further growth of cracks and also new cracks. This can be a cause for the observed regular splittings. Furthermore, actual models (Kührt and Keller, Icarus109, 121-132, 1994; Skorov and Rickman, Planet. Space Sci.43, 1587-1594, 1995) of the gas transport through porous comet surface crusts can be interpreted as to give first indications for thermodynamical parameters in heat conducting and porous cometary crusts which are appropriate for 1 AU conditions to permit the temporary existence of a layer with fluid subsurface water within these crusts. This exciting result of the possible temporary existence of subsurface warm water in comets which approach the Sun within about 1 AU makes a cometary subsurface chemistry much more efficient than expected hitherto.

Reduced Activity of AMP-Activated Protein Kinase Protects against Genetic Models of Motor Neuron Disease

PubMed Central

Lim, M. A.; Selak, M. A.; Xiang, Z.; Krainc, D.; Neve, R. L.; Kraemer, B. C.; Watts, J. L.

2012-01-01

A growing body of research indicates that amyotrophic lateral sclerosis (ALS) patients and mouse models of ALS exhibit metabolic dysfunction. A subpopulation of ALS patients possesses higher levels of resting energy expenditure and lower fat-free mass compared to healthy controls. Similarly, two mutant copper zinc superoxide dismutase 1 (mSOD1) mouse models of familial ALS possess a hypermetabolic phenotype. The pathophysiological relevance of the bioenergetic defects observed in ALS remains largely elusive. AMP-activated protein kinase (AMPK) is a key sensor of cellular energy status and thus might be activated in various models of ALS. Here, we report that AMPK activity is increased in spinal cord cultures expressing mSOD1, as well as in spinal cord lysates from mSOD1 mice. Reducing AMPK activity either pharmacologically or genetically prevents mSOD1-induced motor neuron death in vitro. To investigate the role of AMPK in vivo, we used Caenorhabditis elegans models of motor neuron disease. C. elegans engineered to express human mSOD1 (G85R) in neurons develops locomotor dysfunction and severe fecundity defects when compared to transgenic worms expressing human wild-type SOD1. Genetic reduction of aak-2, the ortholog of the AMPK α2 catalytic subunit in nematodes, improved locomotor behavior and fecundity in G85R animals. Similar observations were made with nematodes engineered to express mutant tat-activating regulatory (TAR) DNA-binding protein of 43 kDa molecular weight. Altogether, these data suggest that bioenergetic abnormalities are likely to be pathophysiologically relevant to motor neuron disease. PMID:22262909

Activity Diagrams for DEVS Models: A Case Study Modeling Health Care Behavior

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

Ozmen, Ozgur; Nutaro, James J

Discrete Event Systems Specification (DEVS) is a widely used formalism for modeling and simulation of discrete and continuous systems. While DEVS provides a sound mathematical representation of discrete systems, its practical use can suffer when models become complex. Five main functions, which construct the core of atomic modules in DEVS, can realize the behaviors that modelers want to represent. The integration of these functions is handled by the simulation routine, however modelers can implement each function in various ways. Therefore, there is a need for graphical representations of complex models to simplify their implementation and facilitate their reproduction. In thismore » work, we illustrate the use of activity diagrams for this purpose in the context of a health care behavior model, which is developed with an agent-based modeling paradigm.« less

[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.

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

Mathematical modelling of the active hearing process in mosquitoes

PubMed Central

Avitabile, D.; Homer, M.; Champneys, A. R.; Jackson, J. C.; Robert, D.

2010-01-01

Insects have evolved diverse and delicate morphological structures in order to capture the inherently low energy of a propagating sound wave. In mosquitoes, the capture of acoustic energy and its transduction into neuronal signals are assisted by the active mechanical participation of the scolopidia. We propose a simple microscopic mechanistic model of the active amplification in 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: spontaneous oscillations, nonlinear amplification, hysteresis, 2 : 1 resonances, frequency response and gain loss owing to hypoxia. The numerical simulations presented here also generate new hypotheses. In particular, the model seems to indicate that scolopidia located towards the tip of Johnston's organ are responsible for the entrainment of the other scolopidia and that they give the largest contribution to the mechanical amplification. PMID:19447819

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.

[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.

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.

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

Mathematics teachers' conceptions about modelling activities and its reflection on their beliefs about mathematics

NASA Astrophysics Data System (ADS)

Shahbari, Juhaina Awawdeh

2018-07-01

The current study examines whether the engagement of mathematics teachers in modelling activities and subsequent changes in their conceptions about these activities affect their beliefs about mathematics. The sample comprised 52 mathematics teachers working in small groups in four modelling activities. The data were collected from teachers' Reports about features of each activity, interviews and questionnaires on teachers' beliefs about mathematics. The findings indicated changes in teachers' conceptions about the modelling activities. Most teachers referred to the first activity as a mathematical problem but emphasized only the mathematical notions or the mathematical operations in the modelling process; changes in their conceptions were gradual. Most of the teachers referred to the fourth activity as a mathematical problem and emphasized features of the whole modelling process. The results of the interviews indicated that changes in the teachers' conceptions can be attributed to structure of the activities, group discussions, solution paths and elicited models. These changes about modelling activities were reflected in teachers' beliefs about mathematics. The quantitative findings indicated that the teachers developed more constructive beliefs about mathematics after engagement in the modelling activities and that the difference was significant, however there was no significant difference regarding changes in their traditional beliefs.

Vibro-acoustic model of an active aircraft cabin window

NASA Astrophysics Data System (ADS)

Aloufi, Badr; Behdinan, Kamran; Zu, Jean

2017-06-01

This paper presents modeling and design of an active structural acoustic control (ASAC) system for controlling the low frequency sound field transmitted through an aircraft cabin window. The system uses stacked piezoelectric elements arranged in a manner to generate out-of-plane actuation point forces acting on the window panel boundaries. A theoretical vibro-acoustic model for an active quadruple-panel system is developed to characterize the dynamic behavior of the system and achieve a good understanding of the active control performance and the physical phenomena of the sound transmission loss (STL) characteristics. The quadruple-panel system represents the passenger window design used in some classes of modern aircraft with an exterior double pane of Plexiglas, an interior dust cover pane and a glazed dimmable pane, all separated by thin air cavities. The STL characteristics of identical pane window configurations with different piezoelectric actuator sets are analyzed. A parametric study describes the influence of important active parameters, such as the input voltage, number and location of the actuator elements, on the STL is investigated. In addition, a mathematical model for obtaining the optimal input voltage is developed to improve the acoustic attenuation capability of the control system. In general, the achieved results indicate that the proposed ASAC design offers a considerable improvement in the passive sound loss performance of cabin window design without significant effects, such as weight increase, on the original design. Also, the results show that the acoustic control of the active model with piezoelectric actuators bonded to the dust cover pane generates high structural vibrations in the radiating panel (dust cover) and an increase in sound power radiation. High active acoustic attenuation can be achieved by designing the ASAC system to apply active control forces on the inner Plexiglas panel or dimmable panel by installing the actuators on the

Gastroprotective activity of Zanthoxylum rhoifolium Lam. in animal models.

PubMed

Freitas, F F B P; Fernandes, H B; Piauilino, C A; Pereira, S S; Carvalho, K I M; Chaves, M H; Soares, P M G; Miura, L M C V; Leite, J R S A; Oliveira, R C M; Oliveira, F A

2011-09-01

The stem barks of Zanthoxylum rhoifolium Lam. (Rutaceae), locally known as "mamica de cadela", are popularly used in dyspepsies, stomachic, tonic, antitumoral, antipyretic and are used in treating flatulence and colic. The objective of this study was to evaluate the gastroprotective effect of the ethanolic extract of Zanthoxylum rhoifolium (EEZR) stem barks in acute gastric lesion models, investigating their possible mechanisms. Mice were used for the evaluation of the acute toxicity, and mice and rats to study the gastroprotective activity. The gastroprotective action of EEZR was analyzed in the absolute ethanol, HCl/ethanol and indomethacin-induced gastric lesion models in mice, hypothermic-restraint stress, and ischemia/reperfusion in rats. In the investigation of the gastroprotective mechanisms of EEZR, the participation of the NO-synthase pathway, ATP-sensitive potassium channels (K(ATP)), the levels of the non-protein sulfhydril groups (NP-SH) and the catalase activity using the ethanol-induced gastric mucosa lesion model and the quantification of the gastric mucus and the antisecretory activity through pylorus ligature model in rats were analyzed. The animals did not present any signs of acute toxicity for the EEZR (up to the 4 g/kg dose, po), and it was not possible to calculate the DL(50). EEZR (125-500 mg/kg) exhibited a significant gastroprotective effect in absolute ethanol, HCl/ethanol, hypothermic-restraint stress, and ischemia/reperfusion-induced gastric lesion models. EEZR (250 and 500 mg/kg) exhibited still a gastroprotective activity in the indomethacin-induced ulcer model. Gastroprotection of EEZR was significantly decreased in pre-treated mice with l-NAME or glibenclamide, the respective nitric oxide synthase and K(ATP) channels inhibitors. Our studies revealed that EEZR (500 mg/kg) prevented the decrease of the non-protein sulfhydril groups (NP-SH) and increased the catalase levels in ethanol-treated animals. Furthermore, the extract (500 mg

Modeling and simulation of fish swimming with active muscles.

PubMed

Curatolo, Michele; Teresi, Luciano

2016-11-21

Our goal is to reproduce the key features of carangiform swimming by modeling muscle functioning using the notion of active distortions, thus emphasizing the kinematical role of muscle, the generation of movement, rather than the dynamical one, the production of force. This approach, already proposed to model the action of muscles in different contexts, is here tested again for the problem of developing an effective and reliable framework to model and simulate swimming. A proper undulatory movement of a fish-like body is reproduced by defining a pattern of distortions, tuned in both space and time, meant to model the muscles activation which produce the flexural motion of body fish; eventually, interactions with the surrounding water yields the desired thrust. Carangiform swimmers have a relatively inflexible anterior body section and a generally flat, flexible posterior section. Because of this configuration, undulations sent rearward along the body attain a significant amplitude only in the posterior section. We compare the performances of different swimming gaits, and we are able to find some important relations between key parameters such as frequencies, wavelength, tail amplitude, and the achieved swim velocity, or the generated thrust, which summarize the swimming performance. In particular, an interesting relation is found between the Strouhal number and the wavelength of muscles activation. We highlight the muscle function during fish locomotion describing the activation of muscles and the relation between the force production and the shortening-lengthening cycle of muscle. We found a great accordance between results and empirical relations, giving an implicit validation of our models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Internal models for interpreting neural population activity during sensorimotor control

PubMed Central

Golub, Matthew D; Yu, Byron M; Chase, Steven M

2015-01-01

To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects’ internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output. DOI: http://dx.doi.org/10.7554/eLife.10015.001 PMID:26646183

Stochastic modeling of the hypothalamic pulse generator activity.

PubMed

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

1994-11-01

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

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

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.

[Purity Detection Model Update of Maize Seeds Based on Active Learning].

PubMed

Tang, Jin-ya; Huang, Min; Zhu, Qi-bing

2015-08-01

Seed purity reflects the degree of seed varieties in typical consistent characteristics, so it is great important to improve the reliability and accuracy of seed purity detection to guarantee the quality of seeds. Hyperspectral imaging can reflect the internal and external characteristics of seeds at the same time, which has been widely used in nondestructive detection of agricultural products. The essence of nondestructive detection of agricultural products using hyperspectral imaging technique is to establish the mathematical model between the spectral information and the quality of agricultural products. Since the spectral information is easily affected by the sample growth environment, the stability and generalization of model would weaken when the test samples harvested from different origin and year. Active learning algorithm was investigated to add representative samples to expand the sample space for the original model, so as to implement the rapid update of the model's ability. Random selection (RS) and Kennard-Stone algorithm (KS) were performed to compare the model update effect with active learning algorithm. The experimental results indicated that in the division of different proportion of sample set (1:1, 3:1, 4:1), the updated purity detection model for maize seeds from 2010 year which was added 40 samples selected by active learning algorithm from 2011 year increased the prediction accuracy for 2011 new samples from 47%, 33.75%, 49% to 98.89%, 98.33%, 98.33%. For the updated purity detection model of 2011 year, its prediction accuracy for 2010 new samples increased by 50.83%, 54.58%, 53.75% to 94.57%, 94.02%, 94.57% after adding 56 new samples from 2010 year. Meanwhile the effect of model updated by active learning algorithm was better than that of RS and KS. Therefore, the update for purity detection model of maize seeds is feasible by active learning algorithm.

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.

[The use of complex interval models for predicting activity of non-nucleoside reverse transcriptase activity].

PubMed

Burliaeva, E V; Tarkhov, A E; Burliaev, V V; Iurkevich, A M; Shvets, V I

2002-01-01

Searching of new anti-HIV agents is still crucial now. In general, researches are looking for inhibitors of certain HIV's vital enzymes, especially for reverse transcriptase (RT) inhibitors. Modern generation of anti-HIV agents represents non-nucleoside reverse transcriptase inhibitors (NNRTIs). They are much less toxic than nucleoside analogues and more chemically stable, thus being slower metabolized and emitted from the human body. Thus, search of new NNRTIs is actual today. Synthesis and study of new anti-HIV drugs is very expensive. So employment of the activity prediction techniques for such a search is very beneficial. This technique allows predicting the activities for newly proposed structures. It is based on the property model built by investigation of a series of known compounds with measured activity. This paper presents an approach of activity prediction based on "structure-activity" models designed to form a hypothesis about probably activity interval estimate. This hypothesis formed is based on structure descriptor domains, calculated for all energetically allowed conformers for each compound in the studied sef. Tetrahydroimidazobenzodiazipenone (TIBO) derivatives and phenylethyltiazolyltiourea (PETT) derivatives illustrated the predictive power of this method. The results are consistent with experimental data and allow to predict inhibitory activity of compounds, which were not included into the training set.

Characterizing and modeling the dynamics of activity and popularity.

PubMed

Zhang, Peng; Li, Menghui; Gao, Liang; Fan, Ying; Di, Zengru

2014-01-01

Social media, regarded as two-layer networks consisting of users and items, turn out to be the most important channels for access to massive information in the era of Web 2.0. The dynamics of human activity and item popularity is a crucial issue in social media networks. In this paper, by analyzing the growth of user activity and item popularity in four empirical social media networks, i.e., Amazon, Flickr, Delicious and Wikipedia, it is found that cross links between users and items are more likely to be created by active users and to be acquired by popular items, where user activity and item popularity are measured by the number of cross links associated with users and items. This indicates that users generally trace popular items, overall. However, it is found that the inactive users more severely trace popular items than the active users. Inspired by empirical analysis, we propose an evolving model for such networks, in which the evolution is driven only by two-step random walk. Numerical experiments verified that the model can qualitatively reproduce the distributions of user activity and item popularity observed in empirical networks. These results might shed light on the understandings of micro dynamics of activity and popularity in social media networks.

Characterizing and Modeling the Dynamics of Activity and Popularity

PubMed Central

Zhang, Peng; Li, Menghui; Gao, Liang; Fan, Ying; Di, Zengru

2014-01-01

Social media, regarded as two-layer networks consisting of users and items, turn out to be the most important channels for access to massive information in the era of Web 2.0. The dynamics of human activity and item popularity is a crucial issue in social media networks. In this paper, by analyzing the growth of user activity and item popularity in four empirical social media networks, i.e., Amazon, Flickr, Delicious and Wikipedia, it is found that cross links between users and items are more likely to be created by active users and to be acquired by popular items, where user activity and item popularity are measured by the number of cross links associated with users and items. This indicates that users generally trace popular items, overall. However, it is found that the inactive users more severely trace popular items than the active users. Inspired by empirical analysis, we propose an evolving model for such networks, in which the evolution is driven only by two-step random walk. Numerical experiments verified that the model can qualitatively reproduce the distributions of user activity and item popularity observed in empirical networks. These results might shed light on the understandings of micro dynamics of activity and popularity in social media networks. PMID:24586586

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.

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.

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.

MODELING MERCURY CONTROL WITH POWDERED ACTIVATED CARBON

EPA Science Inventory

The paper presents a mathematical model of total mercury removed from the flue gas at coal-fired plants equipped with powdered activated carbon (PAC) injection for Mercury control. The developed algorithms account for mercury removal by both existing equipment and an added PAC in...

Developing model-making and model-breaking skills using direct measurement video-based activities

NASA Astrophysics Data System (ADS)

Vonk, Matthew; Bohacek, Peter; Militello, Cheryl; Iverson, Ellen

2017-12-01

This study focuses on student development of two important laboratory skills in the context of introductory college-level physics. The first skill, which we call model making, is the ability to analyze a phenomenon in a way that produces a quantitative multimodal model. The second skill, which we call model breaking, is the ability to critically evaluate if the behavior of a system is consistent with a given model. This study involved 116 introductory physics students in four different sections, each taught by a different instructor. All of the students within a given class section participated in the same instruction (including labs) with the exception of five activities performed throughout the semester. For those five activities, each class section was split into two groups; one group was scaffolded to focus on model-making skills and the other was scaffolded to focus on model-breaking skills. Both conditions involved direct measurement videos. In some cases, students could vary important experimental parameters within the video like mass, frequency, and tension. Data collected at the end of the semester indicate that students in the model-making treatment group significantly outperformed the other group on the model-making skill despite the fact that both groups shared a common physical lab experience. Likewise, the model-breaking treatment group significantly outperformed the other group on the model-breaking skill. This is important because it shows that direct measurement video-based instruction can help students acquire science-process skills, which are critical for scientists, and which are a key part of current science education approaches such as the Next Generation Science Standards and the Advanced Placement Physics 1 course.

Active earth pressure model tests versus finite element analysis

NASA Astrophysics Data System (ADS)

Pietrzak, Magdalena

2017-06-01

The purpose of the paper is to compare failure mechanisms observed in small scale model tests on granular sample in active state, and simulated by finite element method (FEM) using Plaxis 2D software. Small scale model tests were performed on rectangular granular sample retained by a rigid wall. Deformation of the sample resulted from simple wall translation in the direction `from the soil" (active earth pressure state. Simple Coulomb-Mohr model for soil can be helpful in interpreting experimental findings in case of granular materials. It was found that the general alignment of strain localization pattern (failure mechanism) may belong to macro scale features and be dominated by a test boundary conditions rather than the nature of the granular sample.

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

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.

Discriminative latent models for recognizing contextual group activities.

PubMed

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg

2012-08-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.

Active Learning of Classification Models with Likert-Scale Feedback.

PubMed

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

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

Active Learning of Classification Models with Likert-Scale Feedback

PubMed Central

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

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

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.

Hepatoprotective activity of Musa paradisiaca on experimental animal models.

PubMed

Nirmala, M; Girija, K; Lakshman, K; Divya, T

2012-01-01

To investigate the hepatoprotective activity of stem of Musa paradisiaca (M. paradisiaca) in CCl4 and paracetamol induced hepatotoxicity models in rats. Hepatoprotective activity of alcoholic and aqueous extracts of stem of M. paradisiaca was demonstrated by using two experimentally induced hepatotoxicity models. Administration of hepatotoxins (CCl4 and paracetamol) showed significant biochemical and histological deteriorations in the liver of experimental animals. Pretreatment with alcoholic extract (500 mg/kg), more significantly and to a lesser extent the alcoholic extract (250 mg/kg) and aqueous extract (500 mg/kg), reduced the elevated levels of the serum enzymes like serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), alkaline phosphatase (ALP) and bilirubin levels and alcoholic and aqueous extracts reversed the hepatic damage towards the normal, which further evidenced the hepatoprotective activity of stem of M. paradisiaca. The alcoholic extract at doses of 250 and 500 mg/kg, p.o. and aqueous extract at a dose of 500 mg/kg, p.o. of stem of M. paradisiaca have significant effect on the liver of CCl4 and paracetamol induced hepatotoxicity animal models.

Gallbladder shape extraction from ultrasound images using active contour models.

PubMed

Ciecholewski, Marcin; Chochołowicz, Jakub

2013-12-01

Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

Diffusion in different models of active Brownian motion

NASA Astrophysics Data System (ADS)

Lindner, B.; Nicola, E. M.

2008-04-01

Active Brownian particles (ABP) have served as phenomenological models of self-propelled motion in biology. We study the effective diffusion coefficient of two one-dimensional ABP models (simplified depot model and Rayleigh-Helmholtz model) differing in their nonlinear friction functions. Depending on the choice of the friction function the diffusion coefficient does or does not attain a minimum as a function of noise intensity. We furthermore discuss the case of an additional bias breaking the left-right symmetry of the system. We show that this bias induces a drift and that it generally reduces the diffusion coefficient. For a finite range of values of the bias, both models can exhibit a maximum in the diffusion coefficient vs. noise intensity.

Lessons learned from Action Schools! BC--an 'active school' model to promote physical activity in elementary schools.

PubMed

Naylor, Patti-Jean; Macdonald, Heather M; Zebedee, Janelle A; Reed, Katherine E; McKay, Heather A

2006-10-01

The 'active school' model offers promise for promoting school-based physical activity (PA); however, few intervention trials have evaluated its effectiveness. Thus, our purpose was to: (1) describe Action Schools! BC (AS! BC) and its implementation (fidelity and feasibility) and (2) evaluate the impact of AS! BC on school provision of PA. Ten elementary schools were randomly assigned to one of the three conditions: Usual Practice (UP, three schools), Liaison (LS, four schools) or Champion (CS, three schools). Teachers in LS and CS schools received AS! BC training and resources but differed on the level of facilitation provided. UP schools continued with regular PA. Delivery of PA during the 11-month intervention was assessed with weekly Activity Logs and intervention fidelity and feasibility were assessed using Action Plans, workshop evaluations, teacher surveys and focus groups with administrators, teachers, parents and students. Physical activity delivered was significantly greater in LS (+67.4 min/week; 95% CI: 18.7-116.1) and CS (+55.2 min/week; 95% CI: 26.4-83.9) schools than UP schools. Analysis of Action Plans and Activity Logs showed fidelity to the model and moderate levels of compliance (75%). Teachers were highly satisfied with training and support. Benefits of AS! BC included positive changes in the children and school climate, including provision of resources, improved communication and program flexibility. These results support the use of the 'active school' model to positively alter the school environment. The AS! BC model was effective, providing more opportunities for "more children to be more active more often" and as such has the potential to provide health benefits to elementary school children.

On a Quantum Model of Brain Activities

NASA Astrophysics Data System (ADS)

Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

2010-01-01

One of the main activities of the brain is the recognition of signals. A first attempt to explain the process of recognition in terms of quantum statistics was given in [6]. Subsequently, details of the mathematical model were presented in a (still incomplete) series of papers (cf. [7, 2, 5, 10]). In the present note we want to give a general view of the principal ideas of this approach. We will introduce the basic spaces and justify the choice of spaces and operations. Further, we bring the model face to face with basic postulates any statistical model of the recognition process should fulfill. These postulates are in accordance with the opinion widely accepted in psychology and neurology.

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.

Modelling the participation decision and duration of sporting activity in Scotland

PubMed Central

Eberth, Barbara; Smith, Murray D.

2010-01-01

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

Active State Model for Autonomous Systems

NASA Technical Reports Server (NTRS)

Park, Han; Chien, Steve; Zak, Michail; James, Mark; Mackey, Ryan; Fisher, Forest

2003-01-01

The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

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 ...

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

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.

Pressure in an exactly solvable model of active fluid

NASA Astrophysics Data System (ADS)

Marini Bettolo Marconi, Umberto; Maggi, Claudio; Paoluzzi, Matteo

2017-07-01

We consider the pressure in the steady-state regime of three stochastic models characterized by self-propulsion and persistent motion and widely employed to describe the behavior of active particles, namely, the Active Brownian particle (ABP) model, the Gaussian colored noise (GCN) model, and the unified colored noise approximation (UCNA) model. Whereas in the limit of short but finite persistence time, the pressure in the UCNA model can be obtained by different methods which have an analog in equilibrium systems, in the remaining two models only the virial route is, in general, possible. According to this method, notwithstanding each model obeys its own specific microscopic law of evolution, the pressure displays a certain universal behavior. For generic interparticle and confining potentials, we derive a formula which establishes a correspondence between the GCN and the UCNA pressures. In order to provide explicit formulas and examples, we specialize the discussion to the case of an assembly of elastic dumbbells confined to a parabolic well. By employing the UCNA we find that, for this model, the pressure determined by the thermodynamic method coincides with the pressures obtained by the virial and mechanical methods. The three methods when applied to the GCN give a pressure identical to that obtained via the UCNA. Finally, we find that the ABP virial pressure exactly agrees with the UCNA and GCN results.

Modeling Novelty Habituation During Exploratory Activity in Drosophila

PubMed Central

Soibam, Benjamin; Shah, Shishir; Gunaratne, Gemunu H.; Roman, Gregg W.

2013-01-01

Habituation is a common form of non-associative learning in which the organism gradually decreases its response to repeated stimuli. The decrease in exploratory activity of many animal species during exposure to a novel open field arena is a widely studied habituation paradigm. However, a theoretical framework to quantify how the novelty of the arena is learned during habituation is currently missing. Drosophila melanogaster display a high mean absolute activity and a high probability for directional persistence when first introduced to a novel arena. Both measures decrease during habituation to the arena. Here, we propose a phenomenological model of habituation for Drosophila exploration based on two principles: Drosophila form a spatial representation of the arena edge as a set of connected local patches, and repeated exposure to these patches is essential for the habituation of the novelty. The level of exposure depends on the number of visitations and is quantified by a variable referred to as “coverage.” This model was tested by comparing predictions against the experimentally measured behavior of wild type Drosophila. The novelty habituation of wild type Canton-S depends on coverage and is specifically independent of the arena radius. Our model describes the time dependent locomotor activity, ΔD, of Canton-S using an experimentally established stochastic process Pn(ΔD) which depends on the coverage. The quantitative measures of exploration and habituation were further applied to three mutant genotypes. Consistent with a requirement for vision in novelty habituation, blind no receptor potential A7 mutants display a failure in the decay of probability for directional persistence and mean absolute activity. The rutabaga2080 habituation mutant also shows defects in these measures. The kurtz1 non-visual arrestin mutant demonstrates a rapid decay in these measures, implying reduced motivation. The model and the habituation measures offer a powerful framework

Understanding Activity Engagement Across Weekdays and Weekend Days: A Multivariate Multiple Discrete-Continuous Modeling Approach

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

Garikapati, Venu; Astroza, Sebastian; Bhat, Prerna C.

This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are important complementary relationships and competing tradeoffs involved in scheduling and allocating time to various activities across days of the week. Both limited survey data availability and methodological challenges in modeling week-long activity-travel schedules have precluded the development of multi-day activity-travel demand models. With passive and technology-based data collection methods increasinglymore » in vogue, the collection of multi-day travel data may become increasingly commonplace in the years ahead. This paper addresses the methodological challenge associated with modeling multi-day activity-travel demand by formulating a multivariate multiple discrete-continuous probit (MDCP) model system. The comprehensive framework ties together two MDCP model components, one corresponding to weekday time allocation and the other to weekend activity-time allocation. By tying the two MDCP components together, the model system also captures relationships in activity-time allocation between weekdays on the one hand and weekend days on the other. Model estimation on a week-long travel diary data set from the United Kingdom shows that there are significant inter-relationships between weekdays and weekend days in activity-travel scheduling behavior. The model system presented in this paper may serve as a higher-level multi-day activity scheduler in conjunction with existing daily activity-based travel models.« less

Psychosocial Pain Management Moderation: The Limit, Activate, and Enhance Model.

PubMed

Day, Melissa A; Ehde, Dawn M; Jensen, Mark P

2015-10-01

There is a growing emphasis in the pain literature on understanding the following second-order research questions: Why do psychosocial pain treatments work? For whom do various treatments work? This critical review summarizes research that addresses the latter question and proposes a moderation model to help guide future research. A theoretical moderation framework for matching individuals to specific psychosocial pain interventions has been lacking. However, several such frameworks have been proposed in the broad psychotherapy and implementation science literature. Drawing on these theories and adapting them specifically for psychosocial pain treatment, here we propose a Limit, Activate, and Enhance model of pain treatment moderation. This model is unique in that it includes algorithms not only for matching treatments on the basis of patient weaknesses but also for directing patients to interventions that build on their strengths. Critically, this model provides a basis for specific a priori hypothesis generation, and a selection of the possible hypotheses drawn from the model are proposed and discussed. Future research considerations are presented that could refine and expand the model based on theoretically driven empirical evidence. The Limit, Activate, and Enhance model presented here is a theoretically derived framework that provides an a priori basis for hypothesis generation regarding psychosocial pain treatment moderators. The model will advance moderation research via its unique focus on matching patients to specific treatments that (1) limit maladaptive responses, (2) activate adaptive responses, and (3) enhance treatment outcomes based on patient strengths and resources. Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.

Discriminative Latent Models for Recognizing Contextual Group Activities

PubMed Central

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N.; Mori, Greg

2012-01-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities. PMID:22144516

Development and Validation of a Computational Model for Androgen Receptor Activity

PubMed Central

2016-01-01

Testing thousands of chemicals to identify potential androgen receptor (AR) agonists or antagonists would cost millions of dollars and take decades to complete using current validated methods. High-throughput in vitro screening (HTS) and computational toxicology approaches can more rapidly and inexpensively identify potential androgen-active chemicals. We integrated 11 HTS ToxCast/Tox21 in vitro assays into a computational network model to distinguish true AR pathway activity from technology-specific assay interference. The in vitro HTS assays probed perturbations of the AR pathway at multiple points (receptor binding, coregulator recruitment, gene transcription, and protein production) and multiple cell types. Confirmatory in vitro antagonist assay data and cytotoxicity information were used as additional flags for potential nonspecific activity. Validating such alternative testing strategies requires high-quality reference data. We compiled 158 putative androgen-active and -inactive chemicals from a combination of international test method validation efforts and semiautomated systematic literature reviews. Detailed in vitro assay information and results were compiled into a single database using a standardized ontology. Reference chemical concentrations that activated or inhibited AR pathway activity were identified to establish a range of potencies with reproducible reference chemical results. Comparison with existing Tier 1 AR binding data from the U.S. EPA Endocrine Disruptor Screening Program revealed that the model identified binders at relevant test concentrations (<100 μM) and was more sensitive to antagonist activity. The AR pathway model based on the ToxCast/Tox21 assays had balanced accuracies of 95.2% for agonist (n = 29) and 97.5% for antagonist (n = 28) reference chemicals. Out of 1855 chemicals screened in the AR pathway model, 220 chemicals demonstrated AR agonist or antagonist activity and an additional 174 chemicals were predicted to have

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

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.

An Active Learning Exercise for Introducing Agent-Based Modeling

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

Active shape models incorporating isolated landmarks for medical image annotation

NASA Astrophysics Data System (ADS)

Norajitra, Tobias; Meinzer, Hans-Peter; Stieltjes, Bram; Maier-Hein, Klaus H.

2014-03-01

Apart from their robustness in anatomic surface segmentation, purely surface based 3D Active Shape Models lack the ability to automatically detect and annotate non-surface key points of interest. However, annotation of anatomic landmarks is desirable, as it yields additional anatomic and functional information. Moreover, landmark detection might help to further improve accuracy during ASM segmentation. We present an extension of surface-based 3D Active Shape Models incorporating isolated non-surface landmarks. Positions of isolated and surface landmarks are modeled conjoint within a point distribution model (PDM). Isolated landmark appearance is described by a set of haar-like features, supporting local landmark detection on the PDM estimates using a kNN-Classi er. Landmark detection was evaluated in a leave-one-out cross validation on a reference dataset comprising 45 CT volumes of the human liver after shape space projection. Depending on the anatomical landmark to be detected, our experiments have shown in about 1/4 up to more than 1/2 of all test cases a signi cant improvement in detection accuracy compared to the position estimates delivered by the PDM. Our results encourage further research with regard to the combination of shape priors and machine learning for landmark detection within the Active Shape Model Framework.

Hepatoprotective activity of Musa paradisiaca on experimental animal models

PubMed Central

Nirmala, M; Girija, K; Lakshman, K; Divya, T

2012-01-01

Objective To investigate the hepatoprotective activity of stem of Musa paradisiaca (M. paradisiaca) in CCl4 and paracetamol induced hepatotoxicity models in rats. Methods Hepatoprotective activity of alcoholic and aqueous extracts of stem of M. paradisiaca was demonstrated by using two experimentally induced hepatotoxicity models. Results Administration of hepatotoxins (CCl4 and paracetamol) showed significant biochemical and histological deteriorations in the liver of experimental animals. Pretreatment with alcoholic extract (500 mg/kg), more significantly and to a lesser extent the alcoholic extract (250 mg/kg) and aqueous extract (500 mg/kg), reduced the elevated levels of the serum enzymes like serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), alkaline phosphatase (ALP) and bilirubin levels and alcoholic and aqueous extracts reversed the hepatic damage towards the normal, which further evidenced the hepatoprotective activity of stem of M. paradisiaca. Conclusions The alcoholic extract at doses of 250 and 500 mg/kg, p.o. and aqueous extract at a dose of 500 mg/kg, p.o. of stem of M. paradisiaca have significant effect on the liver of CCl4 and paracetamol induced hepatotoxicity animal models. PMID:23569826

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…

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.

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

PubMed

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

An Activation-Based Model of Routine Sequence Errors

DTIC Science & Technology

2015-04-01

part of the ACT-R frame- work (e.g., Anderson, 1983), we adopt a newer, richer no- tion of priming as part of our approach ( Harrison & Trafton, 2010...2014). Other models of routine sequence errors, such as the in- teractive activation network ( IAN ) model (Cooper & Shal- lice, 2006) and the simple...error patterns that results from an interface layout shift. The ideas behind our expanded priming approach, however, could apply to IAN , which uses

Anticancer activities against cholangiocarcinoma, toxicity and pharmacological activities of Thai medicinal plants in animal models

PubMed Central

2012-01-01

Background Chemotherapy of cholangiocarcinoma (CCA), a devastating cancer with increasing worldwide incidence and mortality rates, is largely ineffective. The discovery and development of effective chemotherapeutics is urgently needed. Methods/Design The study aimed at evaluating anticancer activities, toxicity, and pharmacological activities of the curcumin compound (CUR), the crude ethanolic extracts of rhizomes of Zingiber officinale Roscoe (Ginger: ZO) and Atractylodes lancea thung. DC (Khod-Kha-Mao: AL), fruits of Piper chaba Hunt. (De-Plee: PC), and Pra-Sa-Prao-Yhai formulation (a mixture of parts of 18 Thai medicinal plants: PPF) were investigated in animal models. Anti-cholangiocarcinoma (anti-CCA) was assessed using CCA-xenograft nude mouse model. The antihypertensive, analgesic, anti-inflammatory, antipyretic, and anti-ulcer activities and effects on motor coordination were investigated using Rota-rod test, CODA tail-cuff system, writhing and hot plate tests, carrageenan-induced paw edema test, brewer's yeast test, and alcohol-induced gastric ulcer test, respectively. Acute and subacute toxicity tests were performed according to the OECD guideline for testing of chemicals with modification. Results Promising anticancer activity against CCA in nude mouse xenograft model was shown for the ethanolic extract of AL at all oral dose levels (1000, 3000, and 5000 mg/kg body weight) as well as the extracts of ZO, PPF, and CUR compound at the highest dose level (5000, 4000, and 5000 mg/kg body weight, respectively). PC produced no significant anti-CCA activity. Results from acute and subacute toxicity tests both in mice and rats indicate safety profiles of all the test materials in a broad range of dose levels. No significant toxicity except stomach irritation and general CNS depressant signs were observed. Investigation of pharmacological activities of the test materials revealed promising anti-inflammatory (ZO, PPF, and AL), analgesic (CUR and PPF), antipyretic

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

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic-algorithms and allows to obtaining thresholds of landslide activation from the set of historical occurrences and from the rainfall series. GASAKe can be applied to either single landslides or set of similar slope movements in a homogeneous environment. Calibration of the model is based on genetic-algorithms, and provides for families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from these latter, the corresponding mobility functions (i.e. the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to hydro-geological complexity of the site. Generally, smaller values are expected for shallow slope instabilities with respect to large-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing recorded or forecasted rainfall series. Example of application of GASAKe to a medium-scale slope movement (the Uncino landslide at San Fili, in Calabria, Southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, Southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of landslide occurrence. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e. neither missing nor false alarms) has been achieved against 5 activations. As for temporal validation, the experiments performed by considering the extra dates of landslide activation have also proved satisfactory. In view of early-warning applications for civil protection purposes, the capability of the

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

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.

Anti-granuloma activity of Coriandrum sativum in experimental models

PubMed Central

Nair, Vinod; Singh, Surender; Gupta, Yogendra Kumar

2013-01-01

Background: Coriandrum sativum has been used in the traditional systems of medicine for management of arthritis and other inflammatory disorders. Objectives: In this study, we have evaluated the anti-inflammatory and anti-granuloma activities of Coriandrum sativum hydroalcoholic extract (CSHE) in experimental models. Materials and Methods: The anti-inflammatory activity of CSHE was evaluated using carrageenan-induced paw edema model and the anti-granuloma activity of CSHE was evaluated using the subcutaneous cotton pellet implantation-induced granuloma formation and stimulation of peritoneal macrophages with complete Freund's adjuvant. Serum tumor necrosis factor-α (TNF-α), IL-6, IL-1 β levels, and peritoneal macrophage expression of TNF-R1 were evaluated as markers of global inflammation. Results: CSHE at the highest dose tested (32 mg/kg) produced a significant reduction (P < 0.05) in paw edema after carrageenan administration. CSHE treatment also reduced dry granuloma weight in all treated animals. Serum IL-6 and IL-1 β levels were significantly (P < 0.05) lower in the CSHE (32 mg/kg)-treated group as compared to control. Although there was an increase in serum TNF-α level in the CSHE-treated group as compared to control, TNF-R1 expression on peritoneal macrophages was found to be reduced. Conclusion: Thus, the result of this study demonstrates the anti-inflammatory and anti-granuloma activities of CSHE in experimental models, and validates its traditional use for the management of arthritis and other inflammatory disorders. PMID:23741156

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.

Using Hybrid Modeling to Develop Innovative Activities

ERIC Educational Resources Information Center

Lichtman, Brenda; Avans, Diana

2005-01-01

This article describes a hybrid activities model that physical educators can use with students in grades four and above to create virtually a limitless array of novel games. A brief introduction to the basic theory is followed by descriptions of some hybrid games. Hybrid games are typically the result of merging two traditional sports or other…

Realistic Real World Contexts: Model Eliciting Activities

ERIC Educational Resources Information Center

Doruk, Bekir Kürsat

2016-01-01

Researchers have proposed a variety of methods to make a connection between real life and mathematics so that it can be learned in a practical way and enable people to utilise mathematics in their daily lives. Model-eliciting activities (MEAs) were developed to fulfil this need and are very capable of serving this purpose. The reason MEAs are so…

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 ...

Active Brownian motion models and applications to ratchets

NASA Astrophysics Data System (ADS)

Fiasconaro, A.; Ebeling, W.; Gudowska-Nowak, E.

2008-10-01

We give an overview over recent studies on the model of Active Brownian Motion (ABM) coupled to reservoirs providing free energy which may be converted into kinetic energy of motion. First, we present an introduction to a general concept of active Brownian particles which are capable to take up energy from the source and transform part of it in order to perform various activities. In the second part of our presentation we consider applications of ABM to ratchet systems with different forms of differentiable potentials. Both analytical and numerical evaluations are discussed for three cases of sinusoidal, staircaselike and Mateos ratchet potentials, also with the additional loads modelled by tilted potential structure. In addition, stochastic character of the kinetics is investigated by considering perturbation by Gaussian white noise which is shown to be responsible for driving the directionality of the asymptotic flux in the ratchet. This stochastically driven directionality effect is visualized as a strong nonmonotonic dependence of the statistics of the right versus left trajectories of motion leading to a net current of particles. Possible applications of the ratchet systems to molecular motors are also briefly discussed.

Quantitative modeling of multiscale neural activity

NASA Astrophysics Data System (ADS)

Robinson, Peter A.; Rennie, Christopher J.

2007-01-01

The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.

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

Finite-element model of the active organ of Corti

PubMed Central

Elliott, Stephen J.; Baumgart, Johannes

2016-01-01

The cochlear amplifier that provides our hearing with its extraordinary sensitivity and selectivity is thought to be the result of an active biomechanical process within the sensory auditory organ, the organ of Corti. Although imaging techniques are developing rapidly, it is not currently possible, in a fully active cochlea, to obtain detailed measurements of the motion of individual elements within a cross section of the organ of Corti. This motion is predicted using a two-dimensional finite-element model. The various solid components are modelled using elastic elements, the outer hair cells (OHCs) as piezoelectric elements and the perilymph and endolymph as viscous and nearly incompressible fluid elements. The model is validated by comparison with existing measurements of the motions within the passive organ of Corti, calculated when it is driven either acoustically, by the fluid pressure or electrically, by excitation of the OHCs. The transverse basilar membrane (BM) motion and the shearing motion between the tectorial membrane and the reticular lamina are calculated for these two excitation modes. The fully active response of the BM to acoustic excitation is predicted using a linear superposition of the calculated responses and an assumed frequency response for the OHC feedback. PMID:26888950

Modeling individual differences in working memory performance: a source activation account

PubMed Central

Daily, Larry Z.; Lovett, Marsha C.; Reder, Lynne M.

2008-01-01

Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called source activation, which is used to maintain goal-relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. PMID:19079561

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

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

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.

A nonlinear dynamical analogue model of geomagnetic activity

NASA Technical Reports Server (NTRS)

Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Buechner, J.

1992-01-01

Consideration is given to the solar wind-magnetosphere interaction within the framework of deterministic nonlinear dynamics. An earlier dripping faucet analog model of the low-dimensional solar wind-magnetosphere system is reviewed, and a plasma physical counterpart to that model is constructed. A Faraday loop in the magnetotail is considered, and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. The model is characterized as an elementary time-dependent global convection model. The convection evolves within a magnetotail shape that varies in a prescribed manner in response to the dynamical evolution of the convection. The result is a nonlinear model capable of exhibiting a transition from regular to chaotic loading and unloading. The model's behavior under steady loading and also some elementary forms of time-dependent loading is discussed.

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.

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.

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

Validation of a common data model for active safety surveillance research

PubMed Central

Ryan, Patrick B; Reich, Christian G; Hartzema, Abraham G; Stang, Paul E

2011-01-01

Objective Systematic analysis of observational medical databases for active safety surveillance is hindered by the variation in data models and coding systems. Data analysts often find robust clinical data models difficult to understand and ill suited to support their analytic approaches. Further, some models do not facilitate the computations required for systematic analysis across many interventions and outcomes for large datasets. Translating the data from these idiosyncratic data models to a common data model (CDM) could facilitate both the analysts' understanding and the suitability for large-scale systematic analysis. In addition to facilitating analysis, a suitable CDM has to faithfully represent the source observational database. Before beginning to use the Observational Medical Outcomes Partnership (OMOP) CDM and a related dictionary of standardized terminologies for a study of large-scale systematic active safety surveillance, the authors validated the model's suitability for this use by example. Validation by example To validate the OMOP CDM, the model was instantiated into a relational database, data from 10 different observational healthcare databases were loaded into separate instances, a comprehensive array of analytic methods that operate on the data model was created, and these methods were executed against the databases to measure performance. Conclusion There was acceptable representation of the data from 10 observational databases in the OMOP CDM using the standardized terminologies selected, and a range of analytic methods was developed and executed with sufficient performance to be useful for active safety surveillance. PMID:22037893

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.

Predicting changes in volcanic activity through modelling magma ascent rate.

NASA Astrophysics Data System (ADS)

Thomas, Mark; Neuberg, Jurgen

2013-04-01

It is a simple fact that changes in volcanic activity happen and in retrospect they are easy to spot, the dissimilar eruption dynamics between an effusive and explosive event are not hard to miss. However to be able to predict such changes is a much more complicated process. To cause altering styles of activity we know that some part or combination of parts within the system must vary with time, as if there is no physical change within the system, why would the change in eruptive activity occur? What is unknown is which parts or how big a change is needed. We present the results of a suite of conduit flow models that aim to answer these questions by assessing the influence of individual model parameters such as the dissolved water content or magma temperature. By altering these variables in a systematic manner we measure the effect of the changes by observing the modelled ascent rate. We use the ascent rate as we believe it is a very important indicator that can control the style of eruptive activity. In particular, we found that the sensitivity of the ascent rate to small changes in model parameters surprising. Linking these changes to observable monitoring data in a way that these data could be used as a predictive tool is the ultimate goal of this work. We will show that changes in ascent rate can be estimated by a particular type of seismicity. Low frequency seismicity, thought to be caused by the brittle failure of melt is often linked with the movement of magma within a conduit. We show that acceleration in the rate of low frequency seismicity can correspond to an increase in the rate of magma movement and be used as an indicator for potential changes in eruptive activity.

Thinking Egyptian: Active Models for Understanding Spatial Representation.

ERIC Educational Resources Information Center

Schiferl, Ellen

This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…

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…

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.

Medical Writing Competency Model - Section 1: Functions, Tasks, and Activities.

PubMed

Clemow, David B; Wagner, Bertil; Marshallsay, Christopher; Benau, Dan; L'Heureux, Darryl; Brown, David H; Dasgupta, Devjani Ghosh; Girten, Eileen; Hubbard, Frank; Gawrylewski, Helle-Mai; Ebina, Hiroko; Stoltenborg, Janet; York, J P; Green, Kim; Wood, Linda Fossati; Toth, Lisa; Mihm, Michael; Katz, Nancy R; Vasconcelos, Nina-Maria; Sakiyama, Norihisa; Whitsell, Robin; Gopalakrishnan, Shobha; Bairnsfather, Susan; Wanderer, Tatyana; Schindler, Thomas M; Mikyas, Yeshi; Aoyama, Yumiko

2018-01-01

This article provides Section 1 of the 2017 Edition 2 Medical Writing Competency Model that describes the core work functions and associated tasks and activities related to professional medical writing within the life sciences industry. The functions in the Model are scientific communication strategy; document preparation, development, and finalization; document project management; document template, standard, format, and style development and maintenance; outsourcing, alliance partner, and client management; knowledge, skill, ability, and behavior development and sharing; and process improvement. The full Model also includes Section 2, which covers the knowledge, skills, abilities, and behaviors needed for medical writers to be effective in their roles; Section 2 is presented in a companion article. Regulatory, publication, and other scientific writing as well as management of writing activities are covered. The Model was developed to aid medical writers and managers within the life sciences industry regarding medical writing hiring, training, expectation and goal setting, performance evaluation, career development, retention, and role value sharing to cross-functional partners.

Snakes on a plane: modeling flexible active nematics

NASA Astrophysics Data System (ADS)

Selinger, Robin

Active soft matter systems of self-propelled rod-shaped particles exhibit ordered phases and collective behavior that are remarkably different from their passive analogs. In nature, many self-propelled rod-shaped particles, such as gliding bacteria and kinesin-driven microtubules, are flexible and can bend. We model these ``living liquid crystals'' to explore their phase behavior, dynamics, and pattern formation. We model particles as short polymers via molecular dynamics with a Langevin thermostat and various types of activity, substrate, and environments. For self-propelled polar particles gliding on a solid substrate, we map out the phase diagram as a function of particle density and flexibility. We compare simulated defect structures to those observed in colonies of gliding myxobacteria; compare spooling behavior to that observed in microtubule gliding assays; and analyze emergence of nematic and polar order. Next we explore pattern formation of self-propelled polar particles under flexible encapsulation, and on substrates with non-uniform Gaussian curvature. Lastly, we impose an activity mechanism that mimics extensile shear, study flexible particles both on solid substrates and coupled to a lipid membrane, and discuss comparisons to relevant experiments. Work performed in collaboration with Michael Varga (Kent State) and Luca Giomi (Universiteit Leiden.) Work supported by NSF DMR-1409658.

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.

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.

Modeling and Simulation of Viscous Electro-Active Polymers

PubMed Central

Vogel, Franziska; Göktepe, Serdar; Steinmann, Paul; Kuhl, Ellen

2014-01-01

Electro-active materials are capable of undergoing large deformation when stimulated by an electric field. They can be divided into electronic and ionic electro-active polymers (EAPs) depending on their actuation mechanism based on their composition. We consider electronic EAPs, for which attractive Coulomb forces or local re-orientation of polar groups cause a bulk deformation. Many of these materials exhibit pronounced visco-elastic behavior. Here we show the development and implementation of a constitutive model, which captures the influence of the electric field on the visco-elastic response within a geometrically non-linear finite element framework. The electric field affects not only the equilibrium part of the strain energy function, but also the viscous part. To adopt the familiar additive split of the strain from the small strain setting, we formulate the governing equations in the logarithmic strain space and additively decompose the logarithmic strain into elastic and viscous parts. We show that the incorporation of the electric field in the viscous response significantly alters the relaxation and hysteresis behavior of the model. Our parametric study demonstrates that the model is sensitive to the choice of the electro-viscous coupling parameters. We simulate several actuator structures to illustrate the performance of the method in typical relaxation and creep scenarios. Our model could serve as a design tool for micro-electro-mechanical systems, microfluidic devices, and stimuli-responsive gels such as artificial skin, tactile displays, or artificial muscle. PMID:25267881

Micromechanics and constitutive models for soft active materials with phase evolution

NASA Astrophysics Data System (ADS)

Wang, Binglian

Soft active materials, such as shape memory polymers, liquid crystal elastomers, soft tissues, gels etc., are materials that can deform largely in response to external stimuli. Micromechanics analysis of heterogeneous materials based on finite element method is a typically numerical way to study the thermal-mechanical behaviors of soft active materials with phase evolution. While the constitutive models that can precisely describe the stress and strain fields of materials in the process of phase evolution can not be found in the databases of some commercial finite element analysis (FEA) tools such as ANSYS or Abaqus, even the specific constitutive behavior for each individual phase either the new formed one or the original one has already been well-known. So developing a computationally efficient and general three dimensional (3D) thermal-mechanical constitutive model for soft active materials with phase evolution which can be implemented into FEA is eagerly demanded. This paper first solved this problem theoretically by recording the deformation history of each individual phase in the phase evolution process, and adopted the idea of effectiveness by regarding all the new formed phase as an effective phase with an effective deformation to make this theory computationally efficient. A user material subroutine (UMAT) code based on this theoretical constitutive model has been finished in this work which can be added into the material database in Abaqus or ANSYS and can be easily used for most soft active materials with phase evolution. Model validation also has been done through comparison between micromechanical FEA and experiments on a particular composite material, shape memory elastomeric composite (SMEC) which consisted of an elastomeric matrix and the crystallizable fibre. Results show that the micromechanics and the constitutive models developed in this paper for soft active materials with phase evolution are completely relied on.

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

[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.

Modeling crustal deformation near active faults and volcanic centers: a catalog of deformation models and modeling approaches

USGS Publications Warehouse

Battaglia, Maurizio; ,; Peter, F.; Murray, Jessica R.

2013-01-01

This manual provides the physical and mathematical concepts for selected models used to interpret deformation measurements near active faults and volcanic centers. The emphasis is on analytical models of deformation that can be compared with data from the Global Positioning System (GPS) receivers, Interferometric synthetic aperture radar (InSAR), leveling surveys, tiltmeters and strainmeters. Source models include pressurized spherical, ellipsoidal, and horizontal penny-shaped geometries in an elastic, homogeneous, flat half-space. Vertical dikes and faults are described following the mathematical notation for rectangular dislocations in an elastic, homogeneous, flat half-space. All the analytical expressions were verified against numerical models developed by use of COMSOL Multyphics, a Finite Element Analysis software (http://www.comsol.com). In this way, typographical errors present were identified and corrected. Matlab scripts are also provided to facilitate the application of these models.

Unsteady aerodynamic modeling and active aeroelastic control

NASA Technical Reports Server (NTRS)

Edwards, J. W.

1977-01-01

Unsteady aerodynamic modeling techniques are developed and applied to the study of active control of elastic vehicles. The problem of active control of a supercritical flutter mode poses a definite design goal stability, and is treated in detail. The transfer functions relating the arbitrary airfoil motions to the airloads are derived from the Laplace transforms of the linearized airload expressions for incompressible two dimensional flow. The transfer function relating the motions to the circulatory part of these loads is recognized as the Theodorsen function extended to complex values of reduced frequency, and is termed the generalized Theodorsen function. Inversion of the Laplace transforms yields exact transient airloads and airfoil motions. Exact root loci of aeroelastic modes are calculated, providing quantitative information regarding subcritical and supercritical flutter conditions.

Static and Impulsive Models of Solar Active Regions

NASA Technical Reports Server (NTRS)

Patsourakos, S.; Klimchuk, James A.

2008-01-01

The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.

Enriching step-based product information models to support product life-cycle activities

NASA Astrophysics Data System (ADS)

Sarigecili, Mehmet Ilteris

The representation and management of product information in its life-cycle requires standardized data exchange protocols. Standard for Exchange of Product Model Data (STEP) is such a standard that has been used widely by the industries. Even though STEP-based product models are well defined and syntactically correct, populating product data according to these models is not easy because they are too big and disorganized. Data exchange specifications (DEXs) and templates provide re-organized information models required in data exchange of specific activities for various businesses. DEXs show us it would be possible to organize STEP-based product models in order to support different engineering activities at various stages of product life-cycle. In this study, STEP-based models are enriched and organized to support two engineering activities: materials information declaration and tolerance analysis. Due to new environmental regulations, the substance and materials information in products have to be screened closely by manufacturing industries. This requires a fast, unambiguous and complete product information exchange between the members of a supply chain. Tolerance analysis activity, on the other hand, is used to verify the functional requirements of an assembly considering the worst case (i.e., maximum and minimum) conditions for the part/assembly dimensions. Another issue with STEP-based product models is that the semantics of product data are represented implicitly. Hence, it is difficult to interpret the semantics of data for different product life-cycle phases for various application domains. OntoSTEP, developed at NIST, provides semantically enriched product models in OWL. In this thesis, we would like to present how to interpret the GD & T specifications in STEP for tolerance analysis by utilizing OntoSTEP.

Modeling a Transient Pressurization with Active Cooling Sizing Tool

NASA Technical Reports Server (NTRS)

Guzik, Monica C.; Plachta, David W.; Elchert, Justin P.

2011-01-01

As interest in the area of in-space zero boil-off cryogenic propellant storage develops, the need to visualize and quantify cryogen behavior during ventless tank self-pressurization and subsequent cool-down with active thermal control has become apparent. During the course of a mission, such as the launch ascent phase, there are periods that power to the active cooling system will be unavailable. In addition, because it is not feasible to install vacuum jackets on large propellant tanks, as is typically done for in-space cryogenic applications for science payloads, instances like the launch ascent heating phase are important to study. Numerous efforts have been made to characterize cryogenic tank pressurization during ventless cryogen storage without active cooling, but few tools exist to model this behavior in a user-friendly environment for general use, and none exist that quantify the marginal active cooling system size needed for power down periods to manage tank pressure response once active cooling is resumed. This paper describes the Transient pressurization with Active Cooling Tool (TACT), which is based on a ventless three-lump homogeneous thermodynamic self-pressurization model1 coupled with an active cooling system estimator. TACT has been designed to estimate the pressurization of a heated but unvented cryogenic tank, assuming an unavailable power period followed by a given cryocooler heat removal rate. By receiving input data on the tank material and geometry, propellant initial conditions, and passive and transient heating rates, a pressurization and recovery profile can be found, which establishes the time needed to return to a designated pressure. This provides the ability to understand the effect that launch ascent and unpowered mission segments have on the size of an active cooling system. A sample of the trends found show that an active cooling system sized for twice the steady state heating rate would results in a reasonable time for tank

Stochastic E2F activation and reconciliation of phenomenological cell-cycle models.

PubMed

Lee, Tae J; Yao, Guang; Bennett, Dorothy C; Nevins, Joseph R; You, Lingchong

2010-09-21

The transition of the mammalian cell from quiescence to proliferation is a highly variable process. Over the last four decades, two lines of apparently contradictory, phenomenological models have been proposed to account for such temporal variability. These include various forms of the transition probability (TP) model and the growth control (GC) model, which lack mechanistic details. The GC model was further proposed as an alternative explanation for the concept of the restriction point, which we recently demonstrated as being controlled by a bistable Rb-E2F switch. Here, through a combination of modeling and experiments, we show that these different lines of models in essence reflect different aspects of stochastic dynamics in cell cycle entry. In particular, we show that the variable activation of E2F can be described by stochastic activation of the bistable Rb-E2F switch, which in turn may account for the temporal variability in cell cycle entry. Moreover, we show that temporal dynamics of E2F activation can be recast into the frameworks of both the TP model and the GC model via parameter mapping. This mapping suggests that the two lines of phenomenological models can be reconciled through the stochastic dynamics of the Rb-E2F switch. It also suggests a potential utility of the TP or GC models in defining concise, quantitative phenotypes of cell physiology. This may have implications in classifying cell types or states.

Activation of dioxygen by copper metalloproteins and insights from model complexes.

PubMed

Quist, David A; Diaz, Daniel E; Liu, Jeffrey J; Karlin, Kenneth D

2017-04-01

Nature uses dioxygen as a key oxidant in the transformation of biomolecules. Among the enzymes that are utilized for these reactions are copper-containing metalloenzymes, which are responsible for important biological functions such as the regulation of neurotransmitters, dioxygen transport, and cellular respiration. Enzymatic and model system studies work in tandem in order to gain an understanding of the fundamental reductive activation of dioxygen by copper complexes. This review covers the most recent advancements in the structures, spectroscopy, and reaction mechanisms for dioxygen-activating copper proteins and relevant synthetic models thereof. An emphasis has also been placed on cofactor biogenesis, a fundamentally important process whereby biomolecules are post-translationally modified by the pro-enzyme active site to generate cofactors which are essential for the catalytic enzymatic reaction. Significant questions remaining in copper-ion-mediated O 2 -activation in copper proteins are addressed.

A new simple dynamo model for solar activity cycle

NASA Astrophysics Data System (ADS)

Yokoi, Nobumitsu; Schmitt, Dieter

2015-04-01

The solar magnetic activity cycle has been investigated in an elaborated manner with several types of dynamo models [1]. In most of the current mean-field approaches, the inhomogeneity of the large-scale flow is treated as an essential ingredient in the mean magnetic field equation whereas it is completely neglected in the turbulence equation. In this work, a new simple model for the solar activity cycle is proposed. The present model differs from the previous ones mainly in two points. First, in addition to the helicity coefficient α, we consider a term related to the cross helicity, which represents the effect of the inhomogeneous mean flow, in the turbulent electromotive force [2, 3]. Second, this transport coefficient (γ) is not treated as an adjustable parameter, but the evolution equation for γ is simultaneously solved. The basic scenario for the solar activity cycle in this approach is as follows: The toroidal field is induced by the toroidal rotation in mediation by the turbulent cross helicity. Then due to the α or helicity effect, the poloidal field is generated from the toroidal field. The poloidal field induced by the α effect produces a turbulent cross helicity whose sign is opposite to the original one (negative cross-helicity production). The cross helicity with this opposite sign induces a reversed toroidal field. Results of the eigenvalue analysis of the model equations are shown, which confirm the above scenario. References [1] Charbonneau, Living Rev. Solar Phys. 7, 3 (2010). [2] Yoshizawa, A. Phys. Fluids B 2, 1589 (1990). [3] Yokoi, N. Geophys. Astrophys. Fluid Dyn. 107, 114 (2013).

Lessons learned from recent geomagnetic disturbance model validation activities

NASA Astrophysics Data System (ADS)

Pulkkinen, A. A.; Welling, D. T.

2017-12-01

Due to concerns pertaining to geomagnetically induced current impact on ground-based infrastructure, there has been significantly elevated interest in applying models for local geomagnetic disturbance or "delta-B" predictions. Correspondingly there has been elevated need for testing the quality of the delta-B predictions generated by the modern empirical and physics-based models. To address this need, community-wide activities were launched under the GEM Challenge framework and one culmination of the activities was the validation and selection of models that were transitioned into operations at NOAA SWPC. The community-wide delta-B action is continued under the CCMC-facilitated International Forum for Space Weather Capabilities Assessment and its "Ground Magnetic Perturbations: dBdt, delta-B, GICs, FACs" working group. The new delta-B working group builds on the past experiences and expands the collaborations to cover the entire international space weather community. In this paper, we discuss the key lessons learned from the past delta-B validation exercises and lay out the path forward for building on those experience under the new delta-B working group.

Active Learning to Understand Infectious Disease Models and Improve Policy Making

PubMed Central

Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-01-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings. PMID:24743387

Active learning to understand infectious disease models and improve policy making.

PubMed

Willem, Lander; Stijven, Sean; Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-04-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings.

Note on the coupled oscillator model solutions in crystalline optical activity

NASA Astrophysics Data System (ADS)

Vyšín, I.; Ríha, J.; Svácková, K.

2006-06-01

Many methods have been used in the crystalline optical activity solution, among them the traditional method of coupled oscillators. The two coupled oscillator model was first solved by Chandrasekhar, and the most general dispersion relations for the crystalline optical activity can be obtained from its next extensions. However, the Chandrasekhar solution method seems to be based on a mistake in the computations. For this reason, the solution of a more complicated model of coupled oscillators which better corresponds to the structure of real crystals using the Condon relations is presented. This solution leads to the conclusion that, although it is possible to object to the Chandrasekhar solution method, the form of his final dispersion relations is correct. On the other hand, the dispersion relations following from the solution of more complicated coupled oscillator models are more convenient for the interpretation of the crystalline optical activity experimental data, which is demonstrated in examples of crystals of tellurium and benzil.

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.

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...

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.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling

PubMed Central

Hagmann, Patric; Deco, Gustavo

2015-01-01

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model’s prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information. PMID:26317432

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.

A guide to modelling cardiac electrical activity in anatomically detailed ventricles.

PubMed

Clayton, R H; Panfilov, A V

2008-01-01

One of the most recent trends in cardiac electrophysiology is the development of integrative anatomically accurate models of the heart, which include description of cardiac activity from sub-cellular and cellular level to the level of the whole organ. In order to construct this type of model, a researcher needs to collect a wide range of information from books and journal articles on various aspects of biology, physiology, electrophysiology, numerical mathematics and computer programming. The aim of this methodological article is to survey recent developments in integrative modelling of electrical activity in the ventricles of the heart, and to provide a practical guide to the resources and tools that are available for work in this exciting and challenging area.

Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation.

PubMed

Aubert, Agnès; Costalat, Robert; Magistretti, Pierre J; Pellerin, Luc

2005-11-08

A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans.

Modeling of active transmembrane transport in a mixture theory framework.

PubMed

Ateshian, Gerard A; Morrison, Barclay; Hung, Clark T

2010-05-01

This study formulates governing equations for active transport across semi-permeable membranes within the framework of the theory of mixtures. In mixture theory, which models the interactions of any number of fluid and solid constituents, a supply term appears in the conservation of linear momentum to describe momentum exchanges among the constituents. In past applications, this momentum supply was used to model frictional interactions only, thereby describing passive transport processes. In this study, it is shown that active transport processes, which impart momentum to solutes or solvent, may also be incorporated in this term. By projecting the equation of conservation of linear momentum along the normal to the membrane, a jump condition is formulated for the mechano-electrochemical potential of fluid constituents which is generally applicable to nonequilibrium processes involving active transport. The resulting relations are simple and easy to use, and address an important need in the membrane transport literature.

Consistent radiative transfer modeling of active and passive observations of precipitation

NASA Astrophysics Data System (ADS)

Adams, Ian

2016-04-01

Spaceborne platforms such as the Tropical Rainfall Measurement Mission (TRMM) and the Global Precipitation Measurement (GPM) mission exploit a combination of active and passive sensors to provide a greater understanding of the three-dimensional structure of precipitation. While "operationalized" retrieval algorithms require fast forward models, the ability to perform higher fidelity simulations is necessary in order to understand the physics of remote sensing problems by testing assumptions and developing parameterizations for the fast models. To ensure proper synergy between active and passive modeling, forward models must be consistent when modeling the responses of radars and radiometers. This work presents a self-consistent transfer model for simulating radar reflectivities and millimeter wave brightness temperatures for precipitating scenes. To accomplish this, we extended the Atmospheric Radiative Transfer Simulator (ARTS) version 2.3 to solve the radiative transfer equation for active sensors and multiple scattering conditions. Early versions of ARTS (1.1) included a passive Monte Carlo solver, and ARTS is capable of handling atmospheres of up to three dimensions with ellipsoidal planetary geometries. The modular nature of ARTS facilitates extensibility, and the well-developed ray-tracing tools are suited for implementation of Monte Carlo algorithms. Finally, since ARTS handles the full Stokes vector, co- and cross-polarized reflectivity products are possible for scenarios that include nonspherical particles, with or without preferential alignment. The accuracy of the forward model will be demonstrated with precipitation events observed by TRMM and GPM, and the effects of multiple scattering will be detailed. The three-dimensional nature of the radiative transfer model will be useful for understanding the effects of nonuniform beamfill and multiple scattering for spatially heterogeneous precipitation events. The targets of this forward model are GPM (the

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

Activation of dioxygen by copper metalloproteins and insights from model complexes

PubMed Central

Quist, David A.; Diaz, Daniel E.; Liu, Jeffrey J.; Karlin, Kenneth D.

2017-01-01

Nature uses dioxygen as a key oxidant in the transformation of biomolecules. Among the enzymes that are utilized for these reactions are copper-containing met-alloenzymes, which are responsible for important biological functions such as the regulation of neurotransmitters, dioxygen transport, and cellular respiration. Enzymatic and model system studies work in tandem in order to gain an understanding of the fundamental reductive activation of dioxygen by copper complexes. This review covers the most recent advancements in the structures, spectroscopy, and reaction mechanisms for dioxygen-activating copper proteins and relevant synthetic models thereof. An emphasis has also been placed on cofactor biogenesis, a fundamentally important process whereby biomolecules are post-translationally modified by the pro-enzyme active site to generate cofactors which are essential for the catalytic enzymatic reaction. Significant questions remaining in copper-ion-mediated O2-activation in copper proteins are addressed. PMID:27921179

Automatic prediction of tongue muscle activations using a finite element model.

PubMed

Stavness, Ian; Lloyd, John E; Fels, Sidney

2012-11-15

Computational modeling has improved our understanding of how muscle forces are coordinated to generate movement in musculoskeletal systems. Muscular-hydrostat systems, such as the human tongue, involve very different biomechanics than musculoskeletal systems, and modeling efforts to date have been limited by the high computational complexity of representing continuum-mechanics. In this study, we developed a computationally efficient tracking-based algorithm for prediction of muscle activations during dynamic 3D finite element simulations. The formulation uses a local quadratic-programming problem at each simulation time-step to find a set of muscle activations that generated target deformations and movements in finite element muscular-hydrostat models. We applied the technique to a 3D finite element tongue model for protrusive and bending movements. Predicted muscle activations were consistent with experimental recordings of tongue strain and electromyography. Upward tongue bending was achieved by recruitment of the superior longitudinal sheath muscle, which is consistent with muscular-hydrostat theory. Lateral tongue bending, however, required recruitment of contralateral transverse and vertical muscles in addition to the ipsilateral margins of the superior longitudinal muscle, which is a new proposition for tongue muscle coordination. Our simulation framework provides a new computational tool for systematic analysis of muscle forces in continuum-mechanics models that is complementary to experimental data and shows promise for eliciting a deeper understanding of human tongue function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Solubility Prediction of Active Pharmaceutical Compounds with the UNIFAC Model

NASA Astrophysics Data System (ADS)

Nouar, Abderrahim; Benmessaoud, Ibtissem; Koutchoukali, Ouahiba; Koutchoukali, Mohamed Salah

2016-03-01

The crystallization from solution of an active pharmaceutical ingredient requires the knowledge of the solubility in the entire temperature range investigated during the process. However, during the development of a new active ingredient, these data are missing. Its experimental determination is possible, but tedious. UNIFAC Group contribution method Fredenslund et al. (Vapor-liquid equilibria using UNIFAC: a group contribution method, 1977; AIChE J 21:1086, 1975) can be used to predict this physical property. Several modifications on this model have been proposed since its development in 1977, modified UNIFAC of Dortmund Weidlich et al. (Ind Eng Chem Res 26:1372, 1987), Gmehling et al. (Ind Eng Chem Res 32:178, 1993), Pharma-modified UNIFAC Diedrichs et al. (Evaluation und Erweiterung thermodynamischer Modelle zur Vorhersage von Wirkstofflöslichkeiten, PhD Thesis, 2010), KT-UNIFAC Kang et al. (Ind Eng Chem Res 41:3260, 2002), ldots In this study, we used UNIFAC model by considering the linear temperature dependence of interaction parameters as in Pharma-modified UNIFAC and structural groups as defined by KT-UNIFAC first-order model. More than 100 binary datasets were involved in the estimation of interaction parameters. These new parameters were then used to calculate activity coefficient and solubility of some molecules in various solvents at different temperatures. The model gives better results than those from the original UNIFAC and shows good agreement between the experimental solubility and the calculated one.

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.

Interactive modeling activities in the classroom—rotational motion and smartphone gyroscopes

NASA Astrophysics Data System (ADS)

Pörn, Ray; Braskén, Mats

2016-11-01

The wide-spread availability of smartphones makes them a valuable addition to the measurement equipment in both the physics classroom and the instructional laboratory, encouraging an active interaction between measurements and modeling activities. In this paper we illustrate this interaction by making use of the internal gyroscope of a smartphone to study and measure the rotational dynamics of objects rotating about a fixed axis. The workflow described in this paper has been tested in a classroom setting and found to encourage an exploratory approach to both data collecting and modeling.

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

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

Lackmann, Gary

2013-06-10

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured withmore » sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

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.

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.

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

Validation of a "Kane's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Beech, Geoffrey S.; Hampton, R. David

2000-01-01

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller, ARIS provides the ISS response to the first requirement. In November 1999, the authors presented a response to the second ("A 'Kane's Dynamics' model for the Active Rack Isolation System", Hampton and Beech) intended to facilitate an optimal-controls approach to the third. This paper documents the validation of that high-fidelity dynamic model of ARIS. As before, this model contains the full actuator dynamics, however, the umbilical models are not included in this presentation. The validation of this dynamics model was achieved by utilizing two Commercial Off the Shelf (COTS) software tools: Deneb's ENVISION, and Online Dynamics' AUTOLEV. ENVISION is a robotics software package developed for the automotive industry that employs 3-dimensional (3-D) Computer Aided Design (CAD) models to facilitate both forward and inverse kinematics analyses. AUTOLEV is a DOS based interpreter that is designed in general to solve vector based mathematical problems and specifically to solve Dynamics problems using Kane's method.

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.

A Common Core for Active Conceptual Modeling for Learning from Surprises

NASA Astrophysics Data System (ADS)

Liddle, Stephen W.; Embley, David W.

The new field of active conceptual modeling for learning from surprises (ACM-L) may be helpful in preserving life, protecting property, and improving quality of life. The conceptual modeling community has developed sound theory and practices for conceptual modeling that, if properly applied, could help analysts model and predict more accurately. In particular, we need to associate more semantics with links, and we need fully reified high-level objects and relationships that have a clear, formal underlying semantics that follows a natural, ontological approach. We also need to capture more dynamic aspects in our conceptual models to more accurately model complex, dynamic systems. These concepts already exist, and the theory is well developed; what remains is to link them with the ideas needed to predict system evolution, thus enabling risk assessment and response planning. No single researcher or research group will be able to achieve this ambitious vision alone. As a starting point, we recommend that the nascent ACM-L community agree on a common core model that supports all aspects—static and dynamic—needed for active conceptual modeling in support of learning from surprises. A common core will more likely gain the traction needed to sustain the extended ACM-L research effort that will yield the advertised benefits of learning from surprises.

Analysis of creative mathematical thinking ability by using model eliciting activities (MEAs)

NASA Astrophysics Data System (ADS)

Winda, A.; Sufyani, P.; Elah, N.

2018-05-01

Lack of creative mathematical thinking ability can lead to not accustomed with open ended problem. Students’ creative mathematical thinking ability in the first grade at one of junior high school in Tangerang City is not fully developed. The reason of students’ creative mathematical thinking ability is not optimally developed is so related with learning process which has done by the mathematics teacher, maybe the learning design that teacher use is unsuitable for increasing students’ activity in the learning process. This research objective is to see the differences in students’ ways of answering the problems in terms of students’ creative mathematical thinking ability during the implementation of Model Eliciting Activities (MEAs). This research use post-test experimental class design. The indicators for creative mathematical thinking ability in this research arranged in three parts, as follow: (1) Fluency to answer the problems; (2) Flexibility to solve the problems; (3) Originality of answers. The result of this research found that by using the same learning model and same instrument from Model Eliciting Activities (MEAs) there are some differences in the way students answer the problems and Model Eliciting Activities (MEAs) can be one of approach used to increase students’ creative mathematical thinking ability.

Using an agent-based model to simulate children's active travel to school.

PubMed

Yang, Yong; Diez-Roux, Ana V

2013-05-26

Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children's active travel to school. An agent-based model was developed to simulate children's school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school.

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

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

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

Temperature modelling and prediction for activated sludge systems.

PubMed

Lippi, S; Rosso, D; Lubello, C; Canziani, R; Stenstrom, M K

2009-01-01

Temperature is an important factor affecting biomass activity, which is critical to maintain efficient biological wastewater treatment, and also physiochemical properties of mixed liquor as dissolved oxygen saturation and settling velocity. Controlling temperature is not normally possible for treatment systems but incorporating factors impacting temperature in the design process, such as aeration system, surface to volume ratio, and tank geometry can reduce the range of temperature extremes and improve the overall process performance. Determining how much these design or up-grade options affect the tank temperature requires a temperature model that can be used with existing design methodologies. This paper presents a new steady state temperature model developed by incorporating the best aspects of previously published models, introducing new functions for selected heat exchange paths and improving the method for predicting the effects of covering aeration tanks. Numerical improvements with embedded reference data provide simpler formulation, faster execution, easier sensitivity analyses, using an ordinary spreadsheet. The paper presents several cases to validate the model.

Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation

PubMed Central

Aubert, Agnès; Costalat, Robert; Magistretti, Pierre J.; Pellerin, Luc

2005-01-01

A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans. PMID:16260743

A NEW SIMPLE DYNAMO MODEL FOR STELLAR ACTIVITY CYCLE

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

Yokoi, N.; Hamba, F.; Schmitt, D.

2016-06-20

A new simple dynamo model for stellar activity cycle is proposed. By considering an inhomogeneous flow effect on turbulence, it is shown that turbulent cross helicity (velocity–magnetic-field correlation) enters the expression of turbulent electromotive force as the coupling coefficient for the mean absolute vorticity. This makes the present model different from the current α –Ω-type models in two main ways. First, in addition to the usual helicity ( α ) and turbulent magnetic diffusivity ( β ) effects, we consider the cross-helicity effect as a key ingredient of the dynamo process. Second, the spatiotemporal evolution of cross helicity is solvedmore » simultaneously with the mean magnetic fields. The basic scenario is as follows. In the presence of turbulent cross helicity, the toroidal field is induced by the toroidal rotation. Then, as in usual models, the α effect generates the poloidal field from the toroidal one. This induced poloidal field produces a turbulent cross helicity whose sign is opposite to the original one (negative production). With this cross helicity of the reversed sign, a reversal in field configuration starts. Eigenvalue analyses of the simplest possible model give a butterfly diagram, which confirms the above scenario and the equatorward migrations, the phase relationship between the cross helicity and magnetic fields. These results suggest that the oscillation of the turbulent cross helicity is a key for the activity cycle. The reversal of the cross helicity is not the result of the magnetic-field reversal, but the cause of the latter. This new model is expected to open up the possibility of the mean-field or turbulence closure dynamo approaches.« less

Waste production and regional growth of marine activities an econometric model.

PubMed

Bramati, Maria Caterina

2016-11-15

Coastal regions are characterized by intense human activity and climatic pressures, often intensified by competing interests in the use of marine waters. To assess the effect of public spending on the regional economy, an econometric model is here proposed. Not only are the regional investment and the climatic risks included in the model, but also variables related to the anthropogenic pressure, such as population, economic activities and waste production. Feedback effects of economic and demographic expansion on the pollution of coastal areas are also considered. It is found that dangerous waste increases with growing shipping and transportation activities and with growing population density in non-touristic coastal areas. On the other hand, the amount of non-dangerous wastes increases with marine mining, defense and offshore energy production activities. However, lower waste production occurs in areas where aquaculture and touristic industry are more exploited, and accompanied by increasing regional investment in waste disposal. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical Modeling of Flow through Phloem Considering Active Loading

NASA Astrophysics Data System (ADS)

Liu, Jin; Sze, Tsun-Kay Jackie; Dutta, Prashanta

2013-11-01

Transport through phloem is of significant interest in engineering applications including self-powered microfluidic pumps. We present a phloem model, combining protein level mechanics with cellular level fluid transport. Fluid flow and sucrose transport through a petiole sieve tube are simulated using the Nernst-Planck, Navier-Stokes, and continuity equations. Governing equations are solved using the finite volume method with dynamically calculated boundary conditions. Sieve tube cell structure consisting of sieve plates is included in a two dimensional model by computational cell blocking. Sucrose transport is incorporated as a boundary condition through a six-state model, bringing in active loading mechanisms with consideration of physical plant properties. The effects of reaction rates and leaf sucrose concentration are investigated to understand the transport mechanism in petiole sieve tubes. Numerical results show that increasing forward reactions of the proton sucrose transporter significantly promotes the pumping ability. A lower leaf sieve sucrose concentration results in a lower wall inflow velocity, but yields a higher inflow of water due to the active loading mechanism. The overall effect is higher outflow velocity for lower leaf sieve sucrose concentration because the increase in inflow velocity outweighs wall velocity. This new phloem model provides new insights on mechanisms potentially useful for fluidic pumping in self-powered microfluidic pumps. This work is supported in part by the National Science Fundation grant CBET-1250107.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Inactivated Orf virus (Parapoxvirus ovis) elicits antifibrotic activity in models of liver fibrosis.

PubMed

Nowatzky, Janina; Knorr, Andreas; Hirth-Dietrich, Claudia; Siegling, Angela; Volk, Hans-Dieter; Limmer, Andreas; Knolle, Percy; Weber, Olaf

2013-05-01

Inactivated Orf virus (ORFV, Parapoxvirus ovis) demonstrates strong antiviral activity in animal models including a human hepatitis B virus (HBV)-transgenic mouse. In addition, expression of interferon (IFN)-γ and interleukin-10 (IL-10) was induced after administration of inactivated ORFV in these mice. IFN-γ and IL-10 are known to elicit antifibrotic activity. We therefore aimed to study antifibrotic activity of inactivated ORFV in models of liver fibrosis. We characterized ORFV-induced hepatic cytokine expression in rats. We then studied ORFV in two models of liver fibrosis in rats, pig serum-induced liver fibrosis and carbon tetrachloride (CCL4 )-induced liver fibrosis. ORFV induced hepatic expression of IFN-γ and IL-10 in rats. ORFV mediated antifibrotic activity when administrated concomitantly with the fibrosis-inducing agents in both models of liver fibrosis. Importantly, when CCL4 -induced liver fibrosis was already established, ORFV application still showed significant antifibrotic activity. In addition, we were able to demonstrate a direct antifibrotic effect of ORFV on stellate cells. These results establish a potential novel antifibrotic therapeutic approach that not only prevents but also resolves established liver fibrosis. Further studies are required to unravel the details of the mechanisms involved. © 2012 The Japan Society of Hepatology.

Neighborhood Design, Physical Activity, and Wellbeing: Applying the Walkability Model

PubMed Central

Zuniga-Teran, Adriana A.; Orr, Barron J.; Gimblett, Randy H.; Chalfoun, Nader V.; Guertin, David P.; Marsh, Stuart E.

2017-01-01

Neighborhood design affects lifestyle physical activity, and ultimately human wellbeing. There are, however, a limited number of studies that examine neighborhood design types. In this research, we examine four types of neighborhood designs: traditional development, suburban development, enclosed community, and cluster housing development, and assess their level of walkability and their effects on physical activity and wellbeing. We examine significant associations through a questionnaire (n = 486) distributed in Tucson, Arizona using the Walkability Model. Among the tested neighborhood design types, traditional development showed significant associations and the highest value for walkability, as well as for each of the two types of walking (recreation and transportation) representing physical activity. Suburban development showed significant associations and the highest mean values for mental health and wellbeing. Cluster housing showed significant associations and the highest mean value for social interactions with neighbors and for perceived safety from crime. Enclosed community did not obtain the highest means for any wellbeing benefit. The Walkability Model proved useful in identifying the walkability categories associated with physical activity and perceived crime. For example, the experience category was strongly and inversely associated with perceived crime. This study provides empirical evidence of the importance of including vegetation, particularly trees, throughout neighborhoods in order to increase physical activity and wellbeing. Likewise, the results suggest that regular maintenance is an important strategy to improve mental health and overall wellbeing in cities. PMID:28098785

Neighborhood Design, Physical Activity, and Wellbeing: Applying the Walkability Model.

PubMed

Zuniga-Teran, Adriana A; Orr, Barron J; Gimblett, Randy H; Chalfoun, Nader V; Guertin, David P; Marsh, Stuart E

2017-01-13

Neighborhood design affects lifestyle physical activity, and ultimately human wellbeing. There are, however, a limited number of studies that examine neighborhood design types. In this research, we examine four types of neighborhood designs: traditional development, suburban development, enclosed community, and cluster housing development, and assess their level of walkability and their effects on physical activity and wellbeing. We examine significant associations through a questionnaire ( n = 486) distributed in Tucson, Arizona using the Walkability Model. Among the tested neighborhood design types, traditional development showed significant associations and the highest value for walkability, as well as for each of the two types of walking (recreation and transportation) representing physical activity. Suburban development showed significant associations and the highest mean values for mental health and wellbeing. Cluster housing showed significant associations and the highest mean value for social interactions with neighbors and for perceived safety from crime. Enclosed community did not obtain the highest means for any wellbeing benefit. The Walkability Model proved useful in identifying the walkability categories associated with physical activity and perceived crime. For example, the experience category was strongly and inversely associated with perceived crime. This study provides empirical evidence of the importance of including vegetation, particularly trees, throughout neighborhoods in order to increase physical activity and wellbeing. Likewise, the results suggest that regular maintenance is an important strategy to improve mental health and overall wellbeing in cities.

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.

GEM1: First-year modeling and IT activities for the Global Earthquake Model

NASA Astrophysics Data System (ADS)

Anderson, G.; Giardini, D.; Wiemer, S.

2009-04-01

GEM is a public-private partnership initiated by the Organisation for Economic Cooperation and Development (OECD) to build an independent standard for modeling and communicating earthquake risk worldwide. GEM is aimed at providing authoritative, open information about seismic risk and decision tools to support mitigation. GEM will also raise risk awareness and help post-disaster economic development, with the ultimate goal of reducing the toll of future earthquakes. GEM will provide a unified set of seismic hazard, risk, and loss modeling tools based on a common global IT infrastructure and consensus standards. These tools, systems, and standards will be developed in partnership with organizations around the world, with coordination by the GEM Secretariat and its Secretary General. GEM partners will develop a variety of global components, including a unified earthquake catalog, fault database, and ground motion prediction equations. To ensure broad representation and community acceptance, GEM will include local knowledge in all modeling activities, incorporate existing detailed models where possible, and independently test all resulting tools and models. When completed in five years, GEM will have a versatile, penly accessible modeling environment that can be updated as necessary, and will provide the global standard for seismic hazard, risk, and loss models to government ministers, scientists and engineers, financial institutions, and the public worldwide. GEM is now underway with key support provided by private sponsors (Munich Reinsurance Company, Zurich Financial Services, AIR Worldwide Corporation, and Willis Group Holdings); countries including Belgium, Germany, Italy, Singapore, Switzerland, and Turkey; and groups such as the European Commission. The GEM Secretariat has been selected by the OECD and will be hosted at the Eucentre at the University of Pavia in Italy; the Secretariat is now formalizing the creation of the GEM Foundation. Some of GEM's global

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.

Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

PubMed

Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

2015-11-01

Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational

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.

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

[Educational model to develop trustworthy professional activities].

PubMed

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

2015-01-01

The reorganization of the national health system (SNS), enforces reflection and transformation on medical education in clinical contexts. The study presents an educational model to develop entrusted professionals activities (MEDAPROC) to train human resources in health with reliable knowledge, skills and attitudes to work in the shifting scenario of the SNS. The paper discusses international and national documents on skills in medicine. Based on the analysis of 8 domains, 50 skills and 13 entrusted professional activities (RPA) proposed by the Association of the American Medical College (AAMC) we propose a curriculum design, with the example of the undergraduate program of Gynecology and Obstetrics, with the intention to advance to internship and residency in a continuum that marks milestones and clinical practices. The pedagogical design of MEDAPROC was developed within three areas: 1) proposal of the AAMC; 2) curricular content of programs in pre and postgraduate education 3) organization of the daily agenda with academic mechanisms to develop the competencies, cover program items and develop clinical practice in deliberate learning activities, as well as milestones. The MEDAPROC offers versatility, student mobility and curricular flexibility in a system planed by academic units in diverse clinical settings.

[MEDICAL SOCIAL MODELING TECHNOLOGIES FOR ACTIVE AGING IN KAZAKHSTAN].

PubMed

Benberin, V V; Akhetov, A A; Tanbaeva, G Z

2015-01-01

The article discusses a new model for active ageing in Republic of Kazakhstan with participation the state, population and medical social services. Achieving active longevity will lead to positive trends in the development of human capital of the state, because it enables to use experience and knowledge of senior generation in enhancing the effectiveness of socio-economic transformation in health care. The study was carried out on the base of the Central clinical hospital of the President's affairs administration in Republic of Kazakhstan, with the participation of 147 admitted patients of elderly and senile age.

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

A model for promoting physical activity among rural South African adolescent girls

PubMed Central

Kinsman, John; Norris, Shane A.; Kahn, Kathleen; Twine, Rhian; Riggle, Kari; Edin, Kerstin; Mathebula, Jennifer; Ngobeni, Sizzy; Monareng, Nester; Micklesfield, Lisa K.

2015-01-01

Background In South Africa, the expanding epidemic of non-communicable diseases is partly fuelled by high levels of physical inactivity and sedentary behaviour. Women especially are at high risk, and interventions promoting physical activity are urgently needed for girls in their adolescence, as this is the time when many girls adopt unhealthy lifestyles. Objective This qualitative study aimed to identify and describe facilitating factors and barriers that are associated with physical activity among adolescent girls in rural, north-eastern South Africa and, based on these, to develop a model for promoting leisure-time physical activity within this population. Design The study was conducted in and around three secondary schools. Six focus group discussions were conducted with adolescent girls from the schools, and seven qualitative interviews were held with sports teachers and youth leaders. The data were subjected to thematic analysis. Results Seven thematic areas were identified, each of which was associated with the girls’ self-reported levels of physical activity. The thematic areas are 1) poverty, 2) body image ideals, 3) gender, 4) parents and home life, 5) demographic factors, 6) perceived health effects of physical activity, and 7) human and infrastructural resources. More barriers to physical activity were reported than facilitating factors. Conclusions Analysis of the barriers found in the different themes indicated potential remedial actions that could be taken, and these were synthesised into a model for promoting physical activity among South African adolescent girls in resource-poor environments. The model presents a series of action points, seen both from the ‘supply-side’ perspective (such as the provision of resources and training for the individuals, schools, and organisations which facilitate the activities) and from the ‘demand-side’ perspective (such as the development of empowering messages about body image for teenage girls, and

Self-Observation Model Employing an Instinctive Interface for Classroom Active Learning

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Nurkhamid; Wang, Chin-Yeh; Yang, Shu-Han; Chao, Po-Yao

2014-01-01

In a classroom, obtaining active, whole-focused, and engaging learning results from a design is often difficult. In this study, we propose a self-observation model that employs an instinctive interface for classroom active learning. Students can communicate with virtual avatars in the vertical screen and can react naturally according to the…

Accelerometry-based classification of human activities using Markov modeling.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2011-01-01

Accelerometers are a popular choice as body-motion sensors: the reason is partly in their capability of extracting information that is useful for automatically inferring the physical activity in which the human subject is involved, beside their role in feeding biomechanical parameters estimators. Automatic classification of human physical activities is highly attractive for pervasive computing systems, whereas contextual awareness may ease the human-machine interaction, and in biomedicine, whereas wearable sensor systems are proposed for long-term monitoring. This paper is concerned with the machine learning algorithms needed to perform the classification task. Hidden Markov Model (HMM) classifiers are studied by contrasting them with Gaussian Mixture Model (GMM) classifiers. HMMs incorporate the statistical information available on movement dynamics into the classification process, without discarding the time history of previous outcomes as GMMs do. An example of the benefits of the obtained statistical leverage is illustrated and discussed by analyzing two datasets of accelerometer time series.

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.

Fast and exact Newton and Bidirectional fitting of Active Appearance Models.

PubMed

Kossaifi, Jean; Tzimiropoulos, Yorgos; Pantic, Maja

2016-12-21

Active Appearance Models (AAMs) are generative models of shape and appearance that have proven very attractive for their ability to handle wide changes in illumination, pose and occlusion when trained in the wild, while not requiring large training dataset like regression-based or deep learning methods. The problem of fitting an AAM is usually formulated as a non-linear least squares one and the main way of solving it is a standard Gauss-Newton algorithm. In this paper we extend Active Appearance Models in two ways: we first extend the Gauss-Newton framework by formulating a bidirectional fitting method that deforms both the image and the template to fit a new instance. We then formulate a second order method by deriving an efficient Newton method for AAMs fitting. We derive both methods in a unified framework for two types of Active Appearance Models, holistic and part-based, and additionally show how to exploit the structure in the problem to derive fast yet exact solutions. We perform a thorough evaluation of all algorithms on three challenging and recently annotated inthe- wild datasets, and investigate fitting accuracy, convergence properties and the influence of noise in the initialisation. We compare our proposed methods to other algorithms and show that they yield state-of-the-art results, out-performing other methods while having superior convergence properties.

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.

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.

Activity-induced clustering in model dumbbell swimmers: the role of hydrodynamic interactions.

PubMed

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

Activity-induced clustering in model dumbbell swimmers: The role of hydrodynamic interactions

NASA Astrophysics Data System (ADS)

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E.

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

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

Benchmarking in pathology: development of an activity-based costing model.

PubMed

Burnett, Leslie; Wilson, Roger; Pfeffer, Sally; Lowry, John

2012-12-01

Benchmarking in Pathology (BiP) allows pathology laboratories to determine the unit cost of all laboratory tests and procedures, and also provides organisational productivity indices allowing comparisons of performance with other BiP participants. We describe 14 years of progressive enhancement to a BiP program, including the implementation of 'avoidable costs' as the accounting basis for allocation of costs rather than previous approaches using 'total costs'. A hierarchical tree-structured activity-based costing model distributes 'avoidable costs' attributable to the pathology activities component of a pathology laboratory operation. The hierarchical tree model permits costs to be allocated across multiple laboratory sites and organisational structures. This has enabled benchmarking on a number of levels, including test profiles and non-testing related workload activities. The development of methods for dealing with variable cost inputs, allocation of indirect costs using imputation techniques, panels of tests, and blood-bank record keeping, have been successfully integrated into the costing model. A variety of laboratory management reports are produced, including the 'cost per test' of each pathology 'test' output. Benchmarking comparisons may be undertaken at any and all of the 'cost per test' and 'cost per Benchmarking Complexity Unit' level, 'discipline/department' (sub-specialty) level, or overall laboratory/site and organisational levels. We have completed development of a national BiP program. An activity-based costing methodology based on avoidable costs overcomes many problems of previous benchmarking studies based on total costs. The use of benchmarking complexity adjustment permits correction for varying test-mix and diagnostic complexity between laboratories. Use of iterative communication strategies with program participants can overcome many obstacles and lead to innovations.

Modeling the Commuting Travel Activities within Historic Districts in Chinese Cities

PubMed Central

Yin, Fengjun; Hu, Qizhou

2014-01-01

The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well. PMID:25435864

Modeling the commuting travel activities within historic districts in Chinese cities.

PubMed

Ye, Mao; Yu, Miao; Li, Zhibin; Yin, Fengjun; Hu, Qizhou

2014-01-01

The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well.

Kinetic study of solid waste pyrolysis using distributed activation energy model.

PubMed

Bhavanam, Anjireddy; Sastry, R C

2015-02-01

The pyrolysis characteristics of municipal solid waste, agricultural residues such as ground nut shell, cotton husk and their blends are investigated using non-isothermal thermogravimetric analysis (TGA) with in a temperature range of 30-900 °C at different heating rates of 10 °C, 30 °C and 50 °C/min in inert atmosphere. From the thermograms obtained from TGA, it is observed that the maximum rate of degradation occurred in the second stage of the pyrolysis process for all the solid wastes. The distributed activation energy model (DAEM) is used to study the pyrolysis kinetics of the solid wastes. The kinetic parameters E (activation energy), k0 (frequency factor) are calculated from this model. It is found that the range of activation energies for agricultural residues are lower than the municipal solid waste. The activation energies for the municipal solid waste pyrolysis process drastically decreased with addition of agricultural residues. The proposed DAEM is successfully validated with TGA experimental data. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

A GIS based model for active transportation in the built environment

NASA Astrophysics Data System (ADS)

Addison, Veronica Marie Medina

Obesity and physical inactivity have been major risk factors associated with morbidity and mortality in the United States. Recently, obesity and physical inactivity have been on the rise. Determining connections between this trend and the environment could lead to a built environment that is conducive to healthy, active people. In my previous research, I have studied the built environment and its connection to health. For my dissertation, I build on this fundamental work by incorporating energy, specifically by studying the built environment and its connection to energy expenditures. This research models the built environment and combines this with human energy expenditure information in order to provide a planning tool that allows an individual to actively address health issues, particularly obesity. This research focuses on the design and development of an internet based model that enables individuals to understand their own energy expenditures in relation to their environment. The model will work to find the energy consumed by an individual in their navigation through campus. This is accomplished by using Geographic Information Systems (GIS) to model the campus and using it as the basis for calculating energy expended through active transportation. Using GIS to create the model allows for the incorporation of built environment factors such as elevation and energy expenditures in relation to physical exertion rate. This research will contribute to the long-term solution to the obesity epidemic by creating healthy communities through smart growth and sustainable design. This research provides users with a tool to use in their current environment for their personal and community well being.

A "Kanes's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Hampton, R. David; Beech, Geoffrey

1999-01-01

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state-space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop an state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

A "Kane's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Beech, G. S.; Rao, N. N. S.; Rupert, J. K.; Kim, Y. K.

2001-01-01

Many microgravity space science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (International Standard Payload Rack (ISPR)) level. Effective model-based vibration isolation requires: (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop a state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

Modeling Hydrothermal Activity on Enceladus

NASA Astrophysics Data System (ADS)

Stamper, T., Jr.; Farough, A.

2017-12-01

Cassini's mass spectrometer data and gravitational field measurements imply water-rock interactions around the porous core of Enceladus. Using such data we characterize global heat and fluid transport properties of the core and model the ongoing hydrothermal activity on Enceladus. We assume that within the global ocean beneath the surface ice, seawater percolates downward into the core where it is heated and rises to the oceanfloor where it emanates in the form of diffuse discharge. We utilize the data from Hsu et al., [2015] with models of diffuse flow in seafloor hydrothermal systems by Lowell et al., [2015] to characterize the global heat transport properties of the Enceladus's core. Based on direct observations the gravitational acceleration (g) is calculated 0.123 m s-2. We assume fluid's density (ρ) is 10­3 kg m-3 and the specific heat of the fluid (cf) is 4000 Jkg-1 °C-1. From these values effective thermal diffusivity (a*) is calculated as 10­-6 m2 s-1. We also assume the coefficient of thermal expansion of fluid (αf) and the kinematic viscosity of fluid (ν) to be 10-4 °C-1 and 10­-6 m2 s-1 respectively. The estimated Rayleigh number (Ra) ranges between 0.11-2468.0, for core porosity (φ) of 5-15%, permeability (k) between 10-12-10-8 m2 and temperature between 90-200 °C and the depth of fluid circulation of 100 m. High values of Rayleigh number, cause vigorous convection within the core of Enceladus. Numerical modeling of reactive transport in multicomponent, multiphase systems is required to obtain a full understanding of the characteristics and evolution of the hydrothermal system on Enceladus, but simple scaling laws can provide insight into the physics of water-rock interactions.

Development of a simulation model of semi-active suspension for monorail

NASA Astrophysics Data System (ADS)

Hasnan, K.; Didane, D. H.; Kamarudin, M. A.; Bakhsh, Qadir; Abdulmalik, R. E.

2016-11-01

The new Kuala Lumpur Monorail Fleet Expansion Project (KLMFEP) uses semiactive technology in its suspension system. It is recognized that the suspension system influences the ride quality. Thus, among the way to further improve the ride quality is by fine- tuning the semi-active suspension system on the new KL Monorail. The semi-active suspension for the monorail specifically in terms of improving ride quality could be exploited further. Hence a simulation model which will act as a platform to test the design of a complete suspension system particularly to investigate the ride comfort performance is required. MSC Adams software was considered as the tool to develop the simulation platform, where all parameters and data are represented by mathematical equations; whereas the new KL Monorail being the reference model. In the simulation, the model went through step disturbance on the guideway for stability and ride comfort analysis. The model has shown positive results where the monorail is in stable condition as an outcome from stability analysis. The model also scores a Rating 1 classification in ISO 2631 Ride Comfort performance which is very comfortable as an overall outcome from ride comfort analysis. The model is also adjustable, flexibile and understandable by the engineers within the field for the purpose of further development.

Construction and analysis of a modular model of caspase activation in apoptosis

PubMed Central

Harrington, Heather A; Ho, Kenneth L; Ghosh, Samik; Tung, KC

2008-01-01

Background A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic) and intracellular (intrinsic) signals. The extrinsic and intrinsic pathways are characterized by the formation of the death-inducing signaling complex (DISC) and the apoptosome, respectively; both the DISC and the apoptosome are oligomers with complex formation dynamics. Additionally, the extrinsic and intrinsic pathways are coupled through the mitochondrial apoptosis-induced channel via the Bcl-2 family of proteins. Results A model of caspase activation is constructed and analyzed. The apoptosis signaling network is simplified through modularization methodologies and equilibrium abstractions for three functional modules. The mathematical model is composed of a system of ordinary differential equations which is numerically solved. Multiple linear regression analysis investigates the role of each module and reduced models are constructed to identify key contributions of the extrinsic and intrinsic pathways in triggering apoptosis for different cell lines. Conclusion Through linear regression techniques, we identified the feedbacks, dissociation of complexes, and negative regulators as the key components in apoptosis. The analysis and reduced models for our model formulation reveal that the chosen cell lines predominately exhibit strong extrinsic caspase, typical of type I cell, behavior. Furthermore, under the simplified model framework, the selected cells lines exhibit different modes by which caspase activation may occur. Finally the proposed modularized model of apoptosis may generalize behavior for additional cells and tissues, specifically identifying and predicting components responsible for the transition from type I to type II cell behavior. PMID:19077196

Modeling of Word Translation: Activation Flow from Concepts to Lexical Items

ERIC Educational Resources Information Center

Roelofs, Ardi; Dijkstra, Ton; Gerakaki, Svetlana

2013-01-01

Whereas most theoretical and computational models assume a continuous flow of activation from concepts to lexical items in spoken word production, one prominent model assumes that the mapping of concepts onto words happens in a discrete fashion (Bloem & La Heij, 2003). Semantic facilitation of context pictures on word translation has been taken to…

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

PubMed Central

Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

A modified active appearance model based on an adaptive artificial bee colony.

PubMed

Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

Modeling Secondary Organic Aerosols over Europe: Impact of Activity Coefficients and Viscosity

NASA Astrophysics Data System (ADS)

Kim, Y.; Sartelet, K.; Couvidat, F.

2014-12-01

Semi-volatile organic species (SVOC) can condense on suspended particulate materials (PM) in the atmosphere. The modeling of condensation/evaporation of SVOC often assumes that gas-phase and particle-phase concentrations are at equilibrium. However, recent studies show that secondary organic aerosols (SOA) may not be accurately represented by an equilibrium approach between the gas and particle phases, because organic aerosols in the particle phase may be very viscous. The condensation in the viscous liquid phase is limited by the diffusion from the surface of PM to its core. Using a surrogate approach to represent SVOC, depending on the user's choice, the secondary organic aerosol processor (SOAP) may assume equilibrium or model dynamically the condensation/evaporation between the gas and particle phases to take into account the viscosity of organic aerosols. The model is implemented in the three-dimensional chemistry-transport model of POLYPHEMUS. In SOAP, activity coefficients for organic mixtures can be computed using UNIFAC for short-range interactions between molecules and AIOMFAC to also take into account the effect of inorganic species on activity coefficients. Simulations over Europe are performed and POLYPHEMUS/SOAP is compared to POLYPHEMUS/H2O, which was previously used to model SOA using the equilibrium approach with activity coefficients from UNIFAC. Impacts of the dynamic approach on modeling SOA over Europe are evaluated. The concentrations of SOA using the dynamic approach are compared with those using the equilibrium approach. The increase of computational cost is also evaluated.

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

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.

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 Criminal Activity in Urban Landscapes

NASA Astrophysics Data System (ADS)

Brantingham, Patricia; Glässer, Uwe; Jackson, Piper; Vajihollahi, Mona

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

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…

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…

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…

ABO/Rh Blood-Typing Model: A Problem-Solving Activity

ERIC Educational Resources Information Center

Wake, Carol

2005-01-01

An ARO/Rh Blood-Typing kit useful for students to visualize blood-typing activities and practice problem-solving skills with transfusion reactions is presented. The model also enables students to identify relationships between A, B, and Rh antigens and antibodies in blood and to understand molecular mechanisms involved in transfusion agglutination…

Active magnetic bearing control loop modeling for a finite element rotordynamics code

NASA Technical Reports Server (NTRS)

Genta, Giancarlo; Delprete, Cristiana; Carabelli, Stefano

1994-01-01

A mathematical model of an active electromagnetic bearing which includes the actuator, the sensor and the control system is developed and implemented in a specialized finite element code for rotordynamic analysis. The element formulation and its incorporation in the model of the machine are described in detail. A solution procedure, based on a modal approach in which the number of retained modes is controlled by the user, is then shown together with other procedures for computing the steady-state response to both static and unbalance forces. An example of application shows the numerical results obtained on a model of an electric motor suspended on a five active-axis magnetic suspension. The comparison of some of these results with the experimental characteristics of the actual system shows the ability of the present model to predict its performance.

Pharmacokinetics and Toxicology of a Fibroblast Activation Protein (FAP)-activated Prodrug in Murine Xenograft Models of Human Cancer

PubMed Central

Brennen, W. Nathaniel; Rosen, D. Marc; Chaux, Alcides; Netto, George J.; Isaacs, John T.; Denmeade, Samuel R.

2014-01-01

Background As carcinoma progresses, the stroma undergoes a variety of phenotypic changes, including the presence of carcinoma-associated fibroblasts (CAFs) that express fibroblast activation protein (FAP). FAP is a post-prolyl endopeptidase whose expression in a healthy adult is largely restricted to the cancer-associated stroma. FAP-targeted prodrugs with a 100-fold greater therapeutic window over the parent compound were previously generated. Methods Prodrugs and non-cleavable controls were incubated in the presence of FAP. Plasma and tumor half-lives (t1/2) of the full-length and active forms of the prodrugs were determined using LCMS. Biodistribution studies of prodrug activation were performed. Histopathological analysis of tissues from treated animals were compared to vehicle-treated controls. Toxicity and efficacy studies were performed in human breast (MDA-MB-231 and MCF-7) and prostate (LNCaP) cancer xenografts models. Results These FAP-activated prodrugs have a significantly slower clearance from tumor tissue than the circulation (~12 vs. ~4.5 hrs). Micromolar concentrations of active drug persist in the tumor. Active drug is detected in non-target tissues; however, histopathologic evaluation reveals no evidence of drug-induced toxicity. A FAP-activated prodrug (ERGETGP-S12ADT) inhibits tumor growth in multiple human breast and prostate cancer xenograft models. The anti-tumor effect is comparable to that observed with docetaxel, but results in significantly less toxicity. Conclusion FAP-activated prodrugs are a viable strategy for the management of prostate and other cancers. These prodrugs exhibit less toxicity than a commonly used chemotherapeutic agent. Further refinement of the FAP cleavage site for greater specificity may reduce prodrug activation in non-target tissues and enhance clinical benefit. PMID:25053236

Pharmacokinetics and toxicology of a fibroblast activation protein (FAP)-activated prodrug in murine xenograft models of human cancer.

PubMed

Brennen, W Nathaniel; Rosen, D Marc; Chaux, Alcides; Netto, George J; Isaacs, John T; Denmeade, Samuel R

2014-09-01

As carcinoma progresses, the stroma undergoes a variety of phenotypic changes, including the presence of carcinoma-associated fibroblasts (CAFs) that express fibroblast activation protein (FAP). FAP is a post-prolyl endopeptidase whose expression in a healthy adult is largely restricted to the cancer-associated stroma. FAP-targeted prodrugs with a 100-fold greater therapeutic window over the parent compound were previously generated. Prodrugs and non-cleavable controls were incubated in the presence of FAP. Plasma and tumor half-lives (t1/2) of the full-length and active forms of the prodrugs were determined using LCMS. Biodistribution studies of prodrug activation were performed. Histopathological analysis of tissues from treated animals were compared to vehicle-treated controls. Toxicity and efficacy studies were performed in human breast (MDA-MB-231 and MCF-7) and prostate (LNCaP) cancer xenografts models. These FAP-activated prodrugs have a significantly slower clearance from tumor tissue than the circulation (∼12 vs. ∼4.5 hr). Micromolar concentrations of active drug persist in the tumor. Active drug is detected in non-target tissues; however, histopathologic evaluation reveals no evidence of drug-induced toxicity. A FAP-activated prodrug (ERGETGP-S12ADT) inhibits tumor growth in multiple human breast and prostate cancer xenograft models. The anti-tumor effect is comparable to that observed with docetaxel, but results in significantly less toxicity. FAP-activated prodrugs are a viable strategy for the management of prostate and other cancers. These prodrugs exhibit less toxicity than a commonly used chemotherapeutic agent. Further refinement of the FAP cleavage site for greater specificity may reduce prodrug activation in non-target tissues and enhance clinical benefit. © 2014 Wiley Periodicals, Inc.

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.

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.

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.

Thermal oxidative degradation kinetics of agricultural residues using distributed activation energy model and global kinetic model.

PubMed

Ren, Xiu'e; Chen, Jianbiao; Li, Gang; Wang, Yanhong; Lang, Xuemei; Fan, Shuanshi

2018-08-01

The study concerned the thermal oxidative degradation kinetics of agricultural residues, peanut shell (PS) and sunflower shell (SS). The thermal behaviors were evaluated via thermogravimetric analysis and the kinetic parameters were determined by using distributed activation energy model (DAEM) and global kinetic model (GKM). Results showed that thermal oxidative decomposition of two samples processed in three zones; the ignition, burnout, and comprehensive combustibility between two agricultural residues were of great difference; and the combustion performance could be improved by boosting heating rate. The activation energy ranges calculated by the DAEM for the thermal oxidative degradation of PS and SS were 88.94-145.30 kJ mol -1 and 94.86-169.18 kJ mol -1 , respectively. The activation energy obtained by the GKM for the oxidative decomposition of hemicellulose and cellulose was obviously lower than that for the lignin oxidation at identical heating rate. To some degree, the determined kinetic parameters could acceptably simulate experimental data. Copyright © 2018 Elsevier Ltd. All rights reserved.

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…

Selective neural activation in a histologically derived model of peripheral nerve

NASA Astrophysics Data System (ADS)

Butson, Christopher R.; Miller, Ian O.; Normann, Richard A.; Clark, Gregory A.

2011-06-01

Functional electrical stimulation (FES) is a general term for therapeutic methods that use electrical stimulation to aid or replace lost ability. For FES systems that communicate with the nervous system, one critical component is the electrode interface through which the machine-body information transfer must occur. In this paper, we examine the influence of inhomogeneous tissue conductivities and positions of nodes of Ranvier on activation of myelinated axons for neuromuscular control as a function of electrode configuration. To evaluate these effects, we developed a high-resolution bioelectric model of a fascicle from a stained cross-section of cat sciatic nerve. The model was constructed by digitizing a fixed specimen of peripheral nerve, extruding the image along the axis of the nerve, and assigning each anatomical component to one of several different tissue types. Electrodes were represented by current sources in monopolar, transverse bipolar, and longitudinal bipolar configurations; neural activation was determined using coupled field-neuron simulations with myelinated axon cable models. We found that the use of an isotropic tissue medium overestimated neural activation thresholds compared with the use of physiologically based, inhomogeneous tissue medium, even after controlling for mean impedance levels. Additionally, the positions of the cathodic sources relative to the nodes of Ranvier had substantial effects on activation, and these effects were modulated by the electrode configuration. Our results indicate that physiologically based tissue properties cause considerable variability in the neural response, and the inclusion of these properties is an important component in accurately predicting activation. The results are used to suggest new electrode designs to enable selective stimulation of small diameter fibers.

Empowering Prospective Teachers to Become Active Sense-Makers: Multimodal Modeling of the Seasons

NASA Astrophysics Data System (ADS)

Kim, Mi Song

2015-10-01

Situating science concepts in concrete and authentic contexts, using information and communications technologies, including multimodal modeling tools, is important for promoting the development of higher-order thinking skills in learners. However, teachers often struggle to integrate emergent multimodal models into a technology-rich informal learning environment. Our design-based research co-designs and develops engaging, immersive, and interactive informal learning activities called "Embodied Modeling-Mediated Activities" (EMMA) to support not only Singaporean learners' deep learning of astronomy but also the capacity of teachers. As part of the research on EMMA, this case study describes two prospective teachers' co-design processes involving multimodal models for teaching and learning the concept of the seasons in a technology-rich informal learning setting. Our study uncovers four prominent themes emerging from our data concerning the contextualized nature of learning and teaching involving multimodal models in informal learning contexts: (1) promoting communication and emerging questions, (2) offering affordances through limitations, (3) explaining one concept involving multiple concepts, and (4) integrating teaching and learning experiences. This study has an implication for the development of a pedagogical framework for teaching and learning in technology-enhanced learning environments—that is empowering teachers to become active sense-makers using multimodal models.

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.

Evaluation of an Interdisciplinary, Physically Active Lifestyle Course Model

ERIC Educational Resources Information Center

Fede, Marybeth H.

2009-01-01

The purpose of this study was to evaluate a fit for life program at a university and to use the findings from an extensive literature review, consultations with formative and summative committees, and data collection to develop an interdisciplinary, physically active lifestyle (IPAL) course model. To address the 5 research questions examined in…

Activity measurement and effective dose modelling of natural radionuclides in building material.

PubMed

Maringer, F J; Baumgartner, A; Rechberger, F; Seidel, C; Stietka, M

2013-11-01

In this paper the assessment of natural radionuclides' activity concentration in building materials, calibration requirements and related indoor exposure dose models is presented. Particular attention is turned to specific improvements in low-level gamma-ray spectrometry to determine the activity concentration of necessary natural radionuclides in building materials with adequate measurement uncertainties. Different approaches for the modelling of the effective dose indoor due to external radiation resulted from natural radionuclides in building material and results of actual building material assessments are shown. Copyright © 2013 Elsevier Ltd. All rights reserved.

Frost Growth CFD Model of an Integrated Active Desiccant Rooftop Unit

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

Geoghegan, Patrick J; Petrov, Andrei Y; Vineyard, Edward Allan

2008-01-01

A frost growth model is incorporated into a Computational Fluid Dynamics (CFD) simulation of a heat pump by means of a user-defined function in FLUENT, a commercial CFD code. The transient model is applied to the outdoor section of an Integrated Active Desiccant Rooftop (IADR) unit in heating mode. IADR is a hybrid vapor compression and active desiccant unit capable of handling 100% outdoor air (dedicated outdoor air system) or as a total conditioning system, handling both outdoor air and space cooling or heating loads. The predicted increase in flow resistance and loss in heat transfer capacity due to frostmore » build-up are compared to experimental pressure drop readings and thermal imaging. The purpose of this work is to develop a CFD model that is capable of predicting frost growth, an invaluable tool in evaluating the effectiveness of defrost-on-demand cycles.« less

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.

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.

Activity-specific ecological niche models for planning reintroductions of California condors (Gymnogyps californianus)

USGS Publications Warehouse

D'Elia, Jesse; Haig, Susan M.; Johnson, Matthew J.; Marcot, Bruce G.; Young, Richard

2015-01-01

Ecological niche models can be a useful tool to identify candidate reintroduction sites for endangered species but have been infrequently used for this purpose. In this paper, we (1) develop activity-specific ecological niche models (nesting, roosting, and feeding) for the critically endangered California condor (Gymnogyps californianus) to aid in reintroduction planning in California, Oregon, and Washington, USA, (2) test the accuracy of these models using empirical data withheld from model development, and (3) integrate model results with information on condor movement ecology and biology to produce predictive maps of reintroduction site suitability. Our approach, which disentangles niche models into activity-specific components, has applications for other species where it is routinely assumed (often incorrectly) that individuals fulfill all requirements for life within a single environmental space. Ecological niche models conformed to our understanding of California condor ecology, had good predictive performance when tested with data withheld from model development, and aided in the identification of several candidate reintroduction areas outside of the current distribution of the species. Our results suggest there are large unoccupied regions of the California condor’s historical range that have retained ecological features similar to currently occupied habitats, and thus could be considered for future reintroduction efforts. Combining our activity-specific ENMs with ground reconnaissance and information on other threat factors that could not be directly incorporated into empirical ENMs will ultimately improve our ability to select successful reintroduction sites for the California condor.

Modeling the Synergy of Cofilin and Arp2/3 in Lamellipodial Protrusive Activity

PubMed Central

Tania, Nessy; Condeelis, John; Edelstein-Keshet, Leah

2013-01-01

Rapid polymerization of actin filament barbed ends generates protrusive forces at the cell edge, leading to cell migration. Two important regulators of free barbed ends, cofilin and Arp2/3, have been shown to work in synergy (net effect greater than additive). To explore this synergy, we model the dynamics of F-actin at the leading edge, motivated by data from EGF-stimulated mammary carcinoma cells. We study how synergy depends on the localized rates and relative timing of cofilin and Arp2/3 activation at the cell edge. The model incorporates diffusion of cofilin, membrane protrusion, F-actin capping, aging, and severing by cofilin and branch nucleation by Arp2/3 (but not G-actin recycling). In a well-mixed system, cofilin and Arp2/3 can each generate a large pulse of barbed ends on their own, but have little synergy; high synergy occurs only at low activation rates, when few barbed ends are produced. In the full spatially distributed model, both synergy and barbed-end production are significant over a range of activation rates. Furthermore, barbed-end production is greatest when Arp2/3 activation is delayed relative to cofilin. Our model supports a direct role for cofilin-mediated actin polymerization in stimulated cell migration, including chemotaxis and cancer invasion. PMID:24209839

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…

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.

Modeling the SHG activities of diverse protein crystals

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

Haupert, Levi M.; DeWalt, Emma L.; Simpson, Garth J., E-mail: gsimpson@purdue.edu

2012-11-01

The origins of the diversity in the SHG signal from protein crystals are investigated and potential protein-crystal coverage by SHG microscopy is assessed. A symmetry-additive ab initio model for second-harmonic generation (SHG) activity of protein crystals was applied to assess the likely protein-crystal coverage of SHG microscopy. Calculations were performed for 250 proteins in nine point-group symmetries: a total of 2250 crystals. The model suggests that the crystal symmetry and the limit of detection of the instrument are expected to be the strongest predictors of coverage of the factors considered, which also included secondary-structural content and protein size. Much ofmore » the diversity in SHG activity is expected to arise primarily from the variability in the intrinsic protein response as well as the orientation within the crystal lattice. Two or more orders-of-magnitude variation in intensity are expected even within protein crystals of the same symmetry. SHG measurements of tetragonal lysozyme crystals confirmed detection, from which a protein coverage of ∼84% was estimated based on the proportion of proteins calculated to produce SHG responses greater than that of tetragonal lysozyme. Good agreement was observed between the measured and calculated ratios of the SHG intensity from lysozyme in tetragonal and monoclinic lattices.« less

Arctic chlorine activation and ozone depletion: Comparison of chemistry transport models with satellite observations.

NASA Astrophysics Data System (ADS)

Grooß, J.-U.; Wegner, T.; Müller, R.; Chipperfield, M. P.; Feng, W.; Santee, M. L.

2009-04-01

The accurate simulation of Arctic stratospheric ozone depletion has been an issue for two decades. However, there are still notable quantitative discrepancies between the models and observations. We show results from the SLIMCAT and CLaMS 3D chemistry-transport models that differ in some aspects of simulated chlorine activation and descent in the polar vortex. Consequently, the estimates of accumulated ozone depletion in the polar vortex for these two models in cold Arctic winters still largely disagree. As shown recently by Santee et al. (JGR, 2008) using MLS and ACE data, the extent of chlorine activation for the cold Arctic winter of 2004/2005 within the basic SLIMCAT model is overestimated with the likely consequence of too much simulated ozone depletion. In contrast, the CLaMS simulation for the same winter shows too little chlorine activation compared to observations, and therefore likely too little loss. For SLIMCAT the version used by Santee et al. has been updated to replace the equilibrium treatment of NAT PSCs with a Lagrangian microphysical scheme. This leads to smaller regions of NAT particles and less denitrification, in better agreement with observations. The impact of this on the modeled extent of chlorine activation will be discussed. For CLaMS we have changed the parameterization of heterogeneous reactions on liquid aerosols from Carslaw et al. to that of Shi et al. (2001), with which chlorine activation on liquid aerosol becomes more efficient. In turn, the simulated chlorine activation agrees better with the observations. The impact of these model changes on chlorine activation and ozone loss will be assessed and remaining model-observation discrepancies will be discussed in terms of different model formulations. We will also show the impact of recent lab measurements of Cl2O2 absorption cross sections by von Hobe et al. (2009) on the simulated ozone depletion. References: von Hobe, M., F. Stroh, H. Beckers, T. Benter, and H. Willner, The UV

Hot-bench simulation of the active flexible wing wind-tunnel model

NASA Technical Reports Server (NTRS)

Buttrill, Carey S.; Houck, Jacob A.

1990-01-01

Two simulations, one batch and one real-time, of an aeroelastically-scaled wind-tunnel model were developed. The wind-tunnel model was a full-span, free-to-roll model of an advanced fighter concept. The batch simulation was used to generate and verify the real-time simulation and to test candidate control laws prior to implementation. The real-time simulation supported hot-bench testing of a digital controller, which was developed to actively control the elastic deformation of the wind-tunnel model. Time scaling was required for hot-bench testing. The wind-tunnel model, the mathematical models for the simulations, the techniques employed to reduce the hot-bench time-scale factors, and the verification procedures are described.

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.

Structure activity relationship modelling of milk protein-derived peptides with dipeptidyl peptidase IV (DPP-IV) inhibitory activity.

PubMed

Nongonierma, Alice B; FitzGerald, Richard J

2016-05-01

Quantitative structure activity type models were developed in an attempt to predict the key features of peptide sequences having dipeptidyl peptidase IV (DPP-IV) inhibitory activity. The models were then employed to help predict the potential of peptides, which are currently reported in the literature to be present in the intestinal tract of humans following milk/dairy product ingestion, to act as inhibitors of DPP-IV. Two models (z- and v-scale) for short (2-5 amino acid residues) bovine milk peptides, behaving as competitive inhibitors of DPP-IV, were developed. The z- and the v-scale models (p<0.05, R(2) of 0.829 and 0.815, respectively) were then applied to 56 milk protein-derived peptides previously reported in the literature to be found in the intestinal tract of humans which possessed a structural feature of DPP-IV inhibitory peptides (P at the N2 position). Ten of these peptides were synthetized and tested for their in vitro DPP-IV inhibitory properties. There was no agreement between the predicted and experimentally determined DPP-IV half maximal inhibitory concentrations (IC50) for the competitive peptide inhibitors. However, the ranking for DPP-IV inhibitory potency of the competitive peptide inhibitors was conserved. Furthermore, potent in vitro DPP-IV inhibitory activity was observed with two peptides, LPVPQ (IC50=43.8±8.8μM) and IPM (IC50=69.5±8.7μM). Peptides present within the gastrointestinal tract of human may have promise for the development of natural DPP-IV inhibitors for the management of serum glucose. Copyright © 2016 Elsevier Inc. All rights reserved.

Synthetic Models for Nickel-Iron Hydrogenase Featuring Redox-Active Ligands.

PubMed

Schilter, David; Gray, Danielle L; Fuller, Amy L; Rauchfuss, Thomas B

2017-05-01

The nickel-iron hydrogenase enzymes efficiently and reversibly interconvert protons, electrons, and dihydrogen. These redox proteins feature iron-sulfur clusters that relay electrons to and from their active sites. Reported here are synthetic models for nickel-iron hydrogenase featuring redox-active auxiliaries that mimic the iron-sulfur cofactors. The complexes prepared are Ni II (μ-H)Fe II Fe II species of formula [(diphosphine)Ni(dithiolate)(μ-H)Fe(CO) 2 (ferrocenylphosphine)] + or Ni II Fe I Fe II complexes [(diphosphine)Ni(dithiolate)Fe(CO) 2 (ferrocenylphosphine)] + (diphosphine = Ph 2 P(CH 2 ) 2 PPh 2 or Cy 2 P(CH 2 ) 2 PCy 2 ; dithiolate = - S(CH 2 ) 3 S - ; ferrocenylphosphine = diphenylphosphinoferrocene, diphenylphosphinomethyl(nonamethylferrocene) or 1,1'-bis(diphenylphosphino)ferrocene). The hydride species is a catalyst for hydrogen evolution, while the latter hydride-free complexes can exist in four redox states - a feature made possible by the incorporation of the ferrocenyl groups. Mixed-valent complexes of 1,1'-bis(diphenylphosphino)ferrocene have one of the phosphine groups unbound, with these species representing advanced structural models with both a redox-active moiety (the ferrocene group) and a potential proton relay (the free phosphine) proximal to a nickel-iron dithiolate.

SCREENING OF WILD FRUIT TREES WITH GASTROPROTECTIVE ACTIVITY IN DIFFERENT EXPERIMENTAL MODELS.

PubMed

Nesello, Luciane Angela Nottar; Campos, Adriana; Rosa, Roseane Leandra da; Andrade, Sérgio Faloni de; Cechinel, Valdir

2017-01-01

Given the increase of people with gastrointestinal disorders, the search for alternative treatments with fewer side effects is vital, as well as the demand for food or plants that can help protect the stomach. The aim of this study was to evaluate the gastroprotective action of the extracts of wild fruit trees of Myrcianthes pungens (guabiju); Inga vera Willd. (ingá-banana) and Marlierea tomentosa Cambess. (guarapuruna) in in vivo pharmacological models. The different parts of the fruits were separately subjected to a process of extraction by methanol. Two experimental pharmacological models were conducted in mice; the gastric ulcer model induced by non-steroidal anti-inflammatory (indomethacin), and the gastric ulcer model induced by ethanol/HCl, which allowed us to evaluate the gastroprotective activity of the extracts at a dose of 250 mg/kg. Subsequently, the total lesion area (mm2) and relative lesion area (%) were determined. The results showed significant gastroprotective activity against the aggressive agents used - ethanol and indomethacin - for all the extracts tested. It is assumed that the fruits have bioactive compounds such as antioxidant substances that act on the prostaglandin levels, protecting them from the damage caused by ethanol and indomethacin. These results prompt further studies to isolate and identify the active properties.

Novel three-stage kinetic model for aqueous benzene adsorption on activated carbon.

PubMed

Choi, Jae-Woo; Choi, Nag-Choul; Lee, Soon-Jae; Kim, Dong-Ju

2007-10-15

We propose a novel kinetic model for adsorption of aqueous benzene onto both granular activated carbon (GAC) and powdered activated carbon (PAC). The model is based on mass conservation of benzene coupled with three-stage adsorption: (1) the first portion for an instantaneous stage or external surface adsorption, (2) the second portion for a gradual stage with rate-limiting intraparticle diffusion, and (3) the third portion for a constant stage in which the aqueous phase no longer interacts with activated carbon. An analytical solution of the kinetic model was validated with the kinetic data obtained from aqueous benzene adsorption onto GAC and PAC in batch experiments with two different solution concentrations (C(0)=300 mg L(-1), 600 mg L(-1)). Experimental results revealed that benzene adsorption for the two concentrations followed three distinct stages for PAC but two stages for GAC. The analytical solution could successfully describe the kinetic adsorption of aqueous benzene in the batch reaction system, showing a fast instantaneous adsorption followed by a slow rate-limiting adsorption and a final long constant adsorption. Use of the two-stage model gave incorrect values of adsorption coefficients in the analytical solution due to inability to describe the third stage.

Modeling Radial Holoblastic Cleavage: A Laboratory Activity for Developmental Biology.

ERIC Educational Resources Information Center

Ellis, Linda K.

2000-01-01

Introduces a laboratory activity designed for an undergraduate developmental biology course. Uses Play-Doh (plastic modeling clay) to build a multicellular embryo in order to provide a 3-D demonstration of cleavage. Includes notes for the instructor and student directions. (YDS)

A fully resolved fluid-structure-muscle-activation model for esophageal transport

NASA Astrophysics Data System (ADS)

Kou, Wenjun; Bhalla, Amneet P. S.; Griffith, Boyce E.; Johnson, Mark; Patankar, Neelesh A.

2013-11-01

Esophageal transport is a mechanical and physiological process that transfers the ingested food bolus from the pharynx to the stomach through a multi-layered esophageal tube. The process involves interactions between the bolus, esophageal wall composed of mucosal, circular muscle (CM) and longitudinal muscle (LM) layers, and neurally coordinated muscle activation including CM contraction and LM shortening. In this work, we present a 3D fully-resolved model of esophageal transport based on the immersed boundary method. The model describes the bolus as a Newtonian fluid, the esophageal wall as a multi-layered elastic tube represented by springs and beams, and the muscle activation as a traveling wave of sequential actuation/relaxation of muscle fibers, represented by springs with dynamic rest lengths. Results on intraluminal pressure profile and bolus shape will be shown, which are qualitatively consistent with experimental observations. Effects of activating CM contraction only, LM shortening only or both, for the bolus transport, are studied. A comparison among them can help to identify the role of each type of muscle activation. The support of grant R01 DK56033 and R01 DK079902 from NIH is gratefully acknowledged.

Decoding natural images from evoked brain activities using encoding models with invertible mapping.

PubMed

Li, Chao; Xu, Junhai; Liu, Baolin

2018-05-21

Recent studies have built encoding models in the early visual cortex, and reliable mappings have been made between the low-level visual features of stimuli and brain activities. However, these mappings are irreversible, so that the features cannot be directly decoded. To solve this problem, we designed a sparse framework-based encoding model that predicted brain activities from a complete feature representation. Moreover, according to the distribution and activation rules of neurons in the primary visual cortex (V1), three key transformations were introduced into the basic feature to improve the model performance. In this setting, the mapping was simple enough that it could be inverted using a closed-form formula. Using this mapping, we designed a hybrid identification method based on the support vector machine (SVM), and tested it on a published functional magnetic resonance imaging (fMRI) dataset. The experiments confirmed the rationality of our encoding model, and the identification accuracies for 2 subjects increased from 92% and 72% to 98% and 92% with the chance level only 0.8%. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Design of a communicative model from a social perspective oriented toward physical activity].

PubMed

Prieto-Rodríguez, Adriana; Moreno-Angarita, Marisol; Cardozo-Vásquez, Yency S

2006-12-01

A communication model was designed and put into practice, in the form of a Network throughout three regions in Colombia; Bogotá, Antioquia and Quindío. Based on a macro-intentional model, this network was aimed at strengthening understanding around the subject of physical activity among those people affected by the issue, from a multidimensional perspective. The test population was defined and working groups were formed around three strategies: social production, transmission and democratization, during a three-month period. RESULTS Messages were developed based around the ideas of the community producers themselves; the initial concepts were widened to include the body, self care, physical activity and health. Communication models related to health, aimed at developing personal skills including the ability to communicate and build shared experience, can be assimilated and incorporated into broadcasts on health issues. This model serves as a communication strategy which strengthens the building of shared broadcasts on health issues. This kind of focus requires the development of local activity and capacity-building within the community.

Dynamical analysis of uterine cell electrical activity model.

PubMed

Rihana, S; Santos, J; Mondie, S; Marque, C

2006-01-01

The uterus is a physiological system consisting of a large number of interacting smooth muscle cells. The uterine excitability changes remarkably with time, generally quiescent during pregnancy, the uterus exhibits forceful synchronized contractions at term leading to fetus expulsion. These changes characterize thus a dynamical system susceptible of being studied through formal mathematical tools. Multiple physiological factors are involved in the regulation process of this complex system. Our aim is to relate the physiological factors to the uterine cell dynamic behaviors. Taking into account a previous work presented, in which the electrical activity of a uterine cell is described by a set of ordinary differential equations, we analyze the impact of physiological parameters on the response of the model, and identify the main subsystems generating the complex uterine electrical activity, with respect to physiological data.

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

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

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Modeling of Relation between Transaction Network and Production Activity for Firms

NASA Astrophysics Data System (ADS)

Iino, T.; Iyetomi, H.

Bak et al. [Ricerche Economiche 47 (1993), 3] proposed a self-organizing model for production activity of interacting firms to illustrate how large fluctuations can be triggered by small independent shocks in aggregate economy. This paper develops the original transaction model based on a regular network with layered order flow to accommodate more realistic networks. Simulations in the generalized model so obtained are then carried out for various networks to examine the influence caused by change of the network structure.

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

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.

CFD-aided modelling of activated sludge systems - A critical review.

PubMed

Karpinska, Anna M; Bridgeman, John

2016-01-01

Nowadays, one of the major challenges in the wastewater sector is the successful design and reliable operation of treatment processes, which guarantee high treatment efficiencies to comply with effluent quality criteria, while keeping the investment and operating cost as low as possible. Although conceptual design and process control of activated sludge plants are key to ensuring these goals, they are still based on general empirical guidelines and operators' experience, dominated often by rule of thumb. This review paper discusses the rationale behind the use of Computational Fluid Dynamics (CFD) to model aeration, facilitating enhancement of treatment efficiency and reduction of energy input. Several single- and multiphase approaches commonly used in CFD studies of aeration tank operation, are comprehensively described, whilst the shortcomings of the modelling assumptions imposed to evaluate mixing and mass transfer in AS tanks are identified and discussed. Examples and methods of coupling of CFD data with biokinetics, accounting for the actual flow field and its impact on the oxygen mass transfer and yield of the biological processes occurring in the aeration tanks, are also critically discussed. Finally, modelling issues, which remain unaddressed, (e.g. coupling of the AS tank with secondary clarifier and the use of population balance models to simulate bubbly flow or flocculation of the activated sludge), are also identified and discussed. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Active muscle response using feedback control of a finite element human arm model.

PubMed

Östh, Jonas; Brolin, Karin; Happee, Riender

2012-01-01

Mathematical human body models (HBMs) are important research tools that are used to study the human response in car crash situations. Development of automotive safety systems requires the implementation of active muscle response in HBM, as novel safety systems also interact with vehicle occupants in the pre-crash phase. In this study, active muscle response was implemented using feedback control of a nonlinear muscle model in the right upper extremity of a finite element (FE) HBM. Hill-type line muscle elements were added, and the active and passive properties were assessed. Volunteer tests with low impact loading resulting in elbow flexion motions were performed. Simulations of posture maintenance in a gravity field and the volunteer tests were successfully conducted. It was concluded that feedback control of a nonlinear musculoskeletal model can be used to obtain posture maintenance and human-like reflexive responses in an FE HBM.

Active choice but not too active: Public perspectives on biobank consent models

PubMed Central

Simon, Christian M.; L’Heureux, Jamie; Murray, Jeffrey C.; Winokur, Patricia; Weiner, George; Newbury, Elizabeth; Shinkunas, Laura; Zimmerman, Bridget

2013-01-01

Purpose Despite important recent work, US public attitudes toward specific biobank consent models are not well understood. Public opinion data can help shape efforts to develop ethically sound and publicly trusted mechanisms for informing and consenting prospective biobank donors. The purpose of this study was to explore public perspectives toward a range of consent models currently being used or considered for use among comprehensive US biobanks. Methods The study used an exploratory mixed-methods design, using focus groups and telephone surveys. Eligible participants were English-speaking residents in the catchment area of a comprehensive biobank being developed at the University of Iowa. Results Forty-eight participants in seven focus groups and 751 survey participants were recruited. Biobanks were unfamiliar to almost all study participants but were seen as valuable resources. Most focus group (63%) and survey (67%) participants preferred a prospective opt-in over an opt-out consent approach. Broad, research-unspecific consent was preferred over categorical and study-specific consent models for purposes of approving future research use. Conclusion Many individuals may want to make an active and informed choice at the point of being approached for biobank participation but are prepared to consent broadly to future research use and to forego additional choices as a result. PMID:21555942

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.