conceptual models predict: Topics by Science.gov

Sample records for conceptual models predict

Estimation of Model's Marginal likelihood Using Adaptive Sparse Grid Surrogates in Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Zeng, X.

2015-12-01

A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.
On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.
SITE CHARACTERIZATION TO SUPPORT DEVELOPMENT OF CONCEPTUAL SITE MODELS AND TRANSPORT MODELS FOR MONITORING CONTAMINANTS IN GROUND WATER

EPA Science Inventory

The development of conceptual and predictive models is an important tool to guide site characterization in support of monitoring contaminants in ground water. The accuracy of predictive models is limited by the adequacy of the input data and the assumptions made to constrain mod...
The Role of Cognitive, Metacognitive, and Motivational Variables in Conceptual Change: Preservice Early Childhood Teachers' Conceptual Understanding of the Cause of Lunar Phases

ERIC Educational Resources Information Center

Sackes, Mesut

2010-01-01

This study seeks to explore and describe the role of cognitive, metacognitive, and motivational variables in conceptual change. More specifically, the purposes of the study were (1) to investigate the predictive ability of a learning model that was developed based on the intentional conceptual change perspective in predicting change in conceptual…
To master or perform? Exploring relations between achievement goals and conceptual change learning.

PubMed

Ranellucci, John; Muis, Krista R; Duffy, Melissa; Wang, Xihui; Sampasivam, Lavanya; Franco, Gina M

2013-09-01

Research is needed to explore conceptual change in relation to achievement goal orientations and depth of processing. To address this need, we examined relations between achievement goals, use of deep versus shallow processing strategies, and conceptual change learning using a think-aloud protocol. Seventy-three undergraduate students were assessed on their prior knowledge and misconceptions about Newtonian mechanics, and then reported their achievement goals and participated in think-aloud protocols while reading Newtonian physics texts. A mastery-approach goal orientation positively predicted deep processing strategies, shallow processing strategies, and conceptual change. In contrast, a performance-approach goal orientation did not predict either of the processing strategies, but negatively predicted conceptual change. A performance-avoidance goal orientation negatively predicted deep processing strategies and conceptual change. Moreover, deep and shallow processing strategies positively predicted conceptual change as well as recall. Finally, both deep and shallow processing strategies mediated relations between mastery-approach goals and conceptual change. Results provide some support for Dole and Sinatra's (1998) Cognitive Reconstruction of Knowledge Model of conceptual change but also challenge specific facets with regard to the role of depth of processing in conceptual change. © 2012 The British Psychological Society.
The site-scale saturated zone flow model for Yucca Mountain: Calibration of different conceptual models and their impact on flow paths

USGS Publications Warehouse

Zyvoloski, G.; Kwicklis, E.; Eddebbarh, A.-A.; Arnold, B.; Faunt, C.; Robinson, B.A.

2003-01-01

This paper presents several different conceptual models of the Large Hydraulic Gradient (LHG) region north of Yucca Mountain and describes the impact of those models on groundwater flow near the potential high-level repository site. The results are based on a numerical model of site-scale saturated zone beneath Yucca Mountain. This model is used for performance assessment predictions of radionuclide transport and to guide future data collection and modeling activities. The numerical model is calibrated by matching available water level measurements using parameter estimation techniques, along with more informal comparisons of the model to hydrologic and geochemical information. The model software (hydrologic simulation code FEHM and parameter estimation software PEST) and model setup allows for efficient calibration of multiple conceptual models. Until now, the Large Hydraulic Gradient has been simulated using a low-permeability, east-west oriented feature, even though direct evidence for this feature is lacking. In addition to this model, we investigate and calibrate three additional conceptual models of the Large Hydraulic Gradient, all of which are based on a presumed zone of hydrothermal chemical alteration north of Yucca Mountain. After examining the heads and permeabilities obtained from the calibrated models, we present particle pathways from the potential repository that record differences in the predicted groundwater flow regime. The results show that Large Hydraulic Gradient can be represented with the alternate conceptual models that include the hydrothermally altered zone. The predicted pathways are mildly sensitive to the choice of the conceptual model and more sensitive to the quality of calibration in the vicinity on the repository. These differences are most likely due to different degrees of fit of model to data, and do not represent important differences in hydrologic conditions for the different conceptual models. ?? 2002 Elsevier Science B.V. All rights reserved.
Conceptual modelling to predict unobserved system states - the case of groundwater flooding in the UK Chalk

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Ireson, A. M.

2017-12-01

Chalk aquifers represent an important source of drinking water in the UK. Due to its fractured-porous structure, Chalk aquifers are characterized by highly dynamic groundwater fluctuations that enhance the risk of groundwater flooding. The risk of groundwater flooding can be assessed by physically-based groundwater models. But for reliable results, a-priori information about the distribution of hydraulic conductivities and porosities is necessary, which is often not available. For that reason, conceptual simulation models are often used to predict groundwater behaviour. They commonly require calibration by historic groundwater observations. Consequently, their prediction performance may reduce significantly, when it comes to system states that did not occur within the calibration time series. In this study, we calibrate a conceptual model to the observed groundwater level observations at several locations within a Chalk system in Southern England. During the calibration period, no groundwater flooding occurred. We then apply our model to predict the groundwater dynamics of the system at a time that includes a groundwater flooding event. We show that the calibrated model provides reasonable predictions before and after the flooding event but it over-estimates groundwater levels during the event. After modifying the model structure to include topographic information, the model is capable of prediction the groundwater flooding event even though groundwater flooding never occurred in the calibration period. Although straight forward, our approach shows how conceptual process-based models can be applied to predict system states and dynamics that did not occur in the calibration period. We believe such an approach can be transferred to similar cases, especially to regions where rainfall intensities are expected to trigger processes and system states that may have not yet been observed.
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.
Conceptual Web Users' Actions Prediction for Ontology-Based Browsing Recommendations

NASA Astrophysics Data System (ADS)

Robal, Tarmo; Kalja, Ahto

The Internet consists of thousands of web sites with different kinds of structures. However, users are browsing the web according to their informational expectations towards the web site searched, having an implicit conceptual model of the domain in their minds. Nevertheless, people tend to repeat themselves and have partially shared conceptual views while surfing the web, finding some areas of web sites more interesting than others. Herein, we take advantage of the latter and provide a model and a study on predicting users' actions based on the web ontology concepts and their relations.
Evaluation of a distributed catchment scale water balance model

NASA Technical Reports Server (NTRS)

Troch, Peter A.; Mancini, Marco; Paniconi, Claudio; Wood, Eric F.

1993-01-01

The validity of some of the simplifying assumptions in a conceptual water balance model is investigated by comparing simulation results from the conceptual model with simulation results from a three-dimensional physically based numerical model and with field observations. We examine, in particular, assumptions and simplifications related to water table dynamics, vertical soil moisture and pressure head distributions, and subsurface flow contributions to stream discharge. The conceptual model relies on a topographic index to predict saturation excess runoff and on Philip's infiltration equation to predict infiltration excess runoff. The numerical model solves the three-dimensional Richards equation describing flow in variably saturated porous media, and handles seepage face boundaries, infiltration excess and saturation excess runoff production, and soil driven and atmosphere driven surface fluxes. The study catchments (a 7.2 sq km catchment and a 0.64 sq km subcatchment) are located in the North Appalachian ridge and valley region of eastern Pennsylvania. Hydrologic data collected during the MACHYDRO 90 field experiment are used to calibrate the models and to evaluate simulation results. It is found that water table dynamics as predicted by the conceptual model are close to the observations in a shallow water well and therefore, that a linear relationship between a topographic index and the local water table depth is found to be a reasonable assumption for catchment scale modeling. However, the hydraulic equilibrium assumption is not valid for the upper 100 cm layer of the unsaturated zone and a conceptual model that incorporates a root zone is suggested. Furthermore, theoretical subsurface flow characteristics from the conceptual model are found to be different from field observations, numerical simulation results, and theoretical baseflow recession characteristics based on Boussinesq's groundwater equation.
Mental models accurately predict emotion transitions.

PubMed

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.
Evidence for the Continuous Latent Structure of Mania in the Epidemiologic Catchment Area from Multiple Latent Structure and Construct Validation Methodologies

PubMed Central

Prisciandaro, James J.; Roberts, John E.

2011-01-01

Background Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM), and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study. Methods Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses; including factor analyses, taxometric procedures, and ITLDM; in 10,105 ECA community participants. Additionally, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e., health service utilization, internalizing and externalizing disorders, and suicidal behavior). Results Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6:52:1 odds over the best fitting latent class model of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models. Conclusions The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed. PMID:20507671
A Conceptual Model for the Development of Externalizing Behavior Problems Among Kindergarten Children of Alcoholic Families: Role of Parenting and Children's Self-Regulation

PubMed Central

Eiden, Rina D.; Edwards, Ellen P.; Leonard, Kenneth E.

2009-01-01

The purpose of this study was to test a conceptual model predicting children's externalizing behavior problems in kindergarten in a sample of children with alcoholic (n = 130) and nonalcoholic (n = 97) parents. The model examined the role of parents' alcohol diagnoses, depression, and antisocial behavior at 12–18 months of child age in predicting parental warmth/sensitivity at 2 years of child age. Parental warmth/sensitivity at 2 years was hypothesized to predict children's self-regulation at 3 years (effortful control and internalization of rules), which in turn was expected to predict externalizing behavior problems in kindergarten. Structural equation modeling was largely supportive of this conceptual model. Fathers' alcohol diagnosis at 12–18 months was associated with lower maternal and paternal warmth/sensitivity at 2 years. Lower maternal warmth/sensitivity was longitudinally predictive of lower child self-regulation at 3 years, which in turn was longitudinally predictive of higher externalizing behavior problems in kindergarten, after controlling for prior behavior problems. There was a direct association between parents' depression and children's externalizing behavior problems. Results indicate that one pathway to higher externalizing behavior problems among children of alcoholics may be via parenting and self-regulation in the toddler to preschool years. PMID:17723044
Guidance for the Development of Conceptual Models for a Problem Formulation Developed for Registration Review

EPA Pesticide Factsheets

Conceptual models for aquatic and terrestrial exposures. Graphic representation of predicted relationships between the ecological entities, both listed (threatened and endangered) and non-listed species, and the stressors to which they may be exposed.
Re-Conceptualizing Intimacy and Distance in Instructional Models

ERIC Educational Resources Information Center

Ketterer, John J.

2006-01-01

The idea that distance education lacks intimacy and is therefore inferior is based on an embedded metaphor that sustains a restricted and limiting mental model of ideal instruction. The authors analyze alternative conceptualizations of intimacy, space, and place as factors in the development of effective instructional models. They predict that the…
Mental models accurately predict emotion transitions

PubMed Central

Thornton, Mark A.; Tamir, Diana I.

2017-01-01

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373
A conceptual model predicting internalizing problems in middle childhood among children of alcoholic and nonalcoholic fathers: the role of marital aggression.

PubMed

Eiden, Rina D; Molnar, Danielle S; Colder, Craig; Edwards, Ellen P; Leonard, Kenneth E

2009-09-01

The purpose of this study was to test a conceptual model predicting children's anxiety/depression in middle childhood in a community sample of children with parents who had alcohol problems (n = 112) and those without alcohol problems (n = 101). The conceptual model examined the role of parents' alcohol diagnoses, depression, and antisocial behavior among parents of children ages 12 months to kindergarten age in predicting marital aggression and parental aggravation. Higher levels of marital aggression and parental aggravation were hypothesized to predict children's depression/anxiety within time (18 months to kindergarten age and, prospectively, to age during fourth grade). The sample was recruited from New York State birth records when the children were 12 months old. Assessments were conducted at 12, 18, 24, and 36 months; at kindergarten age; and during fourth grade. Children with alcoholic fathers had higher depression/anxiety scores according to parental reports but not self-reports. Structural equations modeling was largely supportive of the conceptual model. Fathers' alcoholism was associated with higher child anxiety via greater levels of marital aggression among families with alcohol problems. Results also indicated that there was a significant indirect association between parents' depression symptoms and child anxiety via marital aggression. The results highlight the nested nature of risk characteristics in alcoholic families and the important role of marital aggression in predicting children's anxiety/depression. Interventions targeting both parents' alcohol problems and associated marital aggression are likely to provide the dual benefits of improving family interactions and lowering risk of children's internalizing behavior problems.
Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

NASA Astrophysics Data System (ADS)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.
Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

PubMed

Briggs, Andrew H; Baker, Timothy; Risebrough, Nancy A; Chambers, Mike; Gonzalez-McQuire, Sebastian; Ismaila, Afisi S; Exuzides, Alex; Colby, Chris; Tabberer, Maggie; Muellerova, Hana; Locantore, Nicholas; Rutten van Mölken, Maureen P M H; Lomas, David A

2017-05-01

The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.
PREDICTING ATTENUATION OF VIRUSES DURING PERCOLATION IN SOILS: 2. USER'S GUIDE TO THE VIRULO 1.0 COMPUTER MODEL

EPA Science Inventory

In the EPA document Predicting Attenuation of Viruses During Percolation in Soils 1. Probabilistic Model the conceptual, theoretical, and mathematical foundations for a predictive screening model were presented. In this current volume we present a User's Guide for the computer mo...

Exploring Students' Reflective Thinking Practice, Deep Processing Strategies, Effort, and Achievement Goal Orientations

ERIC Educational Resources Information Center

Phan, Huy Phuong

2009-01-01

Recent research indicates that study processing strategies, effort, reflective thinking practice, and achievement goals are important factors contributing to the prediction of students' academic success. Very few studies have combined these theoretical orientations within one conceptual model. This study tested a conceptual model that included, in…
A conceptual precipitation-runoff modeling suite: Model selection, calibration and predictive uncertainty assessment

Treesearch

Tyler Jon Smith

2008-01-01

In Montana and much of the Rocky Mountain West, the single most important parameter in forecasting the controls on regional water resources is snowpack. Despite the heightened importance of snowpack, few studies have considered the representation of uncertainty in coupled snowmelt/hydrologic conceptual models. Uncertainty estimation provides a direct interpretation of...
Conceptual Resources in Self-Developed Explanatory Models: The Importance of Integrating Conscious and Intuitive Knowledge

ERIC Educational Resources Information Center

Cheng, Meng-Fei; Brown, David E.

2010-01-01

This study explores the spontaneous explanatory models children construct, critique, and revise in the context of tasks in which children need to predict, observe, and explain phenomena involving magnetism. It further investigates what conceptual resources students use, and in what ways they use them, to construct explanatory models, and the…
Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 1. Small catchment water balance model

NASA Astrophysics Data System (ADS)

Sivapalan, Murugesu; Ruprecht, John K.; Viney, Neil R.

1996-03-01

A long-term water balance model has been developed to predict the hydrological effects of land-use change (especially forest clearing) in small experimental catchments in the south-west of Western Australia. This small catchment model has been used as the building block for the development of a large catchment-scale model, and has also formed the basis for a coupled water and salt balance model, developed to predict the changes in stream salinity resulting from land-use and climate change. The application of the coupled salt and water balance model to predict stream salinities in two small experimental catchments, and the application of the large catchment-scale model to predict changes in water yield in a medium-sized catchment that is being mined for bauxite, are presented in Parts 2 and 3, respectively, of this series of papers.The small catchment model has been designed as a simple, robust, conceptually based model of the basic daily water balance fluxes in forested catchments. The responses of the catchment to rainfall and pan evaporation are conceptualized in terms of three interdependent subsurface stores A, B and F. Store A depicts a near-stream perched aquifer system; B represents a deeper, permanent groundwater system; and F is an intermediate, unsaturated infiltration store. The responses of these stores are characterized by a set of constitutive relations which involves a number of conceptual parameters. These parameters are estimated by calibration by comparing observed and predicted runoff. The model has performed very well in simulations carried out on Salmon and Wights, two small experimental catchments in the Collie River basin in south-west Western Australia. The results from the application of the model to these small catchments are presented in this paper.
Atmospheric Dispersal and Dispostion of Tephra From a Potential Volcanic Eruption at Yucca Mountain, Nevada

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

G. Keating; W.Statham

2004-02-12

The purpose of this model report is to provide documentation of the conceptual and mathematical model (ASHPLUME) for atmospheric dispersal and subsequent deposition of ash on the land surface from a potential volcanic eruption at Yucca Mountain, Nevada. This report also documents the ash (tephra) redistribution conceptual model. The ASHPLUME conceptual model accounts for incorporation and entrainment of waste fuel particles associated with a hypothetical volcanic eruption through the Yucca Mountain repository and downwind transport of contaminated tephra. The ASHPLUME mathematical model describes the conceptual model in mathematical terms to allow for prediction of radioactive waste/ash deposition on the groundmore » surface given that the hypothetical eruptive event occurs. This model report also describes the conceptual model for tephra redistribution from a basaltic cinder cone. Sensitivity analyses and model validation activities for the ash dispersal and redistribution models are also presented. Analyses documented in this model report will improve and clarify the previous documentation of the ASHPLUME mathematical model and its application to the Total System Performance Assessment (TSPA) for the License Application (TSPA-LA) igneous scenarios. This model report also documents the redistribution model product outputs based on analyses to support the conceptual model.« less
Investigating the Effectiveness of an Active Learning Based-Interactive Conceptual Instruction (ALBICI) on Electric Field Concept

ERIC Educational Resources Information Center

Samsudin, Achmad; Suhandi, Andi; Rusdiana, Dadi; Kaniawati, Ida; Costu, Bayram

2016-01-01

The aim of this study was to develop an Active Learning Based-Interactive Conceptual Instruction (ALBICI) model through PDEODE*E tasks (stands for Predict, Discuss, Explain, Observe, Discuss, Explore, and Explain) for promoting conceptual change and investigating its effectiveness of pre-service physics teachers' understanding on electric field…
The development and validation of Science Learning Inventory (SLI): A conceptual change framework

NASA Astrophysics Data System (ADS)

Seyedmonir, Mehdi

2000-12-01

A multidimensional theoretical model, Conceptual Change Science Learning (CCSL), was developed based on Standard Model of Conceptual Change and Cognitive Reconstruction of Knowledge Model. The model addresses three main components of science learning, namely the learner's conceptual ecology, the message along with its social context, and the cognitive engagement. A learner's conceptual ecology is organized around three clusters, including epistemological beliefs, existing conceptions, and motivation. Learner's cognitive engagement is represented by a continuum from peripheral processing involving shallow cognitive engagement to central processing involving deep cognitive engagement. Through reciprocal, non-sequential interactions of such constructs, the learners' conceptual change is achieved. Using a quantitative empirical approach, three studies were conducted to investigate the theoretical constructs based on the CCSL Model. The first study reports the development and validation of the hypothesized and factor-analytic scales comprising the instrument, Science Learning Inventory (SLI) intended for college students. The self-report instrument was designed in two parts, SLI-A (conceptual ecology and cognitive engagement) with 48 initial items, and SLI-B (science epistemology) with 49 initial items. The items for SLI-B were based on the tenets of Nature of Science as reflected in the recent reform documents, Science for All Americans (Project 2061) and National Science Education Standards. The results of factor analysis indicated seven factors for SLI-A and four factors for SLI-B. The second study investigated the criterion-related (conceptual change) predictive validity of the SLI in an instructional setting (a college-level physics course). The findings suggested the possibility of different interplay of factors and dynamics depending on the nature of the criterion (gain scores from a three-week intervention versus final course grade). Gain scores were predicted by "self-reflective study behavior" and "science self-efficacy" scales of SLI, whereas the course grade was predicted by "metacognitive engagement" and "dynamic scientific truth," (a factor from science epistemology). The third study investigated the effects of text-based conceptual-change strategy (Enhanced Refutational Text; ERT) on Newtonian Laws of Motion, and the efficacy of the SLI scales in a controlled setting. Also, initial divergent and convergent validity procedures are reported in the study. The results provided partial support for the superiority of ERT over expository text. The ERT was an effective intervention for students with no prior physics background but not for students with prior physics background.
Cognitive Demand of Model Tracing Tutor Tasks: Conceptualizing and Predicting How Deeply Students Engage

ERIC Educational Resources Information Center

Kessler, Aaron M.; Stein, Mary Kay; Schunn, Christian D.

2015-01-01

Model tracing tutors represent a technology designed to mimic key elements of one-on-one human tutoring. We examine the situations in which such supportive computer technologies may devolve into mindless student work with little conceptual understanding or student development. To analyze the support of student intellectual work in the model…
SITE CHARACTERIZATION TO SUPPORT MODEL DEVELOPMENT FOR CONTAMINANTS IN GROUND WATER

EPA Science Inventory

The development of conceptual and predictive models is an important tool to guide site characterization in support of monitoring contaminants in ground water. The accuracy of predictive models is limited by the adequacy of the input data and the assumptions made to constrain mod...
Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Kavetski, Dmitri

2010-10-01

A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.
Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.
Predicting Alumni/ae Gift Giving Behavior: A Structural Equation Model Approach.

ERIC Educational Resources Information Center

Mosser, John Wayne

This dissertation focuses on predicting alumni gift giving behavior at a large public research university (University of Michigan). A conceptual model was developed for predicting alumni giving behavior in order to advance the theoretical understanding of how capacity to give, motivation to give, and their interaction effect gift giving behavior.…
The relationship between inadvertent ingestion and dermal exposure pathways: a new integrated conceptual model and a database of dermal and oral transfer efficiencies.

PubMed

Gorman Ng, Melanie; Semple, Sean; Cherrie, John W; Christopher, Yvette; Northage, Christine; Tielemans, Erik; Veroughstraete, Violaine; Van Tongeren, Martie

2012-11-01

Occupational inadvertent ingestion exposure is ingestion exposure due to contact between the mouth and contaminated hands or objects. Although individuals are typically oblivious to their exposure by this route, it is a potentially significant source of occupational exposure for some substances. Due to the continual flux of saliva through the oral cavity and the non-specificity of biological monitoring to routes of exposure, direct measurement of exposure by the inadvertent ingestion route is challenging; predictive models may be required to assess exposure. The work described in this manuscript has been carried out as part of a project to develop a predictive model for estimating inadvertent ingestion exposure in the workplace. As inadvertent ingestion exposure mainly arises from hand-to-mouth contact, it is closely linked to dermal exposure. We present a new integrated conceptual model for dermal and inadvertent ingestion exposure that should help to increase our understanding of ingestion exposure and our ability to simultaneously estimate exposure by the dermal and ingestion routes. The conceptual model consists of eight compartments (source, air, surface contaminant layer, outer clothing contaminant layer, inner clothing contaminant layer, hands and arms layer, perioral layer, and oral cavity) and nine mass transport processes (emission, deposition, resuspension or evaporation, transfer, removal, redistribution, decontamination, penetration and/or permeation, and swallowing) that describe event-based movement of substances between compartments (e.g. emission, deposition, etc.). This conceptual model is intended to guide the development of predictive exposure models that estimate exposure from both the dermal and the inadvertent ingestion pathways. For exposure by these pathways the efficiency of transfer of materials between compartments (for example from surfaces to hands, or from hands to the mouth) are important determinants of exposure. A database of transfer efficiency data relevant for dermal and inadvertent ingestion exposure was developed, containing 534 empirically measured transfer efficiencies measured between 1980 and 2010 and reported in the peer-reviewed and grey literature. The majority of the reported transfer efficiencies (84%) relate to transfer between surfaces and hands, but the database also includes efficiencies for other transfer scenarios, including surface-to-glove, hand-to-mouth, and skin-to-skin. While the conceptual model can provide a framework for a predictive exposure assessment model, the database provides detailed information on transfer efficiencies between the various compartments. Together, the conceptual model and the database provide a basis for the development of a quantitative tool to estimate inadvertent ingestion exposure in the workplace.
The Comparative Accuracy of Two Hydrologic Models in Simulating Warm-Season Runoff for Two Small, Hillslope Catchments

EPA Science Inventory

Runoff prediction is a cornerstone of water resources planning, and therefore modeling performance is a key issue. This paper investigates the comparative advantages of conceptual versus process- based models in predicting warm season runoff for upland, low-yield micro-catchments...
Applying a Cognitive-Affective Model of Conceptual Change to Professional Development

NASA Astrophysics Data System (ADS)

Ebert, Ellen K.; Crippen, Kent J.

2010-04-01

This study evaluated Gregoire’s (2003) Cognitive-Affective Conceptual Change model (CAMCC) for predicting and assessing conceptual change in science teachers engaged in a long-term professional development project set in a large school district in the southwestern United States. A multiple case study method with data from three teacher participants was used to understand the process of integrating and applying a reform message of inquiry based science teaching. Data sources included: responses to example teaching scenarios, reflective essays, lesson plans, classroom observations, and action research projects. Findings show that the CAMCC functioned well in predicting how these teachers made decisions that impacted how they processed the reform message. When the reform message was communicated in such a way as to initiate stress appraisal, conceptual change occurred, producing changes in classroom practice. If the reform message did not initiate stress appraisal, teachers rejected the professional development message and developed heuristic responses. In order to further research and improve practice, propositions for assessments related to the CAMCC are provided.
The Effect of 3D Computer Modeling and Observation-Based Instruction on the Conceptual Change regarding Basic Concepts of Astronomy in Elementary School Students

ERIC Educational Resources Information Center

Kucukozer, Huseyin; Korkusuz, M. Emin; Kucukozer, H. Asuman; Yurumezoglu, Kemal

2009-01-01

This study has examined the impact of teaching certain basic concepts of astronomy through a predict-observe-explain strategy, which includes three-dimensional (3D) computer modeling and observations on conceptual changes seen in sixth-grade elementary school children (aged 11-13; number of students: 131). A pre- and postastronomy instruction…
The Effects of 3D Computer Modelling on Conceptual Change about Seasons and Phases of the Moon

ERIC Educational Resources Information Center

Kucukozer, Huseyin

2008-01-01

In this study, prospective science teachers' misconceptions about the seasons and the phases of the Moon were determined, and then the effects of 3D computer modelling on their conceptual changes were investigated. The topics were covered in two classes with a total of 76 students using a predict-observe-explain strategy supported by 3D computer…
Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

PubMed

Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

2009-01-01

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.
A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2018-01-01

Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric-oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric-oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.
Three-dimensional conceptual model for the Hanford Site unconfined aquifer system: FY 1994 status report

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

Thorne, P.D.; Chamness, M.A.; Vermeul, V.R.

This report documents work conducted during the fiscal year 1994 to development an improved three-dimensional conceptual model of ground-water flow in the unconfined aquifer system across the Hanford Site Ground-Water Surveillance Project, which is managed by Pacific Northwest Laboratory. The main objective of the ongoing effort to develop an improved conceptual model of ground-water flow is to provide the basis for improved numerical report models that will be capable of accurately predicting the movement of radioactive and chemical contaminant plumes in the aquifer beneath Hanford. More accurate ground-water flow models will also be useful in assessing the impacts of changesmore » in facilities and operations. For example, decreasing volumes of operational waste-water discharge are resulting in a declining water table in parts of the unconfined aquifer. In addition to supporting numerical modeling, the conceptual model also provides a qualitative understanding of the movement of ground water and contaminants in the aquifer.« less

Predicting Phosphorus Dynamics Across Physiographic Regions Using a Mixed Hortonian Non-Hortonian Hydrology Model

NASA Astrophysics Data System (ADS)

Collick, A.; Easton, Z. M.; Auerbach, D.; Buchanan, B.; Kleinman, P. J. A.; Fuka, D.

2017-12-01

Predicting phosphorus (P) loss from agricultural watersheds depends on accurate representation of the hydrological and chemical processes governing P mobility and transport. In complex landscapes, P predictions are complicated by a broad range of soils with and without restrictive layers, a wide variety of agricultural management, and variable hydrological drivers. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict runoff and non-point source pollution transport, but is commonly only used with Hortonian (traditional SWAT) or non-Hortonian (SWAT-VSA) initializations. Many shallow soils underlain by a restricting layer commonly generate saturation excess runoff from variable source areas (VSA), which is well represented in a re-conceptualized version, SWAT-VSA. However, many watersheds exhibit traits of both infiltration excess and saturation excess hydrology internally, based on the hydrologic distance from the stream, distribution of soils across the landscape, and characteristics of restricting layers. The objective of this research is to provide an initial look at integrating distributed predictive capabilities that consider both Hortonian and Non-Hortonian solutions simultaneously within a single SWAT-VSA initialization. We compare results from all three conceptual watershed initializations against measured surface runoff and stream P loads and to highlight the model's ability to drive sub-field management of P. All three initializations predict discharge similarly well (daily Nash-Sutcliffe Efficiencies above 0.5), but the new conceptual SWAT-VSA initialization performed best in predicting P export from the watershed, while also identifying critical source areas - those areas generating large runoff and P losses at the sub field level. These results support the use of mixed Hortonian non-Hortonian SWAT-VSA initializations in predicting watershed-scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology.
Evolutionary Maps: A new model for the analysis of conceptual development, with application to the diurnal cycle

NASA Astrophysics Data System (ADS)

Navarro, Manuel

2014-05-01

This paper presents a model of how children generate concrete concepts from perception through processes of differentiation and integration. The model informs the design of a novel methodology (evolutionary maps or emaps), whose implementation on certain domains unfolds the web of itineraries that children may follow in the construction of concrete conceptual knowledge and pinpoints, for each conception, the architecture of the conceptual change that leads to the scientific concept. Remarkably, the generative character of its syntax yields conceptions that, if unknown, amount to predictions that can be tested experimentally. Its application to the diurnal cycle (including the sun's trajectory in the sky) indicates that the model is correct and the methodology works (in some domains). Specifically, said emap predicts a number of exotic trajectories of the sun in the sky that, in the experimental work, were drawn spontaneously both on paper and a dome. Additionally, the application of the emaps theoretical framework in clinical interviews has provided new insight into other cognitive processes. The field of validity of the methodology and its possible applications to science education are discussed.
Predicting herbicide and biocide concentrations in rivers across Switzerland

NASA Astrophysics Data System (ADS)

Wemyss, Devon; Honti, Mark; Stamm, Christian

2014-05-01

Pesticide concentrations vary strongly in space and time. Accordingly, intensive sampling is required to achieve a reliable quantification of pesticide pollution. As this requires substantial resources, loads and concentration ranges in many small and medium streams remain unknown. Here, we propose partially filling the information gap for herbicides and biocides by using a modelling approach that predicts stream concentrations without site-specific calibration simply based on generally available data like land use, discharge and nation-wide consumption data. The simple, conceptual model distinguishes herbicide losses from agricultural fields, private gardens and biocide losses from buildings (facades, roofs). The herbicide model is driven by river discharge and the applied herbicide mass; the biocide model requires precipitation and the footprint area of urban areas containing the biocide. The model approach allows for modelling concentrations across multiple catchments at the daily, or shorter, time scale and for small to medium-sized catchments (1 - 100 km2). Four high resolution sampling campaigns in the Swiss Plateau were used to calibrate the model parameters for six model compounds: atrazine, metolachlor, terbuthylazine, terbutryn, diuron and mecoprop. Five additional sampled catchments across Switzerland were used to directly compare the predicted to the measured concentrations. Analysis of the first results reveals a reasonable simulation of the concentration dynamics for specific rainfall events and across the seasons. Predicted concentration ranges are reasonable even without site-specific calibration. This indicates the transferability of the calibrated model directly to other areas. However, the results also demonstrate systematic biases in that the highest measured peaks were not attained by the model. Probable causes for these deviations are conceptual model limitations and input uncertainty (pesticide use intensity, local precipitation, etc.). Accordingly, the model will be conceptually improved. This presentation will present the model simulations and compare the performance of the original and the modified model versions. Finally, the model will be applied across approximately 50% of the catchments in the Swiss Plateau, where necessary input data is available and where the model concept can be reasonably applied.
Systems biology as a conceptual framework for research in family medicine; use in predicting response to influenza vaccination.

PubMed

Majnarić-Trtica, Ljiljana; Vitale, Branko

2011-10-01

To introduce systems biology as a conceptual framework for research in family medicine, based on empirical data from a case study on the prediction of influenza vaccination outcomes. This concept is primarily oriented towards planning preventive interventions and includes systematic data recording, a multi-step research protocol and predictive modelling. Factors known to affect responses to influenza vaccination include older age, past exposure to influenza viruses, and chronic diseases; however, constructing useful prediction models remains a challenge, because of the need to identify health parameters that are appropriate for general use in modelling patients' responses. The sample consisted of 93 patients aged 50-89 years (median 69), with multiple medical conditions, who were vaccinated against influenza. Literature searches identified potentially predictive health-related parameters, including age, gender, diagnoses of the main chronic ageing diseases, anthropometric measures, and haematological and biochemical tests. By applying data mining algorithms, patterns were identified in the data set. Candidate health parameters, selected in this way, were then combined with information on past influenza virus exposure to build the prediction model using logistic regression. A highly significant prediction model was obtained, indicating that by using a systems biology approach it is possible to answer unresolved complex medical uncertainties. Adopting this systems biology approach can be expected to be useful in identifying the most appropriate target groups for other preventive programmes.
Conceptual ecological models to guide integrated landscape monitoring of the Great Basin

USGS Publications Warehouse

Miller, D.M.; Finn, S.P.; Woodward, Andrea; Torregrosa, Alicia; Miller, M.E.; Bedford, D.R.; Brasher, A.M.

2010-01-01

The Great Basin Integrated Landscape Monitoring Pilot Project was developed in response to the need for a monitoring and predictive capability that addresses changes in broad landscapes and waterscapes. Human communities and needs are nested within landscapes formed by interactions among the hydrosphere, geosphere, and biosphere. Understanding the complex processes that shape landscapes and deriving ways to manage them sustainably while meeting human needs require sophisticated modeling and monitoring. This document summarizes current understanding of ecosystem structure and function for many of the ecosystems within the Great Basin using conceptual models. The conceptual ecosystem models identify key ecological components and processes, identify external drivers, develop a hierarchical set of models that address both site and landscape attributes, inform regional monitoring strategy, and identify critical gaps in our knowledge of ecosystem function. The report also illustrates an approach for temporal and spatial scaling from site-specific models to landscape models and for understanding cumulative effects. Eventually, conceptual models can provide a structure for designing monitoring programs, interpreting monitoring and other data, and assessing the accuracy of our understanding of ecosystem functions and processes.
COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

PubMed

Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M

2018-02-01

Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).
Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

NASA Astrophysics Data System (ADS)

Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

2017-12-01

Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model. This complex model then serves as the basis to compare simpler model structures. Through this approach, predictive uncertainty can be quantified relative to a known reference solution.
Probabilistic prediction of barrier-island response to hurricanes

USGS Publications Warehouse

Plant, Nathaniel G.; Stockdon, Hilary F.

2012-01-01

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.
The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century

DOE PAGES

Abramoff, Rose; Xu, Xiaofeng; Hartman, Melannie; ...

2017-12-20

Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model—the Millennial model—that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation,more » and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. Finally, we review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. Here, we propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development.« less
The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century

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

Abramoff, Rose; Xu, Xiaofeng; Hartman, Melannie

Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model—the Millennial model—that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation,more » and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. Finally, we review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. Here, we propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development.« less
A Study of Child Variance, Volume 4: The Future; Conceptual Project in Emotional Disturbance.

ERIC Educational Resources Information Center

Rhodes, William C.

Presented in the fourth volume in a series are a discussion of critical issues related to child variance and predictions for how society will perceive and respond to child variance in the future. Reviewed in an introductory chapter are the contents of the first three volumes which deal with conceptual models, interventions, and service delivery…
Ultrasonic nondestructive evaluation, microstructure, and mechanical property interrelations

NASA Technical Reports Server (NTRS)

Vary, A.

1984-01-01

Ultrasonic techniques for mechanical property characterizations are reviewed and conceptual models are advanced for explaining and interpreting the empirically based results. At present, the technology is generally empirically based and is emerging from the research laboratory. Advancement of the technology will require establishment of theoretical foundations for the experimentally observed interrelations among ultrasonic measurements, mechanical properties, and microstructure. Conceptual models are applied to ultrasonic assessment of fracture toughness to illustrate an approach for predicting correlations found among ultrasonic measurements, microstructure, and mechanical properties.
Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level. ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed. Examples of mass property stochastic calculations produced during a recent systems study are provided. This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime, few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.
Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed Examples of mass property stochastic calculations produced during a recent systems study are provided This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime,few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.
Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil.

PubMed

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μ(t), increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ²(t) first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μ(t) estimated from the conceptual model performed much better as compared to predictions with μ(t) and σ²(t) estimated from calibration of solute transport at shallow soil depths. The use of μ(t) estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales. Copyright © 2012 Elsevier B.V. All rights reserved.
Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil

NASA Astrophysics Data System (ADS)

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μt, increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ2t first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μt estimated from the conceptual model performed much better as compared to predictions with μt and σ2t estimated from calibration of solute transport at shallow soil depths. The use of μt estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales.
Plant–herbivore–decomposer stoichiometric mismatches and nutrient cycling in ecosystems

PubMed Central

Cherif, Mehdi; Loreau, Michel

2013-01-01

Plant stoichiometry is thought to have a major influence on how herbivores affect nutrient availability in ecosystems. Most conceptual models predict that plants with high nutrient contents increase nutrient excretion by herbivores, in turn raising nutrient availability. To test this hypothesis, we built a stoichiometrically explicit model that includes a simple but thorough description of the processes of herbivory and decomposition. Our results challenge traditional views of herbivore impacts on nutrient availability in many ways. They show that the relationship between plant nutrient content and the impact of herbivores predicted by conceptual models holds only at high plant nutrient contents. At low plant nutrient contents, the impact of herbivores is mediated by the mineralization/immobilization of nutrients by decomposers and by the type of resource limiting the growth of decomposers. Both parameters are functions of the mismatch between plant and decomposer stoichiometries. Our work provides new predictions about the impacts of herbivores on ecosystem fertility that depend on critical interactions between plant, herbivore and decomposer stoichiometries in ecosystems. PMID:23303537
Preservice Early Childhood Teachers' Learning of Science in a Methods Course: Examining the Predictive Ability of an Intentional Learning Model

ERIC Educational Resources Information Center

Saçkes, Mesut; Trundle, Kathy Cabe

2014-01-01

This study investigated the predictive ability of an intentional learning model in the change of preservice early childhood teachers' conceptual understanding of lunar phases. Fifty-two preservice early childhood teachers who were enrolled in an early childhood science methods course participated in the study. Results indicated that the use…
Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale.

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick

2017-04-01

Motivated by climate change and its impact on the scarcity or excess of water in many parts of the world, several agencies and research institutions have taken initiatives in monitoring and predicting the hydrologic cycle at a global scale. Such a monitoring/prediction effort is important for understanding the vulnerability to extreme hydrological events and for providing early warnings. This can be based on an optimal combination of hydro-meteorological models and remote sensing, in which satellite measurements can be used as forcing or calibration data or for regularly updating the model states or parameters. Many advances have been made in these domains and the near future will bring new opportunities with respect to remote sensing as a result of the increasing number of spaceborn sensors enabling the large scale monitoring of water resources. Besides of these advances, there is currently a tendency to refine and further complicate physically-based hydrologic models to better capture the hydrologic processes at hand. However, this may not necessarily be beneficial for large-scale hydrology, as computational efforts are therefore increasing significantly. As a matter of fact, a novel thematic science question that is to be investigated is whether a flexible conceptual model can match the performance of a complex physically-based model for hydrologic simulations at large scale. In this context, the main objective of this study is to investigate how innovative techniques that allow for the estimation of soil moisture from satellite data can help in reducing errors and uncertainties in large scale conceptual hydro-meteorological modelling. A spatially distributed conceptual hydrologic model has been set up based on recent developments of the SUPERFLEX modelling framework. As it requires limited computational efforts, this model enables early warnings for large areas. Using as forcings the ERA-Interim public dataset and coupled with the CMEM radiative transfer model, SUPERFLEX is capable of predicting runoff, soil moisture, and SMOS-like brightness temperature time series. Such a model is traditionally calibrated using only discharge measurements. In this study we designed a multi-objective calibration procedure based on both discharge measurements and SMOS-derived brightness temperature observations in order to evaluate the added value of remotely sensed soil moisture data in the calibration process. As a test case we set up the SUPERFLEX model for the large scale Murray-Darling catchment in Australia ( 1 Million km2). When compared to in situ soil moisture time series, model predictions show good agreement resulting in correlation coefficients exceeding 70 % and Root Mean Squared Errors below 1 %. When benchmarked with the physically based land surface model CLM, SUPERFLEX exhibits similar performance levels. By adapting the runoff routing function within the SUPERFLEX model, the predicted discharge results in a Nash Sutcliff Efficiency exceeding 0.7 over both the calibration and the validation periods.
A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies and its application to four recent severe regional drought events in China

NASA Astrophysics Data System (ADS)

Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.

2017-12-01

Reliable drought prediction is fundamental for seasonal water management. Considering that drought development is closely related to the spatio-temporal evolution of large-scale circulation patterns, we develop a conceptual prediction model of seasonal drought processes based on atmospheric/oceanic Standardized Anomalies (SA). It is essentially the synchronous stepwise regression relationship between 90-day-accumulated atmospheric/oceanic SA-based predictors and 3-month SPI updated daily (SPI3). It is forced with forecasted atmospheric and oceanic variables retrieved from seasonal climate forecast systems, and it can make seamless drought prediction for operational use after a year-to-year calibration. Simulation and prediction of four severe seasonal regional drought processes in China were forced with the NCEP/NCAR reanalysis datasets and the NCEP Climate Forecast System Version 2 (CFSv2) operationally forecasted datasets, respectively. With the help of real-time correction for operational application, model application during four recent severe regional drought events in China revealed that the model is good at development prediction but weak in severity prediction. In addition to weakness in prediction of drought peak, the prediction of drought relief is possible to be predicted as drought recession. This weak performance may be associated with precipitation-causing weather patterns during drought relief. Based on initial virtual analysis on predicted 90-day prospective SPI3 curves, it shows that the 2009/2010 drought in Southwest China and 2014 drought in North China can be predicted and simulated well even for the prospective 1-75 day. In comparison, the prospective 1-45 day may be a feasible and acceptable lead time for simulation and prediction of the 2011 droughts in Southwest China and East China, after which the simulated and predicted developments clearly change.

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.
Software reliability models for fault-tolerant avionics computers and related topics

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1987-01-01

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.
Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2016-12-01

The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions.
Evaluating the Classical Versus an Emerging Conceptual Model of Peatland Methane Dynamics

NASA Astrophysics Data System (ADS)

Yang, Wendy H.; McNicol, Gavin; Teh, Yit Arn; Estera-Molina, Katerina; Wood, Tana E.; Silver, Whendee L.

2017-09-01

Methane (CH4) is a potent greenhouse gas that is both produced and consumed in soils by microbially mediated processes sensitive to soil redox. We evaluated the classical conceptual model of peatland CH4 dynamics—in which the water table position determines the vertical distribution of methanogenesis and methanotrophy—versus an emerging model in which methanogenesis and methanotrophy can both occur throughout the soil profile due to spatially heterogeneous redox and anaerobic CH4 oxidation. We simultaneously measured gross CH4 production and oxidation in situ across a microtopographical gradient in a drained temperate peatland and ex situ along the soil profile, giving us novel insight into the component fluxes of landscape-level net CH4 fluxes. Net CH4 fluxes varied among landforms (p < 0.001), ranging from 180.3 ± 81.2 mg C m-2 d-1 in drainage ditches to -0.7 ± 1.2 mg C m-2 d-1 in the highest landform. Contrary to prediction by the classical conceptual model, variability in methanogenesis alone drove the landscape-level net CH4 flux patterns. Consistent with the emerging model, freshly collected soils from above the water table produced CH4 within anaerobic microsites. Even in soil from beneath the water table, gross CH4 production was best predicted by the methanogenic fraction of carbon mineralization, an index of highly reducing microsites. We measured low rates of anaerobic CH4 oxidation, which may have been limited by relatively low in situ CH4 concentrations in the hummock/hollow soil profile. Our study revealed complex CH4 dynamics better represented by the emerging heterogeneous conceptual model than the classical model based on redox strata.
Modeling and Predicting Pesticide Exposures

EPA Science Inventory

Models provide a means for representing a real system in an understandable way. They take many forms, beginning with conceptual models that explain the way a system works, such as delineation of all the factors and parameters of how a pesticide particle moves in the air after a s...
Diagnosis of streamflow prediction skills in Oregon using Hydrologic Landscape Classification

EPA Science Inventory

A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...
Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction

NASA Astrophysics Data System (ADS)

Kavetski, Dmitri; Clark, Martyn P.

2010-10-01

Despite the widespread use of conceptual hydrological models in environmental research and operations, they remain frequently implemented using numerically unreliable methods. This paper considers the impact of the time stepping scheme on model analysis (sensitivity analysis, parameter optimization, and Markov chain Monte Carlo-based uncertainty estimation) and prediction. It builds on the companion paper (Clark and Kavetski, 2010), which focused on numerical accuracy, fidelity, and computational efficiency. Empirical and theoretical analysis of eight distinct time stepping schemes for six different hydrological models in 13 diverse basins demonstrates several critical conclusions. (1) Unreliable time stepping schemes, in particular, fixed-step explicit methods, suffer from troublesome numerical artifacts that severely deform the objective function of the model. These deformations are not rare isolated instances but can arise in any model structure, in any catchment, and under common hydroclimatic conditions. (2) Sensitivity analysis can be severely contaminated by numerical errors, often to the extent that it becomes dominated by the sensitivity of truncation errors rather than the model equations. (3) Robust time stepping schemes generally produce "better behaved" objective functions, free of spurious local optima, and with sufficient numerical continuity to permit parameter optimization using efficient quasi Newton methods. When implemented within a multistart framework, modern Newton-type optimizers are robust even when started far from the optima and provide valuable diagnostic insights not directly available from evolutionary global optimizers. (4) Unreliable time stepping schemes lead to inconsistent and biased inferences of the model parameters and internal states. (5) Even when interactions between hydrological parameters and numerical errors provide "the right result for the wrong reason" and the calibrated model performance appears adequate, unreliable time stepping schemes make the model unnecessarily fragile in predictive mode, undermining validation assessments and operational use. Erroneous or misleading conclusions of model analysis and prediction arising from numerical artifacts in hydrological models are intolerable, especially given that robust numerics are accepted as mainstream in other areas of science and engineering. We hope that the vivid empirical findings will encourage the conceptual hydrological community to close its Pandora's box of numerical problems, paving the way for more meaningful model application and interpretation.
Model averaging techniques for quantifying conceptual model uncertainty.

PubMed

Singh, Abhishek; Mishra, Srikanta; Ruskauff, Greg

2010-01-01

In recent years a growing understanding has emerged regarding the need to expand the modeling paradigm to include conceptual model uncertainty for groundwater models. Conceptual model uncertainty is typically addressed by formulating alternative model conceptualizations and assessing their relative likelihoods using statistical model averaging approaches. Several model averaging techniques and likelihood measures have been proposed in the recent literature for this purpose with two broad categories--Monte Carlo-based techniques such as Generalized Likelihood Uncertainty Estimation or GLUE (Beven and Binley 1992) and criterion-based techniques that use metrics such as the Bayesian and Kashyap Information Criteria (e.g., the Maximum Likelihood Bayesian Model Averaging or MLBMA approach proposed by Neuman 2003) and Akaike Information Criterion-based model averaging (AICMA) (Poeter and Anderson 2005). These different techniques can often lead to significantly different relative model weights and ranks because of differences in the underlying statistical assumptions about the nature of model uncertainty. This paper provides a comparative assessment of the four model averaging techniques (GLUE, MLBMA with KIC, MLBMA with BIC, and AIC-based model averaging) mentioned above for the purpose of quantifying the impacts of model uncertainty on groundwater model predictions. Pros and cons of each model averaging technique are examined from a practitioner's perspective using two groundwater modeling case studies. Recommendations are provided regarding the use of these techniques in groundwater modeling practice.
Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Li, Wu; Campbell, Richard; Geiselhart, Karl; Shields, Elwood; Nayani, Sudheer; Shenoy, Rajiv

2009-01-01

This paper documents an integration of engine, plume, and computational fluid dynamics (CFD) analyses in the conceptual design of low-boom supersonic aircraft, using a variable fidelity approach. In particular, the Numerical Propulsion Simulation System (NPSS) is used for propulsion system cycle analysis and nacelle outer mold line definition, and a low-fidelity plume model is developed for plume shape prediction based on NPSS engine data and nacelle geometry. This model provides a capability for the conceptual design of low-boom supersonic aircraft that accounts for plume effects. Then a newly developed process for automated CFD analysis is presented for CFD-based plume and boom analyses of the conceptual geometry. Five test cases are used to demonstrate the integrated engine, plume, and CFD analysis process based on a variable fidelity approach, as well as the feasibility of the automated CFD plume and boom analysis capability.
Evaluating Conceptual Site Models with Multicomponent Reactive Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, Z.; Heffner, D.; Price, V.; Temples, T. J.; Nicholson, T. J.

2005-05-01

Modeling ground-water flow and multicomponent reactive chemical transport is a useful approach for testing conceptual site models and assessing the design of monitoring networks. A graded approach with three conceptual site models is presented here with a field case of tetrachloroethene (PCE) transport and biodegradation near Charleston, SC. The first model assumed a one-layer homogeneous aquifer structure with semi-infinite boundary conditions, in which an analytical solution of the reactive solute transport can be obtained with BIOCHLOR (Aziz et al., 1999). Due to the over-simplification of the aquifer structure, this simulation cannot reproduce the monitoring data. In the second approach we used GMS to develop the conceptual site model, a layer-cake multi-aquifer system, and applied a numerical module (MODFLOW and RT3D within GMS) to solve the flow and reactive transport problem. The results were better than the first approach but still did not fit the plume well because the geological structures were still inadequately defined. In the third approach we developed a complex conceptual site model by interpreting log and seismic survey data with Petra and PetraSeis. We detected a major channel and a younger channel, through the PCE source area. These channels control the local ground-water flow direction and provide a preferential chemical transport pathway. Results using the third conceptual site model agree well with the monitoring concentration data. This study confirms that the bias and uncertainty from inadequate conceptual models are much larger than those introduced from an inadequate choice of model parameter values (Neuman and Wierenga, 2003; Meyer et al., 2004). Numerical modeling in this case provides key insight into the hydrogeology and geochemistry of the field site for predicting contaminant transport in the future. Finally, critical monitoring points and performance indicator parameters are selected for future monitoring to confirm system performance.
Aerodynamic Modeling of Transonic Aircraft Using Vortex Lattice Coupled with Transonic Small Disturbance for Conceptual Design

NASA Technical Reports Server (NTRS)

Chaparro, Daniel; Fujiwara, Gustavo E. C.; Ting, Eric; Nguyen, Nhan

2016-01-01

The need to rapidly scan large design spaces during conceptual design calls for computationally inexpensive tools such as the vortex lattice method (VLM). Although some VLM tools, such as Vorview have been extended to model fully-supersonic flow, VLM solutions are typically limited to inviscid, subcritical flow regimes. Many transport aircraft operate at transonic speeds, which limits the applicability of VLM for such applications. This paper presents a novel approach to correct three-dimensional VLM through coupling of two-dimensional transonic small disturbance (TSD) solutions along the span of an aircraft wing in order to accurately predict transonic aerodynamic loading and wave drag for transport aircraft. The approach is extended to predict flow separation and capture the attenuation of aerodynamic forces due to boundary layer viscosity by coupling the TSD solver with an integral boundary layer (IBL) model. The modeling framework is applied to the NASA General Transport Model (GTM) integrated with a novel control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF).
A-DROP: A predictive model for the formation of oil particle aggregates (OPAs).

PubMed

Zhao, Lin; Boufadel, Michel C; Geng, Xiaolong; Lee, Kenneth; King, Thomas; Robinson, Brian; Fitzpatrick, Faith

2016-05-15

Oil-particle interactions play a major role in removal of free oil from the water column. We present a new conceptual-numerical model, A-DROP, to predict oil amount trapped in oil-particle aggregates. A new conceptual formulation of oil-particle coagulation efficiency is introduced to account for the effects of oil stabilization by particles, particle hydrophobicity, and oil-particle size ratio on OPA formation. A-DROP was able to closely reproduce the oil trapping efficiency reported in experimental studies. The model was then used to simulate the OPA formation in a typical nearshore environment. Modeling results indicate that the increase of particle concentration in the swash zone would speed up the oil-particle interaction process; but the oil amount trapped in OPAs did not correspond to the increase of particle concentration. The developed A-DROP model could become an important tool in understanding the natural removal of oil and developing oil spill countermeasures by means of oil-particle aggregation. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

1998-01-01

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.
Vestibulospinal adaptation to microgravity

NASA Technical Reports Server (NTRS)

Paloski, W. H.

1998-01-01

Human balance control is known to be transiently disrupted after spaceflight; however, the mechanisms responsible for postflight postural ataxia are still under investigation. In this report, we propose a conceptual model of vestibulospinal adaptation based on theoretical adaptive control concepts and supported by the results from a comprehensive study of balance control recovery after spaceflight. The conceptual model predicts that immediately after spaceflight the balance control system of a returning astronaut does not expect to receive gravity-induced afferent inputs and that descending vestibulospinal control of balance is disrupted until the central nervous system is able to cope with the newly available vestibular otolith information. Predictions of the model are tested using data from a study of the neurosensory control of balance in astronauts immediately after landing. In that study, the mechanisms of sensorimotor balance control were assessed under normal, reduced, and/or altered (sway-referenced) visual and somatosensory input conditions. We conclude that the adaptive control model accurately describes the neurobehavioral responses to spaceflight and that similar models of altered sensory, motor, or environmental constraints are needed clinically to predict responses that patients with sensorimotor pathologies may have to various visual-vestibular or changing stimulus environments.
ATMOSPHERIC DISPERSAL AND DEPOSITION OF TEPHRA FROM A POTENTIAL VOLCANIC ERUPTION AT YUCCA MOUNTAIN, NEVADA

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

C. Harrington

2004-10-25

The purpose of this model report is to provide documentation of the conceptual and mathematical model (Ashplume) for atmospheric dispersal and subsequent deposition of ash on the land surface from a potential volcanic eruption at Yucca Mountain, Nevada. This report also documents the ash (tephra) redistribution conceptual model. These aspects of volcanism-related dose calculation are described in the context of the entire igneous disruptive events conceptual model in ''Characterize Framework for Igneous Activity'' (BSC 2004 [DIRS 169989], Section 6.1.1). The Ashplume conceptual model accounts for incorporation and entrainment of waste fuel particles associated with a hypothetical volcanic eruption through themore » Yucca Mountain repository and downwind transport of contaminated tephra. The Ashplume mathematical model describes the conceptual model in mathematical terms to allow for prediction of radioactive waste/ash deposition on the ground surface given that the hypothetical eruptive event occurs. This model report also describes the conceptual model for tephra redistribution from a basaltic cinder cone. Sensitivity analyses and model validation activities for the ash dispersal and redistribution models are also presented. Analyses documented in this model report update the previous documentation of the Ashplume mathematical model and its application to the Total System Performance Assessment (TSPA) for the License Application (TSPA-LA) igneous scenarios. This model report also documents the redistribution model product outputs based on analyses to support the conceptual model. In this report, ''Ashplume'' is used when referring to the atmospheric dispersal model and ''ASHPLUME'' is used when referencing the code of that model. Two analysis and model reports provide direct inputs to this model report, namely ''Characterize Eruptive Processes at Yucca Mountain, Nevada and Number of Waste Packages Hit by Igneous Intrusion''. This model report provides direct inputs to the TSPA, which uses the ASHPLUME software described and used in this model report. Thus, ASHPLUME software inputs are inputs to this model report for ASHPLUME runs in this model report. However, ASHPLUME software inputs are outputs of this model report for ASHPLUME runs by TSPA.« less
Large-Scale Transport Model Uncertainty and Sensitivity Analysis: Distributed Sources in Complex Hydrogeologic Systems

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

Sig Drellack, Lance Prothro

2007-12-01

The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result ofmore » the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The simulations are challenged by the distributed sources in each of the Corrective Action Units, by complex mass transfer processes, and by the size and complexity of the field-scale flow models. An efficient methodology utilizing particle tracking results and convolution integrals provides in situ concentrations appropriate for Monte Carlo analysis. Uncertainty in source releases and transport parameters including effective porosity, fracture apertures and spacing, matrix diffusion coefficients, sorption coefficients, and colloid load and mobility are considered. With the distributions of input uncertainties and output plume volumes, global analysis methods including stepwise regression, contingency table analysis, and classification tree analysis are used to develop sensitivity rankings of parameter uncertainties for each model considered, thus assisting a variety of decisions.« less
Drugs and Crime: An Empirically Based, Interdisciplinary Model

ERIC Educational Resources Information Center

Quinn, James F.; Sneed, Zach

2008-01-01

This article synthesizes neuroscience findings with long-standing criminological models and data into a comprehensive explanation of the relationship between drug use and crime. The innate factors that make some people vulnerable to drug use are conceptually similar to those that predict criminality, supporting a spurious reciprocal model of the…
Stage-structured matrix models for organisms with non-geometric development times

Treesearch

Andrew Birt; Richard M. Feldman; David M. Cairns; Robert N. Coulson; Maria Tchakerian; Weimin Xi; James M. Guldin

2009-01-01

Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model...
Beyond the three-component model of organizational commitment.

PubMed

Solinger, Omar N; van Olffen, Woody; Roe, Robert A

2008-01-01

This article offers a conceptual critique of the three-component model (TCM) of organizational commitment (Allen & Meyer, 1990) and proposes a reconceptualization based on standard attitude theory. The authors use the attitude-behavior model by Eagly and Chaiken (1993) to demonstrate that the TCM combines fundamentally different attitudinal phenomena. They argue that general organizational commitment can best be understood as an attitude regarding the organization, while normative and continuance commitment are attitudes regarding specific forms of behavior (i.e., staying or leaving). The conceptual analysis shows that the TCM fails to qualify as general model of organizational commitment but instead represents a specific model for predicting turnover. The authors suggest that the use of the TCM be restricted to this purpose and that Eagly and Chaiken's model be adopted as a generic commitment model template from which a range of models for predicting specific organizational behaviors can be extracted. Finally, they discuss the definition and measurement of the organizational commitment attitude. Covering the affective, cognitive, and behavioral facets of this attitude helps to enhance construct validity and to differentiate the construct from other constructs. 2008 APA
Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

Wildfire ignition-distribution modelling: a comparative study in the Huron-Manistee National Forest, Michigan, USA

Treesearch

Avi Bar Massada; Alexandra D. Syphard; Susan I. Stewart; Volker C. Radeloff

2012-01-01

Wildfire ignition distribution models are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar species-distribution models...
Conceptualizing and Communicating River Restoration

NASA Astrophysics Data System (ADS)

Jacobosn, R. B.

2007-12-01

River restoration increasingly involves collaboration with stakeholders having diverse values and varying technical understanding. In cases where river restoration proceeds through collaborative processes, scientists are required to communicate complex understanding about riverine ecosystem processes to broad audiences. Of particular importance is communication of uncertainties in predictions of ecosystem responses to restoration actions, and how those uncertainties affect monitoring and evaluation strategies. I present a relatively simple conceptual model of how riverine ecosystems operate. The model, which has been used to conceptualize and communicate various river-restoration and management processes in the Lower Missouri River, emphasizes a) the interdependencies of driving regimes (for example, flow, sediment, and water quality), b) the filtering effect of management history, c) the typical hierarchical nature of information about how ecosystems operate, and d) how scientific understanding interacts with decision making. I provide an example of how the conceptual model has been used to illustrate the effects of extensive channel re-engineering of the Lower Missouri River which is intended to mitigate the effects of channelization and flow regulation on aquatic and flood-plain ecosystems. The conceptual model illustrates the logic for prioritizing investments in monitoring and evaluation, interactions among ecosystem components, tradeoffs between ecological and social-commercial benefits, and the feedback loop necessary for successful adaptive management.
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty

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

Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.

2004-03-01

The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates basedmore » on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four projections, and associated kriging variances, were averaged using the posterior model probabilities as weights. Finally, cross-validation was conducted by eliminating from consideration all data from one borehole at a time, repeating the above process, and comparing the predictive capability of the model-averaged result with that of each individual model. Using two quantitative measures of comparison, the model-averaged result was superior to any individual geostatistical model of log permeability considered.« less
Dysregulated Fear in Toddlerhood Predicts Kindergarten Social Withdrawal through Protective Parenting

ERIC Educational Resources Information Center

Kiel, Elizabeth J.; Buss, Kristin A.

2014-01-01

Two recent advances in the study of fearful temperament (behavioural inhibition) include the validation of dysregulated fear as a temperamental construct that more specifically predicts later social withdrawal and anxiety, and the use of conceptual and statistical models that place parenting as a mechanism of development from temperament to these…
Transient Inverse Calibration of Site-Wide Groundwater Model to Hanford Operational Impacts from 1943 to 1996--Alternative Conceptual Model Considering Interaction with Uppermost Basalt Confined Aquifer

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

Vermeul, Vincent R.; Cole, Charles R.; Bergeron, Marcel P.

2001-08-29

The baseline three-dimensional transient inverse model for the estimation of site-wide scale flow parameters, including their uncertainties, using data on the transient behavior of the unconfined aquifer system over the entire historical period of Hanford operations, has been modified to account for the effects of basalt intercommunication between the Hanford unconfined aquifer and the underlying upper basalt confined aquifer. Both the baseline and alternative conceptual models (ACM-1) considered only the groundwater flow component and corresponding observational data in the 3-Dl transient inverse calibration efforts. Subsequent efforts will examine both groundwater flow and transport. Comparisons of goodness of fit measures andmore » parameter estimation results for the ACM-1 transient inverse calibrated model with those from previous site-wide groundwater modeling efforts illustrate that the new 3-D transient inverse model approach will strengthen the technical defensibility of the final model(s) and provide the ability to incorporate uncertainty in predictions related to both conceptual model and parameter uncertainty. These results, however, indicate that additional improvements are required to the conceptual model framework. An investigation was initiated at the end of this basalt inverse modeling effort to determine whether facies-based zonation would improve specific yield parameter estimation results (ACM-2). A description of the justification and methodology to develop this zonation is discussed.« less
A Conceptual Framework for Predicting the Toxicity of Reactive Chemicals: Modeling Soft Electrophilicity

EPA Science Inventory

Although the literature is replete with QSAR models developed for many toxic effects caused by reversible chemical interactions, the development of QSARs for the toxic effects of reactive chemicals lacks a consistent approach. While limitations exit, an appropriate starting-point...
Group-level self-definition and self-investment: a hierarchical (multicomponent) model of in-group identification.

PubMed

Leach, Colin Wayne; van Zomeren, Martijn; Zebel, Sven; Vliek, Michael L W; Pennekamp, Sjoerd F; Doosje, Bertjan; Ouwerkerk, Jaap W; Spears, Russell

2008-07-01

Recent research shows individuals' identification with in-groups to be psychologically important and socially consequential. However, there is little agreement about how identification should be conceptualized or measured. On the basis of previous work, the authors identified 5 specific components of in-group identification and offered a hierarchical 2-dimensional model within which these components are organized. Studies 1 and 2 used confirmatory factor analysis to validate the proposed model of self-definition (individual self-stereotyping, in-group homogeneity) and self-investment (solidarity, satisfaction, and centrality) dimensions, across 3 different group identities. Studies 3 and 4 demonstrated the construct validity of the 5 components by examining their (concurrent) correlations with established measures of in-group identification. Studies 5-7 demonstrated the predictive and discriminant validity of the 5 components by examining their (prospective) prediction of individuals' orientation to, and emotions about, real intergroup relations. Together, these studies illustrate the conceptual and empirical value of a hierarchical multicomponent model of in-group identification.
The importance of conceptual models in the reactive transport simulation of oxygen ingress in sparsely fractured crystalline rock.

PubMed

Macquarrie, K T B; Mayer, K U; Jin, B; Spiessl, S M

2010-03-01

Redox evolution in sparsely fractured crystalline rocks is a key, and largely unresolved, issue when assessing the geochemical suitability of deep geological repositories for nuclear waste. Redox zonation created by the influx of oxygenated waters has previously been simulated using reactive transport models that have incorporated a variety of processes, resulting in predictions for the depth of oxygen penetration that may vary greatly. An assessment and direct comparison of the various underlying conceptual models are therefore needed. In this work a reactive transport model that considers multiple processes in an integrated manner is used to investigate the ingress of oxygen for both single fracture and fracture zone scenarios. It is shown that the depth of dissolved oxygen migration is greatly influenced by the a priori assumptions that are made in the conceptual models. For example, the ability of oxygen to access and react with minerals in the rock matrix may be of paramount importance for single fracture conceptual models. For fracture zone systems, the abundance and reactivity of minerals within the fractures and thin matrix slabs between the fractures appear to provide key controls on O(2) attenuation. The findings point to the need for improved understanding of the coupling between the key transport-reaction feedbacks to determine which conceptual models are most suitable and to provide guidance for which parameters should be targeted in field and laboratory investigations. Copyright 2009 Elsevier B.V. All rights reserved.
Developing rural palliative care: validating a conceptual model.

PubMed

Kelley, Mary Lou; Williams, Allison; DeMiglio, Lily; Mettam, Hilary

2011-01-01

The purpose of this research was to validate a conceptual model for developing palliative care in rural communities. This model articulates how local rural healthcare providers develop palliative care services according to four sequential phases. The model has roots in concepts of community capacity development, evolves from collaborative, generalist rural practice, and utilizes existing health services infrastructure. It addresses how rural providers manage challenges, specifically those related to: lack of resources, minimal community understanding of palliative care, health professionals' resistance, the bureaucracy of the health system, and the obstacles of providing services in rural environments. Seven semi-structured focus groups were conducted with interdisciplinary health providers in 7 rural communities in two Canadian provinces. Using a constant comparative analysis approach, focus group data were analyzed by examining participants' statements in relation to the model and comparing emerging themes in the development of rural palliative care to the elements of the model. The data validated the conceptual model as the model was able to theoretically predict and explain the experiences of the 7 rural communities that participated in the study. New emerging themes from the data elaborated existing elements in the model and informed the requirement for minor revisions. The model was validated and slightly revised, as suggested by the data. The model was confirmed as being a useful theoretical tool for conceptualizing the development of rural palliative care that is applicable in diverse rural communities.
Race and Gender Matter: A Multidimensional Approach to Conceptualizing and Measuring Stress in African American Women

PubMed Central

Woods-Giscombé, Cheryl L.; Lobel, Marci

2008-01-01

Based on prior research and theory, the authors constructed a multidimensional model of stress in African American women comprised of race-related, gender-related, and generic stress. Exposure to and appraisal of these three types of stress were combined into a higher-order global stress factor. Using structural equation modeling, the fit of this stress factor and its ability to predict distress symptoms were examined in 189 socioeconomically diverse African American women aged 21 to 78. Results support the multidimensional conceptualization and operationalization of stress. Race-related, gender-related, and generic stress contributed equally to the global stress factor, and global stress predicted a significant amount of variance in distress symptoms and intensity. This model exhibited better fit than a model without a global stress factor, in which each stress component predicted distress directly. Furthermore, race-related, gender-related, and generic stress did not contribute to distress beyond their representation in the global stress factor. These findings illustrate that stress related to central elements of identity, namely race and gender, cohere with generic stress to define the stress experience of African American women. PMID:18624581
Race and gender matter: a multidimensional approach to conceptualizing and measuring stress in African American women.

PubMed

Woods-Giscombé, Cheryl L; Lobel, Marci

2008-07-01

Based on prior research and theory, the authors constructed a multidimensional model of stress in African American women comprised of race-related, gender-related, and generic stress. Exposure to and appraisal of these three types of stress were combined into a higher-order global stress factor. Using structural equation modeling, the fit of this stress factor and its ability to predict distress symptoms were examined in 189 socioeconomically diverse African American women aged 21 to 78. Results support the multidimensional conceptualization and operationalization of stress. Race-related, gender-related, and generic stress contributed equally to the global stress factor, and global stress predicted a significant amount of variance in distress symptoms and intensity. This model exhibited better fit than a model without a global stress factor, in which each stress component predicted distress directly. Furthermore, race-related, gender-related, and generic stress did not contribute to distress beyond their representation in the global stress factor. These findings illustrate that stress related to central elements of identity, namely race and gender, cohere with generic stress to define the stress experience of African American women. Copyright (c) 2008 APA, all rights reserved.
Improved Aerodynamic Analysis for Hybrid Wing Body Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2012-01-01

This paper provides an overview of ongoing efforts to develop, evaluate, and validate different tools for improved aerodynamic modeling and systems analysis of Hybrid Wing Body (HWB) aircraft configurations. Results are being presented for the evaluation of different aerodynamic tools including panel methods, enhanced panel methods with viscous drag prediction, and computational fluid dynamics. Emphasis is placed on proper prediction of aerodynamic loads for structural sizing as well as viscous drag prediction to develop drag polars for HWB conceptual design optimization. Data from transonic wind tunnel tests at the Arnold Engineering Development Center s 16-Foot Transonic Tunnel was used as a reference data set in order to evaluate the accuracy of the aerodynamic tools. Triangularized surface data and Vehicle Sketch Pad (VSP) models of an X-48B 2% scale wind tunnel model were used to generate input and model files for the different analysis tools. In support of ongoing HWB scaling studies within the NASA Environmentally Responsible Aviation (ERA) program, an improved finite element based structural analysis and weight estimation tool for HWB center bodies is currently under development. Aerodynamic results from these analyses are used to provide additional aerodynamic validation data.
Conceptual Model for Basement and Surface Structure Relationships in an Oblique Collision, Sawtooth Range, MT

NASA Astrophysics Data System (ADS)

Palu, J. M.; Burberry, C. M.

2014-12-01

The reactivation potential of pre-existing basement structures affects the geometry of subsequent deformation structures. A conceptual model depicting the results of these interactions can be applied to multiple fold-thrust systems and lead to valuable deformation predictions. These predictions include the potential for hydrocarbon traps or seismic risk in an actively deforming area. The Sawtooth Range, Montana, has been used as a study area. A model for the development of structures close to the Augusta Syncline in the Sawtooth Range is being developed using: 1) an ArcGIS map of the basement structures of the belt based on analysis of geophysical data indicating gravity anomalies and aeromagnetic lineations, seismic data indicating deformation structures, and well logs for establishing lithologies, previously collected by others and 2) an ArcGIS map of the surface deformation structures of the belt based on interpretation of remote sensing images and verification through the collection of surface field data indicating stress directions and age relationships, resulting in a conceptual model based on the understanding of the interaction of the two previous maps including statistical correlations of data and development of balanced cross-sections using Midland Valley's 2D/3D Move software. An analysis of the model will then indicate viable deformation paths where prominent basement structures influenced subsequently developed deformation structures and reactivated faults. Preliminary results indicate that the change in orientation of thrust faults observed in the Sawtooth Range, from a NNW-SSE orientation near the Gibson Reservoir to a WNW-ESE trend near Haystack Butte correlates with pre-existing deformation structures lying within the Great Falls Tectonic Zone. The Scapegoat-Bannatyne trend appears to be responsible for this orientation change and rather than being a single feature, may be composed of up to 4 NE-SW oriented basement strike-slip faults. This indicates that the pre-existing basement features have a profound effect on the geometry of the later deformation. This conceptual model can also be applied to other deformed belts to provide a prediction for the potential hydrocarbon trap locations of the belt as well as their seismic risk.
Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.
Body composition, muscle capacity, and physical function in older adults: an integrated conceptual model.

PubMed

Brady, Anne O; Straight, Chad R; Evans, Ellen M

2014-07-01

The aging process leads to adverse changes in body composition (increases in fat mass and decreases in skeletal muscle mass), declines in physical function (PF), and ultimately increased risk for disability and loss of independence. Specific components of body composition or muscle capacity (strength and power) may be useful in predicting PF; however, findings have been mixed regarding the most salient predictor of PF. The development of a conceptual model potentially aids in understanding the interrelated factors contributing to PF with the factors of interest being physical activity, body composition, and muscle capacity. This article also highlights sex differences in these domains. Finally, factors known to affect PF, such as sleep, depression, fatigue, and self-efficacy, are discussed. Development of a comprehensive conceptual model is needed to better characterize the most salient factors contributing to PF and to subsequently inform the development of interventions to reduce physical disability in older adults.
FOOTPRINT: A New Tool to Predict the Potential Impact of Biofuels on BTEX Plumes

EPA Science Inventory

Ahsanuzzaman et al. (2008) used the Deeb et al. (2002) conceptual model to construct a simple screening model to estimate the area of a plume of benzene produced from a release of gasoline containing ethanol. The screening model estimates the plume area, or footprint of the plum...
Mathematical Modelling in the Junior Secondary Years: An Approach Incorporating Mathematical Technology

ERIC Educational Resources Information Center

Lowe, James; Carter, Merilyn; Cooper, Tom

2018-01-01

Mathematical models are conceptual processes that use mathematics to describe, explain, and/or predict the behaviour of complex systems. This article is written for teachers of mathematics in the junior secondary years (including out-of-field teachers of mathematics) who may be unfamiliar with mathematical modelling, to explain the steps involved…
Optimal observation network design for conceptual model discrimination and uncertainty reduction

NASA Astrophysics Data System (ADS)

Pham, Hai V.; Tsai, Frank T.-C.

2016-02-01

This study expands the Box-Hill discrimination function to design an optimal observation network to discriminate conceptual models and, in turn, identify a most favored model. The Box-Hill discrimination function measures the expected decrease in Shannon entropy (for model identification) before and after the optimal design for one additional observation. This study modifies the discrimination function to account for multiple future observations that are assumed spatiotemporally independent and Gaussian-distributed. Bayesian model averaging (BMA) is used to incorporate existing observation data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. In addition, the BMA method is adopted to predict future observation data in a statistical sense. The design goal is to find optimal locations and least data via maximizing the Box-Hill discrimination function value subject to a posterior model probability threshold. The optimal observation network design is illustrated using a groundwater study in Baton Rouge, Louisiana, to collect additional groundwater heads from USGS wells. The sources of uncertainty creating multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. Impacts of considering homoscedastic and heteroscedastic future observation data and the sources of uncertainties on potential observation areas are analyzed. Results show that heteroscedasticity should be considered in the design procedure to account for various sources of future observation uncertainty. After the optimal design is obtained and the corresponding data are collected for model updating, total variances of head predictions can be significantly reduced by identifying a model with a superior posterior model probability.
Interplay Between Conceptual Expectations and Movement Predictions Underlies Action Understanding.

PubMed

Ondobaka, Sasha; de Lange, Floris P; Wittmann, Marco; Frith, Chris D; Bekkering, Harold

2015-09-01

Recent accounts of understanding goal-directed action underline the importance of a hierarchical predictive architecture. However, the neural implementation of such an architecture remains elusive. In the present study, we used functional neuroimaging to quantify brain activity associated with predicting physical movements, as they were modulated by conceptual-expectations regarding the purpose of the object involved in the action. Participants observed object-related actions preceded by a cue that generated both conceptual goal expectations and movement goal predictions. In 2 tasks, observers judged whether conceptual or movement goals matched or mismatched the cue. At the conceptual level, expected goals specifically recruited the posterior cingulate cortex, irrespectively of the task and the perceived movement goal. At the movement level, neural activation of the parieto-frontal circuit, including inferior frontal gyrus and the inferior parietal lobe, reflected unpredicted movement goals. Crucially, this movement prediction error was only present when the purpose of the involved object was expected. These findings provide neural evidence that prior conceptual expectations influence processing of physical movement goals and thereby support the hierarchical predictive account of action processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Fracture control of ground water flow and water chemistry in a rock aquitard.

PubMed

Eaton, Timothy T; Anderson, Mary P; Bradbury, Kenneth R

2007-01-01

There are few studies on the hydrogeology of sedimentary rock aquitards although they are important controls in regional ground water flow systems. We formulate and test a three-dimensional (3D) conceptual model of ground water flow and hydrochemistry in a fractured sedimentary rock aquitard to show that flow dynamics within the aquitard are more complex than previously believed. Similar conceptual models, based on regional observations and recently emerging principles of mechanical stratigraphy in heterogeneous sedimentary rocks, have previously been applied only to aquifers, but we show that they are potentially applicable to aquitards. The major elements of this conceptual model, which is based on detailed information from two sites in the Maquoketa Formation in southeastern Wisconsin, include orders of magnitude contrast between hydraulic diffusivity (K/S(s)) of fractured zones and relatively intact aquitard rock matrix, laterally extensive bedding-plane fracture zones extending over distances of over 10 km, very low vertical hydraulic conductivity of thick shale-rich intervals of the aquitard, and a vertical hydraulic head profile controlled by a lateral boundary at the aquitard subcrop, where numerous surface water bodies dominate the shallow aquifer system. Results from a 3D numerical flow model based on this conceptual model are consistent with field observations, which did not fit the typical conceptual model of strictly vertical flow through an aquitard. The 3D flow through an aquitard has implications for predicting ground water flow and for planning and protecting water supplies.

Fracture control of ground water flow and water chemistry in a rock aquitard

USGS Publications Warehouse

Eaton, T.T.; Anderson, M.P.; Bradbury, K.R.

2007-01-01

There are few studies on the hydrogeology of sedimentary rock aquitards although they are important controls in regional ground water flow systems. We formulate and test a three-dimensional (3D) conceptual model of ground water flow and hydrochemistry in a fractured sedimentary rock aquitard to show that flow dynamics within the aquitard are more complex than previously believed. Similar conceptual models, based on regional observations and recently emerging principles of mechanical stratigraphy in heterogeneous sedimentary rocks, have previously been applied only to aquifers, but we show that they are potentially applicable to aquitards. The major elements of this conceptual model, which is based on detailed information from two sites in the Maquoketa Formation in southeastern Wisconsin, include orders of magnitude contrast between hydraulic diffusivity (K/Ss) of fractured zones and relatively intact aquitard rock matrix, laterally extensive bedding-plane fracture zones extending over distances of over 10 km, very low vertical hydraulic conductivity of thick shale-rich intervals of the aquitard, and a vertical hydraulic head profile controlled by a lateral boundary at the aquitard subcrop, where numerous surface water bodies dominate the shallow aquifer system. Results from a 3D numerical flow model based on this conceptual model are consistent with field observations, which did not fit the typical conceptual model of strictly vertical flow through an aquitard. The 3D flow through an aquitard has implications for predicting ground water flow and for planning and protecting water supplies. ?? 2007 National Ground Water Association.
Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.
Outrage Management in Cases of Sexual Harassment as Revealed in Judicial Decisions

ERIC Educational Resources Information Center

McDonald, Paula; Graham, Tina; Martin, Brian

2010-01-01

Sexual harassment can be conceptualized as a series of interactions between harassers and targets that either inhibit or increase outrage by third parties. The outrage management model predicts the kinds of actions likely to be used by perpetrators to minimize outrage, predicts the consequences of failing to use these tactics--namely backfire, and…
Predicting Binge Drinking in College Students: Rational Beliefs, Stress, or Loneliness?

ERIC Educational Resources Information Center

Chen, Yixin; Feeley, Thomas Hugh

2015-01-01

We proposed a conceptual model to predict binge-drinking behavior among college students, based on the theory of planned behavior and the stress-coping hypothesis. A two-wave online survey was conducted with predictors and drinking behavior measured separately over 2 weeks' time. In the Wave 1 survey, 279 students at a public university in the…
Distinctive Features Hold a Privileged Status in the Computation of Word Meaning: Implications for Theories of Semantic Memory

ERIC Educational Resources Information Center

Cree, George S.; McNorgan, Chris; McRae, Ken

2006-01-01

The authors present data from 2 feature verification experiments designed to determine whether distinctive features have a privileged status in the computation of word meaning. They use an attractor-based connectionist model of semantic memory to derive predictions for the experiments. Contrary to central predictions of the conceptual structure…
A Conceptual Framework for SAHRA Integrated Multi-resolution Modeling in the Rio Grande Basin

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Springer, E.; Wagener, T.; Brookshire, D.; Duffy, C.

2004-12-01

The sustainable management of water resources in a river basin requires an integrated analysis of the social, economic, environmental and institutional dimensions of the problem. Numerical models are commonly used for integration of these dimensions and for communication of the analysis results to stakeholders and policy makers. The National Science Foundation Science and Technology Center for Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA) has been developing integrated multi-resolution models to assess impacts of climate variability and land use change on water resources in the Rio Grande Basin. These models not only couple natural systems such as surface and ground waters, but will also include engineering, economic and social components that may be involved in water resources decision-making processes. This presentation will describe the conceptual framework being developed by SAHRA to guide and focus the multiple modeling efforts and to assist the modeling team in planning, data collection and interpretation, communication, evaluation, etc. One of the major components of this conceptual framework is a Conceptual Site Model (CSM), which describes the basin and its environment based on existing knowledge and identifies what additional information must be collected to develop technically sound models at various resolutions. The initial CSM is based on analyses of basin profile information that has been collected, including a physical profile (e.g., topographic and vegetative features), a man-made facility profile (e.g., dams, diversions, and pumping stations), and a land use and ecological profile (e.g., demographics, natural habitats, and endangered species). Based on the initial CSM, a Conceptual Physical Model (CPM) is developed to guide and evaluate the selection of a model code (or numerical model) for each resolution to conduct simulations and predictions. A CPM identifies, conceptually, all the physical processes and engineering and socio-economic activities occurring (or to occur) in the real system that the corresponding numerical models are required to address, such as riparian evapotranspiration responses to vegetation change and groundwater pumping impacts on soil moisture contents. Simulation results from different resolution models and observations of the real system will then be compared to evaluate the consistency among the CSM, the CPMs, and the numerical models, and feedbacks will be used to update the models. In a broad sense, the evaluation of the models (conceptual or numerical), as well as the linkages between them, can be viewed as a part of the overall conceptual framework. As new data are generated and understanding improves, the models will evolve, and the overall conceptual framework is refined. The development of the conceptual framework becomes an on-going process. We will describe the current state of this framework and the open questions that have to be addressed in the future.
Communication Efficacy and Couples’ Cancer Management: Applying a Dyadic Appraisal Model

PubMed Central

Magsamen-Conrad, Kate; Checton, Maria G.; Venetis, Maria K.; Greene, Kathryn

2014-01-01

The purpose of the present study was to apply Berg and Upchurch’s (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients’ confidence in their ability to talk about the cancer predicted their own cancer management. Partners’ confidence predicted their own and the patient’s ability to cope with cancer, which then predicted patients’ perceptions of their general health. Implications and future research are discussed. PMID:25983382
Communication Efficacy and Couples' Cancer Management: Applying a Dyadic Appraisal Model.

PubMed

Magsamen-Conrad, Kate; Checton, Maria G; Venetis, Maria K; Greene, Kathryn

2015-06-01

The purpose of the present study was to apply Berg and Upchurch's (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients' confidence in their ability to talk about the cancer predicted their own cancer management. Partners' confidence predicted their own and the patient's ability to cope with cancer, which then predicted patients' perceptions of their general health. Implications and future research are discussed.
Enhanced capabilities and modified users manual for axial-flow compressor conceptual design code CSPAN

NASA Technical Reports Server (NTRS)

Glassman, Arthur J.; Lavelle, Thomas M.

1995-01-01

Modifications made to the axial-flow compressor conceptual design code CSPAN are documented in this report. Endwall blockage and stall margin predictions were added. The loss-coefficient model was upgraded. Default correlations for rotor and stator solidity and aspect-ratio inputs and for stator-exit tangential velocity inputs were included in the code along with defaults for aerodynamic design limits. A complete description of input and output along with sample cases are included.
The relationship between obsessive beliefs and symptom dimensions in obsessive-compulsive disorder.

PubMed

Wheaton, Michael G; Abramowitz, Jonathan S; Berman, Noah C; Riemann, Bradley C; Hale, Lisa R

2010-10-01

Research findings on the specific relationships between beliefs and OCD symptoms have been inconsistent, yet the existing studies vary in their approach to measuring the highly heterogeneous symptoms of this disorder. The Dimensional Obsessive-Compulsive Scale (DOCS) is a new measure that allows for the assessment of OCD symptom dimensions, rather than types of obsessions and compulsions per se. The present study examined the relationship between OCD symptom dimensions and dysfunctional (obsessive) beliefs believed to underlie these symptom dimensions using a large clinical sample of treatment-seeking adults with OCD. Results revealed that certain obsessive beliefs predicted certain OCD symptom dimensions in a manner consistent with cognitive-behavioral conceptual models. Specifically, contamination symptoms were predicted by responsibility/threat estimation beliefs, symmetry symptoms were predicted by perfectionism/certainty beliefs, unacceptable thoughts were predicted by importance/control of thoughts beliefs and symptoms related to being responsible for harm were predicted by responsibility/threat estimation beliefs. Implications for cognitive conceptualizations of OCD symptom dimensions are discussed. Copyright 2010 Elsevier Ltd. All rights reserved.
Difficulties associated with predicting forage intake by grazing beef cows

USDA-ARS?s Scientific Manuscript database

The current National Research Council (NRC) model is based on a single equation that relates dry matter intake (DMI) to metabolic size and net energy density of the diet offered and was a significant improvement over previous models. However, observed DMI by grazing animals can be conceptualized by...
Where and why do models fail? Perspectives from Oregon Hydrologic Landscape classification

EPA Science Inventory

A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...
Cognitive-Affective Predictors of Women's Readiness to End Domestic Violence Relationships

ERIC Educational Resources Information Center

Shurman, Lauren A.; Rodriguez, Christina M.

2006-01-01

A model of women's readiness to terminate an abusive relationship was examined, using cognitive and emotional factors to predict readiness to change as conceptualized in the transtheoretical model. Factors previously identified in the domestic violence literature were selected to represent cognitive predictors (attribution and attachment style)…
Parental Morality and Family Processes as Predictors of Adolescent Morality

ERIC Educational Resources Information Center

White, Fiona A.; Matawie, Kenan M.

2004-01-01

This study investigated the extent to which parents' moral thought and family processes are involved in the socialization of adolescent moral thought. Olson et al's (1992) Circumplex Model and White's (2000) Family Socialization Model provided the conceptual framework for predicting that families high in cohesion, adaptability and communication…
Coupling groundwater and riparian vegetation models to assess effects of reservoir releases

USGS Publications Warehouse

Springer, Abraham E.; Wright, Julie M.; Shafroth, Patrick B.; Stromberg, Juliet C.; Patten, Duncan T.

1999-01-01

Although riparian areas in the arid southwestern United States are critical for maintaining species diversity, their extent and health have been declining since Euro‐American settlement. The purpose of this study was to develop a methodology to evaluate the potential for riparian vegetation restoration and groundwater recharge. A numerical groundwater flow model was coupled with a conceptual riparian vegetation model to predict hydrologic conditions favorable to maintaining riparian vegetation downstream of a reservoir. A Geographic Information System (GIS) was used for this one‐way coupling. Constant and seasonally varying releases from the dam were simulated using volumes anticipated to be permitted by a regional water supplier. Simulations indicated that seasonally variable releases would produce surface flow 5.4–8.5 km below the dam in a previously dry reach. Using depth to groundwater simulations from the numerical flow model with conceptual models of depths to water necessary for maintenance of riparian vegetation, the GIS analysis predicted a 5‐ to 6.5‐fold increase in the area capable of sustaining riparian vegetation.
Individual differences in emotionality and peri-traumatic processing.

PubMed

Logan, Shanna; O'Kearney, Richard

2012-06-01

Recent cognitive models propose that intrusive trauma memories arise and persist because high levels of emotional arousal triggered by the trauma disrupt conceptual processing of elements of the event, while enhancing sensory/perceptual processing. A trauma film analogue design was used to investigate if the predicted facilitating effects on intrusions from inhibiting conceptual processing and predicted attenuating effects on intrusions from inhibiting sensory processing are moderated by individual differences in emotionality. One hundred and five non-clinical participants viewed a traumatic film while undertaking a conceptual interference task, a sensory interference task, or no interference task. Participants recorded the frequency and intensity of intrusions over the following week. There was no facilitating effect for the conceptual interference task compared to no interference task. A significant attenuation of the frequency of intrusions was evident for those undertaking sensory interference (ŋ(2) = .04). This effect, however, was only present for those with high trait anxiety (d = .82) and not for those with low trait anxiety (d = .08). Relative to high trait anxious controls, high anxious participants who undertook sensory interference also reported lower intensity of intrusions (d = .66). This is the first trauma film analogue study to show that the attenuating effect of concurrent sensory/perceptual processing on the frequency and intensity of subsequent intrusions is evident only for people with high trait anxiety. The results have implications for conceptual models of intrusion development and for their application to the prevention of post traumatic distress. Copyright © 2011 Elsevier Ltd. All rights reserved.
Nurse plants, tree saplings and grazing pressure: changes in facilitation along a biotic environmental gradient.

PubMed

Smit, Christian; Vandenberghe, Charlotte; den Ouden, Jan; Müller-Schärer, Heinz

2007-05-01

Current conceptual models predict that an increase in stress shifts interactions between plants from competitive to facilitative; hence, facilitation is expected to gain in ecological importance with increasing stress. Little is known about how facilitative interactions between plants change with increasing biotic stress, such as that incurred by consumer pressure or herbivory (i.e. disturbance sensu Grime). In grazed ecosystems, the presence of unpalatable plants is reported to protect tree saplings against cattle grazing and enhance tree establishment. In accordance with current conceptual facilitation-stress models, we hypothesised a positive relationship between facilitation and grazing pressure. We tested this hypothesis in a field experiment in which tree saplings of four different species (deciduous Fagus sylvatica, Acer pseudoplatanus and coniferous Abies alba, Picea abies) were planted either inside or outside of the canopy of the spiny nurse shrub Rosa rubiginosa in enclosures differing in grazing pressure (low and high) and in exclosures. During one grazing season we followed the survival of the different tree saplings and the level of browsing on these; we also estimated browsing damage to the nurse shrubs. Shrub damage was highest at the higher grazing pressure. Correspondingly, browsing increased and survival decreased in saplings located inside the canopy of the shrubs at the high grazing pressure compared to the low grazing pressure. Saplings of both deciduous species showed a higher survival than the evergreens, while sapling browsing did not differ between species. The relative facilitation of sapling browsing and sapling survival - i.e. the difference between saplings inside and outside the shrub canopy - decreased at high grazing pressure as the facilitative species became less protective. Interestingly, these findings do not agree with current conceptual facilitation-stress models predicting increasing facilitation with abiotic stress. We used our results to design a conceptual model of facilitation along a biotic environmental gradient. Empirical studies are needed to test the applicability of this model. In conclusion, we suggest that current conceptual facilitation models should at least consider the possibility of decreasing facilitation at high levels of stress.
Modeling the Monthly Water Balance of a First Order Coastal Forested Watershed

Treesearch

S. V. Harder; Devendra M. Amatya; T. J. Callahan; Carl C. Trettin

2006-01-01

A study has been conducted to evaluate a spreadsheet-based conceptual Thornthwaite monthly water balance model and the process-based DRAINMOD model for their reliability in predicting monthly water budgets of a poorly drained, first order forested watershed at the Santee Experimental Forest located along the Lower Coastal Plain of South Carolina. Measured precipitation...
Development of a Conceptual Model to Predict Physical Activity Participation in Adults with Brain Injuries

ERIC Educational Resources Information Center

Driver, Simon

2008-01-01

The purpose was to examine psychosocial factors that influence the physical activity behaviors of adults with brain injuries. Two differing models, based on Harter's model of self-worth, were proposed to examine the relationship between perceived competence, social support, physical self-worth, affect, and motivation. Adults numbering 384 with…
Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling

Treesearch

Wei Wu; James Clark; James Vose

2010-01-01

Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model â GR4J â by coherently assimilating the uncertainties from the...

COMMUNICATION IMPACT, A CONCEPTUAL MODEL ANALYSIS OF INDIVIDUAL PREDISPOSITIONS AND THE ANALYSIS OF THE IMPACT OF A COUNTY CIVIL DEFENSE EDUCATIONAL PROGRAM.

ERIC Educational Resources Information Center

BEAL, GEORGE M.; AND OTHERS

THIS STUDY DEALS WITH COMMUNICATION AT THREE LEVELS--DEVELOPMENT OF A GENERALIZED MODEL OF THE PROCESS WHEREBY COMMUNICATION ACHIEVES IMPACT, THE OPERATIONALIZATION OF THE MODEL, AND TESTING OF THE DEGREE TO WHICH THE MODEL PREDICTS THE RESPONSE OF MEMBERS OF THE POTENTIAL AUDIENCE TO A SPECIFIC COMMUNICATION EVENT. THIS IMPACT MODEL TAKES THE…
Redd Site Selection and Spawning Habitat Use by Fall Chinook Salmon: The Importance of Geomorphic Features in Large Rivers

PubMed

Geist; Dauble

1998-09-01

/ Knowledge of the three-dimensional connectivity between rivers and groundwater within the hyporheic zone can be used to improve the definition of fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat. Information exists on the microhabitat characteristics that define suitable salmon spawning habitat. However, traditional spawning habitat models that use these characteristics to predict available spawning habitat are restricted because they can not account for the heterogeneous nature of rivers. We present a conceptual spawning habitat model for fall chinook salmon that describes how geomorphic features of river channels create hydraulic processes, including hyporheic flows, that influence where salmon spawn in unconstrained reaches of large mainstem alluvial rivers. Two case studies based on empirical data from fall chinook salmon spawning areas in the Hanford Reach of the Columbia River are presented to illustrate important aspects of our conceptual model. We suggest that traditional habitat models and our conceptual model be combined to predict the limits of suitable fall chinook salmon spawning habitat. This approach can incorporate quantitative measures of river channel morphology, including general descriptors of geomorphic features at different spatial scales, in order to understand the processes influencing redd site selection and spawning habitat use. This information is needed in order to protect existing salmon spawning habitat in large rivers, as well as to recover habitat already lost.KEY WORDS: Hyporheic zone; Geomorphology; Spawning habitat; Large rivers; Fall chinook salmon; Habitat management
Using models to manage systems subject to sustainability indicators

USGS Publications Warehouse

Hill, M.C.

2006-01-01

Mathematical and numerical models can provide insight into sustainability indicators using relevant simulated quantities, which are referred to here as predictions. To be useful, many concerns need to be considered. Four are discussed here: (a) mathematical and numerical accuracy of the model; (b) the accuracy of the data used in model development, (c) the information observations provide to aspects of the model important to predictions of interest as measured using sensitivity analysis; and (d) the existence of plausible alternative models for a given system. The four issues are illustrated using examples from conservative and transport modelling, and using conceptual arguments. Results suggest that ignoring these issues can produce misleading conclusions.
The Interactive Role of Emotional Intelligence, Attachment Style, and Resilience in the Prediction of Time Perception in Doctoral Students

ERIC Educational Resources Information Center

Precin, Patricia Jean

2014-01-01

The perception of time (the use of temporal categories to conceptualize experiences) affects human behavior. Students' time perspective predicts academic outcomes: those with future orientations tend to have better academic outcomes than those with past or present, according to Zimbardo and Boyd's psychology of time model, and may contribute to…
A unified approach for composite cost reporting and prediction in the ACT program

NASA Technical Reports Server (NTRS)

Freeman, W. Tom; Vosteen, Louis F.; Siddiqi, Shahid

1991-01-01

The Structures Technology Program Office (STPO) at NASA Langley Research Center has held two workshops with representatives from the commercial airframe companies to establish a plan for development of a standard cost reporting format and a cost prediction tool for conceptual and preliminary designers. This paper reviews the findings of the workshop representatives with a plan for implementation of their recommendations. The recommendations of the cost tracking and reporting committee will be implemented by reinstituting the collection of composite part fabrication data in a format similar to the DoD/NASA Structural Composites Fabrication Guide. The process of data collection will be automated by taking advantage of current technology with user friendly computer interfaces and electronic data transmission. Development of a conceptual and preliminary designers' cost prediction model will be initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design (CAD) programs is assessed.
Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data

USGS Publications Warehouse

Roberts, James H.; Hitt, Nathaniel P.

2010-01-01

Five conceptual models of longitudinal fish community organization in streams were examined: (1) niche diversity model (NDM), (2) stream continuum model (SCM), (3) immigrant accessibility model (IAM), (4) environmental stability model (ESM), and (5) adventitious stream model (ASM). We used differences among models in their predictions about temporal species turnover, along with five spatiotemporal fish community data sets, to evaluate model applicability. Models were similar in predicting a positive species richness–stream size relationship and longitudinal species nestedness, but differed in predicting either similar temporal species turnover throughout the stream continuum (NDM, SCM), higher turnover upstream (IAM, ESM), or higher turnover downstream (ASM). We calculated measures of spatial and temporal variation from spatiotemporal fish data in five wadeable streams in central and eastern North America spanning 34–68 years (French Creek [New York], Piasa Creek [Illinois], Spruce Run [Virginia], Little Stony Creek [Virginia], and Sinking Creek [Virginia]). All streams exhibited substantial species turnover (i.e., at least 27% turnover in stream-scale species pools), in contrast to the predictions of the SCM. Furthermore, community change was greater in downstream than upstream reaches in four of five streams. This result is most consistent with the ASM and suggests that downstream communities are strongly influenced by migrants to and from species pools outside the focal stream. In Sinking Creek, which is isolated from external species pools, temporal species turnover (via increased richness) was higher upstream than downstream, which is a pattern most consistent with the IAM or ESM. These results corroborate the hypothesis that temperate stream habitats and fish communities are temporally dynamic and that fish migration and environmental disturbances play fundamental roles in stream fish community organization.
Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.
Accounting for Variability in Student Responses to Motion Questions

ERIC Educational Resources Information Center

Frank, Brian W.; Kanim, Stephen E.; Gomez, Luanna S.

2008-01-01

We describe the results of an experiment conducted to test predictions about student responses to questions about motion based on an explicit model of student thinking in terms of the cuing of a variety of different physical intuitions or conceptual resources. This particular model allows us to account for observed variations in patterns of…
Integrating the Demonstration Orientation and Standards-Based Models of Achievement Goal Theory

ERIC Educational Resources Information Center

Wynne, Heather Marie

2014-01-01

Achievement goal theory and thus, the empirical measures stemming from the research, are currently divided on two conceptual approaches, namely the reason versus aims-based models of achievement goals. The factor structure and predictive utility of goal constructs from the Patterns of Adaptive Learning Strategies (PALS) and the latest two versions…
Flexible and fast: linguistic shortcut affects both shallow and deep conceptual processing.

PubMed

Connell, Louise; Lynott, Dermot

2013-06-01

Previous research has shown that people use linguistic distributional information during conceptual processing, and that it is especially useful for shallow tasks and rapid responding. Using two conceptual combination tasks, we showed that this linguistic shortcut extends to the processing of novel stimuli, is used in both successful and unsuccessful conceptual processing, and is evident in both shallow and deep conceptual tasks. Specifically, as predicted by the ECCo theory of conceptual combination, people use the linguistic shortcut as a "quick-and-dirty" guide to whether the concepts are likely to combine into a coherent conceptual representation, in both shallow sensibility judgment and deep interpretation generation tasks. Linguistic distributional frequency predicts both the likelihood and the time course of rejecting a novel word compound as nonsensical or uninterpretable. However, it predicts the time course of successful processing only in shallow sensibility judgment, because the deeper conceptual process of interpretation generation does not allow the linguistic shortcut to suffice. Furthermore, the effects of linguistic distributional frequency are independent of any effects of conventional word frequency. We discuss the utility of the linguistic shortcut as a cognitive triage mechanism that can optimize processing in a limited-resource conceptual system.
Model complexity in carbon sequestration:A design of experiment and response surface uncertainty analysis

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, S.

2014-12-01

Geologic carbon sequestration (GCS) is proposed for the Nugget Sandstone in Moxa Arch, a regional saline aquifer with a large storage potential. For a proposed storage site, this study builds a suite of increasingly complex conceptual "geologic" model families, using subsets of the site characterization data: a homogeneous model family, a stationary petrophysical model family, a stationary facies model family with sub-facies petrophysical variability, and a non-stationary facies model family (with sub-facies variability) conditioned to soft data. These families, representing alternative conceptual site models built with increasing data, were simulated with the same CO2 injection test (50 years at 1/10 Mt per year), followed by 2950 years of monitoring. Using the Design of Experiment, an efficient sensitivity analysis (SA) is conducted for all families, systematically varying uncertain input parameters. Results are compared among the families to identify parameters that have 1st order impact on predicting the CO2 storage ratio (SR) at both end of injection and end of monitoring. At this site, geologic modeling factors do not significantly influence the short-term prediction of the storage ratio, although they become important over monitoring time, but only for those families where such factors are accounted for. Based on the SA, a response surface analysis is conducted to generate prediction envelopes of the storage ratio, which are compared among the families at both times. Results suggest a large uncertainty in the predicted storage ratio given the uncertainties in model parameters and modeling choices: SR varies from 5-60% (end of injection) to 18-100% (end of monitoring), although its variation among the model families is relatively minor. Moreover, long-term leakage risk is considered small at the proposed site. In the lowest-SR scenarios, all families predict gravity-stable supercritical CO2 migrating toward the bottom of the aquifer. In the highest-SR scenarios, supercritical CO2 footprints are relatively insignificant by the end of monitoring.
Psychological resilience, pain catastrophizing, and positive emotions: perspectives on comprehensive modeling of individual pain adaptation.

PubMed

Sturgeon, John A; Zautra, Alex J

2013-03-01

Pain is a complex construct that contributes to profound physical and psychological dysfunction, particularly in individuals coping with chronic pain. The current paper builds upon previous research, describes a balanced conceptual model that integrates aspects of both psychological vulnerability and resilience to pain, and reviews protective and exacerbating psychosocial factors to the process of adaptation to chronic pain, including pain catastrophizing, pain acceptance, and positive psychological resources predictive of enhanced pain coping. The current paper identifies future directions for research that will further enrich the understanding of pain adaptation and espouses an approach that will enhance the ecological validity of psychological pain coping models, including introduction of advanced statistical and conceptual models that integrate behavioral, cognitive, information processing, motivational and affective theories of pain.
SPECIATION OF COMPLEX ORGANIC CONTAMINANTS IN WATER WITH RAMAN SPECTROSCOPY

EPA Science Inventory

Pesticides and industrial chemicals are typically complex organic molecules with multiple heteroatoms that can ionize, tautomerize, and form various types of hydrates in water. However, conceptual models for predicting the fate of these chemicals in the environment ignore these ...
Academic motivation, self-concept, engagement, and performance in high school: key processes from a longitudinal perspective.

PubMed

Green, Jasmine; Liem, Gregory Arief D; Martin, Andrew J; Colmar, Susan; Marsh, Herbert W; McInerney, Dennis

2012-10-01

The study tested three theoretically/conceptually hypothesized longitudinal models of academic processes leading to academic performance. Based on a longitudinal sample of 1866 high-school students across two consecutive years of high school (Time 1 and Time 2), the model with the most superior heuristic value demonstrated: (a) academic motivation and self-concept positively predicted attitudes toward school; (b) attitudes toward school positively predicted class participation and homework completion and negatively predicted absenteeism; and (c) class participation and homework completion positively predicted test performance whilst absenteeism negatively predicted test performance. Taken together, these findings provide support for the relevance of the self-system model and, particularly, the importance of examining the dynamic relationships amongst engagement factors of the model. The study highlights implications for educational and psychological theory, measurement, and intervention. Copyright © 2012 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
How are learning physics and student beliefs about learning physics connected? Measuring epistemological self-reflection in an introductory course and investigating its relationship to conceptual learning

NASA Astrophysics Data System (ADS)

May, David B.

2002-11-01

To explore students' epistemological beliefs in a variety of conceptual domains in physics, and in a specific and novel context of measurement, this Dissertation makes use of Weekly Reports, a class assignment in which students reflect in writing on what they learn each week and how they learn it. Reports were assigned to students in the introductory physics course for honors engineering majors at The Ohio State University in two successive years. The Weekly Reports of several students from the first year were analyzed for the kinds of epistemological beliefs exhibited therein, called epistemological self-reflection, and a coding scheme was developed for categorizing and quantifying this reflection. The connection between epistemological self-reflection and conceptual learning in physics seen in a pilot study was replicated in a larger study, in which the coded reflections from the Weekly Reports of thirty students were correlated with their conceptual learning gains. Although the total amount of epistemological self-reflection was not found to be related to conceptual gain, different kinds of epistemological self-reflection were. Describing learning physics concepts in terms of logical reasoning and making personal connections were positively correlated with gains; describing learning from authority figures or by observing phenomena without making inferences were negatively correlated. Linear regression equations were determined in order to quantify the effects on conceptual gain of specific ways of describing learning. In an experimental test of this model, the regression equations and the Weekly Report coding scheme developed from the first year's data were used to predict the conceptual gains of thirty students from the second year. The prediction was unsuccessful, possibly because these students were not given as much feedback on their reflections as were the first-year students. These results show that epistemological beliefs are important factors affecting the conceptual learning of physics students. Also, getting students to reflect meaningfully on their knowledge and learning is difficult and requires consistent feedback. Research into the epistemological beliefs of physics students in different contexts and from different populations can help us develop more complete models of epistemological beliefs, and ultimately improve the conceptual and epistemological knowledge of all students.
Statistical and Conceptual Model Testing Geomorphic Principles through Quantification in the Middle Rio Grande River, NM.

NASA Astrophysics Data System (ADS)

Posner, A. J.

2017-12-01

The Middle Rio Grande River (MRG) traverses New Mexico from Cochiti to Elephant Butte reservoirs. Since the 1100s, cultivating and inhabiting the valley of this alluvial river has required various river training works. The mid-20th century saw a concerted effort to tame the river through channelization, Jetty Jacks, and dam construction. A challenge for river managers is to better understand the interactions between a river training works, dam construction, and the geomorphic adjustments of a desert river driven by spring snowmelt and summer thunderstorms carrying water and large sediment inputs from upstream and ephemeral tributaries. Due to its importance to the region, a vast wealth of data exists for conditions along the MRG. The investigation presented herein builds upon previous efforts by combining hydraulic model results, digitized planforms, and stream gage records in various statistical and conceptual models in order to test our understanding of this complex system. Spatially continuous variables were clipped by a set of river cross section data that is collected at decadal intervals since the early 1960s, creating a spatially homogenous database upon which various statistical testing was implemented. Conceptual models relate forcing variables and response variables to estimate river planform changes. The developed database, represents a unique opportunity to quantify and test geomorphic conceptual models in the unique characteristics of the MRG. The results of this investigation provides a spatially distributed characterization of planform variable changes, permitting managers to predict planform at a much higher resolution than previously available, and a better understanding of the relationship between flow regime and planform changes such as changes to longitudinal slope, sinuosity, and width. Lastly, data analysis and model interpretation led to the development of a new conceptual model for the impact of ephemeral tributaries in alluvial rivers.
The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis

ERIC Educational Resources Information Center

Hagger, Martin S.; Chatzisarantis, Nikos L. D.

2016-01-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the…
Pathways of Change Explaining the Effect of Smoke-Free Legislation on Smoking Cessation in the Netherlands. An Application of the International Tobacco Control Conceptual Model

PubMed Central

de Vries, Hein; Fong, Geoffrey T.; Candel, Math J. J. M.; Thrasher, James F.; van den Putte, Bas; Thompson, Mary E.; Cummings, K. Michael; Willemsen, Marc C.

2012-01-01

Introduction: This study aims to test the pathways of change from individual exposure to smoke-free legislation on smoking cessation, as hypothesized in the International Tobacco Control (ITC) Conceptual Model. Methods: A nationally representative sample of Dutch smokers aged 15 years and older was surveyed during 4 consecutive annual surveys. Of the 1,820 baseline smokers, 1,012 participated in the fourth survey. Structural Equation Modeling was employed to test a model of the effects of individual exposure to smoke-free legislation through policy-specific variables (support for smoke-free legislation and awareness of the harm of [secondhand] smoking) and psychosocial mediators (attitudes, subjective norm, self-efficacy, and intention to quit) on quit attempts and quit success. Results: The effect of individual exposure to smoke-free legislation on smoking cessation was mediated by 1 pathway via support for smoke-free legislation, attitudes about quitting, and intention to quit smoking. Exposure to smoke-free legislation also influenced awareness of the harm of (secondhand) smoking, which in turn influenced the subjective norm about quitting. However, only attitudes about quitting were significantly associated with intention to quit smoking, whereas subjective norm and self-efficacy for quitting were not. Intention to quit predicted quit attempts and quit success, and self-efficacy for quitting predicted quit success. Conclusions: Our findings support the ITC Conceptual Model, which hypothesized that policies influence smoking cessation through policy-specific variables and psychosocial mediators. Smoke-free legislation may increase smoking cessation, provided that it succeeds in influencing support for the legislation. PMID:22491892
Pathways of change explaining the effect of smoke-free legislation on smoking cessation in The Netherlands. An application of the international tobacco control conceptual model.

PubMed

Nagelhout, Gera E; de Vries, Hein; Fong, Geoffrey T; Candel, Math J J M; Thrasher, James F; van den Putte, Bas; Thompson, Mary E; Cummings, K Michael; Willemsen, Marc C

2012-12-01

This study aims to test the pathways of change from individual exposure to smoke-free legislation on smoking cessation, as hypothesized in the International Tobacco Control (ITC) Conceptual Model. A nationally representative sample of Dutch smokers aged 15 years and older was surveyed during 4 consecutive annual surveys. Of the 1,820 baseline smokers, 1,012 participated in the fourth survey. Structural Equation Modeling was employed to test a model of the effects of individual exposure to smoke-free legislation through policy-specific variables (support for smoke-free legislation and awareness of the harm of [secondhand] smoking) and psychosocial mediators (attitudes, subjective norm, self-efficacy, and intention to quit) on quit attempts and quit success. The effect of individual exposure to smoke-free legislation on smoking cessation was mediated by 1 pathway via support for smoke-free legislation, attitudes about quitting, and intention to quit smoking. Exposure to smoke-free legislation also influenced awareness of the harm of (secondhand) smoking, which in turn influenced the subjective norm about quitting. However, only attitudes about quitting were significantly associated with intention to quit smoking, whereas subjective norm and self-efficacy for quitting were not. Intention to quit predicted quit attempts and quit success, and self-efficacy for quitting predicted quit success. Our findings support the ITC Conceptual Model, which hypothesized that policies influence smoking cessation through policy-specific variables and psychosocial mediators. Smoke-free legislation may increase smoking cessation, provided that it succeeds in influencing support for the legislation.
A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables.

Treesearch

Jan A. Henderson; Robin D. Lesher; David H. Peter; Chris D. Ringo

2011-01-01

A gradient-analysis-based model and grid-based map are presented that use the potential vegetation zone as the object of the model. Several new variables are presented that describe the environmental gradients of the landscape at different scales. Boundary algorithms are conceptualized, and then defined, that describe the environmental boundaries between vegetation...

Evaluation and development of satellite inferences of convective storm intensity using combined case study and thunderstorm model simulations

NASA Technical Reports Server (NTRS)

Cotton, W. R.; Tripoli, G. J.

1982-01-01

Observational requirements for predicting convective storm development and intensity as suggested by recent numerical experiments are examined. Recent 3D numerical experiments are interpreted with regard to the relationship between overshooting tops and surface wind gusts. The development of software for emulating satellite inferred cloud properties using 3D cloud model predicted data and the simulation of Heymsfield (1981) Northern Illinois storm are described as well as the development of a conceptual/semi-quantitative model of eastward propagating, mesoscale convective complexes forming to the lee of the Rocky Mountains.
Predicting Relationship Stability among Midlife African American Couples

ERIC Educational Resources Information Center

Cutrona, Carolyn E.; Russell, Daniel W.; Burzette, Rebecca G.; Wesner, Kristin A.; Bryant, Chalandra M.

2011-01-01

Objective: This study examined predictors of relationship stability over 5 years among heterosexual cohabiting and married African American couples raising an elementary-school-age child. The vulnerability-stress-adaptation model of relationships (Karney & Bradbury, 1995) guided the investigation. Contextual variables were conceptualized as…
Entrepreneurship Education and Training in Canada: A Critical Assessment.

ERIC Educational Resources Information Center

Ibrahim, A. B.; Soufani, K.

2002-01-01

Describes providers of entrepreneurship education in Canada: universities, small business centers, banks, nongovernmental organizations, and federal and provincial governments. Presents a conceptual model for entrepreneurship education and training that identifies traits and skills of entrepreneurs, addresses whether these are predictable, and…
EFFECTS OF SUCCESSION ON NITROGEN EXPORT IN THE WEST-CENTRAL CASCADES, OREGON

EPA Science Inventory

Conceptual models predict that unpolluted, aggrading forest ecosystems tightly retain available nitrogen (N) until declining productivity by mature trees and storage in detritus reduces the demand for essential nutrients, and N export increases to equal input. Short-term nitrate ...
An investigation of meaningful understanding and effectiveness of the implementation of Piagetian and Ausubelian theories in physics instruction

NASA Astrophysics Data System (ADS)

Williams, Karen Ann

One section of college students (N = 25) enrolled in an algebra-based physics course was selected for a Piagetian-based learning cycle (LC) treatment while a second section (N = 25) studied in an Ausubelian-based meaningful verbal reception learning treatment (MVRL). This study examined the students' overall (concept + problem solving + mental model) meaningful understanding of force, density/Archimedes Principle, and heat. Also examined were students' meaningful understanding as measured by conceptual questions, problems, and mental models. In addition, students' learning orientations were examined. There were no significant posttest differences between the LC and MVRL groups for students' meaningful understanding or learning orientation. Piagetian and Ausubelian theories explain meaningful understanding for each treatment. Students from each treatment increased their meaningful understanding. However, neither group altered their learning orientation. The results of meaningful understanding as measured by conceptual questions, problem solving, and mental models were mixed. Differences were attributed to the weaknesses and strengths of each treatment. This research also examined four variables (treatment, reasoning ability, learning orientation, and prior knowledge) to find which best predicted students' overall meaningful understanding of physics concepts. None of these variables were significant predictors at the.05 level. However, when the same variables were used to predict students' specific understanding (i.e. concept, problem solving, or mental model understanding), the results were mixed. For forces and density/Archimedes Principle, prior knowledge and reasoning ability significantly predicted students' conceptual understanding. For heat, however, reasoning ability was the only significant predictor of concept understanding. Reasoning ability and treatment were significant predictors of students' problem solving for heat and forces. For density/Archimedes Principle, treatment was the only significant predictor of students' problem solving. None of the variables were significant predictors of mental model understanding. This research suggested that Piaget and Ausubel used different terminology to describe learning yet these theories are similar. Further research is needed to validate this premise and validate the blending of the two theories.
Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.
A Cognitive-Social Model of Fertility Intentions

PubMed Central

Bachrach, Christine A.; Morgan, S. Philip

2014-01-01

We examine the use and value of fertility intentions against the backdrop of theory and research in the cognitive and social sciences. First, we draw on recent brain and cognition research to contextualize fertility intentions within a broader set of conscious and unconscious mechanisms that contribute to mental function. Next, we integrate this research with social theory. Our conceptualizations suggest that people do not necessarily have fertility intentions; they form them only when prompted by specific situations. Intention formation draws on the current situation and on schemas of childbearing and parenthood learned through previous experience, imbued by affect, and organized by self-representation. Using this conceptualization, we review apparently discordant knowledge about the value of fertility intentions in predicting fertility. Our analysis extends and deepens existing explanations for the weak predictive validity of fertility intentions at the individual level and provides a social-cognitive explanation for why intentions predict as well as they do. When focusing on the predictive power of intentions at the aggregate level, our conceptualizations lead us to focus on how social structures frustrate or facilitate intentions and how the structural environment contributes to the formation of reported intentions in the first place. Our analysis suggests that existing measures of fertility intentions are useful but to varying extents and in many cases despite their failure to capture what they seek to measure. PMID:25132695
Identification of the dominant hydrological process and appropriate model structure of a karst catchment through stepwise simplification of a complex conceptual model

NASA Astrophysics Data System (ADS)

Chang, Yong; Wu, Jichun; Jiang, Guanghui; Kang, Zhiqiang

2017-05-01

Conceptual models often suffer from the over-parameterization problem due to limited available data for the calibration. This leads to the problem of parameter nonuniqueness and equifinality, which may bring much uncertainty of the simulation result. How to find out the appropriate model structure supported by the available data to simulate the catchment is still a big challenge in the hydrological research. In this paper, we adopt a multi-model framework to identify the dominant hydrological process and appropriate model structure of a karst spring, located in Guilin city, China. For this catchment, the spring discharge is the only available data for the model calibration. This framework starts with a relative complex conceptual model according to the perception of the catchment and then this complex is simplified into several different models by gradually removing the model component. The multi-objective approach is used to compare the performance of these different models and the regional sensitivity analysis (RSA) is used to investigate the parameter identifiability. The results show this karst spring is mainly controlled by two different hydrological processes and one of the processes is threshold-driven which is consistent with the fieldwork investigation. However, the appropriate model structure to simulate the discharge of this spring is much simpler than the actual aquifer structure and hydrological processes understanding from the fieldwork investigation. A simple linear reservoir with two different outlets is enough to simulate this spring discharge. The detail runoff process in the catchment is not needed in the conceptual model to simulate the spring discharge. More complex model should need more other additional data to avoid serious deterioration of model predictions.
Computational prediction of the pKas of small peptides through Conceptual DFT descriptors

NASA Astrophysics Data System (ADS)

Frau, Juan; Hernández-Haro, Noemí; Glossman-Mitnik, Daniel

2017-03-01

The experimental pKa of a group of simple amines have been plotted against several Conceptual DFT descriptors calculated by means of different density functionals, basis sets and solvation schemes. It was found that the best fits are those that relate the pKa of the amines with the global hardness η through the MN12SX density functional in connection with the Def2TZVP basis set and the SMD solvation model, using water as a solvent. The parameterized equation resulting from the linear regression analysis has then been used for the prediction of the pKa of small peptides of interest in the study of diabetes and Alzheimer disease. The accuracy of the results is relatively good, with a MAD of 0.36 units of pKa.
Framework for Uncertainty Assessment - Hanford Site-Wide Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Bergeron, M. P.; Cole, C. R.; Murray, C. J.; Thorne, P. D.; Wurstner, S. K.

2002-05-01

Pacific Northwest National Laboratory is in the process of development and implementation of an uncertainty estimation methodology for use in future site assessments that addresses parameter uncertainty as well as uncertainties related to the groundwater conceptual model. The long-term goals of the effort are development and implementation of an uncertainty estimation methodology for use in future assessments and analyses being made with the Hanford site-wide groundwater model. The basic approach in the framework developed for uncertainty assessment consists of: 1) Alternate conceptual model (ACM) identification to identify and document the major features and assumptions of each conceptual model. The process must also include a periodic review of the existing and proposed new conceptual models as data or understanding become available. 2) ACM development of each identified conceptual model through inverse modeling with historical site data. 3) ACM evaluation to identify which of conceptual models are plausible and should be included in any subsequent uncertainty assessments. 4) ACM uncertainty assessments will only be carried out for those ACMs determined to be plausible through comparison with historical observations and model structure identification measures. The parameter uncertainty assessment process generally involves: a) Model Complexity Optimization - to identify the important or relevant parameters for the uncertainty analysis; b) Characterization of Parameter Uncertainty - to develop the pdfs for the important uncertain parameters including identification of any correlations among parameters; c) Propagation of Uncertainty - to propagate parameter uncertainties (e.g., by first order second moment methods if applicable or by a Monte Carlo approach) through the model to determine the uncertainty in the model predictions of interest. 5)Estimation of combined ACM and scenario uncertainty by a double sum with each component of the inner sum (an individual CCDF) representing parameter uncertainty associated with a particular scenario and ACM and the outer sum enumerating the various plausible ACM and scenario combinations in order to represent the combined estimate of uncertainty (a family of CCDFs). A final important part of the framework includes identification, enumeration, and documentation of all the assumptions, which include those made during conceptual model development, required by the mathematical model, required by the numerical model, made during the spatial and temporal descretization process, needed to assign the statistical model and associated parameters that describe the uncertainty in the relevant input parameters, and finally those assumptions required by the propagation method. Pacific Northwest National Laboratory is operated for the U.S. Department of Energy under Contract DE-AC06-76RL01830.
Situating School District Resource Decision Making in Policy Context

ERIC Educational Resources Information Center

Spain, Angeline K.

2016-01-01

Decentralization and deregulation policies assume that local educational leaders make better resource decisions than state policy makers do. Conceptual models drawn from organizational theory, however, offer competing predictions about how district central office administrators are likely to leverage their professional expertise in devolved…
NITROGEN FLUX FROM WEST CASCADE RANGE HEADWATER STREAMS DRAINING FORESTS ALONG A SUCCESSIONAL GRADIENT

EPA Science Inventory

Conceptual models predict that unpolluted, aggrading forest ecosystems tightly retain available nitrogen (N) until declining productivity by mature trees reduces the demand for essential nutrients and export increases to equal N inputs. Short-term nitrate loss following disturban...
Evaluating the Predictive Impact of an Emergent Literacy Model on Dyslexia in Italian Children: A Four-Year Prospective Cohort Study.

PubMed

Bigozzi, Lucia; Tarchi, Christian; Pezzica, Sara; Pinto, Giuliana

2016-01-01

The strong differences in manifestation, prevalence, and incidence in dyslexia across languages invite studies in specific writing systems. In particular, the question of the role played by emergent literacy in opaque and transparent writing systems remains a fraught one. This research project tested, through a 4-year prospective cohort study, an emergent literacy model for the analysis of the characteristics of future dyslexic children and normally reading peers in Italian, a transparent writing system. A cohort of 450 children was followed from the last year of kindergarten to the third grade in their reading acquisition process. Dyslexic children were individuated (Grade 3), and their performances in kindergarten in textual competence, phonological awareness, and conceptual knowledge of the writing system were compared with a matched group of normally reading peers. Results showed the predictive relevance of the conceptual knowledge of the writing system. The study's implications are discussed. © Hammill Institute on Disabilities 2014.
Psychological mechanisms in outdoor place and weather assessment: towards a conceptual model

NASA Astrophysics Data System (ADS)

Knez, Igor; Thorsson, Sofia; Eliasson, Ingegärd; Lindberg, Fredrik

2009-01-01

The general aim has been to illuminate the psychological mechanisms involved in outdoor place and weather assessment. This reasoning was conceptualized in a model, tentatively proposing direct and indirect links of influence in an outdoor place-human relationship. The model was subsequently tested by an empirical study, performed in a Nordic city, on the impact of weather and personal factors on participants’ perceptual and emotional estimations of outdoor urban places. In line with our predictions, we report significant influences of weather parameters (air temperature, wind, and cloudlessness) and personal factors (environmental attitude and age) on participants’ perceptual and emotional estimations of outdoor urban places. All this is a modest, yet significant, step towards an understanding of the psychology of outdoor place and weather assessment.
Uncertainty Analysis Framework - Hanford Site-Wide Groundwater Flow and Transport Model

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

Cole, Charles R.; Bergeron, Marcel P.; Murray, Christopher J.

2001-11-09

Pacific Northwest National Laboratory (PNNL) embarked on a new initiative to strengthen the technical defensibility of the predictions being made with a site-wide groundwater flow and transport model at the U.S. Department of Energy Hanford Site in southeastern Washington State. In FY 2000, the focus of the initiative was on the characterization of major uncertainties in the current conceptual model that would affect model predictions. The long-term goals of the initiative are the development and implementation of an uncertainty estimation methodology in future assessments and analyses using the site-wide model. This report focuses on the development and implementation of anmore » uncertainty analysis framework.« less
Robust Bayesian Experimental Design for Conceptual Model Discrimination

NASA Astrophysics Data System (ADS)

Pham, H. V.; Tsai, F. T. C.

2015-12-01

A robust Bayesian optimal experimental design under uncertainty is presented to provide firm information for model discrimination, given the least number of pumping wells and observation wells. Firm information is the maximum information of a system can be guaranteed from an experimental design. The design is based on the Box-Hill expected entropy decrease (EED) before and after the experiment design and the Bayesian model averaging (BMA) framework. A max-min programming is introduced to choose the robust design that maximizes the minimal Box-Hill EED subject to that the highest expected posterior model probability satisfies a desired probability threshold. The EED is calculated by the Gauss-Hermite quadrature. The BMA method is used to predict future observations and to quantify future observation uncertainty arising from conceptual and parametric uncertainties in calculating EED. Monte Carlo approach is adopted to quantify the uncertainty in the posterior model probabilities. The optimal experimental design is tested by a synthetic 5-layer anisotropic confined aquifer. Nine conceptual groundwater models are constructed due to uncertain geological architecture and boundary condition. High-performance computing is used to enumerate all possible design solutions in order to identify the most plausible groundwater model. Results highlight the impacts of scedasticity in future observation data as well as uncertainty sources on potential pumping and observation locations.
Combining Deterministic structures and stochastic heterogeneity for transport modeling

NASA Astrophysics Data System (ADS)

Zech, Alraune; Attinger, Sabine; Dietrich, Peter; Teutsch, Georg

2017-04-01

Contaminant transport in highly heterogeneous aquifers is extremely challenging and subject of current scientific debate. Tracer plumes often show non-symmetric but highly skewed plume shapes. Predicting such transport behavior using the classical advection-dispersion-equation (ADE) in combination with a stochastic description of aquifer properties requires a dense measurement network. This is in contrast to the available information for most aquifers. A new conceptual aquifer structure model is presented which combines large-scale deterministic information and the stochastic approach for incorporating sub-scale heterogeneity. The conceptual model is designed to allow for a goal-oriented, site specific transport analysis making use of as few data as possible. Thereby the basic idea is to reproduce highly skewed tracer plumes in heterogeneous media by incorporating deterministic contrasts and effects of connectivity instead of using unimodal heterogeneous models with high variances. The conceptual model consists of deterministic blocks of mean hydraulic conductivity which might be measured by pumping tests indicating values differing in orders of magnitudes. A sub-scale heterogeneity is introduced within every block. This heterogeneity can be modeled as bimodal or log-normal distributed. The impact of input parameters, structure and conductivity contrasts is investigated in a systematic manor. Furthermore, some first successful implementation of the model was achieved for the well known MADE site.
Innovating Conservation Agriculture: The Case of No-Till Cropping

ERIC Educational Resources Information Center

Coughenour, C. Milton

2003-01-01

The extensive sociological studies of conservation agriculture have provided considerable understanding of farmers' use of conservation practices, but attempts to develop predictive models have failed. Reviews of research findings question the utility of the conceptual and methodological perspectives of prior research. The argument advanced here…
The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.
Prediction of physical workload in reduced gravity environments

NASA Technical Reports Server (NTRS)

Goldberg, Joseph H.

1987-01-01

The background, development, and application of a methodology to predict human energy expenditure and physical workload in low gravity environments, such as a Lunar or Martian base, is described. Based on a validated model to predict energy expenditures in Earth-based industrial jobs, the model relies on an elemental analysis of the proposed job. Because the job itself need not physically exist, many alternative job designs may be compared in their physical workload. The feasibility of using the model for prediction of low gravity work was evaluated by lowering body and load weights, while maintaining basal energy expenditure. Comparison of model results was made both with simulated low gravity energy expenditure studies and with reported Apollo 14 Lunar EVA expenditure. Prediction accuracy was very good for walking and for cart pulling on slopes less than 15 deg, but the model underpredicted the most difficult work conditions. This model was applied to example core sampling and facility construction jobs, as presently conceptualized for a Lunar or Martian base. Resultant energy expenditures and suggested work-rest cycles were well within the range of moderate work difficulty. Future model development requirements were also discussed.

Prevention through Design Adoption Readiness Model (PtD ARM): An integrated conceptual model.

PubMed

Weidman, Justin; Dickerson, Deborah E; Koebel, Charles T

2015-01-01

Prevention through Design (PtD), eliminating hazards at the design-stage of tools and systems, is the optimal method of mitigating occupational health and safety risks. A recent National Institute of Safety and Health initiative has established a goal to increase adoption of PtD innovation in industry. The construction industry has traditionally lagged behind other sectors in the adoption of innovation, in general; and of safety and health prevention innovation, in particular. Therefore, as a first step toward improving adoption trends in this sector, a conceptual model was developed to describe the parameters and causal relationships that influence and predict construction stakeholder "adoption readiness" for PtD technology innovation. This model was built upon three well-established theoretical frameworks: the Health Belief Model, the Diffusion of Innovation Model, and the Technology Acceptance Model. Earp and Ennett's model development methodology was employed to build a depiction of the key constructs and directionality and magnitude of relationships among them. Key constructs were identified from the literature associated with the three theoretical frameworks, with special emphasis given to studies related to construction or OHS technology adoption. A conceptual model is presented. Recommendations for future research are described and include confirmatory structural equation modeling of model parameters and relationships, additional descriptive investigation of barriers to adoption in some trade sectors, and design and evaluation of an intervention strategy.
The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis.

PubMed

Hagger, Martin S; Chatzisarantis, Nikos L D

2016-06-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods.
Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

PubMed

Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
Understanding Quality of Life in Adults with Spinal Cord Injury Via SCI-Related Needs and Secondary Complications.

PubMed

Sweet, Shane N; Noreau, Luc; Leblond, Jean; Dumont, Frédéric S

2014-01-01

Understanding the factors that can predict greater quality of life (QoL) is important for adults with spinal cord injury (SCI), given that they report lower levels of QoL than the general population. To build a conceptual model linking SCI-related needs, secondary complications, and QoL in adults with SCI. Prior to testing the conceptual model, we aimed to develop and evaluate the factor structure for both SCI-related needs and secondary complications. Individuals with a traumatic SCI (N = 1,137) responded to an online survey measuring 13 SCI-related needs, 13 secondary complications, and the Life Satisfaction Questionnaire to assess QoL. The SCI-related needs and secondary complications were conceptualized into factors, tested with a confirmatory factor analysis, and subsequently evaluated in a structural equation model to predict QoL. The confirmatory factor analysis supported a 2-factor model for SCI related needs, χ(2)(61, N = 1,137) = 250.40, P <.001, comparative fit index (CFI) = .93, root mean square error of approximation (RMSEA) = .05, standardized root mean square residual (SRMR) = .04, and for 11 of the 13 secondary complications, χ(2)(44, N = 1,137) = 305.67, P < .001, CFI = .91, RMSEA = .060, SRMR = .033. The final 2 secondary complications were kept as observed constructs. In the structural model, both vital and personal development unmet SCI-related needs (β = -.22 and -.20, P < .05, respectively) and the neuro-physiological systems factor (β = -.45, P < .05) were negatively related with QoL. Identifying unmet SCI-related needs of individuals with SCI and preventing or managing secondary complications are essential to their QoL.
Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.
Abstract Conceptual Feature Ratings Predict Gaze within Written Word Arrays: Evidence from a Visual Wor(l)d Paradigm

ERIC Educational Resources Information Center

Primativo, Silvia; Reilly, Jamie; Crutch, Sebastian J

2017-01-01

The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF…
Continuous Improvement of a Groundwater Model over a 20-Year Period: Lessons Learned.

PubMed

Andersen, Peter F; Ross, James L; Fenske, Jon P

2018-04-17

Groundwater models developed for specific sites generally become obsolete within a few years due to changes in: (1) modeling technology; (2) site/project personnel; (3) project funding; and (4) modeling objectives. Consequently, new models are sometimes developed for the same sites using the latest technology and data, but without potential knowledge gained from the prior models. When it occurs, this practice is particularly problematic because, although technology, data, and observed conditions change, development of the new numerical model may not consider the conceptual model's underpinnings. As a contrary situation, we present the unique case of a numerical flow and trichloroethylene (TCE) transport model that was first developed in 1993 and since revised and updated annually by the same personnel. The updates are prompted by an increase in the amount of data, exposure to a wider range of hydrologic conditions over increasingly longer timeframes, technological advances, evolving modeling objectives, and revised modeling methodologies. The history of updates shows smooth, incremental changes in the conceptual model and modeled aquifer parameters that result from both increase and decrease in complexity. Myriad modeling objectives have included demonstrating the ineffectiveness of a groundwater extraction/injection system, evaluating potential TCE degradation, locating new monitoring points, and predicting likelihood of exceedance of groundwater standards. The application emphasizes an original tenet of successful groundwater modeling: iterative adjustment of the conceptual model based on observations of actual vs. model response. © 2018, National Ground Water Association.
Travel time analysis for a subsurface drained sub-watershed in Upper Big Walnut Creek Watershed, Ohio

USDA-ARS?s Scientific Manuscript database

Runoff travel time, which is a function of watershed and storm characteristics, is an important parameter affecting the prediction accuracy of hydrologic models. Although, time of concentration (tc) is a most widely used time parameter, it has multiple conceptual and computational definitions. Most ...
Conceptualizing Public Attitudes toward the Welfare State: A Comment on Hasenfeld and Rafferty.

ERIC Educational Resources Information Center

Emerson, Michael O.; Van Buren, Mark E.

1992-01-01

Using structural equation technique to replicate results of Hasenfeld and Rafferty's causal model predicting public attitudes toward welfare state programs with the social ideologies of work ethic and social rights. By incorporating estimates of measurement error, results failed to support the authors' original conclusions. Operationalizing key…
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

ERIC Educational Resources Information Center

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…
The conceptualization model problem—surprise

NASA Astrophysics Data System (ADS)

Bredehoeft, John

2005-03-01

The foundation of model analysis is the conceptual model. Surprise is defined as new data that renders the prevailing conceptual model invalid; as defined here it represents a paradigm shift. Limited empirical data indicate that surprises occur in 20-30% of model analyses. These data suggest that groundwater analysts have difficulty selecting the appropriate conceptual model. There is no ready remedy to the conceptual model problem other than (1) to collect as much data as is feasible, using all applicable methods—a complementary data collection methodology can lead to new information that changes the prevailing conceptual model, and (2) for the analyst to remain open to the fact that the conceptual model can change dramatically as more information is collected. In the final analysis, the hydrogeologist makes a subjective decision on the appropriate conceptual model. The conceptualization problem does not render models unusable. The problem introduces an uncertainty that often is not widely recognized. Conceptual model uncertainty is exacerbated in making long-term predictions of system performance. C'est le modèle conceptuel qui se trouve à base d'une analyse sur un modèle. On considère comme une surprise lorsque le modèle est invalidé par des données nouvelles; dans les termes définis ici la surprise est équivalente à un change de paradigme. Des données empiriques limitées indiquent que les surprises apparaissent dans 20 à 30% des analyses effectuées sur les modèles. Ces données suggèrent que l'analyse des eaux souterraines présente des difficultés lorsqu'il s'agit de choisir le modèle conceptuel approprié. Il n'existe pas un autre remède au problème du modèle conceptuel que: (1) rassembler autant des données que possible en utilisant toutes les méthodes applicables—la méthode des données complémentaires peut conduire aux nouvelles informations qui vont changer le modèle conceptuel, et (2) l'analyste doit rester ouvert au fait que le modèle conceptuel peut bien changer lorsque des nouvelles informations apparaissent. Dans l'analyse finale le hydrogéologue prend une décision subjective sur le modèle conceptuel approprié. Le problème du le modèle conceptuel ne doit pas rendre le modèle inutilisable. Ce problème introduit une incertitude qui n'est pas toujours reconnue. Les incertitudes du modèle conceptuel deviennent plus importantes dans les cases de prévisions à long terme dans l'analyse de performance. La base para hacer un análisis de un modelo es el modelo conceptual. Se define aquí la sorpresa como los datos nuevos que convierten en incoherente al modelo conceptual previamente aceptado; tal como se define aquí esto representa un cambio de paradigma. Los datos empíricos limitados indican que estas sorpresas suceden entre un 20 a un 30% de los análisis de modelos. Esto sugiere que los analistas de modelos de agua subterránea tienen dificultades al seleccionar el modelo conceptual apropiado. No hayotra solución disponible a este problema del modelo conceptual diferente de: (1) Recolectar tanta información como sea posible, mediante la utilización de todos los métodos aplicables, lo cual puede resultar en que esta nueva información ayude a cambiar el modelo conceptual vigente, y (2) Que el analista de modelos se mantenga siempre abierto al hecho de que un modelo conceptual puede cambiar de manera total, en la medida en que se colecte mas información. En el análisis final el hidrogeólogo toma una decisión subjetiva en cuanto al modelo conceptual apropiado. El problema de la conceptualización no produce modelos inútiles. El problema presenta una incertidumbre, la cual a menudo no es tenida en cuentade manera adecuada. Esta incertidumbre en los modelos conceptuales se aumenta, cuando se hacen predicciones a largo plazo del comportamiento de un sistema dado.
The Effects of Virtual Versus Physical Lab Manipulatives on Inquiry Skill Acquisition and Conceptual Understanding of Density

NASA Astrophysics Data System (ADS)

Brinson, James R.

The current study compared the effects of virtual versus physical laboratory manipulatives on 84 undergraduate non-science majors' (a) conceptual understanding of density and (b) density-related inquiry skill acquisition. A pre-post comparison study design was used, which incorporated all components of an inquiry-guided classroom, except experimental mode, and which controlled for curriculum, instructor, instructional method, time spent on task, and availability of reference resources. Participants were randomly assigned to either a physical or virtual lab group. Pre- and post-assessments of conceptual understanding and inquiry skills were administered to both groups. Paired-samples t tests revealed a significant mean percent correct score increase for conceptual understanding in both the physical lab group (M = .103, SD = .168), t(38) = -3.82, p < .001, r = .53, two-tailed, and the virtual lab group (M = .084, SD = .177), t(44) = -3.20, p = .003, r = .43, two-tailed. However, a one-way ANCOVA (using pretest scores as the covariate) revealed that the main effect of lab group on conceptual learning gains was not significant, F(1, 81) = 0.081, p = .776, two-tailed. An omnibus test of model coefficients within hierarchical logistic regression revealed that a correct response on inquiry pretest scores was not a significant predictor of a correct post-test response, chi 2(1, N = 84) = 1.68, p = .195, and that when lab mode was added to the model, it did not significantly increase the model's predictive ability, chi2(2, N = 84) = 1.95, p = .377. Thus, the data in the current study revealed no significant difference in the effect of physical versus virtual manipulatives when used to teach conceptual understanding and inquiry skills related to density.
Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 3. The large catchment model

NASA Astrophysics Data System (ADS)

Sivapalan, Murugesu; Viney, Neil R.; Jeevaraj, Charles G.

1996-03-01

This paper presents an application of a long-term, large catchment-scale, water balance model developed to predict the effects of forest clearing in the south-west of Western Australia. The conceptual model simulates the basic daily water balance fluxes in forested catchments before and after clearing. The large catchment is divided into a number of sub-catchments (1-5 km2 in area), which are taken as the fundamental building blocks of the large catchment model. The responses of the individual subcatchments to rainfall and pan evaporation are conceptualized in terms of three inter-dependent subsurface stores A, B and F, which are considered to represent the moisture states of the subcatchments. Details of the subcatchment-scale water balance model have been presented earlier in Part 1 of this series of papers. The response of any subcatchment is a function of its local moisture state, as measured by the local values of the stores. The variations of the initial values of the stores among the subcatchments are described in the large catchment model through simple, linear equations involving a number of similarity indices representing topography, mean annual rainfall and level of forest clearing.The model is applied to the Conjurunup catchment, a medium-sized (39·6 km2) catchment in the south-west of Western Australia. The catchment has been heterogeneously (in space and time) cleared for bauxite mining and subsequently rehabilitated. For this application, the catchment is divided into 11 subcatchments. The model parameters are estimated by calibration, by comparing observed and predicted runoff values, over a 18 year period, for the large catchment and two of the subcatchments. Excellent fits are obtained.
Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation

PubMed Central

Veloz, Tomas; Desjardins, Sylvie

2015-01-01

Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556
Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation.

PubMed

Veloz, Tomas; Desjardins, Sylvie

2015-01-01

Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations.
Laboratory Experiments on Bentonite Samples: FY16 Progress

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

Ruth M. Tinnacher; Tournassat, Christophe; James A. Davis

2016-08-22

The primary goal of this study is to improve the understanding of U(VI) sorption and diffusion behavior in sodium-montmorillonite in order to support the development of realistic conceptual models describing these processes in performance assessment models while (1) accounting for potential changes in system conditions over time and space, (2) avoiding overly conservative transport predictions, and (3) using a minimum number of fitting parameters.
Individual and Social Influences on Students' Attitudes to Debt: A Cross-National Path Analysis Using Data from England and New Zealand

ERIC Educational Resources Information Center

Harrison, Neil; Agnew, Steve

2016-01-01

This study examines the construction of debt attitudes among 439 first-year undergraduates in England and New Zealand. It works from a conceptual model that predicts that attitudes will be partly determined by a range of social factors, mediated through personality and 'financial literacy'. Path analysis is used to explore this model. The proposed…
Conceptual design of flapping-wing micro air vehicles.

PubMed

Whitney, J P; Wood, R J

2012-09-01

Traditional micro air vehicles (MAVs) are miniature versions of full-scale aircraft from which their design principles closely follow. The first step in aircraft design is the development of a conceptual design, where basic specifications and vehicle size are established. Conceptual design methods do not rely on specific knowledge of the propulsion system, vehicle layout and subsystems; these details are addressed later in the design process. Non-traditional MAV designs based on birds or insects are less common and without well-established conceptual design methods. This paper presents a conceptual design process for hovering flapping-wing vehicles. An energy-based accounting of propulsion and aerodynamics is combined with a one degree-of-freedom dynamic flapping model. Important results include simple analytical expressions for flight endurance and range, predictions for maximum feasible wing size and body mass, and critical design space restrictions resulting from finite wing inertia. A new figure-of-merit for wing structural-inertial efficiency is proposed and used to quantify the performance of real and artificial insect wings. The impact of these results on future flapping-wing MAV designs is discussed in detail.
The influence of data-driven versus conceptually-driven processing on the development of PTSD-like symptoms.

PubMed

Kindt, Merel; van den Hout, Marcel; Arntz, Arnoud; Drost, Jolijn

2008-12-01

Ehlers and Clark [(2000). A cognitive model of posttraumatic stress disorder. Behaviour Research and Therapy, 38, 319-345] propose that a predominance of data-driven processing during the trauma predicts subsequent PTSD. We wondered whether, apart from data-driven encoding, sustained data-driven processing after the trauma is also crucial for the development of PTSD. Both hypotheses were tested in two analogue experiments. Experiment 1 demonstrated that relative to conceptually-driven processing (n=20), data-driven processing after the film (n=14), resulted in more intrusions. Experiment 2 demonstrated that relative to the neutral condition (n=24) and the data-driven encoding condition (n=24), conceptual encoding (n=25) reduced suppression of intrusions and a trend emerged for memory fragmentation. The difference between the two encoding styles was due to the beneficial effect of induced conceptual encoding and not to the detrimental effect of data-driven encoding. The data support the viability of the distinction between data-driven/conceptually-driven processing for the understanding of the development of PTSD.
Quantifying Groundwater Availability in Fractured Rock Aquifers of Northern Ugandan Refugee Settlements

NASA Astrophysics Data System (ADS)

Frederiks, R.; Lowry, C.; Mutiibwa, R.; Moisy, S.; Thapa, L.; Oriba, J.

2017-12-01

In the past two years, Uganda has witnessed an influx of nearly one million refugees who have settled in the sparsely populated northwestern region of the country. This rapid population growth has created high demand for clean water resources. Water supply has been unable to keep pace with demand because the fractured rock aquifers underlying the region often produce low yielding wells. To facilitate management of groundwater resources, it is necessary to quantify the spatial distribution of groundwater. In fractured rock aquifers, there is significant spatial variability in water storage because fractures must be both connected and abundant for water to be extracted in usable quantities. Two conceptual models were evaluated to determine the groundwater storage mechanism in the fractured crystalline bedrock aquifers of northwestern Uganda where by permeability is controlled by faulting, which opens up fractures in the bedrock, or weathering, which occurs when water dissolves components of rock. In order to test these two conceptual models, geologic well logs and available hydrologic data were collected and evaluated using geostatistical and numerical groundwater models. The geostatistical analysis focused on identifying spatially distributed patterns of high and low water yield. The conceptual models were evaluated numerically using four inverse groundwater MODFLOW models based on head and estimated flux targets. The models were based on: (1) the mapped bedrock units using an equivalent porous media approach (2) bedrock units with the addition of known fault zones (3) bedrock units with predicted units of deep weathering based on surface slopes, and (4) bedrock units with discrete faults and simulated weathered zones. Predicting permeable zones is vital for water well drilling in much of East Africa and South America where there is an abundance of both fractured rock and tectonic activity. Given that the population of these developing regions is growing, the demand for sufficient clean water is likely to increase significantly in the next few decades. Thus, it is necessary to improve our ability to predict locations of permeable zones in fractured rock aquifers.

Conceptual Models in Health Informatics Research: A Literature Review and Suggestions for Development

PubMed Central

2016-01-01

Background Contributing to health informatics research means using conceptual models that are integrative and explain the research in terms of the two broad domains of health science and information science. However, it can be hard for novice health informatics researchers to find exemplars and guidelines in working with integrative conceptual models. Objectives The aim of this paper is to support the use of integrative conceptual models in research on information and communication technologies in the health sector, and to encourage discussion of these conceptual models in scholarly forums. Methods A two-part method was used to summarize and structure ideas about how to work effectively with conceptual models in health informatics research that included (1) a selective review and summary of the literature of conceptual models; and (2) the construction of a step-by-step approach to developing a conceptual model. Results The seven-step methodology for developing conceptual models in health informatics research explained in this paper involves (1) acknowledging the limitations of health science and information science conceptual models; (2) giving a rationale for one’s choice of integrative conceptual model; (3) explicating a conceptual model verbally and graphically; (4) seeking feedback about the conceptual model from stakeholders in both the health science and information science domains; (5) aligning a conceptual model with an appropriate research plan; (6) adapting a conceptual model in response to new knowledge over time; and (7) disseminating conceptual models in scholarly and scientific forums. Conclusions Making explicit the conceptual model that underpins a health informatics research project can contribute to increasing the number of well-formed and strongly grounded health informatics research projects. This explication has distinct benefits for researchers in training, research teams, and researchers and practitioners in information, health, and other disciplines. PMID:26912288
Conceptual Models in Health Informatics Research: A Literature Review and Suggestions for Development.

PubMed

Gray, Kathleen; Sockolow, Paulina

2016-02-24

Contributing to health informatics research means using conceptual models that are integrative and explain the research in terms of the two broad domains of health science and information science. However, it can be hard for novice health informatics researchers to find exemplars and guidelines in working with integrative conceptual models. The aim of this paper is to support the use of integrative conceptual models in research on information and communication technologies in the health sector, and to encourage discussion of these conceptual models in scholarly forums. A two-part method was used to summarize and structure ideas about how to work effectively with conceptual models in health informatics research that included (1) a selective review and summary of the literature of conceptual models; and (2) the construction of a step-by-step approach to developing a conceptual model. The seven-step methodology for developing conceptual models in health informatics research explained in this paper involves (1) acknowledging the limitations of health science and information science conceptual models; (2) giving a rationale for one's choice of integrative conceptual model; (3) explicating a conceptual model verbally and graphically; (4) seeking feedback about the conceptual model from stakeholders in both the health science and information science domains; (5) aligning a conceptual model with an appropriate research plan; (6) adapting a conceptual model in response to new knowledge over time; and (7) disseminating conceptual models in scholarly and scientific forums. Making explicit the conceptual model that underpins a health informatics research project can contribute to increasing the number of well-formed and strongly grounded health informatics research projects. This explication has distinct benefits for researchers in training, research teams, and researchers and practitioners in information, health, and other disciplines.
Greased Lightning (GL-10) Performance Flight Research: Flight Data Report

NASA Technical Reports Server (NTRS)

McSwain, Robert G.; Glaab, Louis J.; Theodore, Colin R.; Rhew, Ray D. (Editor); North, David D. (Editor)

2017-01-01

Modern aircraft design methods have produced acceptable designs for large conventional aircraft performance. With revolutionary electronic propulsion technologies fueled by the growth in the small UAS (Unmanned Aerial Systems) industry, these same prediction models are being applied to new smaller, and experimental design concepts requiring a VTOL (Vertical Take Off and Landing) capability for ODM (On Demand Mobility). A 50% sub-scale GL-10 flight model was built and tested to demonstrate the transition from hover to forward flight utilizing DEP (Distributed Electric Propulsion)[1][2]. In 2016 plans were put in place to conduct performance flight testing on the 50% sub-scale GL-10 flight model to support a NASA project called DELIVER (Design Environment for Novel Vertical Lift Vehicles). DELIVER was investigating the feasibility of including smaller and more experimental aircraft configurations into a NASA design tool called NDARC (NASA Design and Analysis of Rotorcraft)[3]. This report covers the performance flight data collected during flight testing of the GL-10 50% sub-scale flight model conducted at Beaver Dam Airpark, VA. Overall the flight test data provides great insight into how well our existing conceptual design tools predict the performance of small scale experimental DEP concepts. Low fidelity conceptual design tools estimated the (L/D)( sub max)of the GL-10 50% sub-scale flight model to be 16. Experimentally measured (L/D)( sub max) for the GL-10 50% scale flight model was 7.2. The aerodynamic performance predicted versus measured highlights the complexity of wing and nacelle interactions which is not currently accounted for in existing low fidelity tools.
Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone

PubMed Central

Hawley, Alyse K.; Katsev, Sergei; Torres-Beltran, Monica; Bhatia, Maya P.; Kheirandish, Sam; Michiels, Céline C.; Capelle, David; Lavik, Gaute; Doebeli, Michael; Crowe, Sean A.; Hallam, Steven J.

2016-01-01

Microorganisms are the most abundant lifeform on Earth, mediating global fluxes of matter and energy. Over the past decade, high-throughput molecular techniques generating multiomic sequence information (DNA, mRNA, and protein) have transformed our perception of this microcosmos, conceptually linking microorganisms at the individual, population, and community levels to a wide range of ecosystem functions and services. Here, we develop a biogeochemical model that describes metabolic coupling along the redox gradient in Saanich Inlet—a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones (OMZs). The model reproduces measured biogeochemical process rates as well as DNA, mRNA, and protein concentration profiles across the redox gradient. Simulations make predictions about the role of ubiquitous OMZ microorganisms in mediating carbon, nitrogen, and sulfur cycling. For example, nitrite “leakage” during incomplete sulfide-driven denitrification by SUP05 Gammaproteobacteria is predicted to support inorganic carbon fixation and intense nitrogen loss via anaerobic ammonium oxidation. This coupling creates a metabolic niche for nitrous oxide reduction that completes denitrification by currently unidentified community members. These results quantitatively improve previous conceptual models describing microbial metabolic networks in OMZs. Beyond OMZ-specific predictions, model results indicate that geochemical fluxes are robust indicators of microbial community structure and reciprocally, that gene abundances and geochemical conditions largely determine gene expression patterns. The integration of real observational data, including geochemical profiles and process rate measurements as well as metagenomic, metatranscriptomic and metaproteomic sequence data, into a biogeochemical model, as shown here, enables holistic insight into the microbial metabolic network driving nutrient and energy flow at ecosystem scales. PMID:27655888
Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone.

PubMed

Louca, Stilianos; Hawley, Alyse K; Katsev, Sergei; Torres-Beltran, Monica; Bhatia, Maya P; Kheirandish, Sam; Michiels, Céline C; Capelle, David; Lavik, Gaute; Doebeli, Michael; Crowe, Sean A; Hallam, Steven J

2016-10-04

Microorganisms are the most abundant lifeform on Earth, mediating global fluxes of matter and energy. Over the past decade, high-throughput molecular techniques generating multiomic sequence information (DNA, mRNA, and protein) have transformed our perception of this microcosmos, conceptually linking microorganisms at the individual, population, and community levels to a wide range of ecosystem functions and services. Here, we develop a biogeochemical model that describes metabolic coupling along the redox gradient in Saanich Inlet-a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones (OMZs). The model reproduces measured biogeochemical process rates as well as DNA, mRNA, and protein concentration profiles across the redox gradient. Simulations make predictions about the role of ubiquitous OMZ microorganisms in mediating carbon, nitrogen, and sulfur cycling. For example, nitrite "leakage" during incomplete sulfide-driven denitrification by SUP05 Gammaproteobacteria is predicted to support inorganic carbon fixation and intense nitrogen loss via anaerobic ammonium oxidation. This coupling creates a metabolic niche for nitrous oxide reduction that completes denitrification by currently unidentified community members. These results quantitatively improve previous conceptual models describing microbial metabolic networks in OMZs. Beyond OMZ-specific predictions, model results indicate that geochemical fluxes are robust indicators of microbial community structure and reciprocally, that gene abundances and geochemical conditions largely determine gene expression patterns. The integration of real observational data, including geochemical profiles and process rate measurements as well as metagenomic, metatranscriptomic and metaproteomic sequence data, into a biogeochemical model, as shown here, enables holistic insight into the microbial metabolic network driving nutrient and energy flow at ecosystem scales.
Antecedents of eating disorders and muscle dysmorphia in a non-clinical sample.

PubMed

Lamanna, J; Grieve, F G; Derryberry, W Pitt; Hakman, M; McClure, A

2010-01-01

Muscle Dysmorphia (MD) has recently been conceptualized as the male form of Eating Disorders (ED); although, it is not currently classified as an ED. The current study compares etiological models of MD symptomatology and ED symptomatology. It was hypothesized that sociocultural influences on appearance (SIA) would predict body dissatisfaction (BD), and that this relationship would be mediated by self-esteem (SE) and perfectionism (P); that BD would predict negative affect (NA); and that NA would predict MD and ED symptomatology. Two-hundred-forty-seven female and 101 male college students at a midsouth university completed the study. All participants completed measures assessing each of the constructs, and multiple regression analyses were conducted to test each model's fit. In both models, most predictor paths were significant. These results suggest similarity in symptomatology and etiological models between ED and MD.
Traditions, Paradigms and Basic Concepts in Islamic Psychology.

PubMed

Skinner, Rasjid

2018-03-23

The conceptual tools of psychology aim to explain the complexity of phenomena that psychotherapists observe in their patients and within themselves, as well as to predict the outcome of therapy. Naturally, Muslim psychologists have sought satisfaction in the conceptual tools of their trade and in what has been written in Islamic psychology-notably by Badri (The dilemma of Muslim psychologists, MWH London, London, 1979), who critiqued Western psychology from an Islamic perspective, arguing the need to filter out from Western Psychology which was cross-culturally invalid or was in conflict with Islamic precept. In this paper, I advocate an extension of Badri's (1979) approach and present a working model of the self derived from traditional Islamic thought. This model, though rudimentary and incomplete, I believe, makes better sense of my perceptions as a clinician than any other psychological model within my knowledge.
How uncertain is model-based prediction of copper loads in stormwater runoff?

PubMed

Lindblom, E; Ahlman, S; Mikkelsen, P S

2007-01-01

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.
Dendritic trafficking faces physiologically critical speed-precision tradeoffs

DOE PAGES

Williams, Alex H.; O'Donnell, Cian; Sejnowski, Terrence J.; ...

2016-12-30

Nervous system function requires intracellular transport of channels, receptors, mRNAs, and other cargo throughout complex neuronal morphologies. Local signals such as synaptic input can regulate cargo trafficking, motivating the leading conceptual model of neuron-wide transport, sometimes called the ‘sushi-belt model’. Current theories and experiments are based on this model, yet its predictions are not rigorously understood. We formalized the sushi belt model mathematically, and show that it can achieve arbitrarily complex spatial distributions of cargo in reconstructed morphologies. However, the model also predicts an unavoidable, morphology dependent tradeoff between speed, precision and metabolic efficiency of cargo transport. With experimental estimatesmore » of trafficking kinetics, the model predicts delays of many hours or days for modestly accurate and efficient cargo delivery throughout a dendritic tree. In conclusion, these findings challenge current understanding of the efficacy of nucleus-to-synapse trafficking and may explain the prevalence of local biosynthesis in neurons.« less
Dendritic trafficking faces physiologically critical speed-precision tradeoffs

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

Williams, Alex H.; O'Donnell, Cian; Sejnowski, Terrence J.

Nervous system function requires intracellular transport of channels, receptors, mRNAs, and other cargo throughout complex neuronal morphologies. Local signals such as synaptic input can regulate cargo trafficking, motivating the leading conceptual model of neuron-wide transport, sometimes called the ‘sushi-belt model’. Current theories and experiments are based on this model, yet its predictions are not rigorously understood. We formalized the sushi belt model mathematically, and show that it can achieve arbitrarily complex spatial distributions of cargo in reconstructed morphologies. However, the model also predicts an unavoidable, morphology dependent tradeoff between speed, precision and metabolic efficiency of cargo transport. With experimental estimatesmore » of trafficking kinetics, the model predicts delays of many hours or days for modestly accurate and efficient cargo delivery throughout a dendritic tree. In conclusion, these findings challenge current understanding of the efficacy of nucleus-to-synapse trafficking and may explain the prevalence of local biosynthesis in neurons.« less
An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa.

PubMed

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence.
An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa

PubMed Central

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Purpose Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). Methods An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. Conclusion The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence. PMID:27175067
Persistent grief in the aftermath of mass violence: the predictive roles of posttraumatic stress symptoms, self-efficacy, and disrupted worldview.

PubMed

Smith, Andrew J; Abeyta, Andrew A; Hughes, Michael; Jones, Russell T

2015-03-01

This study tested a conceptual model merging anxiety buffer disruption and social-cognitive theories to predict persistent grief severity among students who lost a close friend, significant other, and/or professor/teacher in tragic university campus shootings. A regression-based path model tested posttraumatic stress (PTS) symptom severity 3 to 4 months postshooting (Time 1) as a predictor of grief severity 1 year postshootings (Time 2), both directly and indirectly through cognitive processes (self-efficacy and disrupted worldview). Results revealed a model that predicted 61% of the variance in Time 2 grief severity. Hypotheses were supported, demonstrating that Time 1 PTS severity indirectly, positively predicted Time 2 grief severity through undermining self-efficacy and more severely disrupting worldview. Findings and theoretical interpretation yield important insights for future research and clinical application. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Transition Models for Engineering Calculations

NASA Technical Reports Server (NTRS)

Fraser, C. J.

2007-01-01

While future theoretical and conceptual developments may promote a better understanding of the physical processes involved in the latter stages of boundary layer transition, the designers of rotodynamic machinery and other fluid dynamic devices need effective transition models now. This presentation will therefore center around the development of of some transition models which have been developed as design aids to improve the prediction codes used in the performance evaluation of gas turbine blading. All models are based on Narasimba's concentrated breakdown and spot growth.
Trajectories of collaborative scientific conceptual change: Middle school students learning about ecosystems in a CSCL environment

NASA Astrophysics Data System (ADS)

Liu, Lei

The dissertation aims to achieve two goals. First, it attempts to establish a new theoretical framework---the collaborative scientific conceptual change model, which explicitly attends to social factor and epistemic practices of science, to understand conceptual change. Second, it report the findings of a classroom study to investigate how to apply this theoretical framework to examine the trajectories of collaborative scientific conceptual change in a CSCL environment and provide pedagogical implications. Two simulations were designed to help students make connections between the macroscopic substances and the aperceptual microscopic entities and underlying processes. The reported study was focused on analyzing the aggregated data from all participants and the video and audio data from twenty focal groups' collaborative activities and the process of their conceptual development in two classroom settings. Mixed quantitative and qualitative analyses were applied to analyze the video/audio data. The results found that, overall participants showed significant improvements from pretest to posttest on system understanding. Group and teacher effect as well as group variability were detected in both students' posttest performance and their collaborative activities, and variability emerged in group interaction. Multiple data analyses found that attributes of collaborative discourse and epistemic practices made a difference in student learning. Generating warranted claims in discourse as well as the predicting, coordinating theory-evidence, and modifying knowledge in epistemic practices had an impact on student's conceptual understanding. However, modifying knowledge was found negatively related to students' learning effect. The case studies show how groups differed in using the computer tools as a medium to conduct collaborative discourse and epistemic practices. Only with certain combination of discourse features and epistemic practices can the group interaction lead to successful convergent understanding. The results of the study imply that the collaborative scientific conceptual change model is an effective framework to study conceptual change and the simulation environment may mediate the development of successful collaborative interactions (including collaborative discourse and epistemic practices) that lead to collaborative scientific conceptual change.
Understanding the Role of Academic Language on Conceptual Understanding in an Introductory Materials Science and Engineering Course

NASA Astrophysics Data System (ADS)

Kelly, Jacquelyn

Students may use the technical engineering terms without knowing what these words mean. This creates a language barrier in engineering that influences student learning. Previous research has been conducted to characterize the difference between colloquial and scientific language. Since this research had not yet been applied explicitly to engineering, conclusions from the area of science education were used instead. Various researchers outlined strategies for helping students acquire scientific language. However, few examined and quantified the relationship it had on student learning. A systemic functional linguistics framework was adopted for this dissertation which is a framework that has not previously been used in engineering education research. This study investigated how engineering language proficiency influenced conceptual understanding of introductory materials science and engineering concepts. To answer the research questions about engineering language proficiency, a convenience sample of forty-one undergraduate students in an introductory materials science and engineering course was used. All data collected was integrated with the course. Measures included the Materials Concept Inventory, a written engineering design task, and group observations. Both systemic functional linguistics and mental models frameworks were utilized to interpret data and guide analysis. A series of regression analyses were conducted to determine if engineering language proficiency predicts group engineering term use, if conceptual understanding predicts group engineering term use, and if conceptual understanding predicts engineering language proficiency. Engineering academic language proficiency was found to be strongly linked to conceptual understanding in the context of introductory materials engineering courses. As the semester progressed, this relationship became even stronger. The more engineering concepts students are expected to learn, the more important it is that they are proficient in engineering language. However, exposure to engineering terms did not influence engineering language proficiency. These results stress the importance of engineering language proficiency for learning, but warn that simply exposing students to engineering terms does not promote engineering language proficiency.
Temporal nonlocality in bistable perception

NASA Astrophysics Data System (ADS)

Atmanspacher, Harald; Filk, Thomas

2012-12-01

A novel conceptual framework for theoretical psychology is presented and illustrated for the example of bistable perception. A basic formal feature of this framework is the non-commutativity of operations acting on mental states. A corresponding model for the bistable perception of ambiguous stimuli, the Necker-Zeno model, is sketched and some empirical evidence for it so far is described. It is discussed how a temporal nonlocality of mental states, predicted by the model, can be understood and tested.
A Multidimensional Analysis of the Joint Strike Fighter (JSF) Acquisition Program from the Perspective of Turkey

DTIC Science & Technology

2016-12-01

Conceptual Models,” includes a thorough analysis of Turkey’s involvement in the F-35 program, based on Allison’s Rational Actor and Organizational ...TuAF, but also suggested an organizational structure similar to the U.S. DOD. In May 1949, the Turkish Parliament passed a law to reform the Turkish... organizational behavior model and a governmental politics model provide a base for improved explanations and predictions. (Allison & Zelikow, 1999) 40
Learning genetic inquiry through the use, revision, and justification of explanatory models

NASA Astrophysics Data System (ADS)

Cartier, Jennifer Lorraine

Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to come to a rich understanding of both the central concepts of transmission genetics and important epistemological aspects of genetic practice.
Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

NASA Astrophysics Data System (ADS)

Feyen, Luc; Caers, Jef

2006-06-01

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.

Solidarity-conflict and ambivalence: testing two conceptual frameworks and their impact on quality of life for older family members.

PubMed

Lowenstein, Ariela

2007-03-01

The purpose of this study was to test empirically two major conceptualizations of parent-child relations in later adulthood-intergenerational solidarity-conflict and ambivalence paradigms-and their predictive validity on elders' quality of life using comparative cross-national data. Data were from a sample of 2,064 elders (aged 75 and older) from the five-country OASIS study (Old Age and Autonomy: The Role of Service Systems and Intergenerational Family Solidarity; Norway, England, Germany, Spain, and Israel). Multivariate and block-recursive regression models estimated the predictivity of the two conceptualizations of family dynamics on quality of life controlling for country, personal characteristics, and activity of daily living functioning. Descriptive analyses indicated that family solidarity, especially the affective/cognitive component (called Solidarity A), was high in all five countries, whereas conflict and ambivalence were low. When I entered all three constructs into the regression Solidarity A, reciprocal intergenerational support and ambivalence predicted quality of life. Controlling for activity of daily living functioning, socioeconomics status, and country, intergenerational relations had only a weak explanatory power, and personal resources explained most of the variance. The data suggest that the three constructs exist simultaneously but in varying combinations, confirming that in cross-cultural contexts family cohesion predominates, albeit with low degrees of conflict and ambivalence. The solidarity construct evidenced relatively robust measurement. More work is required to enhance the ambivalence measurement.
Expectancy-Value and Cognitive Process Outcomes in Mathematics Learning: A Structural Equation Analysis

ERIC Educational Resources Information Center

Phan, Huy P.

2014-01-01

Existing research has yielded evidence to indicate that the expectancy-value theoretical model predicts students' learning in various achievement contexts. Achievement values and self-efficacy expectations, for example, have been found to exert positive effects on cognitive process and academic achievement outcomes. We tested a conceptual model…
Clarifying Relationships among Work and Family Social Support, Stressors, and Work-Family Conflict

ERIC Educational Resources Information Center

Michel, Jesse S.; Mitchelson, Jacqueline K.; Pichler, Shaun; Cullen, Kristin L.

2010-01-01

Although work and family social support predict role stressors and work-family conflict, there has been much ambiguity regarding the conceptual relationships among these constructs. Using path analysis on meta-analytically derived validity coefficients (528 effect sizes from 156 samples), we compare three models to address these concerns and…
Understanding and Using Informants Reporting Discrepancies of Youth Victimization: A Conceptual Model and Recommendations for Research

ERIC Educational Resources Information Center

Goodman, Kimberly L.; De Los Reyes, Andres; Bradshaw, Catherine P.

2010-01-01

Discrepancies often occur among informants' reports of various domains of child and family functioning and are particularly common between parent and child reports of youth violence exposure. However, recent work suggests that discrepancies between parent and child reports predict subsequent poorer child outcomes. We propose a preliminary…
Defining species guilds in the Central Hardwood Forest, USA

Treesearch

Elaine Kennedy Sutherland; Betsy J. Hale; David M. Hix

2000-01-01

Tree regeneration outcomes are challenging to generalize and difficult to predict. Many tree species can establish new propagules in a variety of post-disturbance environments and many different reproductive mechanisms may be used. In order to develop conceptual models that accurately reflect reproductive potential, we need a better understanding of the similarities in...
Longitudinal Examination of Optimism, Personal Self-Efficacy and Student Well-Being: A Path Analysis

ERIC Educational Resources Information Center

Phan, Huy P.

2016-01-01

The present longitudinal study, based on existing theoretical tenets, explored a conceptual model that depicted four major orientations: optimism, self-efficacy, and academic well-being. An important question for consideration, in this case, involved the testing of different untested trajectories that could explain and predict individuals'…
Molecular Reactivity and Absorption Properties of Melanoidin Blue-G1 through Conceptual DFT.

PubMed

Frau, Juan; Glossman-Mitnik, Daniel

2018-03-02

This computational study presents the assessment of eleven density functionals that include CAM-B3LYP, LC-wPBE, M11, M11L, MN12L, MN12SX, N12, N12SX, wB97, wB97X and wB97XD related to the Def2TZVP basis sets together with the Solvation Model Density (SMD) solvation model in calculating the molecular properties and structure of the Blue-G1 intermediate melanoidin pigment. The chemical reactivity descriptors for the system are calculated via the conceptual Density Functional Theory (DFT). The choice of the active sites related to the nucleophilic, electrophilic, as well as radical attacks is made by linking them with the Fukui function indices, the electrophilic Parr functions and the condensed dual descriptor Δ f ( r ) . The prediction of the maximum absorption wavelength tends to be considerably accurate relative to its experimental value. The study found the MN12SX and N12SX density functionals to be the most appropriate density functionals in predicting the chemical reactivity of the studied molecule.
Heteromodal Cortical Areas Encode Sensory-Motor Features of Word Meaning.

PubMed

Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Seidenberg, Mark S; Binder, Jeffrey R

2016-09-21

The capacity to process information in conceptual form is a fundamental aspect of human cognition, yet little is known about how this type of information is encoded in the brain. Although the role of sensory and motor cortical areas has been a focus of recent debate, neuroimaging studies of concept representation consistently implicate a network of heteromodal areas that seem to support concept retrieval in general rather than knowledge related to any particular sensory-motor content. We used predictive machine learning on fMRI data to investigate the hypothesis that cortical areas in this "general semantic network" (GSN) encode multimodal information derived from basic sensory-motor processes, possibly functioning as convergence-divergence zones for distributed concept representation. An encoding model based on five conceptual attributes directly related to sensory-motor experience (sound, color, shape, manipulability, and visual motion) was used to predict brain activation patterns associated with individual lexical concepts in a semantic decision task. When the analysis was restricted to voxels in the GSN, the model was able to identify the activation patterns corresponding to individual concrete concepts significantly above chance. In contrast, a model based on five perceptual attributes of the word form performed at chance level. This pattern was reversed when the analysis was restricted to areas involved in the perceptual analysis of written word forms. These results indicate that heteromodal areas involved in semantic processing encode information about the relative importance of different sensory-motor attributes of concepts, possibly by storing particular combinations of sensory and motor features. The present study used a predictive encoding model of word semantics to decode conceptual information from neural activity in heteromodal cortical areas. The model is based on five sensory-motor attributes of word meaning (color, shape, sound, visual motion, and manipulability) and encodes the relative importance of each attribute to the meaning of a word. This is the first demonstration that heteromodal areas involved in semantic processing can discriminate between different concepts based on sensory-motor information alone. This finding indicates that the brain represents concepts as multimodal combinations of sensory and motor representations. Copyright © 2016 the authors 0270-6474/16/369763-07$15.00/0.
Evaluation and development of satellite inferences of convective storm intensity using combined case study analysis and thunderstorm model simulations

NASA Technical Reports Server (NTRS)

Cotton, W. R.; Tripoli, G. J.

1980-01-01

Major research accomplishments which were achieved during the first year of the grant are summarized. The research concentrated in the following areas: (1) an examination of observational requirements for predicting convective storm development and intensity as suggested by recent numerical experiments; (2) interpretation of recent 3D numerical experiments with regard to the relationship between overshooting tops and surface wind gusts; (3) the development of software for emulating satellite-inferred cloud properties using 3D cloud model predicted data; and (4) the development of a conceptual/semi-quantitative model of eastward propagating, mesoscale convective complexes forming to the lee of the Rocky Mountains.
Visuoperceptual repetition priming and progression of parkinsonian signs in aging

PubMed Central

Fleischman, Debra A.; Buchman, Aron S.; Bienias, Julia L.; Bennett, David A.

2009-01-01

Parkinsonian signs in older persons are associated with numerous adverse health outcomes, however there is limited information about factors which predict progression of these signs. Using generalized linear models, we examined the association between efficiency in visuoperceptual and conceptual processing, measured by repetition priming, and rate of change in parkinsonian signs in a large sample of older persons without cognitive impairment or Parkinson’s disease. Subjects with better visuoperceptual priming, measured by threshold word-identification and word-stem completion, at study baseline, progressed more slowly during follow-up of up to 11 years. Conceptual priming was not associated with change in parkinsonian signs. The findings demonstrate that individual differences in visuoperceptual efficiency, measured by repetition priming, occur in older persons without cognitive impairment and predict important changes in motor function. Reduced visuoperceptual priming in aging may be an early signal of vulnerability in a corticostrial circuit that contributes to sensorimotor integration. PMID:17709154
Validation of Groundwater Models: Meaningful or Meaningless?

NASA Astrophysics Data System (ADS)

Konikow, L. F.

2003-12-01

Although numerical simulation models are valuable tools for analyzing groundwater systems, their predictive accuracy is limited. People who apply groundwater flow or solute-transport models, as well as those who make decisions based on model results, naturally want assurance that a model is "valid." To many people, model validation implies some authentication of the truth or accuracy of the model. History matching is often presented as the basis for model validation. Although such model calibration is a necessary modeling step, it is simply insufficient for model validation. Because of parameter uncertainty and solution non-uniqueness, declarations of validation (or verification) of a model are not meaningful. Post-audits represent a useful means to assess the predictive accuracy of a site-specific model, but they require the existence of long-term monitoring data. Model testing may yield invalidation, but that is an opportunity to learn and to improve the conceptual and numerical models. Examples of post-audits and of the application of a solute-transport model to a radioactive waste disposal site illustrate deficiencies in model calibration, prediction, and validation.
The Sim-SEQ Project: Comparison of Selected Flow Models for the S-3 Site

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

Mukhopadhyay, Sumit; Doughty, Christine A.; Bacon, Diana H.

Sim-SEQ is an international initiative on model comparison for geologic carbon sequestration, with an objective to understand and, if possible, quantify model uncertainties. Model comparison efforts in Sim-SEQ are at present focusing on one specific field test site, hereafter referred to as the Sim-SEQ Study site (or S-3 site). Within Sim-SEQ, different modeling teams are developing conceptual models of CO2 injection at the S-3 site. In this paper, we select five flow models of the S-3 site and provide a qualitative comparison of their attributes and predictions. These models are based on five different simulators or modeling approaches: TOUGH2/EOS7C, STOMP-CO2e,more » MoReS, TOUGH2-MP/ECO2N, and VESA. In addition to model-to-model comparison, we perform a limited model-to-data comparison, and illustrate how model choices impact model predictions. We conclude the paper by making recommendations for model refinement that are likely to result in less uncertainty in model predictions.« less
The Impact of Meaning and Dimensionality on Copying Accuracy in Individuals with Autism

ERIC Educational Resources Information Center

Sheppard, Elizabeth; Ropar, Danielle; Mitchell, Peter

2007-01-01

Weak Central Coherence (Frith, 1989) predicts that, in autism, perceptual processing is relatively unaffected by conceptual analysis. Enhanced Perceptual Functioning (Mottron & Burack, 2001) predicts that the perceptual processing of those with autism is less influenced by conceptual analysis only when higher-level processing is detrimental to…
Promoting Conceptual Change in First Year Students' Understanding of Evaporation

ERIC Educational Resources Information Center

Costu, Bayram; Ayas, Alipasa; Niaz, Mansoor

2010-01-01

We constructed the PDEODE (Predict-Discuss-Explain-Observe-Discuss-Explain) teaching strategy, a variant of the classical POE (Predict-Observe-Explain) activity, to promote conceptual change, and investigated its effectiveness on student understanding of the evaporation concept. The sample consisted of 52 first year students in a primary science…
Multiphase modeling of geologic carbon sequestration in saline aquifers.

PubMed

Bandilla, Karl W; Celia, Michael A; Birkholzer, Jens T; Cihan, Abdullah; Leister, Evan C

2015-01-01

Geologic carbon sequestration (GCS) is being considered as a climate change mitigation option in many future energy scenarios. Mathematical modeling is routinely used to predict subsurface CO2 and resident brine migration for the design of injection operations, to demonstrate the permanence of CO2 storage, and to show that other subsurface resources will not be degraded. Many processes impact the migration of CO2 and brine, including multiphase flow dynamics, geochemistry, and geomechanics, along with the spatial distribution of parameters such as porosity and permeability. In this article, we review a set of multiphase modeling approaches with different levels of conceptual complexity that have been used to model GCS. Model complexity ranges from coupled multiprocess models to simplified vertical equilibrium (VE) models and macroscopic invasion percolation models. The goal of this article is to give a framework of conceptual model complexity, and to show the types of modeling approaches that have been used to address specific GCS questions. Application of the modeling approaches is shown using five ongoing or proposed CO2 injection sites. For the selected sites, the majority of GCS models follow a simplified multiphase approach, especially for questions related to injection and local-scale heterogeneity. Coupled multiprocess models are only applied in one case where geomechanics have a strong impact on the flow. Owing to their computational efficiency, VE models tend to be applied at large scales. A macroscopic invasion percolation approach was used to predict the CO2 migration at one site to examine details of CO2 migration under the caprock. © 2015, National Ground Water Association.
Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change

USGS Publications Warehouse

McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.

2012-01-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.
Assessing conceptual models for subsurface reactive transport of inorganic contaminants

USGS Publications Warehouse

Davis, James A.; Yabusaki, Steven B.; Steefel, Carl; Zachara, John M.; Curtis, Gary P.; Redden, George D.; Criscenti, Louise J.; Honeyman, Bruce D.

2004-01-01

In many subsurface situations where human health and environmental quality are at risk (e.g., contaminant hydrogeology petroleum extraction, carbon sequestration, etc.),scientists and engineers are being asked by federal agency decision-makers to predict the fate of chemical species under conditions where both reactions and transport are processes of first-order importance.In 2002, a working group (WG) was formed by representatives of the U.S. Geological Survey, Environmental Protection Agency, Department of Energy Nuclear Regulatory Commission, Department of Agriculture, and Army Engineer Research and Development Center to assess the role of reactive transport modeling (RTM) in addressing these situations. Specifically the goals of the WG are to (1) evaluate the state of the art in conceptual model development and parameterization for RTM, as applied to soil,vadose zone, and groundwater systems, and (2) prioritize research directions that would enhance the practical utility of RTM.
Groundwater model of the Blue River basin, Nebraska-Twenty years later

USGS Publications Warehouse

Alley, W.M.; Emery, P.A.

1986-01-01

Groundwater flow models have become almost a routine tool of the practicing hydrologist. Yet, surprisingly little attention has been given to true verification analysis of studies using these models. This paper examines predictions for 1982 of water-level declines and streamflow depletions that were made in 1965 using an electric analog groundwater model of the Blue River basin in southeastern Nebraska. Analysis of the model's predictions suggests that the analog model used too low an estimate of net groundwater withdrawals, yet overestimated water-level declines. The model predicted that almost all of the net groundwater pumpage would come from storage in the Pleistocene aquifer within the Blue River basin. It appears likely that the model underestimated the contributions of other sources of water to the pumpage, and that the aquifer storage coefficients used in the model were too low. There is some evidence that groundwater pumpage has had a greater than predicted effect on streamflow. Considerable uncertainty about the basic conceptualization of the hydrology of the Blue River basin greatly limits the reliability of groundwater models developed for the basin. The paper concludes with general perspectives on groundwater modeling gained from this post-audit analysis. ?? 1986.
Learning To Fold Proteins Using Energy Landscape Theory

PubMed Central

Schafer, N.P.; Kim, B.L.; Zheng, W.; Wolynes, P.G.

2014-01-01

This review is a tutorial for scientists interested in the problem of protein structure prediction, particularly those interested in using coarse-grained molecular dynamics models that are optimized using lessons learned from the energy landscape theory of protein folding. We also present a review of the results of the AMH/AMC/AMW/AWSEM family of coarse-grained molecular dynamics protein folding models to illustrate the points covered in the first part of the article. Accurate coarse-grained structure prediction models can be used to investigate a wide range of conceptual and mechanistic issues outside of protein structure prediction; specifically, the paper concludes by reviewing how AWSEM has in recent years been able to elucidate questions related to the unusual kinetic behavior of artificially designed proteins, multidomain protein misfolding, and the initial stages of protein aggregation. PMID:25308991
Macromolecular target prediction by self-organizing feature maps.

PubMed

Schneider, Gisbert; Schneider, Petra

2017-03-01

Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

On the Spatial Foundations of the Conceptual System and Its Enrichment

ERIC Educational Resources Information Center

Mandler, Jean M.

2012-01-01

A theory of how concept formation begins is presented that accounts for conceptual activity in the first year of life, shows how increasing conceptual complexity comes about, and predicts the order in which new types of information accrue to the conceptual system. In a compromise between nativist and empiricist views, it offers a single…
. Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability

USGS Publications Warehouse

Gentile, J.H.; Harwell, M.A.; Cropper, W.; Harwell, C. C.; DeAngelis, Donald L.; Davis, S.; Ogden, J.C.; Lirman, D.

2001-01-01

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.
Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability.

PubMed

Gentile, J H; Harwell, M A; Cropper, W; Harwell, C C; DeAngelis, D; Davis, S; Ogden, J C; Lirman, D

2001-07-02

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability, and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.
Quantification of uncertainties related to the regional application of a conceptual hydrological model in Benin (West Africa)

NASA Astrophysics Data System (ADS)

Bormann, H.; Diekkrüger, B.

2003-04-01

A conceptual model is presented to simulate the water fluxes of regional catchments in Benin (West Africa). The model is applied in the framework of the IMPETUS project (an integrated approach to the efficient management of scarce water resources in West Africa) which aims to assess the effects of environmental and anthropogenic changes on the regional hydrological processes and on the water availability in Benin. In order to assess the effects of decreasing precipitation and increasing human activities on the hydrological processes in the upper Ouémé valley, a scenario analysis is performed to predict possible changes. Therefore a regional hydrological model is proposed which reproduces the recent hydrological processes, and which is able to consider the changes of landscape properties.The study presented aims to check the validity of the conceptual and lumped model under the conditions of the subhumid tree savannah and therefore analyses the importance of possible sources of uncertainty. Main focus is set on the uncertainties caused by input data, model parameters and model structure. As the model simulates the water fluxes at the catchment outlet of the Térou river (3133 km2) in a sufficient quality, first results of a scenario analysis are presented. Changes of interest are the expected future decrease in amount and temporal structure of the precipitation (e.g. minus X percent precipitation during the whole season versus minus X percent precipitation in the end of the rainy season, alternatively), the decrease in soil water storage capacity which is caused by erosion, and the increasing consumption of ground water for drinking water and agricultural purposes. Resuming from the results obtained, the perspectives of lumped and conceptual models are discussed with special regard to available management options of this kind of models. Advantages and disadvantages compared to alternative model approaches (process based, physics based) are discussed.
The nature and development of hypothetico-predictive argumentation with implications for science teaching

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

2003-11-01

This paper explicates a pattern of scientific argumentation in which scientists respond to causal questions with the generation and test of alternative hypotheses through cycles of hypothetico-predictive argumentation. Hypothetico-predictive arguments are employed to test causal claims that exist on at least two levels (designated stage 4 in which the causal claims are perceptible, and stage 5 in which the causal claims are imperceptible). Origins of the ability to construct and comprehend hypothetico-predictive arguments at the highest level can be traced to pre-verbal reasoning of the sensory-motor child and the gradual internalization of verbally mediated arguments involving nominal, categorical, causal and, finally, theoretical propositions. Presumably, the ability to construct and comprehend hypothetico-predictive arguments (an aspect of procedural knowledge) is necessary for the construction of conceptual knowledge (an aspect of declarative knowledge) because such arguments are used during concept construction and conceptual change. Science instruction that focuses on the generation and debate of hypothetico-predictive arguments should improve students' conceptual understanding and their argumentative/reasoning skills.
Perceptual Processing Affects Conceptual Processing

ERIC Educational Resources Information Center

van Dantzig, Saskia; Pecher, Diane; Zeelenberg, Rene; Barsalou, Lawrence W.

2008-01-01

According to the Perceptual Symbols Theory of cognition (Barsalou, 1999), modality-specific simulations underlie the representation of concepts. A strong prediction of this view is that perceptual processing affects conceptual processing. In this study, participants performed a perceptual detection task and a conceptual property-verification task…
Dynamics in microbial communities: Unraveling mechanisms to identify principles

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

Konopka, Allan; Lindemann, Stephen R.; Fredrickson, Jim K.

2015-07-01

Diversity begets higher order properties such as functional stability and robustness in microbial communities, but principles that inform conceptual (and eventually predictive) models of community dynamics are lacking. Recent work has shown that selection as well as dispersal and drift shape communities, but the mechanistic bases for assembly of communities and the forces that maintain their function in the face of environmental perturbation are not well understood. Conceptually, some interactions among community members could generate endogenous dynamics in composition, even in the absence of environmental changes. These endogenous dynamics are further perturbed by exogenous forcing factors to produce a richermore » network of community interactions, and it is this “system” that is the basis for higher order community properties. Elucidation of principles that follow from this conceptual model requires identifying the mechanisms that (a) optimize diversity within a community and (b) impart community stability. The network of interactions between organisms can be an important element by providing a buffer against disturbance beyond the effect of functional redundancy, as alternative pathways with different combinations of microbes can be recruited to fulfill specific functions.« less
The evolution of social and semantic networks in epistemic communities

NASA Astrophysics Data System (ADS)

Margolin, Drew Berkley

This study describes and tests a model of scientific inquiry as an evolving, organizational phenomenon. Arguments are derived from organizational ecology and evolutionary theory. The empirical subject of study is an epistemic community of scientists publishing on a research topic in physics: the string theoretic concept of "D-branes." The study uses evolutionary theory as a means of predicting change in the way members of the community choose concepts to communicate acceptable knowledge claims. It is argued that the pursuit of new knowledge is risky, because the reliability of a novel knowledge claim cannot be verified until after substantial resources have been invested. Using arguments from both philosophy of science and organizational ecology, it is suggested that scientists can mitigate and sensibly share the risks of knowledge discovery within the community by articulating their claims in legitimate forms, i.e., forms that are testable within and relevant to the community. Evidence from empirical studies of semantic usage suggests that the legitimacy of a knowledge claim is influenced by the characteristics of the concepts in which it is articulated. A model of conceptual retention, variation, and selection is then proposed for predicting the usage of concepts and conceptual co-occurrences in the future publications of the community, based on its past. Results substantially supported hypothesized retention and selection mechanisms. Future concept usage was predictable from previous concept usage, but was limited by conceptual carrying capacity as predicted by density dependence theory. Also as predicted, retention was stronger when the community showed a more cohesive social structure. Similarly, concepts that showed structural signatures of high testability and relevance were more likely to be selected after previous usage frequency was controlled for. By contrast, hypotheses for variation mechanisms were not supported. Surprisingly, concepts whose structural position suggested they would be easiest to discover through search processes were used less frequently, once previous usage frequency was controlled for. The study also makes a theoretical contribution by suggesting ways that evolutionary theory can be used to integrate findings from the study of science with insights from organizational communication. A variety of concrete directions for future studies of social and semantic network evolution are also proposed.
Will There Always Be an Institution? II: The Impact of New Service Models--Residential Alternatives to Institutions

ERIC Educational Resources Information Center

Wolfensberger, Wolf

2011-01-01

In this two-part series of articles, it is predicted that institutions will be phased out because of five trends: development of nonresidential community services; new conceptualizations of and attitudes toward residential services: increased usage of individual rather than group residential placements; provision of small, specialized group…
Voluntary Midlife Career Change: Integrating the Transtheoretical Model and the Life-Span, Life-Space Approach

ERIC Educational Resources Information Center

Barclay, Susan R.; Stoltz, Kevin B.; Chung, Y. Barry

2011-01-01

Frequent career change is the predicted experience of workers in the global economy. Self initiating career changers are a substantial subset of the total population of career changers. There is currently a dearth of theory and research to help career counselors conceptualize the career change process for the application of appropriate…
Personalized Medicine and Infectious Disease Management.

PubMed

Jensen, Slade O; van Hal, Sebastiaan J

2017-11-01

A recent study identified pathogen factors associated with an increased mortality risk in Staphylococcus aureus bacteremia, using predictive modelling and a combination of genotypic, phenotypic, and clinical data. This study conceptually validates the benefit of personalized medicine and highlights the potential use of whole genome sequencing in infectious disease management. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Framework for Text Mining in Scientometric Study: A Case Study in Biomedicine Publications

NASA Astrophysics Data System (ADS)

Silalahi, V. M. M.; Hardiyati, R.; Nadhiroh, I. M.; Handayani, T.; Rahmaida, R.; Amelia, M.

2018-04-01

The data of Indonesians research publications in the domain of biomedicine has been collected to be text mined for the purpose of a scientometric study. The goal is to build a predictive model that provides a classification of research publications on the potency for downstreaming. The model is based on the drug development processes adapted from the literatures. An effort is described to build the conceptual model and the development of a corpus on the research publications in the domain of Indonesian biomedicine. Then an investigation is conducted relating to the problems associated with building a corpus and validating the model. Based on our experience, a framework is proposed to manage the scientometric study based on text mining. Our method shows the effectiveness of conducting a scientometric study based on text mining in order to get a valid classification model. This valid model is mainly supported by the iterative and close interactions with the domain experts starting from identifying the issues, building a conceptual model, to the labelling, validation and results interpretation.
Reflectance of a vegetation canopy using the Adding method

NASA Technical Reports Server (NTRS)

Cooper, K.; Smith, J. A.; Pitts, D.

1982-01-01

A modified vegetation reflectance model based on the Adding method is presented as a means to measure the interaction of shortwave radiation within a vegetation canopy. The canopy is conceptualized with reflecting and transmitting leaf facets, with the leaf orientations described by a leaf slope distribution, thereby yielding scattering matrices for canopy layers. The model predictions, when compared with ground-truth measurements, show good agreement except at visible wavelengths, where overestimations are observed. Conditions under which the model satisfies the reciprocity theorem are defined. Extension of the model by including azimuth is indicated.
A health hierarchy of effects model: a synthesis of advertising and health hierarchy conceptualizations.

PubMed

Rouse, R A

1991-01-01

Work by both advertising and health researchers has independently yielded hierarchy of effects models which can be used to predict campaign success. Unfortunately, however, previous work has been criticized as "common sense" approaches which are more "assumed" than "proven." This analysis argues that much of the problem is due to the lack of precision often associated with over-simplified "uni-dimensional" models. Instead, this perspective synthesized a "two-dimensional" health hierarchy of effects model and outlines a pragmatic strategy for campaign measurement.
Automating Structural Analysis of Spacecraft Vehicles

NASA Technical Reports Server (NTRS)

Hrinda, Glenn A.

2004-01-01

A major effort within NASA's vehicle analysis discipline has been to automate structural analysis and sizing optimization during conceptual design studies of advanced spacecraft. Traditional spacecraft structural sizing has involved detailed finite element analysis (FEA) requiring large degree-of-freedom (DOF) finite element models (FEM). Creation and analysis of these models can be time consuming and limit model size during conceptual designs. The goal is to find an optimal design that meets the mission requirements but produces the lightest structure. A structural sizing tool called HyperSizer has been successfully used in the conceptual design phase of a reusable launch vehicle and planetary exploration spacecraft. The program couples with FEA to enable system level performance assessments and weight predictions including design optimization of material selections and sizing of spacecraft members. The software's analysis capabilities are based on established aerospace structural methods for strength, stability and stiffness that produce adequately sized members and reliable structural weight estimates. The software also helps to identify potential structural deficiencies early in the conceptual design so changes can be made without wasted time. HyperSizer's automated analysis and sizing optimization increases productivity and brings standardization to a systems study. These benefits will be illustrated in examining two different types of conceptual spacecraft designed using the software. A hypersonic air breathing, single stage to orbit (SSTO), reusable launch vehicle (RLV) will be highlighted as well as an aeroshell for a planetary exploration vehicle used for aerocapture at Mars. By showing the two different types of vehicles, the software's flexibility will be demonstrated with an emphasis on reducing aeroshell structural weight. Member sizes, concepts and material selections will be discussed as well as analysis methods used in optimizing the structure. Analysis based on the HyperSizer structural sizing software will be discussed. Design trades required to optimize structural weight will be presented.
Conceptual framework for model-based analysis of residence time distribution in twin-screw granulation.

PubMed

Kumar, Ashish; Vercruysse, Jurgen; Vanhoorne, Valérie; Toiviainen, Maunu; Panouillot, Pierre-Emmanuel; Juuti, Mikko; Vervaet, Chris; Remon, Jean Paul; Gernaey, Krist V; De Beer, Thomas; Nopens, Ingmar

2015-04-25

Twin-screw granulation is a promising continuous alternative for traditional batchwise wet granulation processes. The twin-screw granulator (TSG) screws consist of transport and kneading element modules. Therefore, the granulation to a large extent is governed by the residence time distribution within each module where different granulation rate processes dominate over others. Currently, experimental data is used to determine the residence time distributions. In this study, a conceptual model based on classical chemical engineering methods is proposed to better understand and simulate the residence time distribution in a TSG. The experimental data were compared with the proposed most suitable conceptual model to estimate the parameters of the model and to analyse and predict the effects of changes in number of kneading discs and their stagger angle, screw speed and powder feed rate on residence time. The study established that the kneading block in the screw configuration acts as a plug-flow zone inside the granulator. Furthermore, it was found that a balance between the throughput force and conveying rate is required to obtain a good axial mixing inside the twin-screw granulator. Although the granulation behaviour is different for other excipients, the experimental data collection and modelling methods applied in this study are generic and can be adapted to other excipients. Copyright © 2015 Elsevier B.V. All rights reserved.
Progress of Aircraft System Noise Assessment with Uncertainty Quantification for the Environmentally Responsible Aviation Project

NASA Technical Reports Server (NTRS)

Thomas, Russell H.; Burley, Casey L.; Guo, Yueping

2016-01-01

Aircraft system noise predictions have been performed for NASA modeled hybrid wing body aircraft advanced concepts with 2025 entry-into-service technology assumptions. The system noise predictions developed over a period from 2009 to 2016 as a result of improved modeling of the aircraft concepts, design changes, technology development, flight path modeling, and the use of extensive integrated system level experimental data. In addition, the system noise prediction models and process have been improved in many ways. An additional process is developed here for quantifying the uncertainty with a 95% confidence level. This uncertainty applies only to the aircraft system noise prediction process. For three points in time during this period, the vehicle designs, technologies, and noise prediction process are documented. For each of the three predictions, and with the information available at each of those points in time, the uncertainty is quantified using the direct Monte Carlo method with 10,000 simulations. For the prediction of cumulative noise of an advanced aircraft at the conceptual level of design, the total uncertainty band has been reduced from 12.2 to 9.6 EPNL dB. A value of 3.6 EPNL dB is proposed as the lower limit of uncertainty possible for the cumulative system noise prediction of an advanced aircraft concept.
Process-aware EHR BPM systems: two prototypes and a conceptual framework.

PubMed

Webster, Charles; Copenhaver, Mark

2010-01-01

Systematic methods to improve the effectiveness and efficiency of electronic health record-mediated processes will be key to EHRs playing an important role in the positive transformation of healthcare. Business process management (BPM) systematically optimizes process effectiveness, efficiency, and flexibility. Therefore BPM offers relevant ideas and technologies. We provide a conceptual model based on EHR productivity and negative feedback control that links EHR and BPM domains, describe two EHR BPM prototype modules, and close with the argument that typical EHRs must become more process-aware if they are to take full advantage of BPM ideas and technology. A prediction: Future extensible clinical groupware will coordinate delivery of EHR functionality to teams of users by combining modular components with executable process models whose usability (effectiveness, efficiency, and user satisfaction) will be systematically improved using business process management techniques.
Benchmarking of dynamic simulation predictions in two software platforms using an upper limb musculoskeletal model

PubMed Central

Saul, Katherine R.; Hu, Xiao; Goehler, Craig M.; Vidt, Meghan E.; Daly, Melissa; Velisar, Anca; Murray, Wendy M.

2014-01-01

Several opensource or commercially available software platforms are widely used to develop dynamic simulations of movement. While computational approaches are conceptually similar across platforms, technical differences in implementation may influence output. We present a new upper limb dynamic model as a tool to evaluate potential differences in predictive behavior between platforms. We evaluated to what extent differences in technical implementations in popular simulation software environments result in differences in kinematic predictions for single and multijoint movements using EMG- and optimization-based approaches for deriving control signals. We illustrate the benchmarking comparison using SIMM-Dynamics Pipeline-SD/Fast and OpenSim platforms. The most substantial divergence results from differences in muscle model and actuator paths. This model is a valuable resource and is available for download by other researchers. The model, data, and simulation results presented here can be used by future researchers to benchmark other software platforms and software upgrades for these two platforms. PMID:24995410
Dendritic trafficking faces physiologically critical speed-precision tradeoffs

PubMed Central

Williams, Alex H; O'Donnell, Cian; Sejnowski, Terrence J; O'Leary, Timothy

2016-01-01

Nervous system function requires intracellular transport of channels, receptors, mRNAs, and other cargo throughout complex neuronal morphologies. Local signals such as synaptic input can regulate cargo trafficking, motivating the leading conceptual model of neuron-wide transport, sometimes called the ‘sushi-belt model’ (Doyle and Kiebler, 2011). Current theories and experiments are based on this model, yet its predictions are not rigorously understood. We formalized the sushi belt model mathematically, and show that it can achieve arbitrarily complex spatial distributions of cargo in reconstructed morphologies. However, the model also predicts an unavoidable, morphology dependent tradeoff between speed, precision and metabolic efficiency of cargo transport. With experimental estimates of trafficking kinetics, the model predicts delays of many hours or days for modestly accurate and efficient cargo delivery throughout a dendritic tree. These findings challenge current understanding of the efficacy of nucleus-to-synapse trafficking and may explain the prevalence of local biosynthesis in neurons. DOI: http://dx.doi.org/10.7554/eLife.20556.001 PMID:28034367

Benchmarking of dynamic simulation predictions in two software platforms using an upper limb musculoskeletal model.

PubMed

Saul, Katherine R; Hu, Xiao; Goehler, Craig M; Vidt, Meghan E; Daly, Melissa; Velisar, Anca; Murray, Wendy M

2015-01-01

Several opensource or commercially available software platforms are widely used to develop dynamic simulations of movement. While computational approaches are conceptually similar across platforms, technical differences in implementation may influence output. We present a new upper limb dynamic model as a tool to evaluate potential differences in predictive behavior between platforms. We evaluated to what extent differences in technical implementations in popular simulation software environments result in differences in kinematic predictions for single and multijoint movements using EMG- and optimization-based approaches for deriving control signals. We illustrate the benchmarking comparison using SIMM-Dynamics Pipeline-SD/Fast and OpenSim platforms. The most substantial divergence results from differences in muscle model and actuator paths. This model is a valuable resource and is available for download by other researchers. The model, data, and simulation results presented here can be used by future researchers to benchmark other software platforms and software upgrades for these two platforms.
The Emergence of Family-specific Support Constructs: Cross-level Effects of Family-supportive Supervision and Family-Supportive Organization Perceptions on Individual Outcomes.

PubMed

Hill, Rachel T; Matthews, Russell A; Walsh, Benjamin M

2016-12-01

Implicit to the definitions of both family-supportive supervision (FSS) and family-supportive organization perceptions (FSOP) is the argument that these constructs may manifest at a higher (e.g. group or organizational) level. In line with these conceptualizations, grounded in tenants of conservation of resources theory, we argue that FSS and FSOP, as universal resources, are emergent constructs at the organizational level, which have cross-level effects on work-family conflict and turnover intentions. To test our theoretically derived hypotheses, a multilevel model was examined in which FSS and FSOP at the unit level predict individual work-to-family conflict, which in turn predicts turnover intentions. Our hypothesized model was generally supported. Collectively, our results point to FSOP serving as an explanatory mechanism of the effects that mutual perceptions of FSS have on individual experiences of work-to-family conflict and turnover intentions. Lagged (i.e. overtime) cross-level effects of the model were also confirmed in supplementary analyses. Our results extend our theoretical understanding of FSS and FSOP by demonstrating the utility of conceptualizing them as universal resources, opening up a variety of avenues for future research. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Similar support for three different life course socioeconomic models on predicting premature cardiovascular mortality and all-cause mortality

PubMed Central

Rosvall, Maria; Chaix, Basile; Lynch, John; Lindström, Martin; Merlo, Juan

2006-01-01

Background There are at least three broad conceptual models for the impact of the social environment on adult disease: the critical period, social mobility, and cumulative life course models. Several studies have shown an association between each of these models and mortality. However, few studies have investigated the importance of the different models within the same setting and none has been performed in samples of the whole population. The purpose of the present study was to study the relation between socioeconomic position (SEP) and mortality using different conceptual models in the whole population of Scania. Methods In the present investigation we use socioeconomic information on all men (N = 48,909) and women (N = 47,688) born between 1945 and 1950, alive on January, 1st,1990, and living in the Region of Scania, in Sweden. Focusing on three specific life periods (i.e., ages 10–15, 30–35 and 40–45), we examined the association between SEP and the 12-year risk of premature cardiovascular mortality and all-cause mortality. Results There was a strong relation between SEP and mortality among those inside the workforce, irrespective of the conceptual model used. There was a clear upward trend in the mortality hazard rate ratios (HRR) with accumulated exposure to manual SEP in both men (p for trend < 0.001 for both cardiovascular and all-cause mortality) and women (p for trend = 0.01 for cardiovascular mortality) and (p for trend = 0.003 for all-cause mortality). Inter- and intragenerational downward social mobility was associated with an increased mortality risk. When applying similar conceptual models based on workforce participation, it was shown that mortality was affected by the accumulated exposure to being outside the workforce. Conclusion There was a strong relation between SEP and cardiovascular and all-cause mortality, irrespective of the conceptual model used. The critical period, social mobility, and cumulative life course models, showed the same fit to the data. That is, one model could not be pointed out as "the best" model and even in this large unselected sample it was not possible to adjudicate which theories best describe the links between life course SEP and mortality risk. PMID:16889658
Job acquisition for people with severe mental illness enrolled in supported employment programs: a theoretically grounded empirical study.

PubMed

Corbière, Marc; Zaniboni, Sara; Lecomte, Tania; Bond, Gary; Gilles, Pierre-Yves; Lesage, Alain; Goldner, Elliot

2011-09-01

The main purpose of this study was to test a conceptual model based on the theory of planned behaviour (TPB) to explain competitive job acquisition of people with severe mental disorders enrolled in supported employment programs. Using a sample of 281 people with severe mental disorders participating in a prospective study design, the authors examined the contribution of the TPB in a model including clinical (e.g., severity of symptoms), psychosocial (e.g., self-esteem) and work related variables (e.g., length of time absent from the workplace) as predictors of job acquisition. Path analyses were used to test two conceptual models: (1) the model of job acquisition for people with mental illness adapted from the TPB, and (2) the extended TPB including clinical, psychosocial, and work related variables recognized in the literature as significant determinants of competitive employment. Findings revealed that both models presented good fit indices. In total, individual factors predicted 26% of the variance in job search behaviours (behavioural actions). However, client characteristics explained only 8% of variance in work outcomes, suggesting that environmental variables (e.g., stigma towards mental disorders) play an important role in predicting job acquisition. About 56% (N = 157) of our sample obtained competitive employment. Results suggest that employment specialists can be guided in their interventions by the concepts found in the extended model of work integration since most of these are modifiable, such as perceived barriers to employment, self-efficacy, and self-esteem.
Punishment in human choice: direct or competitive suppression?

PubMed Central

Critchfield, Thomas S; Paletz, Elliott M; MacAleese, Kenneth R; Newland, M Christopher

2003-01-01

This investigation compared the predictions of two models describing the integration of reinforcement and punishment effects in operant choice. Deluty's (1976) competitive-suppression model (conceptually related to two-factor punishment theories) and de Villiers' (1980) direct-suppression model (conceptually related to one-factor punishment theories) have been tested previously in nonhumans but not at the individual level in humans. Mouse clicking by college students was maintained in a two-alternative concurrent schedule of variable-interval money reinforcement. Punishment consisted of variable-interval money losses. Experiment 1 verified that money loss was an effective punisher in this context. Experiment 2 consisted of qualitative model comparisons similar to those used in previous studies involving nonhumans. Following a no-punishment baseline, punishment was superimposed upon both response alternatives. Under schedule values for which the direct-suppression model, but not the competitive-suppression model, predicted distinct shifts from baseline performance, or vice versa, 12 of 14 individual-subject functions, generated by 7 subjects, supported the direct-suppression model. When the punishment models were converted to the form of the generalized matching law, least-squares linear regression fits for a direct-suppression model were superior to those of a competitive-suppression model for 6 of 7 subjects. In Experiment 3, a more thorough quantitative test of the modified models, fits for a direct-suppression model were superior in 11 of 13 cases. These results correspond well to those of investigations conducted with nonhumans and provide the first individual-subject evidence that a direct-suppression model, evaluated both qualitatively and quantitatively, describes human punishment better than a competitive-suppression model. We discuss implications for developing better punishment models and future investigations of punishment in human choice. PMID:13677606
Relations among conceptual knowledge, procedural knowledge, and procedural flexibility in two samples differing in prior knowledge.

PubMed

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R

2011-11-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of prior knowledge on the relations. To overcome these problems, we modeled the three constructs in the domain of equation solving as latent factors and tested (a) whether the predictive relations between conceptual and procedural knowledge were bidirectional, (b) whether these interrelations were moderated by prior knowledge, and (c) how both constructs contributed to procedural flexibility. We analyzed data from 2 measurement points each from two samples (Ns = 228 and 304) of middle school students who differed in prior knowledge. Conceptual and procedural knowledge had stable bidirectional relations that were not moderated by prior knowledge. Both kinds of knowledge contributed independently to procedural flexibility. The results demonstrate how changes in complex knowledge structures contribute to competence development.
Making Predictions in a Changing World: The Benefits of Individual-Based Ecology

PubMed Central

Stillman, Richard A.; Railsback, Steven F.; Giske, Jarl; Berger, Uta; Grimm, Volker

2014-01-01

Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions—fitness maximization by individual organisms—is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research. PMID:26955076
Predicting wetland plant community responses to proposed water-level-regulation plans for Lake Ontario: GIS-based modeling

USGS Publications Warehouse

Wilcox, D.A.; Xie, Y.

2007-01-01

Integrated, GIS-based, wetland predictive models were constructed to assist in predicting the responses of wetland plant communities to proposed new water-level regulation plans for Lake Ontario. The modeling exercise consisted of four major components: 1) building individual site wetland geometric models; 2) constructing generalized wetland geometric models representing specific types of wetlands (rectangle model for drowned river mouth wetlands, half ring model for open embayment wetlands, half ellipse model for protected embayment wetlands, and ellipse model for barrier beach wetlands); 3) assigning wetland plant profiles to the generalized wetland geometric models that identify associations between past flooding / dewatering events and the regulated water-level changes of a proposed water-level-regulation plan; and 4) predicting relevant proportions of wetland plant communities and the time durations during which they would be affected under proposed regulation plans. Based on this conceptual foundation, the predictive models were constructed using bathymetric and topographic wetland models and technical procedures operating on the platform of ArcGIS. An example of the model processes and outputs for the drowned river mouth wetland model using a test regulation plan illustrates the four components and, when compared against other test regulation plans, provided results that met ecological expectations. The model results were also compared to independent data collected by photointerpretation. Although data collections were not directly comparable, the predicted extent of meadow marsh in years in which photographs were taken was significantly correlated with extent of mapped meadow marsh in all but barrier beach wetlands. The predictive model for wetland plant communities provided valuable input into International Joint Commission deliberations on new regulation plans and was also incorporated into faunal predictive models used for that purpose.
Prediction of forces and moments for flight vehicle control effectors. Part 1: Validation of methods for predicting hypersonic vehicle controls forces and moments

NASA Technical Reports Server (NTRS)

Maughmer, Mark D.; Ozoroski, L.; Ozoroski, T.; Straussfogel, D.

1990-01-01

Many types of hypersonic aircraft configurations are currently being studied for feasibility of future development. Since the control of the hypersonic configurations throughout the speed range has a major impact on acceptable designs, it must be considered in the conceptual design stage. The ability of the aerodynamic analysis methods contained in an industry standard conceptual design system, APAS II, to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds is considered. Predicted control forces and moments generated by various control effectors are compared with previously published wind tunnel and flight test data for three configurations: the North American X-15, the Space Shuttle Orbiter, and a hypersonic research airplane concept. Qualitative summaries of the results are given for each longitudinal force and moment and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage. Results for most lateral/directional control derivatives are acceptable for conceptual design purposes; however, predictions at supersonic Mach numbers for the change in yawing moment due to aileron deflection and the change in rolling moment due to rudder deflection are found to be unacceptable. Including shielding effects in the analysis is shown to have little effect on lift and pitching moment predictions while improving drag predictions.
A Bayesian context fear learning algorithm/automaton

PubMed Central

Krasne, Franklin B.; Cushman, Jesse D.; Fanselow, Michael S.

2015-01-01

Contextual fear conditioning is thought to involve the synaptic plasticity-dependent establishment in hippocampus of representations of to-be-conditioned contexts which can then become associated with USs in the amygdala. A conceptual and computational model of this process is proposed in which contextual attributes are assumed to be sampled serially and randomly during contextual exposures. Given this assumption, moment-to-moment information about such attributes will often be quite different from one exposure to another and, in particular, between exposures during which representations are created, exposures during which conditioning occurs, and during recall sessions. This presents challenges to current conceptual models of hippocampal function. In order to meet these challenges, our model's hippocampus was made to operate in different modes during representation creation and recall, and non-hippocampal machinery was constructed that controlled these hippocampal modes. This machinery uses a comparison between contextual information currently observed and information associated with existing hippocampal representations of familiar contexts to compute the Bayesian Weight of Evidence that the current context is (or is not) a known one, and it uses this value to assess the appropriateness of creation or recall modes. The model predicts a number of known phenomena such as the immediate shock deficit, spurious fear conditioning to contexts that are absent but similar to actually present ones, and modulation of conditioning by pre-familiarization with contexts. It also predicts a number of as yet unknown phenomena. PMID:26074792
Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering.

PubMed

Markkula, Gustav; Boer, Erwin; Romano, Richard; Merat, Natasha

2018-06-01

A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesting that the nervous system implements intermittent control using a combination of (1) motor primitives, (2) prediction of sensory outcomes of motor actions, and (3) evidence accumulation of prediction errors. It is shown that approximate but useful sensory predictions in the intermittent control context can be constructed without detailed forward models, as a superposition of simple prediction primitives, resembling neurobiologically observed corollary discharges. The proposed mathematical framework allows straightforward extension to intermittent behaviour from existing one-dimensional continuous models in the linear control and ecological psychology traditions. Empirical data from a driving simulator are used in model-fitting analyses to test some of the framework's main theoretical predictions: it is shown that human steering control, in routine lane-keeping and in a demanding near-limit task, is better described as a sequence of discrete stepwise control adjustments, than as continuous control. Results on the possible roles of sensory prediction in control adjustment amplitudes, and of evidence accumulation mechanisms in control onset timing, show trends that match the theoretical predictions; these warrant further investigation. The results for the accumulation-based model align with other recent literature, in a possibly converging case against the type of threshold mechanisms that are often assumed in existing models of intermittent control.
Directional stability of crack propagation

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

Streit, R.D.; Finnie, I.

Despite many alternative models, the original Erdogan and Sih (1963) hypothesis that a crack will grow in the direction perpendicular to the maximum circumferential stress sigma/sub theta/ is seen to be adequate for predicting the angle of crack growth under the condition of mixed mode loading. Their predictions, which were based on the singularity terms in the series expansion for the Mode I and Mode II stress fields, can be improved if the second term in the series is also included. Although conceptually simple, their predictions of the crack growth direction fit very closely to the data obtained from manymore » sources.« less
Conceptual compression for pattern recognition in 3D model output

NASA Astrophysics Data System (ADS)

Prudden, Rachel; Robinson, Niall; Arribas, Alberto

2017-04-01

The problem of data compression is closely related to the idea of comprehension. If you understand a scene at a qualitative level, this should enable you to make reasonable predictions about its contents, meaning that less extra information is needed to encode it precisely. These ideas have already been applied in the field of image compression; see for example the work on conceptual compression by Google DeepMind. Applying similar methods to multidimensional atmospheric data could have significant benefits. Beyond reducing storage demands, the ability to recognise complex features would make it far easier to interpret and search large volumes of meteorological data. Our poster will present some early work in this area.
Effects of stimulus order on discrimination processes in comparative and equality judgements: data and models.

PubMed

Dyjas, Oliver; Ulrich, Rolf

2014-01-01

In typical discrimination experiments, participants are presented with a constant standard and a variable comparison stimulus and their task is to judge which of these two stimuli is larger (comparative judgement). In these experiments, discrimination sensitivity depends on the temporal order of these stimuli (Type B effect) and is usually higher when the standard precedes rather than follows the comparison. Here, we outline how two models of stimulus discrimination can account for the Type B effect, namely the weighted difference model (or basic Sensation Weighting model) and the Internal Reference Model. For both models, the predicted psychometric functions for comparative judgements as well as for equality judgements, in which participants indicate whether they perceived the two stimuli to be equal or not equal, are derived and it is shown that the models also predict a Type B effect for equality judgements. In the empirical part, the models' predictions are evaluated. To this end, participants performed a duration discrimination task with comparative judgements and with equality judgements. In line with the models' predictions, a Type B effect was observed for both judgement types. In addition, a time-order error, as indicated by shifts of the psychometric functions, and differences in response times were observed only for the equality judgement. Since both models entail distinct additional predictions, it seems worthwhile for future research to unite the two models into one conceptual framework.
How should leaf area, sapwood area and stomatal conductance vary with tree height to maximize growth?

PubMed

Buckley, Thomas N; Roberts, David W

2006-02-01

Conventional wisdom holds that the ratio of leaf area to sapwood area (L/S) should decline during height (H) growth to maintain hydraulic homeostasis and prevent stomatal conductance (g(s)) from declining. We contend that L/S should increase with H based on a numerical simulation, a mathematical analysis and a conceptual argument: (1) numerical simulation--a tree growth model, DESPOT (Deducing Emergent Structure and Physiology Of Trees), in which carbon (C) allocation is regulated to maximize C gain, predicts L/S should increase during most of H growth; (2) mathematical analysis--the formal criterion for optimal C allocation, applied to a simplified analytical model of whole tree carbon-water balance, predicts L/S should increase with H if leaf-level gas exchange parameters including g(s) are conserved; and (3) conceptual argument--photosynthesis is limited by several substitutable resources (chiefly nitrogen (N), water and light) and H growth increases the C cost of water transport but not necessarily of N and light capture, so if the goal is to maximize C gain or growth, allocation should shift in favor of increasing photosynthetic capacity and irradiance, rather than sustaining g(s). Although many data are consistent with the prediction that L/S should decline with H, many others are not, and we discuss possible reasons for these discrepancies.
Collaborative Research: Robust Climate Projections and Stochastic Stability of Dynamical Systems

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

Ilya Zaliapin

This project focused on conceptual exploration of El Nino/Southern Oscillation (ENSO) variability and sensitivity using a Delay Differential Equation developed in the project. We have (i) established the existence and continuous dependence of solutions of the model (ii) explored multiple models solutions, and the distribution of solutions extrema, and (iii) established and explored the phase locking phenomenon and the existence of multiple solutions for the same values of model parameters. In addition, we have applied to our model the concept of pullback attractor, which greatly facilitated predictive understanding of the nonlinear model's behavior.
Estimating the Uncertain Mathematical Structure of Hydrological Model via Bayesian Data Assimilation

NASA Astrophysics Data System (ADS)

Bulygina, N.; Gupta, H.; O'Donell, G.; Wheater, H.

2008-12-01

The structure of hydrological model at macro scale (e.g. watershed) is inherently uncertain due to many factors, including the lack of a robust hydrological theory at the macro scale. In this work, we assume that a suitable conceptual model for the hydrologic system has already been determined - i.e., the system boundaries have been specified, the important state variables and input and output fluxes to be included have been selected, and the major hydrological processes and geometries of their interconnections have been identified. The structural identification problem then is to specify the mathematical form of the relationships between the inputs, state variables and outputs, so that a computational model can be constructed for making simulations and/or predictions of system input-state-output behaviour. We show how Bayesian data assimilation can be used to merge both prior beliefs in the form of pre-assumed model equations with information derived from the data to construct a posterior model. The approach, entitled Bayesian Estimation of Structure (BESt), is used to estimate a hydrological model for a small basin in England, at hourly time scales, conditioned on the assumption of 3-dimensional state - soil moisture storage, fast and slow flow stores - conceptual model structure. Inputs to the system are precipitation and potential evapotranspiration, and outputs are actual evapotranspiration and streamflow discharge. Results show the difference between prior and posterior mathematical structures, as well as provide prediction confidence intervals that reflect three types of uncertainty: due to initial conditions, due to input and due to mathematical structure.
Climatic and physiographic controls on catchment-scale nitrate loss at different spatial scales: insights from a top-down model development approach

NASA Astrophysics Data System (ADS)

Shafii, Mahyar; Basu, Nandita; Schiff, Sherry; Van Cappellen, Philippe

2017-04-01

Dramatic increase in nitrogen circulating in the biosphere due to anthropogenic activities has resulted in impairment of water quality in groundwater and surface water causing eutrophication in coastal regions. Understanding the fate and transport of nitrogen from landscape to coastal areas requires exploring the drivers of nitrogen processes in both time and space, as well as the identification of appropriate flow pathways. Conceptual models can be used as diagnostic tools to provide insights into such controls. However, diagnostic evaluation of coupled hydrological-biogeochemical models is challenging. This research proposes a top-down methodology utilizing hydrochemical signatures to develop conceptual models for simulating the integrated streamflow and nitrate responses while taking into account dominant controls on nitrate variability (e.g., climate, soil water content, etc.). Our main objective is to seek appropriate model complexity that sufficiently reproduces multiple hydrological and nitrate signatures. Having developed a suitable conceptual model for a given watershed, we employ it in sensitivity studies to demonstrate the dominant process controls that contribute to the nitrate response at scales of interest. We apply the proposed approach to nitrate simulation in a range of small to large sub-watersheds in the Grand River Watershed (GRW) located in Ontario. Such multi-basin modeling experiment will enable us to address process scaling and investigate the consequences of lumping processes in terms of models' predictive capability. The proposed methodology can be applied to the development of large-scale models that can help decision-making associated with nutrients management at regional scale.
Guided Cognitive Reframing of Adolescent-Father Conflict: Who Mexican American and European American Adolescents Seek and Why

ERIC Educational Resources Information Center

Cookston, Jeffrey T.; Olide, Andres F.; Adams, Michele A.; Fabricius, William V.; Parke, Ross D.

2012-01-01

Adolescents may seek to understand family conflict by seeking out confidants. However, little is known about whom adolescents seek, whether and how such support helps youth, and the factors that predict which sources are sought. This chapter offers a conceptual model of guided cognitive reframing that emphasizes the behavioral, cognitive, and…
Predicting Factors of Perceived Organizational Support by Full-Time and Part-Time Community College Faculty as Relates to Student Retention Rates

ERIC Educational Resources Information Center

Nichols, Sarah K.

2012-01-01

Student retention is socially, politically, and financially important to educational institutions. This quantitative study explored the gap in research regarding the relationship between employment of part-time in lieu of full-time faculty and student retention. The campus climate exchange model (CCEM), served as the conceptual framework in this…

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.
A conceptual life-history model for pallid and shovelnose sturgeon

USGS Publications Warehouse

Wildhaber, Mark L.; DeLonay, Aaron J.; Papoulias, Diana M.; Galat, David L.; Jacobson, Robert B.; Simpkins, Darin G.; Braaten, P. J.; Korschgen, Carl E.; Mac, Michael J.

2007-01-01

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic physical changes to these rivers. These changes have been implicated as causative agents in the decline of pallid sturgeon. The pallid sturgeon, federally listed as endangered, is endemic to the turbid waters of the Missouri River and the Lower Mississippi River. The sympatric shovelnose sturgeon historically was more common and widespread than the pallid sturgeon. Habitat alteration, river regulation, pollution, and over-harvest have resulted in the now predictable patterns of decline and localized extirpation of sturgeon across species and geographic areas. Symptomatic of this generalized pattern of decline is poor reproductive success, and low or no recruitment of wild juveniles to the adult population. The purpose of this report is to introduce a conceptual life-history model of the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons. The conceptual model provided here was developed to organize the understanding about the complex life history of Scaphirhynchus sturgeons. It was designed to be used for communication, planning, and to provide the structure for a population-forecasting model. These models are intended to be dynamic and responsive to new information and changes in river management, thereby providing scientists, stakeholders, and managers with ways to improve understanding of the effects of management actions on the ecological requirements of Scaphirhynchus sturgeons. As new scientific knowledge becomes available, it could be included in the model in many ways at various integration levels.
Sensitivity of the ocean overturning circulation to wind and mixing: theoretical scalings and global ocean models

NASA Astrophysics Data System (ADS)

Nikurashin, Maxim; Gunn, Andrew

2017-04-01

The meridional overturning circulation (MOC) is a planetary-scale oceanic flow which is of direct importance to the climate system: it transports heat meridionally and regulates the exchange of CO2 with the atmosphere. The MOC is forced by wind and heat and freshwater fluxes at the surface and turbulent mixing in the ocean interior. A number of conceptual theories for the sensitivity of the MOC to changes in forcing have recently been developed and tested with idealized numerical models. However, the skill of the simple conceptual theories to describe the MOC simulated with higher complexity global models remains largely unknown. In this study, we present a systematic comparison of theoretical and modelled sensitivity of the MOC and associated deep ocean stratification to vertical mixing and southern hemisphere westerlies. The results show that theories that simplify the ocean into a single-basin, zonally-symmetric box are generally in a good agreement with a realistic, global ocean circulation model. Some disagreement occurs in the abyssal ocean, where complex bottom topography is not taken into account by simple theories. Distinct regimes, where the MOC has a different sensitivity to wind or mixing, as predicted by simple theories, are also clearly shown by the global ocean model. The sensitivity of the Indo-Pacific, Atlantic, and global basins is analysed separately to validate the conceptual understanding of the upper and lower overturning cells in the theory.
Factors that influence police conceptualizations of girls involved in prostitution in six U.S. cities: child sexual exploitation victims or delinquents?

PubMed

Halter, Stephanie

2010-05-01

This study examined how the police conceptualize juveniles involved in prostitution as victims of child sexual exploitation (CSE) or delinquents. Case files from six police agencies in major U.S. cities of 126 youth allegedly involved in prostitution, who were almost entirely girls, provided the data for this inquiry. This study found that 60% of youth in this sample were conceptualized as victims by the police and 40% as offenders. Logistic regression predicted the youths' culpability status as victims. The full model predicted 91% of youth's culpability status correctly and explained 67% of the variance in the youths' culpability status. The police considered youth with greater levels of cooperation, greater presence of identified exploiters, no prior record, and that came to their attention through a report more often as victims. In addition, the police may consider local youth more often as victims. It appears that the police use criminal charges as a paternalistic protective response to detain some of the youth treated as offenders, even though they considered these youth victims. Legislatively mandating this form of CSE as child abuse or adopting a ''secure care'' approach is needed to ensure these youth receive the necessary treatment and services.
Assessing predictability of a hydrological stochastic-dynamical system

NASA Astrophysics Data System (ADS)

Gelfan, Alexander

2014-05-01

The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar to those of the corresponding series of the actual data measured at the station. Beginning from the initial conditions and being forced by Monte-Carlo generated synthetic meteorological series, the model simulated diverging trajectories of soil moisture characteristics (water content of soil column, moisture of different soil layers, etc.). Limit of predictability of the specific characteristic was determined through time of stabilization of variance of the characteristic between the trajectories, as they move away from the initial state. Numerical experiments were carried out with the stochastic-dynamical model to analyze sensitivity of the soil moisture predictability assessments to uncertainty in the initial conditions, to determine effects of the soil hydraulic properties and processes of soil freezing on the predictability. It was found, particularly, that soil water content predictability is sensitive to errors in the initial conditions and strongly depends on the hydraulic properties of soil under both unfrozen and frozen conditions. Even if the initial conditions are "well-established", the assessed predictability of water content of unfrozen soil does not exceed 30-40 days, while for frozen conditions it may be as long as 3-4 months. The latter creates opportunity for utilizing the autumn water content of soil as the predictor for spring snowmelt runoff in the region under consideration.
Groundwater modelling in conceptual hydrological models - introducing space

NASA Astrophysics Data System (ADS)

Boje, Søren; Skaugen, Thomas; Møen, Knut; Myrabø, Steinar

2017-04-01

The tiny Sæternbekken Minifelt (Muren) catchment (7500 m2) in Bærumsmarka, Norway, was during the 1990s, densely instrumented with more than a 100 observation points for measuring groundwater levels. The aim was to investigate the link between shallow groundwater dynamics and runoff. The DDD (Distance Distribution Dynamics) model is a newly developed rainfall-runoff model used operationally by the Norwegian Flood-Forecasting service at NVE. The model estimates the capacity of the subsurface reservoir at different levels of saturation and predicts overland flow. The subsurface in the DDD model has a 2-D representation that calculates the saturated and unsaturated soil moisture along a hillslope representing the entire catchment in question. The groundwater observations from more than two decades ago are used to verify assumptions of the subsurface reservoir in the DDD model and to validate its spatial representation of the subsurface reservoir. The Muren catchment will, during 2017, be re-instrumented in order to continue the work to bridge the gap between conceptual hydrological models, with typically single value or 0-dimension representation of the subsurface, and models with more realistic 2- or 3-dimension representation of the subsurface.
Developing Conceptual Models of Biodegradation: Lessons Learned From a Long-Term Study of a Crude-Oil Contaminant Plume

NASA Astrophysics Data System (ADS)

Cozzarelli, I. M.; Esaid, H. I.; Bekins, B. A.; Eganhouse, R. P.; Baedecker, M.

2002-05-01

Assessment of natural attenuation as a remedial option requires understanding the long-term fate of contaminant compounds. The development of correct conceptual models of biodegradation requires observations at spatial and temporal scales appropriate for the reactions being measured. For example, the availability of electron acceptors such as solid-phase iron oxides may vary at the cm scale due to aquifer heterogeneities. Characterizing the distribution of these oxides may require small-scale measurements over time scales of tens of years in order to assess their impact on the fate of contaminants. The long-term study of natural attenuation of hydrocarbons in a contaminant plume near Bemidji, MN provides insight into how natural attenuation of hydrocarbons evolves over time. The sandy glacial-outwash aquifer at this USGS Toxic Substances Hydrology research site was contaminated by crude oil in 1979. During the 16 years that data have been collected the shape and extent of the contaminant plume changed as redox reactions, most notably iron reduction, progressed over time. Investigation of the controlling microbial reactions in this system required a systematic and multi-scaled approach. Early indications of plume shrinkage were observed over a time scale of a few years, based on observation well data. These changes were associated with iron reduction near the crude-oil source. The depletion of Fe (III) oxides near the contaminant source caused the dissolved iron concentrations to increase and spread downgradient at a rate of approximately 3 m/year. The zone of maximum benzene, toluene, ethylbenzene, and xylene (BTEX) concentrations has also spread within the anoxic plume. Subsequent analyses of sediment and water, collected at small-scale cm intervals from cores in the contaminant plume, provided insight into the evolution of redox zones at smaller scales. Contaminants, such as ortho-xylene, that appeared to be contained near the oil source based on the larger-scale observation well data, were observed to be migrating in thin layers as the aquifer evolved to methanogenic conditions in narrow zones. The impact of adequately identifying the microbially mediated redox reactions was illustrated with a novel inverse modeling effort (using both the USGS solute transport and biodegradation code BIOMOC and the USGS universal inverse modeling code UCODE) to quantify field-scale hydrocarbon dissolution and biodegradation at the Bemidji site. Extensive historical data compiled at the Bemidji site were used, including 1352 concentration observations from 30 wells and 66 core sections. The simulations reproduced the general large-scale evolution of the plume, but the percent BTEX mass removed from the oil body after 18 years varied significantly, depending on which biodegradation conceptual model was used. The best fit was obtained for the iron-reduction conceptual model, which incorporated the finite availability of Fe (III) in the aquifer and reproduced the field observation that depletion of solid-phase iron resulted in increased downgradient transport of BTEX compounds. The predicted benzene plume 50 years after the spill showed significantly higher concentrations of benzene for the iron-reduction model compared to other conceptual models tested. This study demonstrates that the long-term sustainability of the electron acceptors is key to predicting the ultimate fate of the hydrocarbons. Assessing this evolution of redox processes and developing an adequate conceptual model required observations on multiple spatial scales over the course of many years.
Prediction/Discussion-Based Learning Cycle versus Conceptual Change Text: Comparative Effects on Students' Understanding of Genetics

ERIC Educational Resources Information Center

Al khawaldeh, Salem A.

2013-01-01

Background and Purpose: The purpose of this study was to investigate the comparative effects of a prediction/discussion-based learning cycle (HPD-LC), conceptual change text (CCT) and traditional instruction on 10th grade students' understanding of genetics concepts. Sample: Participants were 112 10th basic grade male students in three classes of…
The Comparative Effects of Prediction/Discussion-Based Learning Cycle, Conceptual Change Text, and Traditional Instructions on Student Understanding of Genetics

ERIC Educational Resources Information Center

Yilmaz, Diba; Tekkaya, Ceren; Sungur, Semra

2011-01-01

The present study examined the comparative effects of a prediction/discussion-based learning cycle, conceptual change text (CCT), and traditional instructions on students' understanding of genetics concepts. A quasi-experimental research design of the pre-test-post-test non-equivalent control group was adopted. The three intact classes, taught by…
Exact and conceptual repetition dissociate conceptual memory tests: problems for transfer appropriate processing theory.

PubMed

McDermott, K B; Roediger, H L

1996-03-01

Three experiments examined whether a conceptual implicit memory test (specifically, category instance generation) would exhibit repetition effects similar to those found in free recall. The transfer appropriate processing account of dissociations among memory tests led us to predict that the tests would show parallel effects; this prediction was based upon the theory's assumption that conceptual tests will behave similarly as a function of various independent variables. In Experiment 1, conceptual repetition (i.e., following a target word [e.g., puzzles] with an associate [e.g., jigsaw]) did not enhance priming on the instance generation test relative to the condition of simply presenting the target word once, although this manipulation did affect free recall. In Experiment 2, conceptual repetition was achieved by following a picture with its corresponding word (or vice versa). In this case, there was an effect of conceptual repetition on free recall but no reliable effect on category instance generation or category cued recall. In addition, we obtained a picture superiority effect in free recall but not in category instance generation. In the third experiment, when the same study sequence was used as in Experiment 1, but with instructions that encouraged relational processing, priming on the category instance generation task was enhanced by conceptual repetition. Results demonstrate that conceptual memory tests can be dissociated and present problems for Roediger's (1990) transfer appropriate processing account of dissociations between explicit and implicit tests.
Incorporating learning goals about modeling into an upper-division physics laboratory experiment

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

PubMed

Butlin, B; Wilson, C

2018-04-04

How we conceptualize mental health conditions is important as it impacts on a wide range of mediators of treatment outcome. We do not know how children intuitively conceptualize obsessive-compulsive disorder (OCD), nor do we know the relative impact of biomedical or cognitive behavioural conceptual explanations, yet both are being widely used in psychoeducation for children with OCD. This study identified children's naive concepts of OCD, and the comparative impact of biomedical versus cognitive behavioural psychoeducation on perceived prognosis. A within- and between-subjects experimental design was used. After watching a video of a young person describing their OCD, 202 children completed a questionnaire examining their concepts of the condition. They repeated the questionnaire following a second equivalent video, this time preceded by either biomedical or cognitive behavioural psychoeducation. Participants' naive concepts of OCD reflected predominant models of OCD in healthcare. Even at the minimal dose of psychoeducation, participants' conceptualizations of OCD changed. Prior exposure to OCD resulted in a stronger alignment with the biomedical model. Exposure to biomedical psychoeducation resulted in participants predicting a slower recovery with less chance of complete remission. Psychoeducation for childhood OCD is impactful. Despite its wide use by clinicians and mental health services, biomedical psychoeducation appears to have deleterious effects. Children's concepts of OCD merit attention but caution should be applied in how they are targeted.
Using the Unified Modelling Language (UML) to guide the systemic description of biological processes and systems.

PubMed

Roux-Rouquié, Magali; Caritey, Nicolas; Gaubert, Laurent; Rosenthal-Sabroux, Camille

2004-07-01

One of the main issues in Systems Biology is to deal with semantic data integration. Previously, we examined the requirements for a reference conceptual model to guide semantic integration based on the systemic principles. In the present paper, we examine the usefulness of the Unified Modelling Language (UML) to describe and specify biological systems and processes. This makes unambiguous representations of biological systems, which would be suitable for translation into mathematical and computational formalisms, enabling analysis, simulation and prediction of these systems behaviours.
Candidate Predictors of Health-Related Quality of Life of Colorectal Cancer Survivors: A Systematic Review

PubMed Central

van der Linden, Bernadette W.A.; Winkels, Renate M.; van Duijnhoven, Fränzel J.; Mols, Floortje; van Roekel, Eline H.; Kampman, Ellen; Beijer, Sandra; Weijenberg, Matty P.

2016-01-01

The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals. Implications for Practice: More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models. PMID:26911406
Axisymmetric inlet minimum weight design method

NASA Technical Reports Server (NTRS)

Nadell, Shari-Beth

1995-01-01

An analytical method for determining the minimum weight design of an axisymmetric supersonic inlet has been developed. The goal of this method development project was to improve the ability to predict the weight of high-speed inlets in conceptual and preliminary design. The initial model was developed using information that was available from inlet conceptual design tools (e.g., the inlet internal and external geometries and pressure distributions). Stiffened shell construction was assumed. Mass properties were computed by analyzing a parametric cubic curve representation of the inlet geometry. Design loads and stresses were developed at analysis stations along the length of the inlet. The equivalent minimum structural thicknesses for both shell and frame structures required to support the maximum loads produced by various load conditions were then determined. Preliminary results indicated that inlet hammershock pressures produced the critical design load condition for a significant portion of the inlet. By improving the accuracy of inlet weight predictions, the method will improve the fidelity of propulsion and vehicle design studies and increase the accuracy of weight versus cost studies.
Blue M2: an intermediate melanoidin studied via conceptual DFT.

PubMed

Frau, Juan; Glossman-Mitnik, Daniel

2018-05-31

In this computational study, ten density functionals, viz. CAM-B3LYP, LC-ω PBE, M11, M11L, MN12L, MN12SX, N12, N12SX, ω B97X, and ω B97XD, related to the Def2TZVP basis sets, are assessed together with the SMD solvation model for calculation of the molecular properties and structure of blue-M2 intermediate melanoidin pigment. All the chemical reactivity descriptors for the system are calculated via conceptual density functional theory (DFT). The active sites suitable for nucleophilic, electrophilic, and radical attacks are selected by linking them with the Fukui function indices, electrophilic Parr functions, and condensed dual descriptors Δf(r), respectively. The prediction of the maximum absorption wavelength is considerably accurate relative to its experimental value. The study reveals that the MN12SX and N12SX density functionals are the most appropriate density functionals for predicting the chemical reactivity of the molecule under study.
Designer's unified cost model

NASA Technical Reports Server (NTRS)

Freeman, William T.; Ilcewicz, L. B.; Swanson, G. D.; Gutowski, T.

1992-01-01

A conceptual and preliminary designers' cost prediction model has been initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a data base and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. The approach, goals, plans, and progress is presented for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).
Predictors of Weapon Carrying in Youth Attending Drop-in Centers

PubMed Central

Blumberg, Elaine J.; Liles, Sandy; Kelley, Norma J.; Hovell, Melbourne F.; Bousman, Chad A.; Shillington, Audrey M.; Ji, Ming; Clapp, John

2012-01-01

Objective To test and compare 2 predictive models of weapon carrying in youth (n=308) recruited from 4 drop-in centers in San Diego and Imperial counties. Methods Both models were based on the Behavioral Ecological Model (BEM). Results The first and second models significantly explained 39% and 53% of the variance in weapon carrying, respectively, and both full models shared the significant predictors of being black(−), being Hispanic (−), peer modeling of weapon carrying/jail time(+), and school suspensions(+). Conclusions Results suggest that the BEM offers a generalizable conceptual model that may inform prevention strategies for youth at greatest risk of weapon carrying. PMID:19320622
Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.
The Deceptive Mean: Conceptual Scoring of Cloze Entries Differentially Advantages More Able Readers

ERIC Educational Resources Information Center

O'Toole, J. M.; King, R. A. R.

2011-01-01

The "cloze" test is one possible investigative instrument for predicting text comprehensibility. Conceptual coding of student replacement of deleted words has been considered to be more valid than exact coding, partly because conceptual coding seemed fairer to poorer readers. This paper reports a quantitative study of 447 Australian…

Reducing structural uncertainty in conceptual hydrological modeling in the semi-arid Andes

NASA Astrophysics Data System (ADS)

Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

2014-10-01

The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modeling of a meso-scale Andean catchment (1515 km2) over a 30 year period (1982-2011). The modeling process was decomposed into six model-building decisions related to the following aspects of the system behavior: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modeling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain 8 model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modeling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.
Reducing structural uncertainty in conceptual hydrological modelling in the semi-arid Andes

NASA Astrophysics Data System (ADS)

Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

2015-05-01

The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modelling of a mesoscale Andean catchment (1515 km2) over a 30-year period (1982-2011). The modelling process was decomposed into six model-building decisions related to the following aspects of the system behaviour: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modelling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional (4-D) space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain eight model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modelling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.
Assessment of potential for small hydro/solar power integration in a mountainous, data sparse region: the role of hydrological prediction accuracy

NASA Astrophysics Data System (ADS)

Borga, Marco; Francois, Baptiste; Creutin, Jean-Dominique; Hingray, Benoit; Zoccatelli, Davide; Tardivo, Gianmarco

2015-04-01

In many parts of the world, integration of small hydropower and solar/wind energy sources along river systems is examined as a way to meet pressing renewable energy targets. Depending on the space and time scales considered, hydrometeorological variability may synchronize or desynchronize solar/wind, runoff and the demand opening the possibility to use their complementarity to smooth the intermittency of each individual energy source. Rivers also provide important ecosystem services, including the provision of high quality downstream water supply and the maintenance of in-stream habitats. With future supply and demand of water resources both impacted by environmental change, a good understanding of the potential for the integration among hydropower and solar/wind energy sources in often sparsely gauged catchments is important. In such cases, where complex data-demanding models may be inappropriate, there is a need for simple conceptual modelling approaches that can still capture the main features of runoff generation and artificial regulation processes. In this work we focus on run-of-the-river and solar-power interaction assessment. In order to catch the three key cycles of the load fluctuation - daily, weekly and seasonal, the time step used in the study is the hourly resolution. We examine the performance of a conceptual hydrological model which includes facilities to model dam regulation and diversions and hydrological modules to account for the effect of glaciarised catchments. The model is applied to catchments of the heavily regulated Upper Adige river system (6900 km2), Eastern Italian Alps, which has a long history of hydropower generation. The model is used to characterize and predict the natural flow regime, assess the regulation impacts, and simulate co-fluctuations between run-of- the-river and solar power. The results demonstrates that the simple, conceptual modelling approach developed here can capture the main hydrological and regulation processes well at the three key cycles of the load fluctuations. A specific focus is dedicated on how the results can be communicated to stakeholders in order to provide a basis for discussing the development of new adaptive management strategies.
Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios

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

Jarman, Kenneth D.; Brothers, Alan J.; Whitney, Paul D.

2010-06-06

The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges inmore » the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.« less
Ecological risk assessment conceptual model formulation for nonindigenous species.

PubMed

Landis, Wayne G

2004-08-01

This article addresses the application of ecological risk assessment at the regional scale to the prediction of impacts due to invasive or nonindigenous species (NIS). The first section describes risk assessment, the decision-making process, and introduces regional risk assessment. A general conceptual model for the risk assessment of NIS is then presented based upon the regional risk assessment approach. Two diverse examples of the application of this approach are presented. The first example is based upon the dynamics of introduced plasmids into bacteria populations. The second example is the application risk assessment approach to the invasion of a coastal marine site of Cherry Point, Washington, USA by the European green crab. The lessons learned from the two examples demonstrate that assessment of the risks of invasion of NIS will have to incorporate not only the characteristics of the invasive species, but also the other stresses and impacts affecting the region of interest.
Conceptual Hierarchies in a Flat Attractor Network

PubMed Central

O’Connor, Christopher M.; Cree, George S.; McRae, Ken

2009-01-01

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory. PMID:19543434
Demonstration of the feasibility of automated silicon solar cell fabrication

NASA Technical Reports Server (NTRS)

Taylor, W. E.; Schwartz, F. M.

1975-01-01

A study effort was undertaken to determine the process, steps and design requirements of an automated silicon solar cell production facility. Identification of the key process steps was made and a laboratory model was conceptually designed to demonstrate the feasibility of automating the silicon solar cell fabrication process. A detailed laboratory model was designed to demonstrate those functions most critical to the question of solar cell fabrication process automating feasibility. The study and conceptual design have established the technical feasibility of automating the solar cell manufacturing process to produce low cost solar cells with improved performance. Estimates predict an automated process throughput of 21,973 kilograms of silicon a year on a three shift 49-week basis, producing 4,747,000 hexagonal cells (38mm/side), a total of 3,373 kilowatts at an estimated manufacturing cost of $0.866 per cell or $1.22 per watt.
The wetland continuum: a conceptual framework for interpreting biological studies

USGS Publications Warehouse

Euliss, N.H.; LaBaugh, J.W.; Fredrickson, L.H.; Mushet, D.M.; Swanson, G.A.; Winter, T.C.; Rosenberry, D.O.; Nelson, R.D.

2004-01-01

We describe a conceptual model, the wetland continuum, which allows wetland managers, scientists, and ecologists to consider simultaneously the influence of climate and hydrologic setting on wetland biological communities. Although multidimensional, the wetland continuum is most easily represented as a two-dimensional gradient, with ground water and atmospheric water constituting the horizontal and vertical axis, respectively. By locating the position of a wetland on both axes of the continuum, the potential biological expression of the wetland can be predicted at any point in time. The model provides a framework useful in the organization and interpretation of biological data from wetlands by incorporating the dynamic changes these systems undergo as a result of normal climatic variation rather than placing them into static categories common to many wetland classification systems. While we developed this model from the literature available for depressional wetlands in the prairie pothole region of North America, we believe the concept has application to wetlands in many other geographic locations.
Thinking as the control of imagination: a conceptual framework for goal-directed systems.

PubMed

Pezzulo, Giovanni; Castelfranchi, Cristiano

2009-07-01

This paper offers a conceptual framework which (re)integrates goal-directed control, motivational processes, and executive functions, and suggests a developmental pathway from situated action to higher level cognition. We first illustrate a basic computational (control-theoretic) model of goal-directed action that makes use of internal modeling. We then show that by adding the problem of selection among multiple action alternatives motivation enters the scene, and that the basic mechanisms of executive functions such as inhibition, the monitoring of progresses, and working memory, are required for this system to work. Further, we elaborate on the idea that the off-line re-enactment of anticipatory mechanisms used for action control gives rise to (embodied) mental simulations, and propose that thinking consists essentially in controlling mental simulations rather than directly controlling behavior and perceptions. We conclude by sketching an evolutionary perspective of this process, proposing that anticipation leveraged cognition, and by highlighting specific predictions of our model.
Circadian rhythms of performance: new trends

NASA Technical Reports Server (NTRS)

Carrier, J.; Monk, T. H.

2000-01-01

This brief review is concerned with how human performance efficiency changes as a function of time of day. It presents an overview of some of the research paradigms and conceptual models that have been used to investigate circadian performance rhythms. The influence of homeostatic and circadian processes on performance regulation is discussed. The review also briefly presents recent mathematical models of alertness that have been used to predict cognitive performance. Related topics such as interindividual differences and the postlunch dip are presented.
Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species.

PubMed

Gravel, Dominique; Beaudet, Marilou; Messier, Christian

2008-10-01

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.
Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-making Rating Scale.

PubMed

Lichtenberg, Peter A; Ocepek-Welikson, Katja; Ficker, Lisa J; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A

2018-01-01

The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision-making Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results confirmed the scale's reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. The psychometric properties of the LFDRS support the scale's use as it was proposed. The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments.
Dynamic updating of hippocampal object representations reflects new conceptual knowledge

PubMed Central

Mack, Michael L.; Love, Bradley C.; Preston, Alison R.

2016-01-01

Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal. PMID:27803320
A Simulation Model Articulation of the REA Ontology

NASA Astrophysics Data System (ADS)

Laurier, Wim; Poels, Geert

This paper demonstrates how the REA enterprise ontology can be used to construct simulation models for business processes, value chains and collaboration spaces in supply chains. These models support various high-level and operational management simulation applications, e.g. the analysis of enterprise sustainability and day-to-day planning. First, the basic constructs of the REA ontology and the ExSpect modelling language for simulation are introduced. Second, collaboration space, value chain and business process models and their conceptual dependencies are shown, using the ExSpect language. Third, an exhibit demonstrates the use of value chain models in predicting the financial performance of an enterprise.
a Bayesian Synthesis of Predictions from Different Models for Setting Water Quality Criteria

NASA Astrophysics Data System (ADS)

Arhonditsis, G. B.; Ecological Modelling Laboratory

2011-12-01

Skeptical views of the scientific value of modelling argue that there is no true model of an ecological system, but rather several adequate descriptions of different conceptual basis and structure. In this regard, rather than picking the single "best-fit" model to predict future system responses, we can use Bayesian model averaging to synthesize the forecasts from different models. Hence, by acknowledging that models from different areas of the complexity spectrum have different strengths and weaknesses, the Bayesian model averaging is an appealing approach to improve the predictive capacity and to overcome the ambiguity surrounding the model selection or the risk of basing ecological forecasts on a single model. Our study addresses this question using a complex ecological model, developed by Ramin et al. (2011; Environ Modell Softw 26, 337-353) to guide the water quality criteria setting process in the Hamilton Harbour (Ontario, Canada), along with a simpler plankton model that considers the interplay among phosphate, detritus, and generic phytoplankton and zooplankton state variables. This simple approach is more easily subjected to detailed sensitivity analysis and also has the advantage of fewer unconstrained parameters. Using Markov Chain Monte Carlo simulations, we calculate the relative mean standard error to assess the posterior support of the two models from the existing data. Predictions from the two models are then combined using the respective standard error estimates as weights in a weighted model average. The model averaging approach is used to examine the robustness of predictive statements made from our earlier work regarding the response of Hamilton Harbour to the different nutrient loading reduction strategies. The two eutrophication models are then used in conjunction with the SPAtially Referenced Regressions On Watershed attributes (SPARROW) watershed model. The Bayesian nature of our work is used: (i) to alleviate problems of spatiotemporal resolution mismatch between watershed and receiving waterbody models; and (ii) to overcome the conceptual or scale misalignment between processes of interest and supporting information. The proposed Bayesian approach provides an effective means of empirically estimating the relation between in-stream measurements of nutrient fluxes and the sources/sinks of nutrients within the watershed, while explicitly accounting for the uncertainty associated with the existing knowledge from the system along with the different types of spatial correlation typically underlying the parameter estimation of watershed models. Our modelling exercise offers the first estimates of the export coefficients and the delivery rates from the different subcatchments and thus generates testable hypotheses regarding the nutrient export "hot spots" in the studied watershed. Finally, we conduct modeling experiments that evaluate the potential improvement of the model parameter estimates and the decrease of the predictive uncertainty, if the uncertainty associated with the contemporary nutrient loading estimates is reduced. The lessons learned from this study will contribute towards the development of integrated modelling frameworks.
Simulating pesticide transport in urbanized catchments: a new spatially-distributed dynamic pesticide runoff model

NASA Astrophysics Data System (ADS)

Tang, Ting; Seuntjens, Piet; van Griensven, Ann; Bronders, Jan

2016-04-01

Urban areas can significantly contribute to pesticide contamination in surface water. However, pesticide behaviours in urban areas, particularly on hard surfaces, are far less studied than those in agricultural areas. Pesticide application on hard surfaces (e.g. roadsides and walkways) is of particular concern due to the high imperviousness and therefore high pesticide runoff potential. Experimental studies have shown that pesticide behaviours on and interactions with hard surfaces are important factors controlling the pesticide runoff potential, and therefore the magnitude and timing of peak concentrations in surface water. We conceptualized pesticide behaviours on hard surfaces and incorporated the conceptualization into a new pesticide runoff model. The pesticide runoff model was implemented in a catchment hydrological model WetSpa-Python (Water and Energy Transfer between Soil, Plants and Atmosphere, Python version). The conceptualization for pesticide processes on hard surfaces accounts for the differences in pesticide behaviour on different hard surfaces. Four parameters are used to describe the partitioning and wash-off of each pesticide on hard surfaces. We tested the conceptualization using experimental dataset for five pesticides on two types of hard surfaces, namely concrete and asphalt. The conceptualization gave good performance in accounting for the wash-off pattern for the modelled pesticides and surfaces, according to quantitative evaluations using the Nash-Sutcliffe efficiency and percent bias. The resulting pesticide runoff model WetSpa-PST (WetSpa for PeSTicides) can simulate pesticides and their metabolites at the catchment scale. Overall, it includes four groups of pesticide processes, namely pesticide application, pesticide interception by plant foliage, pesticide processes on land surfaces (including partitioning, degradation and wash-off on hard surface; partitioning, dissipation, infiltration and runoff in soil) and pesticide processes in depression storage (including degradation, infiltration and runoff). Processes on hard surfaces employs the conceptualization described in the paragraph above. The WetSpa-PST model can account for various spatial details of the urban features in a catchment, such as asphalt, concrete and roof areas. The distributed feature also allows users to input detailed pesticide application data of both non-point and point origins. Thanks to the Python modelling framework prototype used in the WetSpa-Python model, processes in the WetSpa-PST model can be simulated at different time steps depending on data availability and the characteristic temporal scale of each process. This helps to increase the computational accuracy during heavy rainfall events, especially for the associated fast transport of pesticides into surface water. Overall, the WetSpa-PST model has good potential in predicting effects of management options on pesticide releases from heavily urbanized catchments.
Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies

PubMed Central

Quinn, T. Alexander; Kohl, Peter

2013-01-01

Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of ‘wet’ and ‘dry’ investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function. PMID:23334215
Artistic misunderstandings: The emotional significance of historical learning in the arts.

PubMed

Bullot, Nicolas J; Reber, Rolf

2017-01-01

The Distancing-Embracing model does not have the conceptual resources to explain artistic misunderstandings and the emotional consequences of historical learning in the arts. Specifically, it suggests implausible predictions about emotional distancing caused by art schemata (e.g., misunderstandings of artistic intentions and contexts). These problems show the need for further inquiries into how historical contextualization modulates negative emotions in the arts.
Challenges of Aircraft Design Integration

DTIC Science & Technology

2003-03-01

predicted by the conceptual stick model and the full FEM of the Challenger wing without winglets . Advanced aerodynamic wing design methods To design wings...Piperni, E. Laurendeau Advanced Aerodynamics Bombardier Aerospace 400 CMte Vertu Road Dorval, Quebec, Canada, H4S 1Y9 Fassi.Kafyeke @notes.canadair.ca Tel...514) 855-7186 Abstract The design of a modern airplane brings together many disciplines: structures, aerodynamics , controls, systems, propulsion
Pharmacokinetic Modeling of JP-8 Jet Fuel Components: II. A Conceptual Framework

DTIC Science & Technology

2003-12-01

example, a single type of (simple) binary interaction between 300 components would require the specification of some 105 interaction coefficients . One...individual substances, via binary mechanisms, is enough to predict the interactions present in the mixture. Secondly, complex mixtures can often be...approximated as pseudo- binary systems, consisting of the compound of interest plus a single interacting complex vehicle with well-defined, composite

Tidal Dynamics and Mixing Over Steep Topography

DTIC Science & Technology

1994-06-01

California continental shelf have been observed at several locations (Huthnance, 1989). Shea and Broenkow (1982) observed large 33 tidally related...enhanced transport inside the canyon (Huthnance, 1989). This type of pressure gradient supports the conceptual model proposed by Shea and Broenkow (1982...predicted an enhanced internal tide up-canyon and near the bottom, verified by observations of strong internal tides by Shea and Broenkow (1982) at
Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change.

PubMed

McCluney, Kevin E; Belnap, Jayne; Collins, Scott L; González, Angélica L; Hagen, Elizabeth M; Nathaniel Holland, J; Kotler, Burt P; Maestre, Fernando T; Smith, Stanley D; Wolf, Blair O

2012-08-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.
Impact of modellers' decisions on hydrological a priori predictions

NASA Astrophysics Data System (ADS)

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2013-07-01

The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2) and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.
Interoception in anxiety and depression

PubMed Central

Stein, Murray B.

2010-01-01

We review the literature on interoception as it relates to depression and anxiety, with a focus on belief, and alliesthesia. The connection between increased but noisy afferent interoceptive input, self-referential and belief-based states, and top-down modulation of poorly predictive signals is integrated into a neuroanatomical and processing model for depression and anxiety. The advantage of this conceptualization is the ability to specifically examine the interface between basic interoception, self-referential belief-based states, and enhanced top-down modulation to attenuate poor predictability. We conclude that depression and anxiety are not simply interoceptive disorders but are altered interoceptive states as a consequence of noisily amplified self-referential interoceptive predictive belief states. PMID:20490545
Social stress, economic hardship, and psychological distress as predictors of sustained abstinence from substance use after treatment.

PubMed

Wahler, Elizabeth A; Otis, Melanie D

2014-11-01

Social characteristics associated with disadvantage, such as racial/ethnic minority status, female gender, and low socioeconomic status (SES), are often associated with increased psychological distress and substance use disorders. This project tests a conceptual model derived from Pearlin's social stress theory for predicting abstinence from substance use between baseline and 1-year follow-up in secondary data from a large statewide sample of Kentucky substance abuse treatment participants (N = 1,123). Racial minority status, employment, and higher education level were predictive of substance use at follow-up, while female gender was predictive of abstinence. Limitations, implications for practice, and suggestions for future research are discussed.
Relationships between social competence, psychopathology and work performance and their predictive value for vocational rehabilitation of schizophrenic outpatients.

PubMed

Hoffmann, H; Kupper, Z

1997-01-17

Earlier studies suggest that social competence has a higher predictive value for vocational outcome than psychopathology. These studies, however, show methodological shortcomings, including the fact that the instruments used for assessing social competence, psychopathology and work performance are strongly interrelated. The present study, involving a population of 34 chronically schizophrenic outpatients enrolled in a vocational rehabilitation program, was conducted in order to determine: (1) how closely the Role Play Test, the Positive and Negative Syndrome Scale and the Work Behavior Assessment Scale are related to each other; and (2) whether social competence is a better predictor of work performance and outcome of vocational rehabilitation than psychopathology. Factor analysis has revealed that the instruments are interrelated, mainly in the dimensions of negative symptoms, social relationships, non-verbal measures of social competence and conceptual disorganization. In backward regression analyses, psychopathological indicators proved to be the best predictors of work performance both cross-sectionally as well as in the longterm course. In the traditional two-syndrome model of schizophrenic psychopathology only negative symptoms were left in the regression model. In a four-dimension model the disorder of relating and the conceptual disorganization dimension were the best predictors. Differences between disorder of relating and social competence, assessed by the Role Play Test, are discussed here as well as the implications of this study for rehabilitation.
Conceptual and logical level of database modeling

NASA Astrophysics Data System (ADS)

Hunka, Frantisek; Matula, Jiri

2016-06-01

Conceptual and logical levels form the top most levels of database modeling. Usually, ORM (Object Role Modeling) and ER diagrams are utilized to capture the corresponding schema. The final aim of business process modeling is to store its results in the form of database solution. For this reason, value oriented business process modeling which utilizes ER diagram to express the modeling entities and relationships between them are used. However, ER diagrams form the logical level of database schema. To extend possibilities of different business process modeling methodologies, the conceptual level of database modeling is needed. The paper deals with the REA value modeling approach to business process modeling using ER-diagrams, and derives conceptual model utilizing ORM modeling approach. Conceptual model extends possibilities for value modeling to other business modeling approaches.
A predictive model of Health Related Quality of life of parents of chronically ill children: the importance of care-dependency of their child and their support system.

PubMed

Hatzmann, Janneke; Maurice-Stam, Heleen; Heymans, Hugo S A; Grootenhuis, Martha A

2009-07-28

Parents of chronically ill children are at risk for a lower Health Related Quality of Life (HRQoL). Insight in the dynamics of factors influencing parental HRQoL is necessary for development of interventions. Aim of the present study was to explore the influence of demographic and disease related factors on parental HRQoL, mediated by employment, income, leisure time, holiday and emotional support in a comprehensive model. In a cross-sectional design, 543 parents of chronically ill children completed questionnaires. A conceptual model of parental HRQoL was developed. Structural equation modeling was performed to explore the relations in the conceptual model, and to test if the model fitted the data. The model fitted the data closely (CHISQ(14) = 11.37, p = 0.66; RMSEA = 0.0, 90%CI [0.00;0.034]. The effect of socio-demographic and medical data on HRQoL was mediated by days on holiday (MCS: beta = .21) and emotional support (PCS: beta = .14; MCS: beta = .28). Also, female gender (beta = -.10), age (beta = .10), being chronically ill as a parent (beta = -.34), and care dependency of the child (beta = -.14; beta = -.15) were directly related to parental HRQoL. The final model was slightly different from the conceptual model. Main factors explaining parental HRQoL seemed to be emotional support, care dependency, days on holiday and being chronically ill as a parent. Holiday and emotional support mediated the effect of demographic and disease-related factors on HRQoL. Hours of employment, leisure time and household income did not mediate between background characteristics and HRQoL, contrasting the hypotheses.
Transient Inverse Calibration of Hanford Site-Wide Groundwater Model to Hanford Operational Impacts - 1943 to 1996

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

Cole, Charles R.; Bergeron, Marcel P.; Wurstner, Signe K.

2001-05-31

This report describes a new initiative to strengthen the technical defensibility of predictions made with the Hanford site-wide groundwater flow and transport model. The focus is on characterizing major uncertainties in the current model. PNNL will develop and implement a calibration approach and methodology that can be used to evaluate alternative conceptual models of the Hanford aquifer system. The calibration process will involve a three-dimensional transient inverse calibration of each numerical model to historical observations of hydraulic and water quality impacts to the unconfined aquifer system from Hanford operations since the mid-1940s.
Predictive Models of Cognitive Outcomes of Developmental Insults

NASA Astrophysics Data System (ADS)

Chan, Yupo; Bouaynaya, Nidhal; Chowdhury, Parimal; Leszczynska, Danuta; Patterson, Tucker A.; Tarasenko, Olga

2010-04-01

Representatives of Arkansas medical, research and educational institutions have gathered over the past four years to discuss the relationship between functional developmental perturbations and their neurological consequences. We wish to track the effect on the nervous system by developmental perturbations over time and across species. Except for perturbations, the sequence of events that occur during neural development was found to be remarkably conserved across mammalian species. The tracking includes consequences on anatomical regions and behavioral changes. The ultimate goal is to develop a predictive model of long-term genotypic and phenotypic outcomes that includes developmental insults. Such a model can subsequently be fostered into an educated intervention for therapeutic purposes. Several datasets were identified to test plausible hypotheses, ranging from evoked potential datasets to sleep-disorder datasets. An initial model may be mathematical and conceptual. However, we expect to see rapid progress as large-scale gene expression studies in the mammalian brain permit genome-wide searches to discover genes that are uniquely expressed in brain circuits and regions. These genes ultimately control behavior. By using a validated model we endeavor to make useful predictions.
Using NEON Data to Test and Refine Conceptual and Numerical Models of Soil Biogeochemical and Microbial Dynamics

NASA Astrophysics Data System (ADS)

Weintraub, S. R.; Stanish, L.; Ayers, E.

2017-12-01

Recent conceptual and numerical models have proposed new mechanisms that underpin key biogeochemical phenomena, including soil organic matter storage and ecosystem response to nitrogen deposition. These models seek to explicitly capture the ecological links among biota, especially microbes, and their physical and chemical environment to represent belowground pools and fluxes and how they respond to perturbation. While these models put forth exciting new concepts, their broad predictive abilities are unclear as some have been developed and tested against only small or regional datasets. The National Ecological Observatory Network (NEON) presents new opportunities to test and validate these models with multi-site data that span wide climatic, edaphic, and ecological gradients. NEON is measuring surface soil biogeochemical pools and fluxes along with diversity, abundance, and functional potential of soil microbiota at 47 sites distributed across the United States. This includes co-located measurements of soil carbon and nitrogen concentrations and stable isotopes, net nitrogen mineralization and nitrification rates, soil moisture, pH, microbial biomass, and community composition via 16S and ITS rRNA sequencing and shotgun metagenomic analyses. Early NEON data demonstrates that these wide edaphic and climatic gradients are related to changes in microbial community structure and functional potential, as well as element pools and process rates. Going forward, NEON's suite of standardized soil data has the potential to advance our understanding of soil communities and processes by allowing us to test the predictions of new soil biogeochemical frameworks and models. Here, we highlight several recently developed models that are ripe for this kind of data validation, and discuss key insights that may result. Further, we explore synergies with other networks, such as (i)LTER and (i)CZO, which may increase our ability to advance the frontiers of soil biogeochemical modeling.
The Use of Behavior Models for Predicting Complex Operations

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2010-01-01

Modeling and simulation (M&S) plays an important role when complex human-system notions are being proposed, developed and tested within the system design process. National Aeronautics and Space Administration (NASA) as an agency uses many different types of M&S approaches for predicting human-system interactions, especially when it is early in the development phase of a conceptual design. NASA Ames Research Center possesses a number of M&S capabilities ranging from airflow, flight path models, aircraft models, scheduling models, human performance models (HPMs), and bioinformatics models among a host of other kinds of M&S capabilities that are used for predicting whether the proposed designs will benefit the specific mission criteria. The Man-Machine Integration Design and Analysis System (MIDAS) is a NASA ARC HPM software tool that integrates many models of human behavior with environment models, equipment models, and procedural / task models. The challenge to model comprehensibility is heightened as the number of models that are integrated and the requisite fidelity of the procedural sets are increased. Model transparency is needed for some of the more complex HPMs to maintain comprehensibility of the integrated model performance. This will be exemplified in a recent MIDAS v5 application model and plans for future model refinements will be presented.
The Cerebellum: Adaptive Prediction for Movement and Cognition

PubMed Central

Sokolov, Arseny A.; Miall, R. Chris; Ivry, Richard B.

2017-01-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we consider two key concepts that have been suggested as general computational principles of cerebellar function, prediction and error-based learning, examining how these might be relevant in the operation of cognitive cerebro-cerebellar loops. PMID:28385461
Early warning signal for interior crises in excitable systems.

PubMed

Karnatak, Rajat; Kantz, Holger; Bialonski, Stephan

2017-10-01

The ability to reliably predict critical transitions in dynamical systems is a long-standing goal of diverse scientific communities. Previous work focused on early warning signals related to local bifurcations (critical slowing down) and nonbifurcation-type transitions. We extend this toolbox and report on a characteristic scaling behavior (critical attractor growth) which is indicative of an impending global bifurcation, an interior crisis in excitable systems. We demonstrate our early warning signal in a conceptual climate model as well as in a model of coupled neurons known to exhibit extreme events. We observed critical attractor growth prior to interior crises of chaotic as well as strange-nonchaotic attractors. These observations promise to extend the classes of transitions that can be predicted via early warning signals.
Assessment of Alternative Conceptual Models Using Reactive Transport Modeling with Monitoring Data

NASA Astrophysics Data System (ADS)

Dai, Z.; Price, V.; Heffner, D.; Hodges, R.; Temples, T.; Nicholson, T.

2005-12-01

Monitoring data proved very useful in evaluating alternative conceptual models, simulating contaminant transport behavior, and reducing uncertainty. A graded approach using three alternative conceptual site models was formulated to simulate a field case of tetrachloroethene (PCE) transport and biodegradation. These models ranged from simple to complex in their representation of subsurface heterogeneities. The simplest model was a single-layer homogeneous aquifer that employed an analytical reactive transport code, BIOCHLOR (Aziz et al., 1999). Due to over-simplification of the aquifer structure, this simulation could not reproduce the monitoring data. The second model consisted of a multi-layer conceptual model, in combination with numerical modules, MODFLOW and RT3D within GMS, to simulate flow and reactive transport. Although the simulation results from the second model were comparatively better than those from the simple model, they still did not adequately reproduce the monitoring well concentrations because the geological structures were still inadequately defined. Finally, a more realistic conceptual model was formulated that incorporated heterogeneities and geologic structures identified from well logs and seismic survey data using the Petra and PetraSeis software. This conceptual model included both a major channel and a younger channel that were detected in the PCE source area. In this model, these channels control the local ground-water flow direction and provide a preferential chemical transport pathway. Simulation results using this conceptual site model proved compatible with the monitoring concentration data. This study demonstrates that the bias and uncertainty from inadequate conceptual models are much larger than those introduced from an inadequate choice of model parameter values (Neuman and Wierenga, 2003; Meyer et al., 2004; Ye et al., 2004). This case study integrated conceptual and numerical models, based on interpreted local hydrogeologic and geochemical data, with detailed monitoring plume data. It provided key insights for confirming alternative conceptual site models and assessing the performance of monitoring networks. A monitoring strategy based on this graded approach for assessing alternative conceptual models can provide the technical bases for identifying critical monitoring locations, adequate monitoring frequency, and performance indicator parameters for performance monitoring involving ground-water levels and PCE concentrations.
A Structural Equation Model of Conceptual Change in Physics

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Sinatra, Gale M.

2011-01-01

A model of conceptual change in physics was tested on introductory-level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics…
Universal model for water costs of gas exchange by animals and plants

PubMed Central

Woods, H. Arthur; Smith, Jennifer N.

2010-01-01

For terrestrial animals and plants, a fundamental cost of living is water vapor lost to the atmosphere during exchange of metabolic gases. Here, by bringing together previously developed models for specific taxa, we integrate properties common to all terrestrial gas exchangers into a universal model of water loss. The model predicts that water loss scales to gas exchange with an exponent of 1 and that the amount of water lost per unit of gas exchanged depends on several factors: the surface temperature of the respiratory system near the outside of the organism, the gas consumed (oxygen or carbon dioxide), the steepness of the gradients for gas and vapor, and the transport mode (convective or diffusive). Model predictions were largely confirmed by data on 202 species in five taxa—insects, birds, bird eggs, mammals, and plants—spanning nine orders of magnitude in rate of gas exchange. Discrepancies between model predictions and data seemed to arise from biologically interesting violations of model assumptions, which emphasizes how poorly we understand gas exchange in some taxa. The universal model provides a unified conceptual framework for analyzing exchange-associated water losses across taxa with radically different metabolic and exchange systems. PMID:20404161
Universal model for water costs of gas exchange by animals and plants.

PubMed

Woods, H Arthur; Smith, Jennifer N

2010-05-04

For terrestrial animals and plants, a fundamental cost of living is water vapor lost to the atmosphere during exchange of metabolic gases. Here, by bringing together previously developed models for specific taxa, we integrate properties common to all terrestrial gas exchangers into a universal model of water loss. The model predicts that water loss scales to gas exchange with an exponent of 1 and that the amount of water lost per unit of gas exchanged depends on several factors: the surface temperature of the respiratory system near the outside of the organism, the gas consumed (oxygen or carbon dioxide), the steepness of the gradients for gas and vapor, and the transport mode (convective or diffusive). Model predictions were largely confirmed by data on 202 species in five taxa--insects, birds, bird eggs, mammals, and plants--spanning nine orders of magnitude in rate of gas exchange. Discrepancies between model predictions and data seemed to arise from biologically interesting violations of model assumptions, which emphasizes how poorly we understand gas exchange in some taxa. The universal model provides a unified conceptual framework for analyzing exchange-associated water losses across taxa with radically different metabolic and exchange systems.
Testing for ontological errors in probabilistic forecasting models of natural systems

PubMed Central

Marzocchi, Warner; Jordan, Thomas H.

2014-01-01

Probabilistic forecasting models describe the aleatory variability of natural systems as well as our epistemic uncertainty about how the systems work. Testing a model against observations exposes ontological errors in the representation of a system and its uncertainties. We clarify several conceptual issues regarding the testing of probabilistic forecasting models for ontological errors: the ambiguity of the aleatory/epistemic dichotomy, the quantification of uncertainties as degrees of belief, the interplay between Bayesian and frequentist methods, and the scientific pathway for capturing predictability. We show that testability of the ontological null hypothesis derives from an experimental concept, external to the model, that identifies collections of data, observed and not yet observed, that are judged to be exchangeable when conditioned on a set of explanatory variables. These conditional exchangeability judgments specify observations with well-defined frequencies. Any model predicting these behaviors can thus be tested for ontological error by frequentist methods; e.g., using P values. In the forecasting problem, prior predictive model checking, rather than posterior predictive checking, is desirable because it provides more severe tests. We illustrate experimental concepts using examples from probabilistic seismic hazard analysis. Severe testing of a model under an appropriate set of experimental concepts is the key to model validation, in which we seek to know whether a model replicates the data-generating process well enough to be sufficiently reliable for some useful purpose, such as long-term seismic forecasting. Pessimistic views of system predictability fail to recognize the power of this methodology in separating predictable behaviors from those that are not. PMID:25097265
Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Pseudomonas aeruginosa dose response and bathing water infection.

PubMed

Roser, D J; van den Akker, B; Boase, S; Haas, C N; Ashbolt, N J; Rice, S A

2014-03-01

Pseudomonas aeruginosa is the opportunistic pathogen mostly implicated in folliculitis and acute otitis externa in pools and hot tubs. Nevertheless, infection risks remain poorly quantified. This paper reviews disease aetiologies and bacterial skin colonization science to advance dose-response theory development. Three model forms are identified for predicting disease likelihood from pathogen density. Two are based on Furumoto & Mickey's exponential 'single-hit' model and predict infection likelihood and severity (lesions/m2), respectively. 'Third-generation', mechanistic, dose-response algorithm development is additionally scoped. The proposed formulation integrates dispersion, epidermal interaction, and follicle invasion. The review also details uncertainties needing consideration which pertain to water quality, outbreaks, exposure time, infection sites, biofilms, cerumen, environmental factors (e.g. skin saturation, hydrodynamics), and whether P. aeruginosa is endogenous or exogenous. The review's findings are used to propose a conceptual infection model and identify research priorities including pool dose-response modelling, epidermis ecology and infection likelihood-based hygiene management.
Using the theory of reasoned action to model retention in rural primary care physicians.

PubMed

Feeley, Thomas Hugh

2003-01-01

Much research attention has focused on medical students', residents', and physicians' decisions to join a rural practice, but far fewer studies have examined retention of rural primary care physicians. The current review uses Fishbein and Ajzen's Theory of Reasoned Action (TRA) to organize the literature on the predictors and correlates of retention of rural practicing physicians. TRA suggests turnover behavior is directly predicted by one's turnover intentions, which are, in turn, predicted by one's attitudes about rural practice and perceptions of salient others' (eg, spouse's) attitudes about rural practice and rural living. Narrative literature review of scholarship in predicting and understanding predictors and correlates of rural physician retention. The TRA model provides a useful conceptual model to organize the literature on rural physician retention. Physicians' subjective norms regarding rural practice are an important source of influence in the decision to remain or leave one's position, and this relation should be more fully examined in future research.
Preliminary development of POEAW in enhancing K-11 students’ understanding level on impulse and momentum

NASA Astrophysics Data System (ADS)

Luthfiani, T. A.; Sinaga, P.; Samsudin, A.

2018-05-01

We have been analyzed that there were limited research about Predict-Observe- Explain which use writing process with conceptual change text strategy. This study aims to develop a learning model namely Predict-Observe-Explain-Apply-Writing (POEAW) which is able to enhance students’ understanding level. The research method utilized the 4D model (Defining, Designing, Developing and Disseminating) that is formally limited to Developing Stage. There are four experts who judge the learning component (syntax, lesson plan, teaching material and student worksheet) and matter component (learning quality and content component). The result of this study are obtained expert validity test score average of 87% for learning content and 89% for matter component that means the POEAW is valid and can be tested in classroom learning. This research producing POEAW learning model that has five main steps, Predict, Observe, Explain, Apply and Write. To sum up, we have early developed POEAW in enhancing K-11 students’ understanding levels on impulse and momentum.
Predicting Predator Recognition in a Changing World.

PubMed

Carthey, Alexandra J R; Blumstein, Daniel T

2018-02-01

Through natural as well as anthropogenic processes, prey can lose historically important predators and gain novel ones. Both predator gain and loss frequently have deleterious consequences. While numerous hypotheses explain the response of individuals to novel and familiar predators, we lack a unifying conceptual model that predicts the fate of prey following the introduction of a novel or a familiar (reintroduced) predator. Using the concept of eco-evolutionary experience, we create a new framework that allows us to predict whether prey will recognize and be able to discriminate predator cues from non-predator cues and, moreover, the likely persistence outcomes for 11 different predator-prey interaction scenarios. This framework generates useful and testable predictions for ecologists, conservation scientists, and decision-makers. Copyright © 2017 Elsevier Ltd. All rights reserved.
Predictors of medication adherence in high risk youth of color living with HIV.

PubMed

Macdonell, Karen E; Naar-King, Sylvie; Murphy, Debra A; Parsons, Jeffrey T; Harper, Gary W

2010-07-01

To test predictors of medication adherence in high-risk racial or ethnic minority youth living with HIV (YLH) using a conceptual model of social cognitive predictors including a continuous measure of motivational readiness. Youth were participants in a multi-site clinical trial examining the efficacy of a motivational intervention. Racial-minority YLH (primarily African American) who were prescribed antiretroviral medication were included (N = 104). Data were collected using computer-assisted personal interviewing method via an Internet-based application and questionnaires. Using path analysis with bootstrapping, most youth reported suboptimal adherence, which predicted higher viral load. Higher motivational readiness predicted optimal adherence, and higher social support predicted readiness. Decisional balance was indirectly related to adherence. The model provided a plausible framework for understanding adherence in this population. Culturally competent interventions focused on readiness and social support may be helpful for improving adherence in YLH.
Derivation of a GIS-based watershed-scale conceptual model for the St. Jones River Delaware from habitat-scale conceptual models.

PubMed

Reiter, Michael A; Saintil, Max; Yang, Ziming; Pokrajac, Dragoljub

2009-08-01

Conceptual modeling is a useful tool for identifying pathways between drivers, stressors, Valued Ecosystem Components (VECs), and services that are central to understanding how an ecosystem operates. The St. Jones River watershed, DE is a complex ecosystem, and because management decisions must include ecological, social, political, and economic considerations, a conceptual model is a good tool for accommodating the full range of inputs. In 2002, a Four-Component, Level 1 conceptual model was formed for the key habitats of the St. Jones River watershed, but since the habitat level of resolution is too fine for some important watershed-scale issues we developed a functional watershed-scale model using the existing narrowed habitat-scale models. The narrowed habitat-scale conceptual models and associated matrices developed by Reiter et al. (2006) were combined with data from the 2002 land use/land cover (LULC) GIS-based maps of Kent County in Delaware to assemble a diagrammatic and numerical watershed-scale conceptual model incorporating the calculated weight of each habitat within the watershed. The numerical component of the assembled watershed model was subsequently subjected to the same Monte Carlo narrowing methodology used for the habitat versions to refine the diagrammatic component of the watershed-scale model. The narrowed numerical representation of the model was used to generate forecasts for changes in the parameters "Agriculture" and "Forest", showing that land use changes in these habitats propagated through the results of the model by the weighting factor. Also, the narrowed watershed-scale conceptual model identified some key parameters upon which to focus research attention and management decisions at the watershed scale. The forecast and simulation results seemed to indicate that the watershed-scale conceptual model does lead to different conclusions than the habitat-scale conceptual models for some issues at the larger watershed scale.
A hierarchical perspective of plant diversity

USGS Publications Warehouse

Sarr, Daniel; Hibbs, D.E.; Huston, M.

2005-01-01

Predictive models of plant diversity have typically focused on either a landscapea??s capacity for richness (equilibrium models), or on the processes that regulate competitive exclusion, and thus allow species to coexist (nonequilibrium models). Here, we review the concepts and purposes of a hierarchical, multiscale model of the controls of plant diversity that incorporates the equilibrium model of climatic favorability at macroscales, nonequilibrium models of competition at microscales, and a mixed model emphasizing environmental heterogeneity at mesoscales. We evaluate the conceptual model using published data from three spatially nested datasets: (1) a macroscale analysis of ecoregions in the continental and western U.S.; (2) a mesoscale study in California; and (3) a microscale study in the Siskiyou Mountains of Oregon and California. At the macroscale (areas from 3889 km2 to 638,300 km2), climate (actual evaporation) was a strong predictor of tree diversity (R2 = 0.80), as predicted by the conceptual model, but area was a better predictor for vascular plant diversity overall (R2 = 0.38), which suggests different types of plants differ in their sensitivity to climatic controls. At mesoscales (areas from 1111 km2 to 15,833 km2 ), climate was still an important predictor of richness (R2 = 0.52), but, as expected, topographic heterogeneity explained an important share of the variance (R2 = 0.19), showed positive correlations with diversity of trees, shrubs, and annual and perennial herbs, and was the primary predictor of shrub and annual plant species richness. At microscales (0.1 ha plots), spatial patterns of diversity showed a clear unimodal pattern along a climatea??driven productivity gradient and a negative relationship with soil fertility. The strong decline in understory and total diversity at the most productive sites suggests that competitive controls, as predicted, can override climatic controls at this scale. We conclude that this hierarchical, multiscale model provides a sound basis to understand and analyze plant species diversity. Specifically, future research should employ the principles in this paper to explore climatic controls on species richness of different life forms, better quantify environmental heterogeneity in landscapes, and analyze how these largea??scale factors interact with local nonequilibrium dynamics to maintain plant diversity.
Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

NASA Technical Reports Server (NTRS)

Douglas, Anne R.; Stolarski, Richard S.; Strahan, Susan E.; Connell, Peter S.

2004-01-01

The most important use of atmospheric chemistry and transport models is to predict the future composition of the atmosphere. The amounts of gases like chlorofluorcarbons, methyl bromide, nitrous oxide and methane are changing and the stratospheric ozone layer will change because these gases are changing. Methyl bromide, nitrous oxide and methane all have natural sources, and also change because of human activity. Chlorofluorcarbons are man-made gases; these are known to decrease stratospheric ozone and future production is banned. They are long-lived gases, and many decades will pass before they are insignificant in the atmosphere. The models are used to predict changes in ozone and other gases; this is a straightforward application. The models must be also tested using observations for the present day atmosphere. This is a challenging task, because the model contains more than 50 species and more than 150 chemical reactions. Data from satellites, ground stations, aircraft and balloons are used to evaluate the model. Different models that are used in international assessments produce different results; in the most recent assessment some predict that ozone will return to 1980 levels by 2025 and others predict that this will not happen until 2050. Since all the parts of the models are conceptually the same, there must be differences in implementation that produce these differences, This work takes a single model, two different sets of winds and temperatures, and repeats the same prediction for the future. Here we compare the results for these two simulations with many observations. The purpose is to identify differences in the model results for the present atmosphere that will lead to different predictions. This sort of controlled comparison will reduce uncertainty in the predictions for stratospheric ozone.
Social Support, Trust in Health Information, and Health Information-Seeking Behaviors (HISBs): A Study Using the 2012 Annenberg National Health Communication Survey (ANHCS).

PubMed

Yang, Qinghua; Chen, Yixin; Wendorf Muhamad, Jessica

2017-09-01

We proposed a conceptual model to predict health information-seeking behaviors (HISBs) from three different sources (family, the Internet, doctors). To test the model, a structural equation modeling (SEM) analysis was conducted using data from the 2012 Annenberg National Health Communication Survey (ANHCS) (N = 3,285). Findings suggest higher social support from family predicts higher trust in health information from family members (abbreviated as trust in this article). Trust is positively related to HISBs from all three sources, with the path linking trust to HISB from family being the strongest. The effect of social support on HISB from family is partially mediated by trust, while effect of social support on HISBs from the Internet/doctors is fully mediated by trust. Implications of the study are discussed.
Comparison of particle-tracking and lumped-parameter age-distribution models for evaluating vulnerability of production wells to contamination

USGS Publications Warehouse

Eberts, S.M.; Böhlke, J.K.; Kauffman, L.J.; Jurgens, B.C.

2012-01-01

Environmental age tracers have been used in various ways to help assess vulnerability of drinking-water production wells to contamination. The most appropriate approach will depend on the information that is available and that which is desired. To understand how the well will respond to changing nonpoint-source contaminant inputs at the water table, some representation of the distribution of groundwater ages in the well is needed. Such information for production wells is sparse and difficult to obtain, especially in areas lacking detailed field studies. In this study, age distributions derived from detailed groundwater-flow models with advective particle tracking were compared with those generated from lumped-parameter models to examine conditions in which estimates from simpler, less resource-intensive lumped-parameter models could be used in place of estimates from particle-tracking models. In each of four contrasting hydrogeologic settings in the USA, particle-tracking and lumped-parameter models yielded roughly similar age distributions and largely indistinguishable contaminant trends when based on similar conceptual models and calibrated to similar tracer data. Although model calibrations and predictions were variably affected by tracer limitations and conceptual ambiguities, results illustrated the importance of full age distributions, rather than apparent tracer ages or model mean ages, for trend analysis and forecasting.
Quantum structure in economics: The Ellsberg paradox

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Sozzo, Sandro

2012-03-01

The expected utility hypothesis and Savage's Sure-Thing Principle are violated in real life decisions, as shown by the Allais and Ellsberg paradoxes. The popular explanation in terms of ambiguity aversion is not completely accepted. As a consequence, uncertainty is still problematical in economics. To overcome these difficulties a distinction between risk and ambiguity has been introduced which depends on the existence of a Kolmogorovian probabilistic structure modeling these uncertainties. On the other hand, evidence of everyday life suggests that context plays a fundamental role in human decisions under uncertainty. Moreover, it is well known from physics that any probabilistic structure modeling contextual interactions between entities structurally needs a non-Kolmogorovian framework admitting a quantum-like representation. For this reason, we have recently introduced a notion of contextual risk to mathematically capture situations in which ambiguity occurs. We prove in this paper that the contextual risk approach can be applied to the Ellsberg paradox, and elaborate a sphere model within our hidden measurement formalism which reveals that it is the overall conceptual landscape that is responsible of the disagreement between actual human decisions and the predictions of expected utility theory, which generates the paradox. This result points to the presence of a quantum conceptual layer in human thought which is superposed to the usually assumed classical logical layer, and conceptually supports the thesis of several authors suggesting the presence of quantum structure in economics and decision theory.
Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

ERIC Educational Resources Information Center

Berman, Jeanette; Smyth, Robyn

2015-01-01

This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…
Proposed Modifications to the Conceptual Model of Coaching Efficacy and Additional Validity Evidence for the Coaching Efficacy Scale II-High School Teams

ERIC Educational Resources Information Center

Myers, Nicholas; Feltz, Deborah; Chase, Melissa

2011-01-01

The purpose of this study was to determine whether theoretically relevant sources of coaching efficacy could predict the measures derived from the Coaching Efficacy Scale II-High School Teams (CES II-HST). Data were collected from head coaches of high school teams in the United States (N = 799). The analytic framework was a multiple-group…
Growing up in Poverty and Civic Engagement: The Role of Kindergarten Executive Function and Play Predicting Participation in 8th Grade Extracurricular Activities

ERIC Educational Resources Information Center

Astuto, Jennifer; Ruck, Martin

2017-01-01

In the United States a "civic engagement gap" persists between low-income youth and their higher-income counterparts. To examine the developmental origins of civic engagement in a sample of U.S. children growing up in poverty, a conceptual model was tested employing the Early Childhood Longitudinal Study-Kindergarten Class (ECLS-K)…
Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors

NASA Astrophysics Data System (ADS)

Del Giudice, Dario; Löwe, Roland; Madsen, Henrik; Mikkelsen, Peter Steen; Rieckermann, Jörg

2015-07-01

In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can provide probabilistic predictions of wastewater discharge in a similarly reliable way, both for periods ranging from a few hours up to more than 1 week ahead of time. The EBD produces more accurate predictions on long horizons but relies on computationally heavy MCMC routines for parameter inferences. These properties make it more suitable for off-line applications. The IND can help in diagnosing the causes of output errors and is computationally inexpensive. It produces best results on short forecast horizons that are typical for online applications.
Concepts Within Reach: Action Performance Predicts Action Language Processing in Stroke

PubMed Central

Desai, Rutvik H.; Herter, Troy; Riccardi, Nicholas; Rorden, Chris; Fridriksson, Julius

2015-01-01

The relationship between the brain’s conceptual or semantic and sensory-motor systems remains controversial. Here, we tested manual and conceptual abilities of 41 chronic stroke patients in order to examine their relationship. Manual abilities were assed through a reaching task using an exoskeleton robot. Semantic abilities were assessed with implicit as well as explicit semantic tasks, for both verbs and nouns. The results show that that the degree of selective impairment for action word processing was predicted by the degree of impairment in reaching performance. Moreover, the implicit semantic measures showed a correlation with a global reaching parameter, while the explicit semantic similarity judgment task predicted performance in action initiation. These results indicate that action concepts are dynamically grounded through motoric simulations, and that more details are simulated for more explicit semantic tasks. This is evidence for a close and causal relationship between sensory-motor and conceptual systems of the brain. PMID:25858602
State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

USGS Publications Warehouse

Provencher, Louis; Frid, Leonardo; Czembor, Christina; Morisette, Jeffrey T.

2016-01-01

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.
Child Maltreatment and Autonomic Nervous System Reactivity: Identifying Dysregulated Stress Reactivity Patterns using the Biopsychosocial Model of Challenge and Threat

PubMed Central

McLaughlin, Katie A.; Sheridan, Margaret A.; Alves, Sonia; Mendes, Wendy Berry

2014-01-01

OBJECTIVE Disruptions in stress response system development have been posited as mechanisms linking child maltreatment (CM) to psychopathology. Existing theories predict elevated sympathetic nervous system (SNS) reactivity following CM, but evidence for this is inconsistent. We present a novel framework for conceptualizing stress reactivity following CM using the biopsychosocial model of challenge and threat. We predicted that in the context of a social-evaluative stressor, maltreated adolescents would exhibit a threat pattern of reactivity, involving SNS activation paired with elevated vascular resistance and blunted cardiac output (CO) reactivity. METHODS A sample of 168 adolescents (mean age=14.9 years) participated. Recruitment targeted maltreated adolescents; 38.2% qualified as maltreated. Electrocardiogram, impedance cardiography, and blood pressure were acquired at rest and during an evaluated social stressor (Trier Social Stress Test). Pre-ejection period (PEP), CO, and total peripheral resistance (TPR) reactivity were computed during task preparation, speech-delivery, and verbal mental-arithmetic. Internalizing and externalizing symptoms were assessed. RESULTS Maltreatment was unrelated to PEP reactivity during preparation or speech, but maltreated adolescents had reduced PEP reactivity during math. Maltreatment exposure (F(1,145)=3.8-9.4, p=.053-<.001) and severity (β=−.10-.12, p=.030-.007) were associated with significantly reduced CO reactivity during all components of the stress-task and marginally associated with elevated TPR reactivity (F(1,145)=3.8-9.4, p=.053-<.001; β=.07-.11, p=.11-.009, respectively). Threat reactivity was negatively associated with externalizing symptoms. CONCLUSIONS Child maltreatment is associated with a dysregulated pattern of physiological reactivity consistent with theoretical conceptualizations of threat but not previously examined in relation to maltreatment, suggesting a more nuanced pattern of stress reactivity than predicted by current theoretical models. PMID:25170753
Conceptualizing agency: Folkpsychological and folkcommunicative perspectives on plants.

PubMed

Ojalehto, Bethany L; Medin, Douglas L; García, Salino G

2017-05-01

The present research addresses cultural variation in concepts of agency. Across two experiments, we investigate how Indigenous Ngöbe of Panama and US college students interpret and make inferences about nonhuman agency, focusing on plants as a critical test case. In Experiment 1, participants predicted goal-directed actions for plants and other nonhuman kinds and judged their capacities for intentional agency. Goal-directed action is pervasive among living kinds and as such we expected cultural agreement on these predictions. However, we expected that interpretation of the capacities involved would differ based on cultural folktheories. As expected, Ngöbe and US participants both inferred that plants would engage in goal-directed action but Ngöbe were more likely to attribute intentional agency capacities to plants. Experiment 2 extends these findings by investigating action predictions and capacity attributions linked to complex forms of plant social agency recently discovered in botanical sciences (communication, kin altruism). We hypothesized that the Ngöbe view of plants as active agents would productively guide inferences for plant social interaction. Indeed, Ngöbe were more likely than US participants to infer that plants can engage in social behaviors and they also attributed more social agency capacities to plants. We consolidate these findings by using bottom-up consensus modeling to show that these cultural differences reflect two distinct conceptual models of agency rather than variations on a single (universal) model. We consider these findings in light of current theories of domain-specificity and animism, and offer an alternative account based on a folktheory of communication that infers agency on the basis of relational interactions rather than having a mind. Copyright © 2017 Elsevier B.V. All rights reserved.
Conceptual Change Texts in Chemistry Teaching: A Study on the Particle Model of Matter

ERIC Educational Resources Information Center

Beerenwinkel, Anne; Parchmann, Ilka; Grasel, Cornelia

2011-01-01

This study explores the effect of a conceptual change text on students' awareness of common misconceptions on the particle model of matter. The conceptual change text was designed based on principles of text comprehensibility, of conceptual change instruction and of instructional approaches how to introduce the particle model. It was evaluated in…

Field-scale forward modelling of a shallow marine carbonate ramp: the Upper Jurassic Arab Formation (onshore Abu Dhabi - UAE)

NASA Astrophysics Data System (ADS)

Marchionda, Elisabetta; Deschamps, Rémy; Nader, Fadi H.; Ceriani, Andrea; Di Giulio, Andrea; Lawrence, David; Morad, Daniel J.

2017-04-01

The stratigraphic record of a carbonate system is the result of the interplay of several local and global factors that control the physical and the biological responses within a basin. Conceptual models cannot be detailed enough to take into account all the processes that control the deposition of sediments. The evaluation of the key controlling parameters on the sedimentation can be investigated with the use of stratigraphic forward models, that permit dynamic and quantitative simulations of the sedimentary basin infill. This work focuses on an onshore Abu Dhabi field (UAE) and it aims to provide a complete picture of the stratigraphic evolution of Upper Jurassic Arab Formation (Fm.). In this study, we started with the definition of the field-scale conceptual depositional model of the Formation, resulting from facies and well log analysis based on five wells. The Arab Fm. could be defined as a shallow marine carbonate ramp, that ranges from outer ramp deposits to supratidal/evaporitic facies association (from bottom to top). With the reconstruction of the sequence stratigraphic pattern and several paleofacies maps, it was possible to suggest multiple directions of progradations at local scale. Then, a 3D forward modelling tool has been used to i) identify and quantify the controlling parameters on geometries and facies distribution of the Arab Fm.; ii) predict the stratigraphic architecture of the Arab Fm.; and iii) integrate and validate the conceptual model. Numerous constraints were set during the different simulations and sensitivity analyses were performed testing the carbonate production, eustatic oscillations and transport parameters. To verify the geological consistency the 3D forward modelling has been calibrated with the available control points (five wells) in terms of thickness and facies distribution.
Methodological Developments in Geophysical Assimilation Modeling

NASA Astrophysics Data System (ADS)

Christakos, George

2005-06-01

This work presents recent methodological developments in geophysical assimilation research. We revisit the meaning of the term "solution" of a mathematical model representing a geophysical system, and we examine its operational formulations. We argue that an assimilation solution based on epistemic cognition (which assumes that the model describes incomplete knowledge about nature and focuses on conceptual mechanisms of scientific thinking) could lead to more realistic representations of the geophysical situation than a conventional ontologic assimilation solution (which assumes that the model describes nature as is and focuses on form manipulations). Conceptually, the two approaches are fundamentally different. Unlike the reasoning structure of conventional assimilation modeling that is based mainly on ad hoc technical schemes, the epistemic cognition approach is based on teleologic criteria and stochastic adaptation principles. In this way some key ideas are introduced that could open new areas of geophysical assimilation to detailed understanding in an integrated manner. A knowledge synthesis framework can provide the rational means for assimilating a variety of knowledge bases (general and site specific) that are relevant to the geophysical system of interest. Epistemic cognition-based assimilation techniques can produce a realistic representation of the geophysical system, provide a rigorous assessment of the uncertainty sources, and generate informative predictions across space-time. The mathematics of epistemic assimilation involves a powerful and versatile spatiotemporal random field theory that imposes no restriction on the shape of the probability distributions or the form of the predictors (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated) and accounts rigorously for the uncertainty features of the geophysical system. In the epistemic cognition context the assimilation concept may be used to investigate critical issues related to knowledge reliability, such as uncertainty due to model structure error (conceptual uncertainty).
Identifying habitats at risk: simple models can reveal complex ecosystem dynamics.

PubMed

Maxwell, Paul S; Pitt, Kylie A; Olds, Andrew D; Rissik, David; Connolly, Rod M

2015-03-01

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.
Scale-dependency of effective hydraulic conductivity on fire-affected hillslopes

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Lane, Patrick N. J.; Nyman, Petter; Noske, Philip J.; Cawson, Jane G.; Oono, Akiko; Sheridan, Gary J.

2016-07-01

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution (KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire-affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment-scale estimates. Furthermore, the distribution of Ks was not clearly log-normal and scale-independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply-limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.
Centrifugal and Axial Pump Design and Off-Design Performance Prediction

NASA Technical Reports Server (NTRS)

Veres, Joseph P.

1995-01-01

A meanline pump-flow modeling method has been developed to provide a fast capability for modeling pumps of cryogenic rocket engines. Based on this method, a meanline pump-flow code PUMPA was written that can predict the performance of pumps at off-design operating conditions, given the loss of the diffusion system at the design point. The design-point rotor efficiency and slip factors are obtained from empirical correlations to rotor-specific speed and geometry. The pump code can model axial, inducer, mixed-flow, and centrifugal pumps and can model multistage pumps in series. The rapid input setup and computer run time for this meanline pump flow code make it an effective analysis and conceptual design tool. The map-generation capabilities of the code provide the information needed for interfacing with a rocket engine system modeling code. The off-design and multistage modeling capabilities of PUMPA permit the user to do parametric design space exploration of candidate pump configurations and to provide head-flow maps for engine system evaluation.
Integrating Conceptual Knowledge Within and Across Representational Modalities

PubMed Central

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-01-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within- and between-modality is accomplished using either direct connectivity, or a central semantic hub. In deep models, modalities are connected via cascading integration sites with successively wider receptive fields. Four experiments provide the first direct behavioral tests of these models using speeded tasks involving feature inference and concept activation. Shallow models predict no within-modal versus cross-modal difference in either task, whereas deep models predict a within-modal advantage for feature inference, but a cross-modal advantage for concept activation. Experiments 1 and 2 used relatedness judgments to tap participants’ knowledge of relations for within- and cross-modal feature pairs. Experiments 3 and 4 used a dual feature verification task. The pattern of decision latencies across Experiments 1 to 4 is consistent with a deep integration hierarchy. PMID:21093853
Designers' unified cost model

NASA Technical Reports Server (NTRS)

Freeman, W.; Ilcewicz, L.; Swanson, G.; Gutowski, T.

1992-01-01

The Structures Technology Program Office (STPO) at NASA LaRC has initiated development of a conceptual and preliminary designers' cost prediction model. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state-of-the-art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a database and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. This paper presents the team members, approach, goals, plans, and progress to date for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).
Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state.

PubMed

Perendeci, Altinay; Arslan, Sever; Tanyolaç, Abdurrahman; Celebi, Serdar S

2009-10-01

A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a sugar factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5-10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.
When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.
The long oasis: understanding and managing saline floodplains in southeastern Australia

NASA Astrophysics Data System (ADS)

Woods, J.; Green, G.; Laattoe, T.; Purczel, C.; Riches, V.; Li, C.; Denny, M.

2017-12-01

In a semi-arid region of southeastern Australia, the River Murray is the predominant source of freshwater for town water supply, irrigation, and floodplain ecosystems. The river interacts with aquifers where the salinity routinely exceeds 18,000 mg/l. River regulation, extraction, land clearance, and irrigation have reduced the size and frequency of floods while moving more salt into the floodplain. Floodplain ecosystem health has declined. Management options to improve floodplain health under these modified conditions include environmental watering, weirpool manipulation, and groundwater pumping. To benefit long-lived tree species, floodplain management needs to increase soil moisture availability. A conceptual model was developed of floodplain processes impacting soil moisture availability. The implications and limitations of the conceptualization were investigated using a series of numerical models, each of which simulated a subset of the processes under current and managed conditions. The aim was to determine what range of behaviors the models predicted, and to identify which parameters were key to accurately predicting the success of management options. Soil moisture availability was found to depend strongly on the properties of the floodplain clay, which controls vertical recharge during inundation. Groundwater freshening near surface water features depended on the riverbed conductivity and the penetration of the river into the floodplain sediments. Evapotranspiration is another critical process, and simulations revealed the limitations of standard numerical codes in environments where both evaporation and transpiration depend on salinity. Finally, maintenance of viable populations of floodplain trees is conceptually understood to rely on the persistence of adequate soil moisture availability over time, but thresholds for duration of exposure to low moisture availability that lead to decline and irreversible decline in tree condition are a major knowledge gap. The work identified critical data gaps which will be addressed in monitoring guidelines to improve management. This includes: hydrogeochemical sampling; in situ soil monitoring combined with tree health observations; monitoring of actual evapotranspiration; and monitoring of bores close to surface water sources.
Validation of the Continuum of Care Conceptual Model for Athletic Therapy

PubMed Central

Lafave, Mark R.; Butterwick, Dale; Eubank, Breda

2015-01-01

Utilization of conceptual models in field-based emergency care currently borrows from existing standards of medical and paramedical professions. The purpose of this study was to develop and validate a comprehensive conceptual model that could account for injuries ranging from nonurgent to catastrophic events including events that do not follow traditional medical or prehospital care protocols. The conceptual model should represent the continuum of care from the time of initial injury spanning to an athlete's return to participation in their sport. Finally, the conceptual model should accommodate both novices and experts in the AT profession. This paper chronicles the content validation steps of the Continuum of Care Conceptual Model for Athletic Therapy (CCCM-AT). The stages of model development were domain and item generation, content expert validation using a three-stage modified Ebel procedure, and pilot testing. Only the final stage of the modified Ebel procedure reached a priori 80% consensus on three domains of interest: (1) heading descriptors; (2) the order of the model; (3) the conceptual model as a whole. Future research is required to test the use of the CCCM-AT in order to understand its efficacy in teaching and practice within the AT discipline. PMID:26464897
Subtypes of developmental dyslexia: testing the predictions of the dual-route and connectionist frameworks.

PubMed

Peterson, Robin L; Pennington, Bruce F; Olson, Richard K

2013-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg's connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with "pure" phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with "relative" phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. Copyright © 2012 Elsevier B.V. All rights reserved.
Subtypes of developmental dyslexia: Testing the predictions of the dual-route and connectionist frameworks

PubMed Central

Peterson, Robin L.; Pennington, Bruce F.; Olson, Richard K.

2012-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the dual-route cascaded model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg’s connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with “pure” phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with “relative” phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. PMID:23010562
Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

NASA Astrophysics Data System (ADS)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.
The affordance-matching hypothesis: how objects guide action understanding and prediction

PubMed Central

Bach, Patric; Nicholson, Toby; Hudson, Matthew

2014-01-01

Action understanding lies at the heart of social interaction. Prior research has often conceptualized this capacity in terms of a motoric matching of observed actions to an action in one’s motor repertoire, but has ignored the role of object information. In this manuscript, we set out an alternative conception of intention understanding, which places the role of objects as central to our observation and comprehension of the actions of others. We outline the current understanding of the interconnectedness of action and object knowledge, demonstrating how both rely heavily on the other. We then propose a novel framework, the affordance-matching hypothesis, which incorporates these findings into a simple model of action understanding, in which object knowledge—what an object is for and how it is used—can inform and constrain both action interpretation and prediction. We will review recent empirical evidence that supports such an object-based view of action understanding and we relate the affordance matching hypothesis to recent proposals that have re-conceptualized the role of mirror neurons in action understanding. PMID:24860468
Impact of modellers' decisions on hydrological a priori predictions

NASA Astrophysics Data System (ADS)

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2014-06-01

In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.
Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-Making Rating Scale

PubMed Central

Lichtenberg, Peter A.; Ocepek-Welikson, Katja; Ficker, Lisa J.; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A.

2017-01-01

Objectives The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. Methods A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results Results confirmed the scale’s reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. Conclusions The psychometric properties of the LFDRS support the scale’s use as it was proposed in Lichtenberg et al., 2015. Clinical Implications The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments. PMID:29077531
Improved Conceptual Models Methodology (ICoMM) for Validation of Non-Observable Systems

DTIC Science & Technology

2015-12-01

distribution is unlimited IMPROVED CONCEPTUAL MODELS METHODOLOGY (ICoMM) FOR VALIDATION OF NON-OBSERVABLE SYSTEMS by Sang M. Sok December 2015...REPORT TYPE AND DATES COVERED Dissertation 4. TITLE AND SUBTITLE IMPROVED CONCEPTUAL MODELS METHODOLOGY (ICoMM) FOR VALIDATION OF NON-OBSERVABLE...importance of the CoM. The improved conceptual model methodology (ICoMM) is developed in support of improving the structure of the CoM for both face and
Habit, identity, and repetitive action: a prospective study of binge-drinking in UK students.

PubMed

Gardner, Benjamin; de Bruijn, Gert-Jan; Lally, Phillippa

2012-09-01

Repeated action can lead to the formation of habits and identification as 'the kind of person' that performs the behaviour. This has led to the suggestion that identity-relevance is a facet of habit. This study explores conceptual overlap between habit and identity, and examines where the two constructs fit into an extended Theory of Planned Behaviour (TPB) model of binge-drinking among university students. Prospective, questionnaire-based correlational design. A total of 167 UK university students completed baseline measures of past behaviour, self-identity, the Self-Report Habit Index (SRHI), and TPB constructs. One week later, 128 participants completed a follow-up behaviour measure. Factor analyses of the SRHI and four identity items revealed two correlated but distinct factors, relating to habit and identity, respectively. Hierarchical regression analyses of intention and behaviour showed that identity contributed over and above TPB constructs to the prediction of intention, whereas habit predicted behaviour directly, and interacted with intentions in predicting behaviour. Habits unexpectedly strengthened the intention-behaviour relation, such that strong intenders were more likely to binge-drink where they also had strong habits. Identity and habit are conceptually discrete and impact differently on binge-drinking. Findings have implications for habit theory and measurement. Recommendations for student alcohol consumption reduction initiatives are offered. ©2011 The British Psychological Society.
The Emergence of Organizing Structure in Conceptual Representation.

PubMed

Lake, Brenden M; Lawrence, Neil D; Tenenbaum, Joshua B

2018-06-01

Both scientists and children make important structural discoveries, yet their computational underpinnings are not well understood. Structure discovery has previously been formalized as probabilistic inference about the right structural form-where form could be a tree, ring, chain, grid, etc. (Kemp & Tenenbaum, 2008). Although this approach can learn intuitive organizations, including a tree for animals and a ring for the color circle, it assumes a strong inductive bias that considers only these particular forms, and each form is explicitly provided as initial knowledge. Here we introduce a new computational model of how organizing structure can be discovered, utilizing a broad hypothesis space with a preference for sparse connectivity. Given that the inductive bias is more general, the model's initial knowledge shows little qualitative resemblance to some of the discoveries it supports. As a consequence, the model can also learn complex structures for domains that lack intuitive description, as well as predict human property induction judgments without explicit structural forms. By allowing form to emerge from sparsity, our approach clarifies how both the richness and flexibility of human conceptual organization can coexist. Copyright © 2018 Cognitive Science Society, Inc.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism.

PubMed

Graham, Emily B; Crump, Alex R; Resch, Charles T; Fansler, Sarah; Arntzen, Evan; Kennedy, David W; Fredrickson, Jim K; Stegen, James C

2016-01-01

Community assembly processes generate shifts in species abundances that influence ecosystem cycling of carbon and nutrients, yet our understanding of assembly remains largely separate from ecosystem-level functioning. Here, we investigate relationships between assembly and changes in microbial metabolism across space and time in hyporheic microbial communities. We pair sampling of two habitat types (i.e., attached and planktonic) through seasonal and sub-hourly hydrologic fluctuation with null modeling and temporally explicit multivariate statistics. We demonstrate that multiple selective pressures-imposed by sediment and porewater physicochemistry-integrate to generate changes in microbial community composition at distinct timescales among habitat types. These changes in composition are reflective of contrasting associations of Betaproteobacteria and Thaumarchaeota with ecological selection and with seasonal changes in microbial metabolism. We present a conceptual model based on our results in which metabolism increases when oscillating selective pressures oppose temporally stable selective pressures. Our conceptual model is pertinent to both macrobial and microbial systems experiencing multiple selective pressures and presents an avenue for assimilating community assembly processes into predictions of ecosystem-level functioning.
Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.
The added value of remote sensing products in constraining hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

2017-04-01

The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.
Biases in affective forecasting and recall in individuals with depression and anxiety symptoms.

PubMed

Wenze, Susan J; Gunthert, Kathleen C; German, Ramaris E

2012-07-01

The authors used experience sampling to investigate biases in affective forecasting and recall in individuals with varying levels of depression and anxiety symptoms. Participants who were higher in depression symptoms demonstrated stronger (more pessimistic) negative mood prediction biases, marginally stronger negative mood recall biases, and weaker (less optimistic) positive mood prediction and recall biases. Participants who were higher in anxiety symptoms demonstrated stronger negative mood prediction biases, but positive mood prediction biases that were on par with those who were lower in anxiety. Anxiety symptoms were not associated with mood recall biases. Neither depression symptoms nor anxiety symptoms were associated with bias in event prediction. Their findings fit well with the tripartite model of depression and anxiety. Results are also consistent with the conceptualization of anxiety as a "forward-looking" disorder, and with theories that emphasize the importance of pessimism and general negative information processing in depressive functioning.
The Cerebellum: Adaptive Prediction for Movement and Cognition.

PubMed

Sokolov, Arseny A; Miall, R Chris; Ivry, Richard B

2017-05-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops. Copyright © 2017 Elsevier Ltd. All rights reserved.
The neural basis of conceptual–emotional integration and its role in major depressive disorder

PubMed Central

Green, Sophie; Ralph, Matthew A. Lambon; Moll, Jorge; Zakrzewski, Jessica; Deakin, John F. William; Grafman, Jordan; Zahn, Roland

2013-01-01

The importance of differentiating between social concepts when appraising actions (e.g., understanding behavior as critical vs. fault-finding) and its contribution to vulnerability to major depressive disorder (MDD) is unknown. We predicted poor integration of differentiated conceptual knowledge when people with MDD appraise their social actions, contributing to their tendency to grossly overgeneralize self-blame (e.g., “I am unlikable rather than critical”). To test this hypothesis, we used a neuropsychological test measuring social conceptual differentiation and its relationship with emotional biases in a remitted MDD and a control group. During fMRI, guilt- and indignation-evoking sentences were presented. As predicted, conceptual overgeneralization was associated with increased emotional intensity when appraising social actions. Interdependence of conceptual overgeneralization and negative emotional biases was stronger in MDD (reproducible in the subgroup without medication) and was associated with overgeneralized self-blame. This high conceptual–emotional interdependence was associated with functional disconnection between the right superior anterior temporal lobe (ATL) and right dorsolateral prefrontal cortex (PFC) as well as a septal region across groups when experiencing guilt (SPM8). Strong coupling of conceptual information (ATL) with information about the context of actions and emotions (frontal-subcortical regions) is thus associated with appraisal being less dependent on conceptual overgeneralization, thereby protecting against excessive self-blame. PMID:23826933
Risk factors for pressure ulcer development in critically Ill patients: a conceptual model to guide research.

PubMed

Benoit, Richard; Mion, Lorraine

2012-08-01

This paper presents a proposed conceptual model to guide research on pressure ulcer risk in critically ill patients, who are at high risk for pressure ulcer development. However, no conceptual model exists that guides risk assessment in this population. Results from a review of prospective studies were evaluated for design quality and level of statistical reporting. Multivariate findings from studies having high or medium design quality by the National Institute of Health and Clinical Excellence standards were conceptually grouped. The conceptual groupings were integrated into Braden and Bergstrom's (Braden and Bergstrom [1987] Rehabilitation Nursing, 12, 8-12, 16) conceptual model, retaining their original constructs and augmenting their concept of intrinsic factors for tissue tolerance. The model could enhance consistency in research on pressure ulcer risk factors. Copyright © 2012 Wiley Periodicals, Inc.
A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury

DTIC Science & Technology

2013-10-01

Interpersonal scales were developed to provide an assessment of the respondent’s interpersonal style along two dimensions: a warmly affiliative versus...a cold rejecting style , and a dominating/controlling versus a meekly submissive style . These axes provide a useful way of conceptualizing many...Hours 9. How many hours per week do you spend in active homemaking including parenting , housekeeping, and food preparation
A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury

DTIC Science & Technology

2014-10-01

Interpersonal scales were developed to provide an assessment of the respondent’s interpersonal style along two dimensions: a warmly affiliative...versus a cold rejecting style , and a dominating/controlling versus a meekly submissive style . These axes provide a useful way of conceptualizing many...Hours 9. How many hours per week do you spend in active homemaking including parenting , housekeeping, and food preparation
A model-averaging method for assessing groundwater conceptual model uncertainty.

PubMed

Ye, Ming; Pohlmann, Karl F; Chapman, Jenny B; Pohll, Greg M; Reeves, Donald M

2010-01-01

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with additional modeling components that represent other hydrogeological conditions yields a total of 25 groundwater flow models. As all the models are plausible given available data and information, evaluating model uncertainty becomes inevitable. On the other hand, hydraulic parameters (e.g., hydraulic conductivity) are uncertain in each model, giving rise to parametric uncertainty. Propagation of the uncertainty in the models and model parameters through groundwater modeling causes predictive uncertainty in model predictions (e.g., hydraulic head and flow). Parametric uncertainty within each model is assessed using Monte Carlo simulation, and model uncertainty is evaluated using the model averaging method. Two model-averaging techniques (on the basis of information criteria and GLUE) are discussed. This study shows that contribution of model uncertainty to predictive uncertainty is significantly larger than that of parametric uncertainty. For the recharge and geological components, uncertainty in the geological interpretations has more significant effect on model predictions than uncertainty in the recharge estimates. In addition, weighted residuals vary more for the different geological models than for different recharge models. Most of the calibrated observations are not important for discriminating between the alternative models, because their weighted residuals vary only slightly from one model to another.
Coronary Artery Calcium Scoring: Is It Time for a Change in Methodology?

PubMed

Blaha, Michael J; Mortensen, Martin Bødtker; Kianoush, Sina; Tota-Maharaj, Rajesh; Cainzos-Achirica, Miguel

2017-08-01

Quantification of coronary artery calcium (CAC) has been shown to be reliable, reproducible, and predictive of cardiovascular risk. Formal CAC scoring was introduced in 1990, with early scoring algorithms notable for their simplicity and elegance. Yet, with little evidence available on how to best build a score, and without a conceptual model guiding score development, these scores were, to a large degree, arbitrary. In this review, we describe the traditional approaches for clinical CAC scoring, noting their strengths, weaknesses, and limitations. We then discuss a conceptual model for developing an improved CAC score, reviewing the evidence supporting approaches most likely to lead to meaningful score improvement (for example, accounting for CAC density and regional distribution). After discussing the potential implementation of an improved score in clinical practice, we follow with a discussion of the future of CAC scoring, asking the central question: do we really need a new CAC score? Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Statistical Modeling of Fire Occurrence Using Data from the Tōhoku, Japan Earthquake and Tsunami.

PubMed

Anderson, Dana; Davidson, Rachel A; Himoto, Keisuke; Scawthorn, Charles

2016-02-01

In this article, we develop statistical models to predict the number and geographic distribution of fires caused by earthquake ground motion and tsunami inundation in Japan. Using new, uniquely large, and consistent data sets from the 2011 Tōhoku earthquake and tsunami, we fitted three types of models-generalized linear models (GLMs), generalized additive models (GAMs), and boosted regression trees (BRTs). This is the first time the latter two have been used in this application. A simple conceptual framework guided identification of candidate covariates. Models were then compared based on their out-of-sample predictive power, goodness of fit to the data, ease of implementation, and relative importance of the framework concepts. For the ground motion data set, we recommend a Poisson GAM; for the tsunami data set, a negative binomial (NB) GLM or NB GAM. The best models generate out-of-sample predictions of the total number of ignitions in the region within one or two. Prefecture-level prediction errors average approximately three. All models demonstrate predictive power far superior to four from the literature that were also tested. A nonlinear relationship is apparent between ignitions and ground motion, so for GLMs, which assume a linear response-covariate relationship, instrumental intensity was the preferred ground motion covariate because it captures part of that nonlinearity. Measures of commercial exposure were preferred over measures of residential exposure for both ground motion and tsunami ignition models. This may vary in other regions, but nevertheless highlights the value of testing alternative measures for each concept. Models with the best predictive power included two or three covariates. © 2015 Society for Risk Analysis.
The role of 3D visualisation as an analytical tool preparatory to numerical modelling [rapid communication

NASA Astrophysics Data System (ADS)

Robins, N. S.; Rutter, H. K.; Dumpleton, S.; Peach, D. W.

2005-01-01

Groundwater investigation has long depended on the process of developing a conceptual flow model as a precursor to developing a mathematical model, which in turn may lead in complex aquifers to the development of a numerical approximation model. The assumptions made in the development of the conceptual model depend heavily on the geological framework defining the aquifer, and if the conceptual model is inappropriate then subsequent modelling will also be incorrect. Paradoxically, the development of a robust conceptual model remains difficult, not least because this 3D paradigm is usually reduced to 2D plans and sections. 3D visualisation software is now available to facilitate the development of the conceptual model, to make the model more robust and defensible and to assist in demonstrating the hydraulics of the aquifer system. Case studies are presented to demonstrate the role and cost-effectiveness of the visualisation process.
Fundamentals and techniques of nonimaging optics for solar energy concentration

NASA Astrophysics Data System (ADS)

Winston, R.; Gallagher, J. J.

1980-05-01

The properties of a variety of new and previously known nonimaging optical configurations were investigated. A thermodynamic model which explains quantitatively the enhancement of effective absorptance of gray body receivers through cavity effects was developed. The classic method of Liu and Jordan, which allows one to predict the diffuse sunlight levels through correlation with the total and direct fraction was revised and updated and applied to predict the performance of nonimaging solar collectors. The conceptual design for an optimized solar collector which integrates the techniques of nonimaging concentration with evacuated tube collector technology was carried out and is presently the basis for a separately funded hardware development project.
A-DROP: A predictive model for the formation of oil particle aggregates (OPAs)

USGS Publications Warehouse

Zhao, Lin; Boufadel, Michel C.; Geng, Xiaolong; Lee, Kenneth; King, Thomas; Robinson, Brian; Fitzpatrick, Faith A.

2016-01-01

Oil–particle interactions play a major role in removal of free oil from the water column. We present a new conceptual–numerical model, A-DROP, to predict oil amount trapped in oil–particle aggregates. A new conceptual formulation of oil–particle coagulation efficiency is introduced to account for the effects of oil stabilization by particles, particle hydrophobicity, and oil–particle size ratio on OPA formation. A-DROP was able to closely reproduce the oil trapping efficiency reported in experimental studies. The model was then used to simulate the OPA formation in a typical nearshore environment. Modeling results indicate that the increase of particle concentration in the swash zone would speed up the oil–particle interaction process; but the oil amount trapped in OPAs did not correspond to the increase of particle concentration. The developed A-DROP model could become an important tool in understanding the natural removal of oil and developing oil spill countermeasures by means of oil–particle aggregation.
A model of burnout and life satisfaction amongst nurses.

PubMed

Demerouti, E; Bakker, A B; Nachreiner, F; Schaufeli, W B

2000-08-01

This study, among 109 German nurses, tested a theoretically derived model of burnout and overall life satisfaction. The model discriminates between two conceptually different categories of working conditions, namely job demands and job resources. It was hypothesized that: (1) job demands, such as demanding contacts with patients and time pressure, are most predictive of exhaustion; (2) job resources, such as (poor) rewards and (lack of) participation in decision making, are most predictive of disengagement from work; and (3) job demands and job resources have an indirect impact on nurses' life satisfaction, through the experience of burnout (i.e., exhaustion and disengagement). A model including each of these relationships was tested simultaneously with structural equations modelling. Results confirm the strong effects of job demands and job resources on exhaustion and disengagement respectively, and the mediating role of burnout between the working conditions and life satisfaction. These findings contribute to existing knowledge about antecedents and consequences of occupational burnout, and provide guidelines for interventions aimed at preventing or reducing burnout among nurses.
Implications of Simulation Conceptual Model Development for Simulation Management and Uncertainty Assessment

NASA Technical Reports Server (NTRS)

Pace, Dale K.

2000-01-01

A simulation conceptual model is a simulation developers way of translating modeling requirements (i. e., what is to be represented by the simulation or its modification) into a detailed design framework (i. e., how it is to be done), from which the software, hardware, networks (in the case of distributed simulation), and systems/equipment that will make up the simulation can be built or modified. A conceptual model is the collection of information which describes a simulation developers concept about the simulation and its pieces. That information consists of assumptions, algorithms, characteristics, relationships, and data. Taken together, these describe how the simulation developer understands what is to be represented by the simulation (entities, actions, tasks, processes, interactions, etc.) and how that representation will satisfy the requirements to which the simulation responds. Thus the conceptual model is the basis for judgment about simulation fidelity and validity for any condition that is not specifically tested. The more perspicuous and precise the conceptual model, the more likely it is that the simulation development will both fully satisfy requirements and allow demonstration that the requirements are satisfied (i. e., validation). Methods used in simulation conceptual model development have significant implications for simulation management and for assessment of simulation uncertainty. This paper suggests how to develop and document a simulation conceptual model so that the simulation fidelity and validity can be most effectively determined. These ideas for conceptual model development apply to all simulation varieties. The paper relates these ideas to uncertainty assessments as they relate to simulation fidelity and validity. The paper also explores implications for simulation management from conceptual model development methods, especially relative to reuse of simulation components.
Spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin

USGS Publications Warehouse

Kenney, Terry A.; Gerner, Steven J.; Buto, Susan G.; Spangler, Lawrence E.

2009-01-01

The Upper Colorado River Basin (UCRB) discharges more than 6 million tons of dissolved solids annually, about 40 to 45 percent of which are attributed to agricultural activities. The U.S. Department of the Interior estimates economic damages related to salinity in excess of $330 million annually in the Colorado River Basin. Salinity in the UCRB, as measured by dissolved-solids load and concentration, has been studied extensively during the past century. Over this period, a solid conceptual understanding of the sources and transport mechanisms of dissolved solids in the basin has been developed. This conceptual understanding was incorporated into the U.S. Geological Survey Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model to examine statistically the dissolved-solids supply and transport within the UCRB. Geologic and agricultural sources of dissolved solids in the UCRB were defined and represented in the model. On the basis of climatic and hydrologic conditions along with data availability, water year 1991 was selected for examination with SPARROW. Dissolved-solids loads for 218 monitoring sites were used to calibrate a dissolved-solids SPARROW model for the UCRB. The calibrated model generally captures the transport mechanisms that deliver dissolved solids to streams of the UCRB as evidenced by R2 and yield R2 values of 0.98 and 0.71, respectively. Model prediction error is approximated at 51 percent. Model results indicate that of the seven geologic source groups, the high-yield sedimentary Mesozoic rocks have the largest yield of dissolved solids, about 41.9 tons per square mile (tons/mi2). Irrigated sedimentary-clastic Mesozoic lands have an estimated yield of 1,180 tons/mi2, and irrigated sedimentary-clastic Tertiary lands have an estimated yield of 662 tons/mi2. Coefficients estimated for the seven landscape transport characteristics seem to agree well with the conceptual understanding of the role they play in the delivery of dissolved solids to streams in the UCRB. Predictions of dissolved-solids loads were generated for more than 10,000 stream reaches of the stream network defined in the UCRB. From these estimates, the downstream accumulation of dissolved solids, including natural and agricultural components, were examined in selected rivers. Contributions from each of the 11 dissolved-solids sources were also examined at select locations in the Grand, Green, and San Juan Divisions of the UCRB. At the downstream boundary of the UCRB, the Colorado River at Lees Ferry, Arizona, monitoring site, the dissolved-solids contribution of irrigated agricultural lands and natural sources were about 45 and 57 percent, respectively. Finally, model predictions, including the contributions of natural and agricultural sources for selected locations in the UCRB, were compared with results from two previous studies.
[Proposed model of vascular trauma by mean of mechanical characterization of endovascular prostheses (stents) based on structural analysis by FEA].

PubMed

Bustamante, John; Uribe, Pablo; Sosa, Mauricio; Valencia, Raúl

2016-01-01

The accumulated evidence on angioplasty techniques with stents has raised a controversy about the factors that influence the final vascular response. Indeed, several studies have shown there might be re-stenosis between 30% to 40% about 6 months after placement, relating to the design of the device as one of the main causes. This paper proposes the functional characterization of endovascular stents, analyzing its mechanical influence in the vascular system and predicting implicit traumatic factors in the vessel. A structural analysis was made for several computational models of endovascular stents using Finite Element Analysis in order to predict the mechanical behavior and the vascular trauma. In this way, the stents were considered as tubular devices composed of multiple links under radial pressure loads, reflecting stress concentration effects. The analysis allowed to visualize how the geometry of stents is adjusted under several load conditions, in order to obtain the response of "solid-solid" interaction between the stent and the arterial wall. Thus, an analysis was performed in order to calculate stress, and a conceptual model that explains its mechanical impact on the stent-vessel interaction, was raised, to infer on the functionality from the design of the devices. The proposed conceptual model allows to determine the relationship between the conditions of mechanical interaction of the stents, and warns about the effects in what would be the operation of the device on the vascular environment. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.
Disease phobia and disease conviction are separate dimensions underlying hypochondriasis.

PubMed

Fergus, Thomas A; Valentiner, David P

2010-12-01

The current study uses data from a large nonclinical college student sample (N = 503) to examine a structural model of hypochondriasis (HC). This model predicts the distinctiveness of two dimensions (disease phobia and disease conviction) purported to underlie the disorder, and that these two dimensions are differentially related to variables important to health anxiety and somatoform disorders, respectively. Results were generally consistent with the hypothesized model. Specifically, (a) body perception variables (somatosensory amplification and anxiety sensitivity - physical) emerged as significant predictors of disease phobia, but not disease conviction; (b) emotion dysregulation variables (cognitive avoidance and cognitive reappraisal) emerged as significant predictors of disease conviction, but not disease phobia; and (c) both disease phobia and disease conviction independently predicted medical utilization. Further, collapsing disease phobia and disease conviction onto a single latent factor provided an inadequate fit to the data. Conceptual and therapeutic implications of these results are discussed. 2010 Elsevier Ltd. All rights reserved.

An investigation of the transdiagnostic model of eating disorders in the context of muscle dysmorphia.

PubMed

Murray, Stuart B; Rieger, Elizabeth; Karlov, Lisa; Touyz, Stephen W

2013-03-01

Muscle dysmorphia is a psychiatric disorder that has been conceptually linked to eating disorders, although its precise nosology remains unclear. To further investigate this notion, the present study examined the applicability of the transdiagnostic model of eating disorders to muscle dysmorphia. One hundred and nineteen male undergraduate students completed self-report measures of multidimensional perfectionism, mood intolerance, self-esteem, interpersonal problems, and muscle dysmorphia symptomatology. Self-oriented perfectionism, socially prescribed perfectionism, mood intolerance, and low self-esteem significantly predicted muscle dysmorphia symptomatology, whereas other-oriented perfectionism and interpersonal problems did not demonstrate significant predictive value when accounting for the other transdiagnostic constructs. The transdiagnostic model of eating disorders may potentially be applied to enhance our understanding of the maintenance of muscle dysmorphic features in addition to eating disorder symptomatology. Copyright © 2012 John Wiley & Sons, Ltd and Eating Disorders Association.
A structured interview for the assessment of the Five-Factor Model of personality: facet-level relations to the axis II personality disorders.

PubMed

Trull, T J; Widiger, T A; Burr, R

2001-04-01

The Structured Interview for the Five-Factor Model (SIFFM; Trull & Widiger, 1997) is an 120-item semistructured interview that assesses both adaptive and maladaptive features of the personality traits included in the five-factor model of personality, or "Big Five." In this article, we evaluate the ability of SIFFM scores to predict personality disorder symptomatology in a sample of 232 adults (46 outpatients and 186 nonclinical college students). Personality disorder symptoms were assessed using the Personality Diagnostic Questionnaire-Revised (PDQ-R; Hyler & Rider, 1987). Results indicated that many of the predicted associations between lower-order personality traits and personality disorders were supported. Further, many of these associations held even after controlling for comorbid personality disorder symptoms. These findings may help inform conceptualizations of the personality disorders, as well as etiological theories and treatment.
The 2 × 2 Standpoints Model of Achievement Goals

PubMed Central

Korn, Rachel M.; Elliot, Andrew J.

2016-01-01

In the present research, we proposed and tested a 2 × 2 standpoints model of achievement goals grounded in the development-demonstration and approach-avoidance distinctions. Three empirical studies are presented. Study 1 provided evidence supporting the structure and psychometric properties of a newly developed measure of the goals of the 2 × 2 standpoints model. Study 2 documented the predictive utility of these goal constructs for intrinsic motivation: development-approach and development-avoidance goals were positive predictors, and demonstration-avoidance goals were a negative predictor of intrinsic motivation. Study 3 documented the predictive utility of these goal constructs for performance attainment: Demonstration-approach goals were a positive predictor and demonstration-avoidance goals were a negative predictor of exam performance. The conceptual and empirical contributions of the present research were discussed within the broader context of existing achievement goal theory and research. PMID:27242641
Coupling sensing to crop models for closed-loop plant production in advanced life support systems

NASA Astrophysics Data System (ADS)

Cavazzoni, James; Ling, Peter P.

1999-01-01

We present a conceptual framework for coupling sensing to crop models for closed-loop analysis of plant production for NASA's program in advanced life support. Crop status may be monitored through non-destructive observations, while models may be independently applied to crop production planning and decision support. To achieve coupling, environmental variables and observations are linked to mode inputs and outputs, and monitoring results compared with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. In this paper, we demonstrate this coupling using machine vision sensing of canopy height and top projected canopy area, and the CROPGRO crop growth model. Model simulations and scenarios are used for illustration. We also compare model predictions of the machine vision variables with data from soybean experiments conducted at New Jersey Agriculture Experiment Station Horticulture Greenhouse Facility, Rutgers University. Model simulations produce reasonable agreement with the available data, supporting our illustration.
Observational attachment theory-based parenting measures predict children's attachment narratives independently from social learning theory-based measures.

PubMed

Matias, Carla; O'Connor, Thomas G; Futh, Annabel; Scott, Stephen

2014-01-01

Conceptually and methodologically distinct models exist for assessing quality of parent-child relationships, but few studies contrast competing models or assess their overlap in predicting developmental outcomes. Using observational methodology, the current study examined the distinctiveness of attachment theory-based and social learning theory-based measures of parenting in predicting two key measures of child adjustment: security of attachment narratives and social acceptance in peer nominations. A total of 113 5-6-year-old children from ethnically diverse families participated. Parent-child relationships were rated using standard paradigms. Measures derived from attachment theory included sensitive responding and mutuality; measures derived from social learning theory included positive attending, directives, and criticism. Child outcomes were independently-rated attachment narrative representations and peer nominations. Results indicated that Attachment theory-based and Social Learning theory-based measures were modestly correlated; nonetheless, parent-child mutuality predicted secure child attachment narratives independently of social learning theory-based measures; in contrast, criticism predicted peer-nominated fighting independently of attachment theory-based measures. In young children, there is some evidence that attachment theory-based measures may be particularly predictive of attachment narratives; however, no single model of measuring parent-child relationships is likely to best predict multiple developmental outcomes. Assessment in research and applied settings may benefit from integration of different theoretical and methodological paradigms.
Learning the facts in medical school is not enough: which factors predict successful application of procedural knowledge in a laboratory setting?

PubMed

Schmidmaier, Ralf; Eiber, Stephan; Ebersbach, Rene; Schiller, Miriam; Hege, Inga; Holzer, Matthias; Fischer, Martin R

2013-02-22

Medical knowledge encompasses both conceptual (facts or "what" information) and procedural knowledge ("how" and "why" information). Conceptual knowledge is known to be an essential prerequisite for clinical problem solving. Primarily, medical students learn from textbooks and often struggle with the process of applying their conceptual knowledge to clinical problems. Recent studies address the question of how to foster the acquisition of procedural knowledge and its application in medical education. However, little is known about the factors which predict performance in procedural knowledge tasks. Which additional factors of the learner predict performance in procedural knowledge? Domain specific conceptual knowledge (facts) in clinical nephrology was provided to 80 medical students (3rd to 5th year) using electronic flashcards in a laboratory setting. Learner characteristics were obtained by questionnaires. Procedural knowledge in clinical nephrology was assessed by key feature problems (KFP) and problem solving tasks (PST) reflecting strategic and conditional knowledge, respectively. Results in procedural knowledge tests (KFP and PST) correlated significantly with each other. In univariate analysis, performance in procedural knowledge (sum of KFP+PST) was significantly correlated with the results in (1) the conceptual knowledge test (CKT), (2) the intended future career as hospital based doctor, (3) the duration of clinical clerkships, and (4) the results in the written German National Medical Examination Part I on preclinical subjects (NME-I). After multiple regression analysis only clinical clerkship experience and NME-I performance remained independent influencing factors. Performance in procedural knowledge tests seems independent from the degree of domain specific conceptual knowledge above a certain level. Procedural knowledge may be fostered by clinical experience. More attention should be paid to the interplay of individual clinical clerkship experiences and structured teaching of procedural knowledge and its assessment in medical education curricula.
The Cancer Family Caregiving Experience: An Updated and Expanded Conceptual Model

PubMed Central

Fletcher, Barbara Swore; Miaskowski, Christine; Given, Barbara; Schumacher, Karen

2011-01-01

Objective The decade from 2000–2010 was an era of tremendous growth in family caregiving research specific to the cancer population. This research has implications for how cancer family caregiving is conceptualized, yet the most recent comprehensive model of cancer family caregiving was published ten years ago. Our objective was to develop an updated and expanded comprehensive model of the cancer family caregiving experience, derived from concepts and variables used in research during past ten years. Methods A conceptual model was developed based on cancer family caregiving research published from 2000–2010. Results Our updated and expanded model has three main elements: 1) the stress process, 2) contextual factors, and 3) the cancer trajectory. Emerging ways of conceptualizing the relationships between and within model elements are addressed, as well as an emerging focus on caregiver-patient dyads as the unit of analysis. Conclusions Cancer family caregiving research has grown dramatically since 2000 resulting in a greatly expanded conceptual landscape. This updated and expanded model of the cancer family caregiving experience synthesizes the conceptual implications of an international body of work and demonstrates tremendous progress in how cancer family caregiving research is conceptualized. PMID:22000812
Bidirectional associations between bedtime parenting and infant sleep: Parenting quality, parenting practices, and their interaction.

PubMed

Philbrook, Lauren E; Teti, Douglas M

2016-06-01

In keeping with transactional conceptualizations of infant sleep development (Sadeh, Tikotzky, & Scher, 2010), the present study was an examination of longitudinal, bidirectional linkages between bedtime parenting (through direct observations of parenting practices and quality) and infant sleep across the first 6 months postpartum. In doing so, we also drew from Darling and Steinberg's (1993) conceptual model to examine parenting quality as a moderator of linkages between specific bedtime practices and infant sleep. Multilevel model analyses revealed that the strongest increases in infant nighttime sleep across the first 6 months occurred among infants of mothers who engaged in low levels of nursing at bedtime. Within-person linkages between mothers' emotional availability (EA) at bedtime, infant distress, and infant sleep were found, such that at time points when mothers were more emotionally available, infants were less distressed and slept more throughout the night. Several moderating effects of maternal EA on linkages between parenting practices and infant sleep were obtained that were consistent with predictions from Darling and Steinberg (1993). Higher maternal EA in combination with less close contact at bedtime was associated with more infant sleep across the night on average, and higher EA in combination with fewer arousing bedtime activities predicted more rapid increases in infant sleep with age. Finally, there was evidence of infant-driven effects, as higher infant nighttime distress predicted lower EA at subsequent time points. Results showcased the complex, reciprocal interplay between parents and infants in the development of infant sleep patterns and parenting behavior during the first 6 months postpartum. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Bidirectional Associations between Bedtime Parenting and Infant Sleep: Parenting Quality, Parenting Practices, and their Interaction

PubMed Central

Philbrook, Lauren E.; Teti, Douglas M.

2016-01-01

In keeping with transactional conceptualizations of infant sleep development (Sadeh et al., 2010), the present study examined longitudinal, bidirectional linkages between bedtime parenting (direct observations of parenting practices and quality) and infant sleep across the first six months postpartum. In doing so, we also drew from Darling and Steinberg's (1993) conceptual model to examine parenting quality as a moderator of linkages between specific bedtime practices and infant sleep. Multilevel model analyses revealed that the strongest increases in infant nighttime sleep across the first six months occurred among infants of mothers who engaged in low levels of nursing at bedtime. Within-person linkages between mothers' emotional availability (EA) at bedtime, infant distress, and infant sleep were found, such that at time points when mothers were more emotionally available, infants were less distressed and slept more throughout the night. Several moderating effects of maternal EA on linkages between parenting practices and infant sleep were obtained that were consistent with predictions from Darling and Steinberg (1993). Higher maternal EA in combination with less close contact at bedtime was associated with more infant sleep across the night on average, and higher EA in combination with fewer arousing bedtime activities predicted more rapid increases in infant sleep with age. Finally, there was evidence of infant-driven effects, as higher infant nighttime distress predicted lower EA at subsequent time points. Results showcased the complex, reciprocal interplay between parents and infants in the development of infant sleep patterns and parenting behavior during the first six months postpartum. PMID:27010601
Examining the Effects of Model-Based Inquiry on Concepetual Understanding and Engagement in Science

NASA Astrophysics Data System (ADS)

Baze, Christina L.

Model-Based Inquiry (MBI) is an instructional model which engages students in the scientific practices of modeling, explanation, and argumentation while they work to construct explanations for natural phenomena. This instructional model has not been previously studied at the community college level. The purpose of this study is to better understand how MBI affects the development of community college students' conceptual understanding of evolution and engagement in the practices of science. Mixed-methods were employed to collect quantitative and qualitative data through the multiple-choice Concepts Inventory of Natural Selection, student artifacts, and semi-structured interviews. Participants were enrolled in Biology Concepts, an introductory class for non-science majors, at a small, rural community college in the southwestern United States. Preliminary data shows that conceptual understanding is not adversely affected by the implementation of MBI, and that students gain valuable insights into the practices of science. Specifically, students who participated in the MBI intervention group gained a better understanding of the role of models in explaining and predicting phenomena and experienced feeling ownership of their ideas, an appropriate depth of thinking, more opportunities for collaboration, and coherence and context within the unit. Implications of this study will be of interest to postsecondary science educators and researchers who seek to reform and improve science education.
Ethnic differences in predictors of hearing protection behavior between Black and White workers.

PubMed

Hong, OiSaeng; Lusk, Sally L; Ronis, David L

2005-01-01

The purpose of the study is to determine whether there are ethnic differences in predictors of hearing protection behavior between Black and White workers. The Predictors of Use of Hearing Protection Model (PUHPM) derived from Pender's Health Promotion Model (Pender, 1987) was used as a conceptual model. A total of 2,119 (297 Blacks, 1,822 Whites) were included in the analysis. Internal consistency of instrument items was assessed using theta reliability estimates. Significant predictors of the use of hearing protective devices (HPDs) for Black and White workers and differences in predictors between the two groups were examined using multiple regression with interaction terms. Ethnic differences in scale or individual item scores were assessed using chi-square and t-test analyses. Different factors influenced hearing protection behavior among Black and White workers. The model was much less predictive of Blacks' hearing protection behavior than Whites' (R2 = .12 vs. .36). Since the PUHPM was not as effective in predicting hearing protection behavior for Blacks as for Whites, future studies are needed to expand the PUHPM through qualitative study and to develop culturally appropriate models to identify factors that better predict hearing protection behavior as a basis for developing effective interventions.
Alcohol expectancy multiaxial assessment: a memory network-based approach.

PubMed

Goldman, Mark S; Darkes, Jack

2004-03-01

Despite several decades of activity, alcohol expectancy research has yet to merge measurement approaches with developing memory theory. This article offers an expectancy assessment approach built on a conceptualization of expectancy as an information processing network. The authors began with multidimensional scaling models of expectancy space, which served as heuristics to suggest confirmatory factor analytic dimensional models for entry into covariance structure predictive models. It is argued that this approach permits a relatively thorough assessment of the broad range of potential expectancy dimensions in a format that is very flexible in terms of instrument length and specificity versus breadth of focus. ((c) 2004 APA, all rights reserved)
On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

PubMed

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.
Perceptual processing affects conceptual processing.

PubMed

Van Dantzig, Saskia; Pecher, Diane; Zeelenberg, René; Barsalou, Lawrence W

2008-04-05

According to the Perceptual Symbols Theory of cognition (Barsalou, 1999), modality-specific simulations underlie the representation of concepts. A strong prediction of this view is that perceptual processing affects conceptual processing. In this study, participants performed a perceptual detection task and a conceptual property-verification task in alternation. Responses on the property-verification task were slower for those trials that were preceded by a perceptual trial in a different modality than for those that were preceded by a perceptual trial in the same modality. This finding of a modality-switch effect across perceptual processing and conceptual processing supports the hypothesis that perceptual and conceptual representations are partially based on the same systems. 2008 Cognitive Science Society, Inc.
Why College Students Cheat: A Conceptual Model of Five Factors

ERIC Educational Resources Information Center

Yu, Hongwei; Glanzer, Perry L.; Johnson, Byron R.; Sriram, Rishi; Moore, Brandon

2018-01-01

Though numerous studies have identified factors associated with academic misconduct, few have proposed conceptual models that could make sense of multiple factors. In this study, we used structural equation modeling (SEM) to test a conceptual model of five factors using data from a relatively large sample of 2,503 college students. The results…
Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

NASA Astrophysics Data System (ADS)

Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

2006-03-01

The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.
Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.
A multidisciplinary-based conceptual model of a fractured sedimentary bedrock aquitard: improved prediction of aquitard integrity

NASA Astrophysics Data System (ADS)

Runkel, Anthony C.; Tipping, Robert G.; Meyer, Jessica R.; Steenberg, Julia R.; Retzler, Andrew J.; Parker, Beth L.; Green, Jeff A.; Barry, John D.; Jones, Perry M.

2018-06-01

A hydrogeologic conceptual model that improves understanding of variability in aquitard integrity is presented for a fractured sedimentary bedrock unit in the Cambrian-Ordovician aquifer system of midcontinent North America. The model is derived from multiple studies on the siliciclastic St. Lawrence Formation and adjacent strata across a range of scales and geologic conditions. These studies employed multidisciplinary techniques including borehole flowmeter logging, high-resolution depth-discrete multilevel well monitoring, fracture stratigraphy, fluorescent dye tracing, and three-dimensional (3D) distribution of anthropogenic tracers regionally. The paper documents a bulk aquitard that is highly anisotropic because of poor connectivity of vertical fractures across matrix with low permeability, but with ubiquitous bed parallel partings. The partings provide high bulk horizontal hydraulic conductivity, analogous to aquifers in the system, while multiple preferential termination horizons of vertical fractures serve as discrete low vertical hydraulic conductivity intervals inhibiting vertical flow. The aquitard has substantial variability in its ability to protect underlying groundwater from contamination. Across widespread areas where the aquitard is deeply buried by younger bedrock, preferential termination horizons provide for high aquitard integrity (i.e. protection). Protection is diminished close to incised valleys where stress release and weathering has enhanced secondary pore development, including better connection of fractures across these horizons. These conditions, along with higher hydraulic head gradients in the same areas and more complex 3D flow where the aquitard is variably incised, allow for more substantial transport to deeper aquifers. The conceptual model likely applies to other fractured sedimentary bedrock aquitards within and outside of this region.
Towards scaling interannual ecohydrological responses of conifer forests to bark beetle infestations from individuals to landscapes

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Ewers, B. E.; Peckham, S. D.; Savoy, P.; Reed, D. E.; Frank, J. M.

2013-12-01

Widespread epidemics of forest-damaging insects have severe implications for the interconnections between water and ecosystem processes under present-day climate. How these systems respond to future climates is highly uncertain, and so there is a need for a better understanding of the effects of such disturbances on plant hydraulics, and the consequent effects on ecosystem processes. Moreover, large-scale manifestations of such disturbances require scaling knowledge obtained from individual trees or stands up to a regional extent. This requires a conceptual framework that integrates physical and biological processes that are immutable and scalable. Indeed, in Western North America multiple conifer species have been impacted by the bark beetle epidemic, but the prediction of such widespread outbreaks under changing environmental conditions must be generalized from a relatively small number of ground-based observations. Using model-data fusion we examine the fundamental principles that drive ecological and hydrological responses to bark beetles infestation from individuals to regions. The study includes a mid-elevation (2750 m a.s.l) lodgepole pine forest and higher (3190 m a.s.l.) elevation Engelmann spruce - fir forest in southern Wyoming. The study included a suite of observations, comprising leaf gas exchange, non-structural carbon (NSC), plant hydraulics, including sap flux transpiration (E), vulnerability to cavitation, leaf water potentials, and eddy covariance, were made pre-, during-, and post-disturbance, as the bark beetle infestation moved through these areas. Numerous observations tested hypotheses generated by the Terrestrial Regional Ecosystem Exchange Simulator (TREES), which integrates soil hydraulics and dynamic tree hydraulics (cavitation) with canopy energy and gas exchange, and operates at scales from individuals to landscapes. TREES accurately predicted E and NSC dynamics among individuals spanning pre- and post-disturbance periods, with the 95% prediction bounds of the model capturing 95% of observations. Based on support from our model-data fusion we advance a conceptual framework, grounded on the idea of plant hydraulic traits shifting from equilibrium to non-equilibrium states between soil and vegetation, with some traits that forms a key interconnection between water and ecosystem responses to bark beetle disturbance shifting back to equilibrium within five years. Implications of future climate conditions are then examined using our conceptual framework, by exploring the water and carbon responses to insect outbreaks with and without co-occurring drought and heat stress.
A conceptual modeling framework for discrete event simulation using hierarchical control structures.

PubMed

Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

2015-08-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

Conceptualizing Telehealth in Nursing Practice: Advancing a Conceptual Model to Fill a Virtual Gap.

PubMed

Nagel, Daniel A; Penner, Jamie L

2016-03-01

Increasingly nurses use various telehealth technologies to deliver health care services; however, there has been a lag in research and generation of empirical knowledge to support nursing practice in this expanding field. One challenge to generating knowledge is a gap in development of a comprehensive conceptual model or theoretical framework to illustrate relationships of concepts and phenomena inherent to adoption of a broad range of telehealth technologies to holistic nursing practice. A review of the literature revealed eight published conceptual models, theoretical frameworks, or similar entities applicable to nursing practice. Many of these models focus exclusively on use of telephones and four were generated from qualitative studies, but none comprehensively reflect complexities of bridging nursing process and elements of nursing practice into use of telehealth. The purpose of this article is to present a review of existing conceptual models and frameworks, discuss predominant themes and features of these models, and present a comprehensive conceptual model for telehealth nursing practice synthesized from this literature for consideration and further development. This conceptual model illustrates characteristics of, and relationships between, dimensions of telehealth practice to guide research and knowledge development in provision of holistic person-centered care delivery to individuals by nurses through telehealth technologies. © The Author(s) 2015.
Preface to RIGiM 2009

NASA Astrophysics Data System (ADS)

Rolland, Colette; Yu, Eric; Salinesi, Camille; Castro, Jaelson

The use of intentional concepts, the notion of "goal" in particular, has been prominent in recent approaches to requirement engineering (RE). Goal-oriented frameworks and methods for requirements engineering (GORE) have been keynote topics in requirements engineering, conceptual modelling, and more generally in software engineering. What are the conceptual modelling foundations in these approaches? RIGiM (Requirements Intentions and Goals in Conceptual Modelling) aims to provide a forum for discussing the interplay between requirements engineering and conceptual modelling, and in particular, to investigate how goal- and intention-driven approaches help in conceptualising purposeful systems. What are the fundamental objectives and premises of requirements engineering and conceptual modelling respectively, and how can they complement each other? What are the demands on conceptual modelling from the standpoint of requirements engineering? What conceptual modelling techniques can be further taken advantage of in requirements engineering? What are the upcoming modelling challenges and issues in GORE? What are the unresolved open questions? What lessons are there to be learnt from industrial experiences? What empirical data are there to support the cost-benefit analysis when adopting GORE methods? Are there application domains or types of project settings for which goals and intentional approaches are particularly suitable or not suitable? What degree of formalization and automation, or interactivity is feasible and appropriate for what types of participants during requirements engineering?
Profiles of inconsistent knowledge in children's pathways of conceptual change.

PubMed

Schneider, Michael; Hardy, Ilonca

2013-09-01

Conceptual change requires learners to restructure parts of their conceptual knowledge base. Prior research has identified the fragmentation and the integration of knowledge as 2 important component processes of knowledge restructuring but remains unclear as to their relative importance and the time of their occurrence during development. Previous studies mostly were based on the categorization of answers in interview studies and led to mixed empirical results, suggesting that methodological improvements might be helpful. We assessed 161 third-graders' knowledge about floating and sinking of objects in liquids at 3 measurement points by means of multiple-choice tests. The tests assessed how strongly the children agreed with commonly found but mutually incompatible statements about floating and sinking. A latent profile transition analysis of the test scores revealed 5 profiles, some of which indicated the coexistence of inconsistent pieces of knowledge in learners. The majority of students (63%) were on 1 of 7 developmental pathways between these profiles. Thus, a child's knowledge profile at a point in time can be used to predict further development. The degree of knowledge integration decreased on some individual developmental paths, increased on others, and remained stable on still others. The study demonstrates the usefulness of explicit quantitative models of conceptual change. The results support a constructivist perspective on conceptual development, in which developmental changes of a learner's knowledge base result from idiosyncratic, yet systematic knowledge-construction processes. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Modelling guidelines--terminology and guiding principles

NASA Astrophysics Data System (ADS)

Refsgaard, Jens Christian; Henriksen, Hans Jørgen

2004-01-01

Some scientists argue, with reference to Popper's scientific philosophical school, that models cannot be verified or validated. Other scientists and many practitioners nevertheless use these terms, but with very different meanings. As a result of an increasing number of examples of model malpractice and mistrust to the credibility of models, several modelling guidelines are being elaborated in recent years with the aim of improving the quality of modelling studies. This gap between the views and the lack of consensus experienced in the scientific community and the strongly perceived need for commonly agreed modelling guidelines is constraining the optimal use and benefits of models. This paper proposes a framework for quality assurance guidelines, including a consistent terminology and a foundation for a methodology bridging the gap between scientific philosophy and pragmatic modelling. A distinction is made between the conceptual model, the model code and the site-specific model. A conceptual model is subject to confirmation or falsification like scientific theories. A model code may be verified within given ranges of applicability and ranges of accuracy, but it can never be universally verified. Similarly, a model may be validated, but only with reference to site-specific applications and to pre-specified performance (accuracy) criteria. Thus, a model's validity will always be limited in terms of space, time, boundary conditions and types of application. This implies a continuous interaction between manager and modeller in order to establish suitable accuracy criteria and predictions associated with uncertainty analysis.
The relevance of the philosophical 'mind-body problem' for the status of psychosomatic medicine: a conceptual analysis of the biopsychosocial model.

PubMed

Van Oudenhove, Lukas; Cuypers, Stefaan

2014-05-01

Psychosomatic medicine, with its prevailing biopsychosocial model, aims to integrate human and exact sciences with their divergent conceptual models. Therefore, its own conceptual foundations, which often remain implicit and unknown, may be critically relevant. We defend the thesis that choosing between different metaphysical views on the 'mind-body problem' may have important implications for the conceptual foundations of psychosomatic medicine, and therefore potentially also for its methods, scientific status and relationship with the scientific disciplines it aims to integrate: biomedical sciences (including neuroscience), psychology and social sciences. To make this point, we introduce three key positions in the philosophical 'mind-body' debate (emergentism, reductionism, and supervenience physicalism) and investigate their consequences for the conceptual basis of the biopsychosocial model in general and its 'psycho-biological' part ('mental causation') in particular. Despite the clinical merits of the biopsychosocial model, we submit that it is conceptually underdeveloped or even flawed, which may hamper its use as a proper scientific model.
Conceptual overlap between moral norms and anticipated regret in the prediction of intention: implications for theory of planned behaviour research.

PubMed

Newton, Joshua D; Newton, Fiona J; Ewing, Michael T; Burney, Sue; Hay, Margaret

2013-01-01

Moral norms and anticipated regret are widely used extensions to the theory of planned behaviour, yet there is some evidence to suggest that these constructs may conceptually overlap as predictors of intention. Two health-related behaviours with distinct moral implications (Study 1: organ donation registration, N = 352 and Study 2: condom usage, N = 1815) were therefore examined to ascertain whether moral norms and anticipated regret are indeed conceptually distinct. While evidence consistent with conceptual overlap was identified in Study 1, the evidence for such overlap in Study 2 was more ambiguous. In Study 3, a meta-analysis of existing literature revealed that the relationship between moral norms and anticipated regret was moderated by the extent of the moral implications arising from the behaviour under examination. Taken together, these findings suggest that conceptual overlap between moral norms and anticipated regret is more likely to occur among behaviours with obvious moral implications. Researchers wishing to examine the predictive utility of moral norms and anticipated regret among such behaviours would therefore be advised to aggregate these measures to form a composite variable (personal norms).
A mobile-mobile transport model for simulating reactive transport in connected heterogeneous fields

NASA Astrophysics Data System (ADS)

Lu, Chunhui; Wang, Zhiyuan; Zhao, Yue; Rathore, Saubhagya Singh; Huo, Jinge; Tang, Yuening; Liu, Ming; Gong, Rulan; Cirpka, Olaf A.; Luo, Jian

2018-05-01

Mobile-immobile transport models can be effective in reproducing heavily tailed breakthrough curves of concentration. However, such models may not adequately describe transport along multiple flow paths with intermediate velocity contrasts in connected fields. We propose using the mobile-mobile model for simulating subsurface flow and associated mixing-controlled reactive transport in connected fields. This model includes two local concentrations, one in the fast- and the other in the slow-flow domain, which predict both the concentration mean and variance. The normalized total concentration variance within the flux is found to be a non-monotonic function of the discharge ratio with a maximum concentration variance at intermediate values of the discharge ratio. We test the mobile-mobile model for mixing-controlled reactive transport with an instantaneous, irreversible bimolecular reaction in structured and connected random heterogeneous domains, and compare the performance of the mobile-mobile to the mobile-immobile model. The results indicate that the mobile-mobile model generally predicts the concentration breakthrough curves (BTCs) of the reactive compound better. Particularly, for cases of an elliptical inclusion with intermediate hydraulic-conductivity contrasts, where the travel-time distribution shows bimodal behavior, the prediction of both the BTCs and maximum product concentration is significantly improved. Our results exemplify that the conceptual model of two mobile domains with diffusive mass transfer in between is in general good for predicting mixing-controlled reactive transport, and particularly so in cases where the transfer in the low-conductivity zones is by slow advection rather than diffusion.
Development of a semi-automated model identification and calibration tool for conceptual modelling of sewer systems.

PubMed

Wolfs, Vincent; Villazon, Mauricio Florencio; Willems, Patrick

2013-01-01

Applications such as real-time control, uncertainty analysis and optimization require an extensive number of model iterations. Full hydrodynamic sewer models are not sufficient for these applications due to the excessive computation time. Simplifications are consequently required. A lumped conceptual modelling approach results in a much faster calculation. The process of identifying and calibrating the conceptual model structure could, however, be time-consuming. Moreover, many conceptual models lack accuracy, or do not account for backwater effects. To overcome these problems, a modelling methodology was developed which is suited for semi-automatic calibration. The methodology is tested for the sewer system of the city of Geel in the Grote Nete river basin in Belgium, using both synthetic design storm events and long time series of rainfall input. A MATLAB/Simulink(®) tool was developed to guide the modeller through the step-wise model construction, reducing significantly the time required for the conceptual modelling process.
Prediction/discussion-based learning cycle versus conceptual change text: comparative effects on students' understanding of genetics

NASA Astrophysics Data System (ADS)

khawaldeh, Salem A. Al

2013-07-01

Background and purpose: The purpose of this study was to investigate the comparative effects of a prediction/discussion-based learning cycle (HPD-LC), conceptual change text (CCT) and traditional instruction on 10th grade students' understanding of genetics concepts. Sample: Participants were 112 10th basic grade male students in three classes of the same school located in an urban area. The three classes taught by the same biology teacher were randomly assigned as a prediction/discussion-based learning cycle class (n = 39), conceptual change text class (n = 37) and traditional class (n = 36). Design and method: A quasi-experimental research design of pre-test-post-test non-equivalent control group was adopted. Participants completed the Genetics Concept Test as pre-test-post-test, to examine the effects of instructional strategies on their genetics understanding. Pre-test scores and Test of Logical Thinking scores were used as covariates. Results: The analysis of covariance showed a statistically significant difference between the experimental and control groups in the favor of experimental groups after treatment. However, no statistically significant difference between the experimental groups (HPD-LC versus CCT instruction) was found. Conclusions: Overall, the findings of this study support the use of the prediction/discussion-based learning cycle and conceptual change text in both research and teaching. The findings may be useful for improving classroom practices in teaching science concepts and for the development of suitable materials promoting students' understanding of science.
Conceptual Models and Guidelines for Clinical Assessment of Financial Capacity

PubMed Central

Marson, Daniel

2016-01-01

The ability to manage financial affairs is a life skill of critical importance, and neuropsychologists are increasingly asked to assess financial capacity across a variety of settings. Sound clinical assessment of financial capacity requires knowledge and appreciation of applicable clinical conceptual models and principles. However, the literature has presented relatively little conceptual guidance for clinicians concerning financial capacity and its assessment. This article seeks to address this gap. The article presents six clinical models of financial capacity : (1) the early gerontological IADL model of Lawton, (2) the clinical skills model and (3) related cognitive psychological model developed by Marson and colleagues, (4) a financial decision-making model adapting earlier decisional capacity work of Appelbaum and Grisso, (5) a person-centered model of financial decision-making developed by Lichtenberg and colleagues, and (6) a recent model of financial capacity in the real world developed through the Institute of Medicine. Accompanying presentation of the models is discussion of conceptual and practical perspectives they represent for clinician assessment. Based on the models, the article concludes by presenting a series of conceptually oriented guidelines for clinical assessment of financial capacity. In summary, sound assessment of financial capacity requires knowledge and appreciation of clinical conceptual models and principles. Awareness of such models, principles and guidelines will strengthen and advance clinical assessment of financial capacity. PMID:27506235
Beyond Warmth and Conflict: The Developmental Utility of a Boundary Conceptualization of Sibling Relationship Processes

PubMed Central

Bascoe, Sonnette M.; Davies, Patrick T.; Cummings, E. Mark

2012-01-01

Translating relationship boundaries conceptualizations to the study of sibling relationships, this study examined the utility of sibling enmeshment and disengagement in predicting child adjustment difficulties in a sample of 282 mothers and adolescents (Mean age = 12.7 years). Mothers completed a semi-structured interview at the first measurement occasion to assess sibling interaction patterns. Adolescents, mothers, and teachers reported on children’s adjustment problems across two annual waves of assessment. Supporting the incremental utility of a boundary conceptualization of sibling relationships, results of latent difference score analyses indicated that coder ratings of sibling enmeshment and disengagement uniquely predicted greater adolescent adjustment difficulties even after taking into account standard indices of sibling relationship quality (i.e., warmth, conflict) and sibling structural characteristics (e.g., sex). PMID:22862542
CONCEPTUAL MODELS AND METHODS TO GUIDE DIAGNOSTIC RESEARCH INTO CAUSES OF IMPAIRMENT TO AQUATIC ECOSYSTEMS

EPA Science Inventory

Methods and conceptual models to guide the development of tools for diagnosing the causes of biological impairment within aquatic ecosystems of the United States are described in this report. The conceptual models developed here address nutrients, suspended and bedded sediments (...
Feasibility of Using Neural Network Models to Accelerate the Testing of Mechanical Systems

NASA Technical Reports Server (NTRS)

Fusaro, Robert L.

1998-01-01

Verification testing is an important aspect of the design process for mechanical mechanisms, and full-scale, full-length life testing is typically used to qualify any new component for use in space. However, as the required life specification is increased, full-length life tests become more costly and lengthen the development time. At the NASA Lewis Research Center, we theorized that neural network systems may be able to model the operation of a mechanical device. If so, the resulting neural network models could simulate long-term mechanical testing with data from a short-term test. This combination of computer modeling and short-term mechanical testing could then be used to verify the reliability of mechanical systems, thereby eliminating the costs associated with long-term testing. Neural network models could also enable designers to predict the performance of mechanisms at the conceptual design stage by entering the critical parameters as input and running the model to predict performance. The purpose of this study was to assess the potential of using neural networks to predict the performance and life of mechanical systems. To do this, we generated a neural network system to model wear obtained from three accelerated testing devices: 1) A pin-on-disk tribometer; 2) A line-contact rub-shoe tribometer; 3) A four-ball tribometer.
Reconceptualization of the Authoritarian Parenting Style and Parental Control: Some Initial Items.

ERIC Educational Resources Information Center

Chao, Ruth K.

This study compared standard conceptualizations for parenting style, parental involvement in school, and parents' socialization goals with alternative conceptualizations, in relation to children's academic achievement. Specifically, the study asked: (1) whether ethnicity is predictive of achievement scores when included in analyses involving the…
New Conceptual Model for Soil Treatment Units: Formation of Multiple Hydraulic Zones during Unsaturated Wastewater Infiltration.

PubMed

Geza, Mengistu; Lowe, Kathryn S; Huntzinger, Deborah N; McCray, John E

2013-07-01

Onsite wastewater treatment systems are commonly used in the United States to reclaim domestic wastewater. A distinct biomat forms at the infiltrative surface, causing resistance to flow and decreasing soil moisture below the biomat. To simulate these conditions, previous modeling studies have used a two-layer approach: a thin biomat layer (1-5 cm thick) and the native soil layer below the biomat. However, the effect of wastewater application extends below the biomat layer. We used numerical modeling supported by experimental data to justify a new conceptual model that includes an intermediate zone (IZ) below the biomat. The conceptual model was set up using Hydrus 2D and calibrated against soil moisture and water flux measurements. The estimated hydraulic conductivity value for the IZ was between biomat and the native soil. The IZ has important implications for wastewater treatment. When the IZ was not considered, a loading rate of 5 cm d resulted in an 8.5-cm ponding. With the IZ, the same loading rate resulted in a 9.5-cm ponding. Without the IZ, up to 3.1 cm d of wastewater could be applied without ponding; with the IZ, only up to 2.8 cm d could be applied without ponding. The IZ also plays a significant role in soil moisture distribution. Without the IZ, near-saturation conditions were observed only within the biomat, whereas near-saturation conditions extended below the biomat with the IZ. Accurate prediction of ponding is important to prevent surfacing of wastewater. The degree of water and air saturation influences pollutant treatment efficiency through residence time, volatility, and biochemical reactions. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
A new technology for determining transport parameters in porous media

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

Conca, J.L.; Wright, J.

The UFA Method can directly and rapidly measure transport parameters for any porous medium over a wide range of water contents and conditions. UFA results for subsurface sediments at a mixed-waste disposal site at the Hanford Site in Washington State provided the data necessary for detailed hydrostratigraphic mapping, subsurface flux and recharge distributions, and subsurface chemical mapping. Seven hundred unsaturated conductivity measurements along with pristine pore water extractions were obtained in only six months using the UFA. These data are used to provide realistic information to conceptual models, predictive models and restoration strategies.
The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization

PubMed Central

van der Steen, M. C. (Marieke); Keller, Peter E.

2013-01-01

A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)—the temporal coordination of an action with events in a predictable external rhythm—is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM. PMID:23772211
A conceptual modeling framework for discrete event simulation using hierarchical control structures

PubMed Central

Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

2015-01-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940
Can the Neuman Systems Model be adapted to the Malaysian nursing context?

PubMed

Shamsudin, Nafsiah

2002-04-01

Nursing in Malaysia is still developing as a profession. Issues such as using nursing conceptual models or frameworks in the delivery of nursing care have not been addressed by the majority of nurses. One reason for this has been the level of education and preparation of nurses, while another reason lies with the origins of existing nursing conceptual models. Most nursing conceptual models have their origins in North America. Their utility by nurses of different cultures and academic preparations might not be appropriate. Nursing is a social activity, an interaction between the nurse and the patient. It is carried out in a social environment within a particular culture. Conceptual models developed in one culture might not be readily implanted into another culture. This paper discusses how a conceptual model developed in North America; that is, the Neuman Systems Model, can be adapted into the Malaysian nursing context.
Experimental test of contemporary mathematical models of visual letter recognition.

PubMed

Townsend, J T; Ashby, F G

1982-12-01

A letter confusion experiment that used brief durations manipulated payoffs across the four stimulus letters, which were composed of line segments equal in length. The observers were required to report the features they perceived as well as to give a letter response. The early feature-sampling process is separated from the later letter-decision process in the substantive feature models, and predictions are thus obtained for the frequencies of feature report as well as letter report. Four substantive visual feature-processing models are developed and tested against one another and against three models of a more descriptive nature. The substantive models predict the decisional letter report phase much better than they do the feature-sampling phase, but the best overall 4 X 4 letter confusion matrix fits are obtained with one of the descriptive models, the similarity choice model. The present and other recent results suggest that the assumption that features are sampled in a stochastically independent manner may not be generally valid. The traditional high-threshold conceptualization of feature sampling is also falsified by the frequent reporting by observers of features not contained in the stimulus letter.

Conceptual Model Learning Objects and Design Recommendations for Small Screens

ERIC Educational Resources Information Center

Churchill, Daniel

2011-01-01

This article presents recommendations for the design of conceptual models for applications via handheld devices such as personal digital assistants and some mobile phones. The recommendations were developed over a number of years through experience that involves design of conceptual models, and applications of these multimedia representations with…
Semantic Description of Educational Adaptive Hypermedia Based on a Conceptual Model

ERIC Educational Resources Information Center

Papasalouros, Andreas; Retalis, Symeon; Papaspyrou, Nikolaos

2004-01-01

The role of conceptual modeling in Educational Adaptive Hypermedia Applications (EAHA) is especially important. A conceptual model of an educational application depicts the instructional solution that is implemented, containing information about concepts that must be ac-quired by learners, tasks in which learners must be involved and resources…
A Multivariate Model of Conceptual Change

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Heddy, Benjamin; Bailey, MarLynn; Farley, John

2016-01-01

The present study used the Cognitive Reconstruction of Knowledge Model (CRKM) model of conceptual change as a framework for developing and testing how key cognitive, motivational, and emotional variables are linked to conceptual change in physics. This study extends an earlier study developed by Taasoobshirazi and Sinatra ("J Res Sci…
Conceptual Model of Research to Reduce Stigma Related to Mental Disorders in Adolescents

PubMed Central

Pinto-Foltz, Melissa D.; Logsdon, M. Cynthia

2010-01-01

Purpose: To explicate an initial conceptual model that is amenable to testing and guiding anti-stigma interventions with adolescents. Design/Sources Used: Multidisciplinary research and theoretical articles were reviewed. . Conclusions: The conceptual model may guide anti-stigma interventions, and undergo testing and refinement in the future to reflect scientific advances in stigma reduction among adolescents. Use of a conceptual model enhances empirical evaluation of anti-stigma interventions yielding a casual explanation for the intervention effects and enhances clinical applicability of interventions across settings. PMID:19916813
[Self-Determination in Medical Rehabilitation - Development of a Conceptual Model for Further Theoretical Discussion].

PubMed

Senin, Tatjana; Meyer, Thorsten

2018-01-22

Aim was to gather theoretical knowledge about self-determination and to develop a conceptual model for medical rehabilitation- which serves as a basis for discussion. We performed a literature research in electronic databases. Various theories and research results were adopted and transferred to the context of medical rehabilitation and into a conceptual model. The conceptual model of self-determination reflects on a continuum which forms of self-determination may be present in situations of medical rehabilitation treatments. The location on the continuum depends theoretically on the manifestation of certain internal and external factors that may influence each other. The model provides a first conceptualization of self-determination focusing on medical rehabilitation which should be further refined and tested empirically. © Georg Thieme Verlag KG Stuttgart · New York.
The risk of establishment of aquatic invasive species: joining invasibility and propagule pressure

PubMed Central

Leung, Brian; Mandrak, Nicholas E

2007-01-01

Invasive species are increasingly becoming a policy priority. This has spurred researchers and managers to try to estimate the risk of invasion. Conceptually, invasions are dependent both on the receiving environment (invasibility) and on the ability to reach these new areas (propagule pressure). However, analyses of risk typically examine only one or the other. Here, we develop and apply a joint model of invasion risk that simultaneously incorporates invasibility and propagule pressure. We present arguments that the behaviour of these two elements of risk differs substantially—propagule pressure is a function of time, whereas invasibility is not—and therefore have different management implications. Further, we use the well-studied zebra mussel (Dreissena polymorpha) to contrast predictions made using the joint model to those made by separate invasibility and propagule pressure models. We show that predictions of invasion progress as well as of the long-term invasion pattern are strongly affected by using a joint model. PMID:17711834
The risk of establishment of aquatic invasive species: joining invasibility and propagule pressure.

PubMed

Leung, Brian; Mandrak, Nicholas E

2007-10-22

Invasive species are increasingly becoming a policy priority. This has spurred researchers and managers to try to estimate the risk of invasion. Conceptually, invasions are dependent both on the receiving environment (invasibility) and on the ability to reach these new areas (propagule pressure). However, analyses of risk typically examine only one or the other. Here, we develop and apply a joint model of invasion risk that simultaneously incorporates invasibility and propagule pressure. We present arguments that the behaviour of these two elements of risk differs substantially--propagule pressure is a function of time, whereas invasibility is not--and therefore have different management implications. Further, we use the well-studied zebra mussel (Dreissena polymorpha) to contrast predictions made using the joint model to those made by separate invasibility and propagule pressure models. We show that predictions of invasion progress as well as of the long-term invasion pattern are strongly affected by using a joint model.
Data Modeling & the Infrastructural Nature of Conceptual Tools

ERIC Educational Resources Information Center

Lesh, Richard; Caylor, Elizabeth; Gupta, Shweta

2007-01-01

The goal of this paper is to demonstrate the infrastructural nature of many modern conceptual technologies. The focus of this paper is on conceptual tools associated with elementary types of data modeling. We intend to show a variety of ways in which these conceptual tools not only express thinking, but also mold and shape thinking. And those ways…
Exploring the social dimension of sandy beaches through predictive modelling.

PubMed

Domínguez-Tejo, Elianny; Metternicht, Graciela; Johnston, Emma L; Hedge, Luke

2018-05-15

Sandy beaches are unique ecosystems increasingly exposed to human-induced pressures. Consistent with emerging frameworks promoting this holistic approach towards beach management, is the need to improve the integration of social data into management practices. This paper aims to increase understanding of links between demographics and community values and preferred beach activities, as key components of the social dimension of the beach environment. A mixed method approach was adopted to elucidate users' opinions on beach preferences and community values through a survey carried out in Manly Local Government Area in Sydney Harbour, Australia. A proposed conceptual model was used to frame demographic models (using age, education, employment, household income and residence status) as predictors of these two community responses. All possible regression-model combinations were compared using Akaike's information criterion. Best models were then used to calculate quantitative likelihoods of the responses, presented as heat maps. Findings concur with international research indicating the relevance of social and restful activities as important social links between the community and the beach environment. Participant's age was a significant variable in the four predictive models. The use of predictive models informed by demographics could potentially increase our understanding of interactions between the social and ecological systems of the beach environment, as a prelude to integrated beach management approaches. The research represents a practical demonstration of how demographic predictive models could support proactive approaches to beach management. Copyright © 2018 Elsevier Ltd. All rights reserved.
On the incremental validity of irrational beliefs to predict subjective well-being while controlling for personality factors.

PubMed

Spörrle, Matthias; Strobel, Maria; Tumasjan, Andranik

2010-11-01

This research examines the incremental validity of irrational thinking as conceptualized by Albert Ellis to predict diverse aspects of subjective well-being while controlling for the influence of personality factors. Rational-emotive behavior therapy (REBT) argues that irrational beliefs result in maladaptive emotions leading to reduced well-being. Although there is some early scientific evidence for this relation, it has never been investigated whether this connection would still persist when statistically controlling for the Big Five personality factors, which were consistently found to be important determinants of well-being. Regression analyses revealed significant incremental validity of irrationality over personality factors when predicting life satisfaction, but not when predicting subjective happiness. Results are discussed with respect to conceptual differences between these two aspects of subjective well-being.
A Conceptual Model for Increasing Use of Electronic Medical Records by Primary Care Physicians Through End-User Support.

PubMed

Randhawa, Gurprit K

2017-01-01

A conceptual model for exploring the relationship between end-user support (EUS) and electronic medical record (EMR) use by primary care physicians is presented. The model was developed following a review of conceptual and theoretical frameworks related to technology adoption/use and EUS. The model includes (a) one core construct (facilitating conditions), (b) four antecedents and one postcedent of facilitating conditions, and (c) four moderators. EMR use behaviour is the key outcome of the model. The proposed conceptual model should be tested. The model may be used to inform planning and decision-making for EMR implementations to increase EMR use for benefits realization.
Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.
Identifying structural elements needed for development of a predictive life-history model for pallid and shovelnose sturgeons

USGS Publications Warehouse

Wildhaber, Mark L.; DeLonay, A.J.; Papoulias, D.M.; Galat, D.L.; Jacobson, R.B.; Simpkins, D.G.; Braaten, P.J.; Korschgen, C.E.; Mac, M.J.

2011-01-01

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic changes to the river systems and their biota. These changes have been implicated in the decline of the pallid sturgeon (Scaphirhynchus albus), which has been listed as a United States federal endangered species. The sympatric shovelnose sturgeon (S. platorynchus) is more common and widespread but has also been in decline. The decline of pallid sturgeon is considered symptomatic of poor reproductive success and low or no recruitment. In order to organize information about these species and provide a basis for future development of a predictive model to help guide recovery efforts, we present an expert-vetted, conceptual life-history framework that incorporates the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons.
Dissimilarity based Partial Least Squares (DPLS) for genomic prediction from SNPs.

PubMed

Singh, Priyanka; Engel, Jasper; Jansen, Jeroen; de Haan, Jorn; Buydens, Lutgarde Maria Celina

2016-05-04

Genomic prediction (GP) allows breeders to select plants and animals based on their breeding potential for desirable traits, without lengthy and expensive field trials or progeny testing. We have proposed to use Dissimilarity-based Partial Least Squares (DPLS) for GP. As a case study, we use the DPLS approach to predict Bacterial wilt (BW) in tomatoes using SNPs as predictors. The DPLS approach was compared with the Genomic Best-Linear Unbiased Prediction (GBLUP) and single-SNP regression with SNP as a fixed effect to assess the performance of DPLS. Eight genomic distance measures were used to quantify relationships between the tomato accessions from the SNPs. Subsequently, each of these distance measures was used to predict the BW using the DPLS prediction model. The DPLS model was found to be robust to the choice of distance measures; similar prediction performances were obtained for each distance measure. DPLS greatly outperformed the single-SNP regression approach, showing that BW is a comprehensive trait dependent on several loci. Next, the performance of the DPLS model was compared to that of GBLUP. Although GBLUP and DPLS are conceptually very different, the prediction quality (PQ) measured by DPLS models were similar to the prediction statistics obtained from GBLUP. A considerable advantage of DPLS is that the genotype-phenotype relationship can easily be visualized in a 2-D scatter plot. This so-called score-plot provides breeders an insight to select candidates for their future breeding program. DPLS is a highly appropriate method for GP. The model prediction performance was similar to the GBLUP and far better than the single-SNP approach. The proposed method can be used in combination with a wide range of genomic dissimilarity measures and genotype representations such as allele-count, haplotypes or allele-intensity values. Additionally, the data can be insightfully visualized by the DPLS model, allowing for selection of desirable candidates from the breeding experiments. In this study, we have assessed the DPLS performance on a single trait.
Prosociality: the contribution of traits, values, and self-efficacy beliefs.

PubMed

Caprara, Gian Vittorio; Alessandri, Guido; Eisenberg, Nancy

2012-06-01

The present study examined how agreeableness, self-transcendence values, and empathic self-efficacy beliefs predict individuals' tendencies to engage in prosocial behavior (i.e., prosociality) across time. Participants were 340 young adults, 190 women and 150 men, age approximately 21 years at Time 1 and 25 years at Time 2. Measures of agreeableness, self-transcendence, empathic self-efficacy beliefs, and prosociality were collected at 2 time points. The findings corroborated the posited paths of relations, with agreeableness directly predicting self-transcendence and indirectly predicting empathic self-efficacy beliefs and prosociality. Self-transcendence mediated the relation between agreeableness and empathic self-efficacy beliefs. Empathic self-efficacy beliefs mediated the relation of agreeableness and self-transcendence to prosociality. Finally, earlier prosociality predicted agreeableness and empathic self-efficacy beliefs assessed at Time 2. The posited conceptual model accounted for a significant portion of variance in prosociality and provides guidance to interventions aimed at promoting prosociality. 2012 APA, all rights reserved
Mid- and long-term runoff predictions by an improved phase-space reconstruction model.

PubMed

Hong, Mei; Wang, Dong; Wang, Yuankun; Zeng, Xiankui; Ge, Shanshan; Yan, Hengqian; Singh, Vijay P

2016-07-01

In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall-runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ''wet years and dry years predictability barrier,'' to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff. Copyright © 2015 Elsevier Inc. All rights reserved.
Health literacy and public health: a systematic review and integration of definitions and models.

PubMed

Sørensen, Kristine; Van den Broucke, Stephan; Fullam, James; Doyle, Gerardine; Pelikan, Jürgen; Slonska, Zofia; Brand, Helmut

2012-01-25

Health literacy concerns the knowledge and competences of persons to meet the complex demands of health in modern society. Although its importance is increasingly recognised, there is no consensus about the definition of health literacy or about its conceptual dimensions, which limits the possibilities for measurement and comparison. The aim of the study is to review definitions and models on health literacy to develop an integrated definition and conceptual model capturing the most comprehensive evidence-based dimensions of health literacy. A systematic literature review was performed to identify definitions and conceptual frameworks of health literacy. A content analysis of the definitions and conceptual frameworks was carried out to identify the central dimensions of health literacy and develop an integrated model. The review resulted in 17 definitions of health literacy and 12 conceptual models. Based on the content analysis, an integrative conceptual model was developed containing 12 dimensions referring to the knowledge, motivation and competencies of accessing, understanding, appraising and applying health-related information within the healthcare, disease prevention and health promotion setting, respectively. Based upon this review, a model is proposed integrating medical and public health views of health literacy. The model can serve as a basis for developing health literacy enhancing interventions and provide a conceptual basis for the development and validation of measurement tools, capturing the different dimensions of health literacy within the healthcare, disease prevention and health promotion settings.
Estimating the Need for Medical Intervention due to Sleep Disruption on the International Space Station

NASA Technical Reports Server (NTRS)

Myers, Jerry G.; Lewandowski, Beth E.; Brooker, John E.; Hurst, S. R.; Mallis, Melissa M.; Caldwell, J. Lynn

2008-01-01

During ISS and shuttle missions, difficulties with sleep affect more than half of all US crews. Mitigation strategies to help astronauts cope with the challenges of disrupted sleep patterns can negatively impact both mission planning and vehicle design. The methods for addressing known detrimental impacts for some mission scenarios may have a substantial impact on vehicle specific consumable mass or volume or on the mission timeline. As part of the Integrated Medical Model (IMM) task, NASA Glenn Research Center is leading the development of a Monte Carlo based forecasting tool designed to determine the consumables required to address risks related to sleep disruption. The model currently focuses on the International Space Station and uses an algorithm that assembles representative mission schedules and feeds this into a well validated model that predicts relative levels of performance, and need for sleep (SAFTE Model, IBR Inc). Correlation of the resulting output to self-diagnosed needs for hypnotics, stimulants, and other pharmaceutical countermeasures, allows prediction of pharmaceutical use and the uncertainty of the specified prediction. This paper outlines a conceptual model for determining a rate of pharmaceutical utilization that can be used in the IMM model for comparison and optimization of mitigation methods with respect to all other significant medical needs and interventions.
Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

NASA Technical Reports Server (NTRS)

Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

2010-01-01

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.
Multiparadigm Design Environments

DTIC Science & Technology

1992-01-01

following results: 1. New methods for programming in terms of conceptual models 2. Design of object-oriented languages 3. Compiler optimization and...experimented with object-based methods for programming directly in terms of conceptual models, object-oriented language design, computer program...expect the3e results to have a strong influence on future ,,j :- ...... L ! . . • a mm ammmml ll Illlll • l I 1 Conceptual Programming Conceptual

Combining Different Conceptual Change Methods within 5E Model: A Sample Teaching Design of "Cell" Concept and its Organelles

ERIC Educational Resources Information Center

Urey, Mustafa; Calik, Muammer

2008-01-01

Since students' misconceptions are not completely remedied by means of only one conceptual change method, the authors assume that using different conceptual methods embedded within the 5E model will not only be more effective in enhancing students' conceptual understanding, but also may eliminate all students' misconceptions. The aim of this study…
The Value of Conceptual Models in Coping with Complexity and Interdisciplinarity in Environmental Sciences Education

ERIC Educational Resources Information Center

Fortuin, Karen P. J.; van Koppen, C. S. A.; Leemans, Rik

2011-01-01

Conceptual models are useful for facing the challenges of environmental sciences curriculum and course developers and students. These challenges are inherent to the interdisciplinary and problem-oriented character of environmental sciences curricula. In this article, we review the merits of conceptual models in facing these challenges. These…
Integrating conceptual knowledge within and across representational modalities.

PubMed

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-02-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within- and between-modality is accomplished using either direct connectivity, or a central semantic hub. In deep models, modalities are connected via cascading integration sites with successively wider receptive fields. Four experiments provide the first direct behavioral tests of these models using speeded tasks involving feature inference and concept activation. Shallow models predict no within-modal versus cross-modal difference in either task, whereas deep models predict a within-modal advantage for feature inference, but a cross-modal advantage for concept activation. Experiments 1 and 2 used relatedness judgments to tap participants' knowledge of relations for within- and cross-modal feature pairs. Experiments 3 and 4 used a dual-feature verification task. The pattern of decision latencies across Experiments 1-4 is consistent with a deep integration hierarchy. Copyright © 2010 Elsevier B.V. All rights reserved.
UNSAT-H Version 2. 0: Unsaturated soil water and heat flow model

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

Fayer, M.J.; Jones, T.L.

1990-04-01

This report documents UNSAT-H Version 2.0, a model for calculating water and heat flow in unsaturated media. The documentation includes the bases for the conceptual model and its numerical implementation, benchmark test cases, example simulations involving layered soils and plant transpiration, and the code listing. Waste management practices at the Hanford Site have included disposal of low-level wastes by near-surface burial. Predicting the future long-term performance of any such burial site in terms of migration of contaminants requires a model capable of simulating water flow in the unsaturated soils above the buried waste. The model currently used to meet thismore » need is UNSAT-H. This model was developed at Pacific Northwest Laboratory to assess water dynamics of near-surface, waste-disposal sites at the Hanford Site. The code is primarily used to predict deep drainage as a function of such environmental conditions as climate, soil type, and vegetation. UNSAT-H is also used to simulate the effects of various practices to enhance isolation of wastes. 66 refs., 29 figs., 7 tabs.« less
Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model.

PubMed

Dalege, Jonas; Borsboom, Denny; van Harreveld, Frenk; van den Berg, Helma; Conner, Mark; van der Maas, Han L J

2016-01-01

This article introduces the Causal Attitude Network (CAN) model, which conceptualizes attitudes as networks consisting of evaluative reactions and interactions between these reactions. Relevant evaluative reactions include beliefs, feelings, and behaviors toward the attitude object. Interactions between these reactions arise through direct causal influences (e.g., the belief that snakes are dangerous causes fear of snakes) and mechanisms that support evaluative consistency between related contents of evaluative reactions (e.g., people tend to align their belief that snakes are useful with their belief that snakes help maintain ecological balance). In the CAN model, the structure of attitude networks conforms to a small-world structure: evaluative reactions that are similar to each other form tight clusters, which are connected by a sparser set of "shortcuts" between them. We argue that the CAN model provides a realistic formalized measurement model of attitudes and therefore fills a crucial gap in the attitude literature. Furthermore, the CAN model provides testable predictions for the structure of attitudes and how they develop, remain stable, and change over time. Attitude strength is conceptualized in terms of the connectivity of attitude networks and we show that this provides a parsimonious account of the differences between strong and weak attitudes. We discuss the CAN model in relation to possible extensions, implication for the assessment of attitudes, and possibilities for further study. (c) 2015 APA, all rights reserved).
General-circulation-model simulations of future snowpack in the western United States

USGS Publications Warehouse

McCabe, G.J.; Wolock, D.M.

1999-01-01

April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western US. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.
Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report

DOE Data Explorer

Iovenitti, Joe

2014-01-02

The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The overall project area is 2500km2 with the Calibration Area (Dixie Valley Geothermal Wellfield) being about 170km2. The Final Scientific Report (FSR) is submitted in two parts (I and II). FSR part I presents (1) an assessment of the readily available public domain data and some proprietary data provided by terra-gen power, llc, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region. FSR Part II presents (1) 278 new gravity stations; (2) enhanced gravity-magnetic modeling; (3) 42 new ambient seismic noise survey stations; (4) an integration of the new seismic noise data with a regional seismic network; (5) a new methodology and approach to interpret this data; (5) a novel method to predict rock type and temperature based on the newly interpreted data; (6) 70 new magnetotelluric (MT) stations; (7) an integrated interpretation of the enhanced MT data set; (8) the results of a 308 station soil CO2 gas survey; (9) new conductive thermal modeling in the project area; (10) new convective modeling in the Calibration Area; (11) pseudo-convective modeling in the Calibration Area; (12) enhanced data implications and qualitative geoscience correlations at three scales (a) Regional, (b) Project, and (c) Calibration Area; (13) quantitative geostatistical exploratory data analysis; and (14) responses to nine questions posed in the proposal for this investigation. Enhanced favorability/trust maps were not generated because there was not a sufficient amount of new, fully-vetted (see below) rock type, temperature, and stress data. The enhanced seismic data did generate a new method to infer rock type and temperature (However, in the opinion of the Principal Investigator for this project, this new methodology needs to be tested and evaluated at other sites in the Basin and Range before it is used to generate the referenced maps. As in the baseline conceptual model, the enhanced findings can be applied to both the hydrothermal system and EGS in the Dixie Valley region).
Performance of two predictive uncertainty estimation approaches for conceptual Rainfall-Runoff Model: Bayesian Joint Inference and Hydrologic Uncertainty Post-processing

NASA Astrophysics Data System (ADS)

Hernández-López, Mario R.; Romero-Cuéllar, Jonathan; Camilo Múnera-Estrada, Juan; Coccia, Gabriele; Francés, Félix

2017-04-01

It is noticeably important to emphasize the role of uncertainty particularly when the model forecasts are used to support decision-making and water management. This research compares two approaches for the evaluation of the predictive uncertainty in hydrological modeling. First approach is the Bayesian Joint Inference of hydrological and error models. Second approach is carried out through the Model Conditional Processor using the Truncated Normal Distribution in the transformed space. This comparison is focused on the predictive distribution reliability. The case study is applied to two basins included in the Model Parameter Estimation Experiment (MOPEX). These two basins, which have different hydrological complexity, are the French Broad River (North Carolina) and the Guadalupe River (Texas). The results indicate that generally, both approaches are able to provide similar predictive performances. However, the differences between them can arise in basins with complex hydrology (e.g. ephemeral basins). This is because obtained results with Bayesian Joint Inference are strongly dependent on the suitability of the hypothesized error model. Similarly, the results in the case of the Model Conditional Processor are mainly influenced by the selected model of tails or even by the selected full probability distribution model of the data in the real space, and by the definition of the Truncated Normal Distribution in the transformed space. In summary, the different hypotheses that the modeler choose on each of the two approaches are the main cause of the different results. This research also explores a proper combination of both methodologies which could be useful to achieve less biased hydrological parameter estimation. For this approach, firstly the predictive distribution is obtained through the Model Conditional Processor. Secondly, this predictive distribution is used to derive the corresponding additive error model which is employed for the hydrological parameter estimation with the Bayesian Joint Inference methodology.
Guided Cognitive Reframing of Adolescent-Father Conflict: Who Mexican American and European Adolescents Seek and Why

PubMed Central

Cookston, Jeffrey T; Olide, Andres F.; Adams, Michele; Fabricius, William V.; Braver, Sanford L.; Parke, Ross D.

2013-01-01

Adolescents may seek to understand family conflict by seeking out confidants. However, little is known about whom adolescents seek, whether and how such support helps youth, and the factors that predict which sources are sought. This chapter offers a conceptual model of guided cognitive reframing that emphasizes the behavioral, cognitive, and affective implications of confidant support as well as individual, family, and cultural factors linked to support seeking. We present empirical data from 392 families of 7th graders of Mexican and European ancestry to predict whether adolescents seek mothers, co-resident fathers, and other sources and provide directions for subsequent research. PMID:22407883
Strategies to predict metal mobility in surficial mining environments

USGS Publications Warehouse

Smith, Kathleen S.

2007-01-01

This report presents some strategies to predict metal mobility at mining sites. These strategies are based on chemical, physical, and geochemical information about metals and their interactions with the environment. An overview of conceptual models, metal sources, and relative mobility of metals under different geochemical conditions is presented, followed by a discussion of some important physical and chemical properties of metals that affect their mobility, bioavailability, and toxicity. The physical and chemical properties lead into a discussion of the importance of the chemical speciation of metals. Finally, environmental and geochemical processes and geochemical barriers that affect metal speciation are discussed. Some additional concepts and applications are briefly presented at the end of this report.
The Contribution of Agreeableness and Self-efficacy Beliefs to Prosociality

PubMed Central

CAPRARA, GIAN VITTORIO; ALESSANDRI, GUIDO; DI GIUNTA, LAURA; PANERAI, LAURA; EISENBERG, NANCY

2010-01-01

The present study examined how agreeableness and self-efficacy beliefs about responding empathically to others’ needs predict individuals’ prosociality across time. Participants were 377 adolescents (66% males) aged 16 at Time 1 and 18 at Time 2 who took part at this study. Measures of agreeableness, empathic self-efficacy and prosociality were collected at two time points. The findings corroborated the posited paths of relations to assigning agreeableness a major role in predicting the level of individuals’ prosociality. Empathic self-efficacy beliefs partially mediated the relation of agreeableness to prosociality. The posited conceptual model accounted for a significant portion of variance in prosociality and provides guidance with respect to interventions aimed at promoting prosociality. PMID:20592954
OBO to UML: Support for the development of conceptual models in the biomedical domain.

PubMed

Waldemarin, Ricardo C; de Farias, Cléver R G

2018-04-01

A conceptual model abstractly defines a number of concepts and their relationships for the purposes of understanding and communication. Once a conceptual model is available, it can also be used as a starting point for the development of a software system. The development of conceptual models using the Unified Modeling Language (UML) facilitates the representation of modeled concepts and allows software developers to directly reuse these concepts in the design of a software system. The OBO Foundry represents the most relevant collaborative effort towards the development of ontologies in the biomedical domain. The development of UML conceptual models in the biomedical domain may benefit from the use of domain-specific semantics and notation. Further, the development of these models may also benefit from the reuse of knowledge contained in OBO ontologies. This paper investigates the support for the development of conceptual models in the biomedical domain using UML as a conceptual modeling language and using the support provided by the OBO Foundry for the development of biomedical ontologies, namely entity kind and relationship types definitions provided by the Basic Formal Ontology (BFO) and the OBO Core Relations Ontology (OBO Core), respectively. Further, the paper investigates the support for the reuse of biomedical knowledge currently available in OBOFFF ontologies in the development these conceptual models. The paper describes a UML profile for the OBO Core Relations Ontology, which basically defines a number of stereotypes to represent BFO entity kinds and OBO Core relationship types definitions. The paper also presents a support toolset consisting of a graphical editor named OBO-RO Editor, which directly supports the development of UML models using the extensions defined by our profile, and a command-line tool named OBO2UML, which directly converts an OBOFFF ontology into a UML model. Copyright © 2018 Elsevier Inc. All rights reserved.
Improving inflow forecasting into hydropower reservoirs through a complementary modelling framework

NASA Astrophysics Data System (ADS)

Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K.

2014-10-01

Accuracy of reservoir inflow forecasts is instrumental for maximizing the value of water resources and benefits gained through hydropower generation. Improving hourly reservoir inflow forecasts over a 24 h lead-time is considered within the day-ahead (Elspot) market of the Nordic exchange market. We present here a new approach for issuing hourly reservoir inflow forecasts that aims to improve on existing forecasting models that are in place operationally, without needing to modify the pre-existing approach, but instead formulating an additive or complementary model that is independent and captures the structure the existing model may be missing. Besides improving forecast skills of operational models, the approach estimates the uncertainty in the complementary model structure and produces probabilistic inflow forecasts that entrain suitable information for reducing uncertainty in the decision-making processes in hydropower systems operation. The procedure presented comprises an error model added on top of an un-alterable constant parameter conceptual model, the models being demonstrated with reference to the 207 km2 Krinsvatn catchment in central Norway. The structure of the error model is established based on attributes of the residual time series from the conceptual model. Deterministic and probabilistic evaluations revealed an overall significant improvement in forecast accuracy for lead-times up to 17 h. Season based evaluations indicated that the improvement in inflow forecasts varies across seasons and inflow forecasts in autumn and spring are less successful with the 95% prediction interval bracketing less than 95% of the observations for lead-times beyond 17 h.
A post audit and inverse modeling in reactive transport: 50 years of artificial recharge in the Amsterdam Water Supply Dunes

NASA Astrophysics Data System (ADS)

Karlsen, R. H.; Smits, F. J. C.; Stuyfzand, P. J.; Olsthoorn, T. N.; van Breukelen, B. M.

2012-08-01

SummaryThis article describes the post audit and inverse modeling of a 1-D forward reactive transport model. The model simulates the changes in water quality following artificial recharge of pre-treated water from the river Rhine in the Amsterdam Water Supply Dunes using the PHREEQC-2 numerical code. One observation dataset is used for model calibration, and another dataset for validation of model predictions. The total simulation time of the model is 50 years, from 1957 to 2007, with recharge composition varying on a monthly basis and the post audit is performed 26 years after the former model simulation period. The post audit revealed that the original model could reasonably predict conservative transport and kinetic redox reactions (oxygen and nitrate reduction coupled to the oxidation of soil organic carbon), but showed discrepancies in the simulation of cation exchange. Conceptualizations of the former model were inadequate to accurately simulate water quality changes controlled by cation exchange, especially concerning the breakthrough of potassium and magnesium fronts. Changes in conceptualization and model design, including the addition of five flow paths, to a total of six, and the use of parameter estimation software (PEST), resulted in a better model to measurement fit and system representation. No unique parameter set could be found for the model, primarily due to high parameter correlations, and an assessment of the predictive error was made using a calibration constrained Monte-Carlo method, and evaluated against field observations. The predictive error was found to be low for Na+ and Ca2+, except for greater travel times, while the K+ and Mg2+ error was restricted to the exchange fronts at some of the flow paths. Optimized cation exchange coefficients were relatively high, especially for potassium, but still within the observed range in literature. The exchange coefficient for potassium agrees with strong fixation on illite, a main clay mineral in the area. Optimized CEC values were systematically lower than clay and organic matter contents indicated, possibly reflecting preferential flow of groundwater through the more permeable but less reactive aquifer parts. Whereas the artificial recharge initially acted as an intrusion of relatively saline water triggering Na+ for Ca2+ exchange, further increasing total hardness of the recharged water, the gradual long-term reduction in salinity of the river Rhine since the mid 1970s has shifted to an intrusion of fresher water causing Ca2+ for Na+ exchange. As a result, seasonal and longer term reversal of the initial cation exchange processes was observed adding to the general long-term reduction in total hardness of the recharged Rhine water.
Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

NASA Astrophysics Data System (ADS)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.
A Bayesian Framework for Analysis of Pseudo-Spatial Models of Comparable Engineered Systems with Application to Spacecraft Anomaly Prediction Based on Precedent Data

NASA Astrophysics Data System (ADS)

Ndu, Obibobi Kamtochukwu

To ensure that estimates of risk and reliability inform design and resource allocation decisions in the development of complex engineering systems, early engagement in the design life cycle is necessary. An unfortunate constraint on the accuracy of such estimates at this stage of concept development is the limited amount of high fidelity design and failure information available on the actual system under development. Applying the human ability to learn from experience and augment our state of knowledge to evolve better solutions mitigates this limitation. However, the challenge lies in formalizing a methodology that takes this highly abstract, but fundamentally human cognitive, ability and extending it to the field of risk analysis while maintaining the tenets of generalization, Bayesian inference, and probabilistic risk analysis. We introduce an integrated framework for inferring the reliability, or other probabilistic measures of interest, of a new system or a conceptual variant of an existing system. Abstractly, our framework is based on learning from the performance of precedent designs and then applying the acquired knowledge, appropriately adjusted based on degree of relevance, to the inference process. This dissertation presents a method for inferring properties of the conceptual variant using a pseudo-spatial model that describes the spatial configuration of the family of systems to which the concept belongs. Through non-metric multidimensional scaling, we formulate the pseudo-spatial model based on rank-ordered subjective expert perception of design similarity between systems that elucidate the psychological space of the family. By a novel extension of Kriging methods for analysis of geospatial data to our "pseudo-space of comparable engineered systems", we develop a Bayesian inference model that allows prediction of the probabilistic measure of interest.
Computational Prediction of the Protonation Sites of Ac-Lys-(Ala)n-Lys-NH2 Peptides through Conceptual DFT Descriptors.

PubMed

Sastre, Sebastián; Frau, Juan; Glossman-Mitnik, Daniel

2017-03-13

Six density functionals (M11, M11L, MN12L, MN12SX, N12, and N12SX) in connection with the Def2TZVP basis set and the SMD solvation model (water as a solvent) have been assessed for the calculation of the molecular structure and properties of several peptides with the general formulaAc-Lys-(Ala)n-Lys-NH2,withn=0to5 [...].
A Conceptual Model of the Severe-Storm Environment for Inclusion into Air Weather Service Severe-Storm Analysis and Forecast Procedures.

DTIC Science & Technology

1984-11-16

thunderstorm forecasting , Bull. Am. Meteorol. Soc. 34:250-252. 19. Galway , J.G. (1956) The lifted index as a prediction of latent instability, Bull...downwind, which are geographically related and can be traced through time by a forecaster . In fact, a typical Great Plains severe-storm situation has...weather station setting, only one sounding can be plotted and anal- yzed because of time constraints. Appendix C contains two single-station forecast
Self-Induced Faraday Instability Laser

NASA Astrophysics Data System (ADS)

Perego, A. M.; Smirnov, S. V.; Staliunas, K.; Churkin, D. V.; Wabnitz, S.

2018-05-01

We predict the onset of self-induced parametric or Faraday instabilities in a laser, spontaneously caused by the presence of pump depletion, which leads to a periodic gain landscape for light propagating in the cavity. As a result of the instability, continuous wave oscillation becomes unstable even in the normal dispersion regime of the cavity, and a periodic train of pulses with ultrahigh repetition rate is generated. Application to the case of Raman fiber lasers is described, in good quantitative agreement between our conceptual analysis and numerical modeling.
Self-Induced Faraday Instability Laser.

PubMed

Perego, A M; Smirnov, S V; Staliunas, K; Churkin, D V; Wabnitz, S

2018-05-25

We predict the onset of self-induced parametric or Faraday instabilities in a laser, spontaneously caused by the presence of pump depletion, which leads to a periodic gain landscape for light propagating in the cavity. As a result of the instability, continuous wave oscillation becomes unstable even in the normal dispersion regime of the cavity, and a periodic train of pulses with ultrahigh repetition rate is generated. Application to the case of Raman fiber lasers is described, in good quantitative agreement between our conceptual analysis and numerical modeling.

Plant allometry, leaf nitrogen and phosphorus stoichiometry, and interspecific trends in annual growth rates.

PubMed

Niklas, Karl J

2006-02-01

Life forms as diverse as unicellular algae, zooplankton, vascular plants, and mammals appear to obey quarter-power scaling rules. Among the most famous of these rules is Kleiber's (i.e. basal metabolic rates scale as the three-quarters power of body mass), which has a botanical analogue (i.e. annual plant growth rates scale as the three-quarters power of total body mass). Numerous theories have tried to explain why these rules exist, but each has been heavily criticized either on conceptual or empirical grounds. N,P-STOICHIOMETRY: Recent models predicting growth rates on the basis of how total cell, tissue, or organism nitrogen and phosphorus are allocated, respectively, to protein and rRNA contents may provide the answer, particularly in light of the observation that annual plant growth rates scale linearly with respect to standing leaf mass and that total leaf mass scales isometrically with respect to nitrogen but as the three-quarters power of leaf phosphorus. For example, when these relationships are juxtaposed with other allometric trends, a simple N,P-stoichiometric model successfully predicts the relative growth rates of 131 diverse C3 and C4 species. The melding of allometric and N,P-stoichiometric theoretical insights provides a robust modelling approach that conceptually links the subcellular 'machinery' of protein/ribosomal metabolism to observed growth rates of uni- and multicellular organisms. Because the operation of this 'machinery' is basic to the biology of all life forms, its allometry may provide a mechanistic explanation for the apparent ubiquity of quarter-power scaling rules.
DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.
Simulation of green roof runoff under different substrate depths and vegetation covers by coupling a simple conceptual and a physically based hydrological model.

PubMed

Soulis, Konstantinos X; Valiantzas, John D; Ntoulas, Nikolaos; Kargas, George; Nektarios, Panayiotis A

2017-09-15

In spite of the well-known green roof benefits, their widespread adoption in the management practices of urban drainage systems requires the use of adequate analytical and modelling tools. In the current study, green roof runoff modeling was accomplished by developing, testing, and jointly using a simple conceptual model and a physically based numerical simulation model utilizing HYDRUS-1D software. The use of such an approach combines the advantages of the conceptual model, namely simplicity, low computational requirements, and ability to be easily integrated in decision support tools with the capacity of the physically based simulation model to be easily transferred in conditions and locations other than those used for calibrating and validating it. The proposed approach was evaluated with an experimental dataset that included various green roof covers (either succulent plants - Sedum sediforme, or xerophytic plants - Origanum onites, or bare substrate without any vegetation) and two substrate depths (either 8 cm or 16 cm). Both the physically based and the conceptual models matched very closely the observed hydrographs. In general, the conceptual model performed better than the physically based simulation model but the overall performance of both models was sufficient in most cases as it is revealed by the Nash-Sutcliffe Efficiency index which was generally greater than 0.70. Finally, it was showcased how a physically based and a simple conceptual model can be jointly used to allow the use of the simple conceptual model for a wider set of conditions than the available experimental data and in order to support green roof design. Copyright © 2017 Elsevier Ltd. All rights reserved.
Conceptual foundations of a palliative approach: a knowledge synthesis.

PubMed

Sawatzky, Richard; Porterfield, Pat; Lee, Joyce; Dixon, Duncan; Lounsbury, Kathleen; Pesut, Barbara; Roberts, Della; Tayler, Carolyn; Voth, James; Stajduhar, Kelli

2016-01-15

Much of what we understand about the design of healthcare systems to support care of the dying comes from our experiences with providing palliative care for dying cancer patients. It is increasingly recognized that in addition to cancer, high quality end of life care should be an integral part of care that is provided for those with other advancing chronic life-limiting conditions. A "palliative approach" has been articulated as one way of conceptualizing this care. However, there is a lack of conceptual clarity regarding the essential characteristics of a palliative approach to care. The goal of this research was to delineate the key characteristics of a palliative approach found in the empiric literature in order to establish conceptual clarity. We conducted a knowledge synthesis of empirical peer-reviewed literature. Search terms pertaining to "palliative care" and "chronic life-limiting conditions" were identified. A comprehensive database search of 11 research databases for the intersection of these terms yielded 190,204 documents. A subsequent computer-assisted approach using statistical predictive classification methods was used to identify relevant documents, resulting in a final yield of 91 studies. Narrative synthesis methods and thematic analysis were used to then identify and conceptualize key characteristics of a palliative approach. The following three overarching themes were conceptualized to delineate a palliative approach: (1) upstream orientation towards the needs of people who have life-limiting conditions and their families, (2) adaptation of palliative care knowledge and expertise, (3) operationalization of a palliative approach through integration into systems and models of care that do not specialize in palliative care. Our findings provide much needed conceptual clarity regarding a palliative approach. Such clarity is of fundamental importance for the development of healthcare systems that facilitate the integration of a palliative approach in the care of people who have chronic life-limiting conditions.
Development of Conceptual Models for Internet Search: A Case Study.

ERIC Educational Resources Information Center

Uden, Lorna; Tearne, Stephen; Alderson, Albert

This paper describes the creation and evaluation of a World Wide Web-based courseware module, using conceptual models based on constructivism, that teaches novices how to use the Internet for searching. Questionnaires and interviews were used to understand the difficulties of a group of novices. The conceptual model of the experts for the task was…
Feasibility of Implementing an All-Volunteer Force for the ROK Armed Forces

DTIC Science & Technology

2007-03-01

Korea’s current military/economic/political/social factors for voluntary recruitment through an open-systems conceptual model. Results indicate that the...recruitment through an open-systems conceptual model. Results indicate that the draft should be maintained for the near future, but this does not...7 A. A CONCEPTUAL MODEL FOR DEFENSE ORGANIZATION
Teacher Emotion Research: Introducing a Conceptual Model to Guide Future Research

ERIC Educational Resources Information Center

Fried, Leanne; Mansfield, Caroline; Dobozy, Eva

2015-01-01

This article reports on the development of a conceptual model of teacher emotion through a review of teacher emotion research published between 2003 and 2013. By examining 82 publications regarding teacher emotion, the main aim of the review was to identify how teacher emotion was conceptualised in the literature and develop a conceptual model to…
Showing Automatically Generated Students' Conceptual Models to Students and Teachers

ERIC Educational Resources Information Center

Perez-Marin, Diana; Pascual-Nieto, Ismael

2010-01-01

A student conceptual model can be defined as a set of interconnected concepts associated with an estimation value that indicates how well these concepts are used by the students. It can model just one student or a group of students, and can be represented as a concept map, conceptual diagram or one of several other knowledge representation…
Applying a Conceptual Model in Sport Sector Work- Integrated Learning Contexts

ERIC Educational Resources Information Center

Agnew, Deborah; Pill, Shane; Orrell, Janice

2017-01-01

This paper applies a conceptual model for work-integrated learning (WIL) in a multidisciplinary sports degree program. Two examples of WIL in sport will be used to illustrate how the conceptual WIL model is being operationalized. The implications for practice are that curriculum design must recognize a highly flexible approach to the nature of…
Using Item Response Theory to Conduct a Distracter Analysis on Conceptual Inventory of Natural Selection

ERIC Educational Resources Information Center

Battisti, Bryce Thomas; Hanegan, Nikki; Sudweeks, Richard; Cates, Rex

2010-01-01

Concept inventories are often used to assess current student understanding although conceptual change models are problematic. Due to controversies with conceptual change models and the realities of student assessment, it is important that concept inventories are evaluated using a variety of theoretical models to improve quality. This study used a…
Application of a baseflow filter for evaluating model structure suitability of the IHACRES CMD

NASA Astrophysics Data System (ADS)

Kim, H. S.

2015-02-01

The main objective of this study was to assess the predictive uncertainty from the rainfall-runoff model structure coupling a conceptual module (non-linear module) with a metric transfer function module (linear module). The methodology was primarily based on the comparison between the outputs of the rainfall-runoff model and those from an alternative model approach. An alternative model approach was used to minimise uncertainties arising from data and the model structure. A baseflow filter was adopted to better understand deficiencies in the forms of the rainfall-runoff model by avoiding the uncertainties related to data and the model structure. The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment. In the assessment of model structure suitability, the consistency (or variability) of catchment response over time and space in model performance and parameter values has been investigated to detect problems related to the temporal and spatial variability of the model accuracy. The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters. A graphical comparison of model residuals, effective rainfall estimates and hydrographs was used to determine a model's ability related to systematic model deviation between simulated and observed behaviours and general behavioural differences in the timing and magnitude of peak flows. The model's predictability was very sensitive to catchment response characteristics. The linear module performs reasonably well in the wetter catchments but has considerable difficulties when applied to the drier catchments where a hydrologic response is dominated by quick flow. The non-linear module has a potential limitation in its capacity to capture non-linear processes for converting observed rainfall into effective rainfall in both the wetter and drier catchments. The comparative study based on a better quantification of the accuracy and precision of hydrological modelling predictions yields a better understanding for the potential improvement of model deficiencies.
Groundwater Fate and Transport Modeling for Texarkana Wood Preserving Company Superfund Site, Texarkana, Texas

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

Arnett, Ronald Chester

Fate and transport model results are presented for the Texarkana Wood Preserving Company (TWPC)superfund site. The conceptual model assumes two sources of contamination, specifically, the areas around the old and new process areas. Recent data show the presence of non-aqueous phase liquids (NAPL) in the aquifer that are also sources of dissolved contamination in the aquifer. A flow model was constructed and calibrated against measured hydraulic heads at permanent monitoring wells. Good matches were obtained between model simulated heads and most measured heads. An unexplained exception occurs at monitoring well MW-13 down gradient of the site beyond the measured contaminantmore » plume where the model predicts heads that are more than 2 ft. lower than reported field measurements. Adjusting hydraulic parameters in the model could not account for this anomaly and still preserve the head matches at other wells. There is likely a moderate deficiency in the conceptual model or perhaps a data error. Other information such as substantial amounts of infiltrating surface water in the area or a correction in surveyed elevation would improve the flow model. A particle tracking model calculated a travel time from the new process area to the Day’s Creek discharge location on the order of 40 years. Travel times from the old process area to Day’s Creek were calculated to be on the order of 80 years. While these calculations are subject to some uncertainty, travel times of decades are indicated.« less
Preschool Spontaneous Focusing on Numerosity Predicts Rational Number Conceptual Knowledge 6 Years Later

ERIC Educational Resources Information Center

McMullen, Jake; Hannula-Sormunen, Minna M.; Lehtinen, Erno

2015-01-01

Recent evidence suggests that early natural number knowledge is a predictor of later rational number conceptual knowledge, even though students' difficulties with rational numbers have also been explained by the overuse of natural number concepts--often referred to as the natural number bias. Hannula and Lehtinen ("Learn Instr"…
Students' "Uses and Gratification Expectancy" Conceptual Framework in Relation to E-Learning Resources

ERIC Educational Resources Information Center

Mondi, Makingu; Woods, Peter; Rafi, Ahmad

2007-01-01

This paper presents the systematic development of a "Uses and Gratification Expectancy" (UGE) conceptual framework which is able to predict students' "Perceived e-Learning Experience." It is argued that students' UGE as regards e-learning resources cannot be implicitly or explicitly explored without first examining underlying communication…
Beyond Warmth and Conflict: The Developmental Utility of a Boundary Conceptualization of Sibling Relationship Processes

ERIC Educational Resources Information Center

Bascoe, Sonnette M.; Davies, Patrick T.; Cummings, E. Mark

2012-01-01

Translating relationship boundaries conceptualizations to the study of sibling relationships, this study examined the utility of sibling enmeshment and disengagement in predicting child adjustment difficulties in a sample of 282 mothers and adolescents (mean age = 12.7 years). Mothers completed a semistructured interview at the first measurement…
Modifying Knowledge, Emotions, and Attitudes Regarding Genetically Modified Foods

ERIC Educational Resources Information Center

Heddy, Benjamin C.; Danielson, Robert W.; Sinatra, Gale M.; Graham, Jesse

2017-01-01

The purpose of this study was to explore whether conceptual change predicted emotional and attitudinal change while learning about genetically modified foods (GMFs). Participants were 322 college students; half read a refutation text designed to shift conceptual knowledge, emotions, and attitudes, while the other half served as a control group.…
Executive functions predict conceptual learning of science.

PubMed

Rhodes, Sinéad M; Booth, Josephine N; Palmer, Lorna Elise; Blythe, Richard A; Delibegovic, Mirela; Wheate, Nial J

2016-06-01

We examined the relationship between executive functions and both factual and conceptual learning of science, specifically chemistry, in early adolescence. Sixty-three pupils in their second year of secondary school (aged 12-13 years) participated. Pupils completed tasks of working memory (Spatial Working Memory), inhibition (Stop-Signal), attention set-shifting (ID/ED), and planning (Stockings of Cambridge), from the CANTAB. They also participated in a chemistry teaching session, practical, and assessment on the topic of acids and alkalis designed specifically for this study. Executive function data were related to (1) the chemistry assessment which included aspects of factual and conceptual learning and (2) a recent school science exam. Correlational analyses between executive functions and both the chemistry assessment and science grades revealed that science achievements were significantly correlated with working memory. Linear regression analysis revealed that visuospatial working memory ability was predictive of chemistry performance. Interestingly, this relationship was observed solely in relation to the conceptual learning condition of the assessment highlighting the role of executive functions in understanding and applying knowledge about what is learned within science teaching. © 2016 The British Psychological Society.
Conceptual Distinctiveness Supports Detailed Visual Long-Term Memory for Real-World Objects

PubMed Central

Konkle, Talia; Brady, Timothy F.; Alvarez, George A.; Oliva, Aude

2012-01-01

Humans have a massive capacity to store detailed information in visual long-term memory. The present studies explored the fidelity of these visual long-term memory representations and examined how conceptual and perceptual features of object categories support this capacity. Observers viewed 2,800 object images with a different number of exemplars presented from each category. At test, observers indicated which of 2 exemplars they had previously studied. Memory performance was high and remained quite high (82% accuracy) with 16 exemplars from a category in memory, demonstrating a large memory capacity for object exemplars. However, memory performance decreased as more exemplars were held in memory, implying systematic categorical interference. Object categories with conceptually distinctive exemplars showed less interference in memory as the number of exemplars increased. Interference in memory was not predicted by the perceptual distinctiveness of exemplars from an object category, though these perceptual measures predicted visual search rates for an object target among exemplars. These data provide evidence that observers’ capacity to remember visual information in long-term memory depends more on conceptual structure than perceptual distinctiveness. PMID:20677899
Overcoming redundancies in bedside nursing assessments by validating a parsimonious meta-tool: findings from a methodological exercise study.

PubMed

Palese, Alvisa; Marini, Eva; Guarnier, Annamaria; Barelli, Paolo; Zambiasi, Paola; Allegrini, Elisabetta; Bazoli, Letizia; Casson, Paola; Marin, Meri; Padovan, Marisa; Picogna, Michele; Taddia, Patrizia; Chiari, Paolo; Salmaso, Daniele; Marognolli, Oliva; Canzan, Federica; Ambrosi, Elisa; Saiani, Luisa; Grassetti, Luca

2016-10-01

There is growing interest in validating tools aimed at supporting the clinical decision-making process and research. However, an increased bureaucratization of clinical practice and redundancies in the measures collected have been reported by clinicians. Redundancies in clinical assessments affect negatively both patients and nurses. To validate a meta-tool measuring the risks/problems currently estimated by multiple tools used in daily practice. A secondary analysis of a database was performed, using a cross-validation and a longitudinal study designs. In total, 1464 patients admitted to 12 medical units in 2012 were assessed at admission with the Brass, Barthel, Conley and Braden tools. Pertinent outcomes such as the occurrence of post-discharge need for resources and functional decline at discharge, as well as falls and pressure sores, were measured. Explorative factor analysis of each tool, inter-tool correlations and a conceptual evaluation of the redundant/similar items across tools were performed. Therefore, the validation of the meta-tool was performed through explorative factor analysis, confirmatory factor analysis and the structural equation model to establish the ability of the meta-tool to predict the outcomes estimated by the original tools. High correlations between the tools have emerged (from r 0.428 to 0.867) with a common variance from 18.3% to 75.1%. Through a conceptual evaluation and explorative factor analysis, the items were reduced from 42 to 20, and the three factors that emerged were confirmed by confirmatory factor analysis. According to the structural equation model results, two out of three emerged factors predicted the outcomes. From the initial 42 items, the meta-tool is composed of 20 items capable of predicting the outcomes as with the original tools. © 2016 John Wiley & Sons, Ltd.
Reliability and Maintainability model (RAM) user and maintenance manual. Part 2

NASA Technical Reports Server (NTRS)

Ebeling, Charles E.

1995-01-01

This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided.

The predictive capacity of perceived expressed emotion as a dynamic entity of adolescents from the general community.

PubMed

Hale, William W; Raaijmakers, Quinten A W; van Hoof, Anne; Meeus, Wim H J

2011-06-01

In previous studies, it has been demonstrated that high parental expressed emotion (EE) is predictive of depressive, aggressive and delinquency symptoms of adolescents. Two issues have received much less prominence in EE research, these being studies of adolescent perceived EE and the measurement of the EE as a dynamic, developmental construct. This 4-year, three-wave, longitudinal study of perceived EE of adolescents from the general community examines if adolescent perceived EE measured with the traditional, one-measurement EE approach as well as adolescent perceived EE measured with a repeated measured, dynamic EE approach can predict adolescent depressive, aggressive and delinquency symptoms. Dutch adolescents (N = 285; 51% girls; M = 13 years) from the general community were prospectively studied annually for 4 years. At all waves, the adolescents completed the Level of Expressed Emotion (LEE) questionnaire and at the final wave also completed self-rated measures of depressive, aggressive and delinquent symptoms. Growth models were used to predict adolescent symptoms from adolescent perceived EE. Growth models significantly predicted adolescent depressive, aggressive and delinquency symptoms from adolescent perceived EE. This study of the LEE demonstrates that developmental characteristics of EE are predictive of adolescents' symptoms. These findings hold implications for current EE intervention therapies and the conceptualization of EE.
Preliminary estimates of spatially distributed net infiltration and recharge for the Death Valley region, Nevada-California

USGS Publications Warehouse

Hevesi, J.A.; Flint, A.L.; Flint, L.E.

2002-01-01

A three-dimensional ground-water flow model has been developed to evaluate the Death Valley regional flow system, which includes ground water beneath the Nevada Test Site. Estimates of spatially distributed net infiltration and recharge are needed to define upper boundary conditions. This study presents a preliminary application of a conceptual and numerical model of net infiltration. The model was developed in studies at Yucca Mountain, Nevada, which is located in the approximate center of the Death Valley ground-water flow system. The conceptual model describes the effects of precipitation, runoff, evapotranspiration, and redistribution of water in the shallow unsaturated zone on predicted rates of net infiltration; precipitation and soil depth are the two most significant variables. The conceptual model was tested using a preliminary numerical model based on energy- and water-balance calculations. Daily precipitation for 1980 through 1995, averaging 202 millimeters per year over the 39,556 square kilometers area of the ground-water flow model, was input to the numerical model to simulate net infiltration ranging from zero for a soil thickness greater than 6 meters to over 350 millimeters per year for thin soils at high elevations in the Spring Mountains overlying permeable bedrock. Estimated average net infiltration over the entire ground-water flow model domain is 7.8 millimeters per year.To evaluate the application of the net-infiltration model developed on a local scale at Yucca Mountain, to net-infiltration estimates representing the magnitude and distribution of recharge on a regional scale, the net-infiltration results were compared with recharge estimates obtained using empirical methods. Comparison of model results with previous estimates of basinwide recharge suggests that the net-infiltration estimates obtained using this model may overestimate recharge because of uncertainty in modeled precipitation, bedrock permeability, and soil properties for locations such as the Spring Mountains. Although this model is preliminary and uncalibrated, it provides a first approximation of the spatial distribution of net infiltration for the Death Valley region under current climatic conditions.
Neighborhood income and major depressive disorder in a large Dutch population: results from the LifeLines Cohort study.

PubMed

Klijs, Bart; Kibele, Eva U B; Ellwardt, Lea; Zuidersma, Marij; Stolk, Ronald P; Wittek, Rafael P M; Mendes de Leon, Carlos M; Smidt, Nynke

2016-08-11

Previous studies are inconclusive on whether poor socioeconomic conditions in the neighborhood are associated with major depressive disorder. Furthermore, conceptual models that relate neighborhood conditions to depressive disorder have not been evaluated using empirical data. In this study, we investigated whether neighborhood income is associated with major depressive episodes. We evaluated three conceptual models. Conceptual model 1: The association between neighborhood income and major depressive episodes is explained by diseases, lifestyle factors, stress and social participation. Conceptual model 2: A low individual income relative to the mean income in the neighborhood is associated with major depressive episodes. Conceptual model 3: A high income of the neighborhood buffers the effect of a low individual income on major depressive disorder. We used adult baseline data from the LifeLines Cohort Study (N = 71,058) linked with data on the participants' neighborhoods from Statistics Netherlands. The current presence of a major depressive episode was assessed using the MINI neuropsychiatric interview. The association between neighborhood income and major depressive episodes was assessed using a mixed effect logistic regression model adjusted for age, sex, marital status, education and individual (equalized) income. This regression model was sequentially adjusted for lifestyle factors, chronic diseases, stress, and social participation to evaluate conceptual model 1. To evaluate conceptual models 2 and 3, an interaction term for neighborhood income*individual income was included. Multivariate regression analysis showed that a low neighborhood income is associated with major depressive episodes (OR (95 % CI): 0.82 (0.73;0.93)). Adjustment for diseases, lifestyle factors, stress, and social participation attenuated this association (ORs (95 % CI): 0.90 (0.79;1.01)). Low individual income was also associated with major depressive episodes (OR (95 % CI): 0.72 (0.68;0.76)). The interaction of individual income*neighborhood income on major depressive episodes was not significant (p = 0.173). Living in a low-income neighborhood is associated with major depressive episodes. Our results suggest that this association is partly explained by chronic diseases, lifestyle factors, stress and poor social participation, and thereby partly confirm conceptual model 1. Our results do not support conceptual model 2 and 3.
Health literacy and public health: A systematic review and integration of definitions and models

PubMed Central

2012-01-01

Background Health literacy concerns the knowledge and competences of persons to meet the complex demands of health in modern society. Although its importance is increasingly recognised, there is no consensus about the definition of health literacy or about its conceptual dimensions, which limits the possibilities for measurement and comparison. The aim of the study is to review definitions and models on health literacy to develop an integrated definition and conceptual model capturing the most comprehensive evidence-based dimensions of health literacy. Methods A systematic literature review was performed to identify definitions and conceptual frameworks of health literacy. A content analysis of the definitions and conceptual frameworks was carried out to identify the central dimensions of health literacy and develop an integrated model. Results The review resulted in 17 definitions of health literacy and 12 conceptual models. Based on the content analysis, an integrative conceptual model was developed containing 12 dimensions referring to the knowledge, motivation and competencies of accessing, understanding, appraising and applying health-related information within the healthcare, disease prevention and health promotion setting, respectively. Conclusions Based upon this review, a model is proposed integrating medical and public health views of health literacy. The model can serve as a basis for developing health literacy enhancing interventions and provide a conceptual basis for the development and validation of measurement tools, capturing the different dimensions of health literacy within the healthcare, disease prevention and health promotion settings. PMID:22276600
Novel application of red-light runner proneness theory within traffic microsimulation to an actual signal junction.

PubMed

Bell, Margaret Carol; Galatioto, Fabio; Giuffrè, Tullio; Tesoriere, Giovanni

2012-05-01

Building on previous research a conceptual framework, based on potential conflicts analysis, has provided a quantitative evaluation of 'proneness' to red-light running behaviour at urban signalised intersections of different geometric, flow and driver characteristics. The results provided evidence that commonly used violation rates could cause inappropriate evaluation of the extent of the red-light running phenomenon. Initially, an in-depth investigation of the functional form of the mathematical relationship between the potential and actual red-light runners was carried out. The application of the conceptual framework was tested on a signalised intersection in order to quantify the proneness to red-light running. For the particular junction studied proneness for daytime was found to be 0.17 north and 0.16 south for opposing main road approaches and 0.42 east and 0.59 west for the secondary approaches. Further investigations were carried out using a traffic microsimulation model, to explore those geometric features and traffic volumes (arrival patterns at the stop-line) that significantly affect red-light running. In this way the prediction capability of the proposed potential conflict model was improved. A degree of consistency in the measured and simulated red-light running was observed and the conceptual framework was tested through a sensitivity analysis applied to different stop-line positions and traffic volume variations. The microsimulation, although at its early stages of development, has shown promise in its ability to model unintentional red light running behaviour and following further work through application to other junctions, potentially provides a tool for evaluation of alternative junction designs on proneness. In brief, this paper proposes and applies a novel approach to model red-light running using a microsimulation and demonstrates consistency with the observed and theoretical results. Copyright © 2011 Elsevier Ltd. All rights reserved.
Assessing Competence in Collaborative Case Conceptualization: Development and Preliminary Psychometric Properties of the Collaborative Case Conceptualization Rating Scale (CCC-RS).

PubMed

Kuyken, Willem; Beshai, Shadi; Dudley, Robert; Abel, Anna; Görg, Nora; Gower, Philip; McManus, Freda; Padesky, Christine A

2016-03-01

Case conceptualization is assumed to be an important element in cognitive-behavioural therapy (CBT) because it describes and explains clients' presentations in ways that inform intervention. However, we do not have a good measure of competence in CBT case conceptualization that can be used to guide training and elucidate mechanisms. The current study addresses this gap by describing the development and preliminary psychometric properties of the Collaborative Case Conceptualization - Rating Scale (CCC-RS; Padesky et al., 2011). The CCC-RS was developed in accordance with the model posited by Kuyken et al. (2009). Data for this study (N = 40) were derived from a larger trial (Wiles et al., 2013) with adults suffering from resistant depression. Internal consistency and inter-rater reliability were calculated. Further, and as a partial test of the scale's validity, Pearson's correlation coefficients were obtained for scores on the CCC-RS and key scales from the Cognitive Therapy Scale - Revised (CTS-R; Blackburn et al., 2001). The CCC-RS showed excellent internal consistency (α = .94), split-half (.82) and inter-rater reliabilities (ICC =.84). Total scores on the CCC-RS were significantly correlated with scores on the CTS-R (r = .54, p < .01). Moreover, the Collaboration subscale of the CCC-RS was significantly correlated (r = .44) with its counterpart of the CTS-R in a theoretically predictable manner. These preliminary results indicate that the CCC-RS is a reliable measure with adequate face, content and convergent validity. Further research is needed to replicate and extend the current findings to other facets of validity.
A Systematic Review of Conceptual Frameworks of Medical Complexity and New Model Development.

PubMed

Zullig, Leah L; Whitson, Heather E; Hastings, Susan N; Beadles, Chris; Kravchenko, Julia; Akushevich, Igor; Maciejewski, Matthew L

2016-03-01

Patient complexity is often operationalized by counting multiple chronic conditions (MCC) without considering contextual factors that can affect patient risk for adverse outcomes. Our objective was to develop a conceptual model of complexity addressing gaps identified in a review of published conceptual models. We searched for English-language MEDLINE papers published between 1 January 2004 and 16 January 2014. Two reviewers independently evaluated abstracts and all authors contributed to the development of the conceptual model in an iterative process. From 1606 identified abstracts, six conceptual models were selected. One additional model was identified through reference review. Each model had strengths, but several constructs were not fully considered: 1) contextual factors; 2) dynamics of complexity; 3) patients' preferences; 4) acute health shocks; and 5) resilience. Our Cycle of Complexity model illustrates relationships between acute shocks and medical events, healthcare access and utilization, workload and capacity, and patient preferences in the context of interpersonal, organizational, and community factors. This model may inform studies on the etiology of and changes in complexity, the relationship between complexity and patient outcomes, and intervention development to improve modifiable elements of complex patients.
The ecology and evolution of temperature-dependent reaction norms for sex determination in reptiles: a mechanistic conceptual model.

PubMed

Pezaro, Nadav; Doody, J Sean; Thompson, Michael B

2017-08-01

Sex-determining mechanisms are broadly categorised as being based on either genetic or environmental factors. Vertebrate sex determination exhibits remarkable diversity but displays distinct phylogenetic patterns. While all eutherian mammals possess XY male heterogamety and female heterogamety (ZW) is ubiquitous in birds, poikilothermic vertebrates (fish, amphibians and reptiles) exhibit multiple genetic sex-determination (GSD) systems as well as environmental sex determination (ESD). Temperature is the factor controlling ESD in reptiles and temperature-dependent sex determination (TSD) in reptiles has become a focal point in the study of this phenomenon. Current patterns of climate change may cause detrimental skews in the population sex ratios of reptiles exhibiting TSD. Understanding the patterns of variation, both within and among populations and linking such patterns with the selection processes they are associated with, is the central challenge of research aimed at predicting the capacity of populations to adapt to novel conditions. Here we present a conceptual model that innovates by defining an individual reaction norm for sex determination as a range of incubation temperatures. By deconstructing individual reaction norms for TSD and revealing their underlying interacting elements, we offer a conceptual solution that explains how variation among individual reaction norms can be inferred from the pattern of population reaction norms. The model also links environmental variation with the different patterns of TSD and describes the processes from which they may arise. Specific climate scenarios are singled out as eco-evolutionary traps that may lead to demographic extinction or a transition to either male or female heterogametic GSD. We describe how the conceptual principles can be applied to interpret TSD data and to explain the adaptive capacity of TSD to climate change as well as its limits and the potential applications for conservation and management programs. © 2016 Cambridge Philosophical Society.
Open Vehicle Sketch Pad Aircraft Modeling Strategies

NASA Technical Reports Server (NTRS)

Hahn, Andrew S.

2013-01-01

Geometric modeling of aircraft during the Conceptual design phase is very different from that needed for the Preliminary or Detailed design phases. The Conceptual design phase is characterized by the rapid, multi-disciplinary analysis of many design variables by a small engineering team. The designer must walk a line between fidelity and productivity, picking tools and methods with the appropriate balance of characteristics to achieve the goals of the study, while staying within the available resources. Identifying geometric details that are important, and those that are not, is critical to making modeling and methodology choices. This is true for both the low-order analysis methods traditionally used in Conceptual design as well as the highest-order analyses available. This paper will highlight some of Conceptual design's characteristics that drive the designer s choices as well as modeling examples for several aircraft configurations using the open source version of the Vehicle Sketch Pad (Open VSP) aircraft Conceptual design geometry modeler.
Post-audits of Three Groundwater Models for Evaluating Plume Containment

NASA Astrophysics Data System (ADS)

Andersen, P. F.

2003-12-01

Groundwater extraction systems were designed using numerical models at three sites within a U.S. Army Ammunition Plant in Tennessee. Each site, and hence model, has unique qualities such as boundary conditions, extensiveness of the contaminant plume, and quantity and quality of hydrogeologic data. Performance of each of these extraction systems has been evaluated throughout their operation, providing an opportunity to perform post-audits on the accuracy of the groundwater models that were used in their design. Areas of comparison between the models and the observed response in the natural systems include hydraulic head, drawdown, horizontal and vertical gradients, and extent of capture zones. The results of the post-audits show the importance of using all available data in the construction and calibration of the models, the importance of having sufficient data, and the critical nature of an accurate conceptual model. The post-audits also show that although it may be possible to assess the accuracy of the model predictions, it is often not possible to explain the reasons for discrepancies between predicted and observed results. From a practical perspective, parameter uncertainty is important to account for in the development of the models and subsequent design of the extraction systems.
[Psychosocial factors at work and cardiovascular diseases: contribution of the Effort-Reward Imbalance model].

PubMed

Niedhammer, I; Siegrist, J

1998-11-01

The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.
Synthetic calibration of a Rainfall-Runoff Model

USGS Publications Warehouse

Thompson, David B.; Westphal, Jerome A.; ,

1990-01-01

A method for synthetically calibrating storm-mode parameters for the U.S. Geological Survey's Precipitation-Runoff Modeling System is described. Synthetic calibration is accomplished by adjusting storm-mode parameters to minimize deviations between the pseudo-probability disributions represented by regional regression equations and actual frequency distributions fitted to model-generated peak discharge and runoff volume. Results of modeling storm hydrographs using synthetic and analytic storm-mode parameters are presented. Comparisons are made between model results from both parameter sets and between model results and observed hydrographs. Although mean storm runoff is reproducible to within about 26 percent of the observed mean storm runoff for five or six parameter sets, runoff from individual storms is subject to large disparities. Predicted storm runoff volume ranged from 2 percent to 217 percent of commensurate observed values. Furthermore, simulation of peak discharges was poor. Predicted peak discharges from individual storm events ranged from 2 percent to 229 percent of commensurate observed values. The model was incapable of satisfactorily executing storm-mode simulations for the study watersheds. This result is not considered a particular fault of the model, but instead is indicative of deficiencies in similar conceptual models.
Challenges in Requirements Engineering: A Research Agenda for Conceptual Modeling

NASA Astrophysics Data System (ADS)

March, Salvatore T.; Allen, Gove N.

Domains for which information systems are developed deal primarily with social constructions—conceptual objects and attributes created by human intentions and for human purposes. Information systems play an active role in these domains. They document the creation of new conceptual objects, record and ascribe values to their attributes, initiate actions within the domain, track activities performed, and infer conclusions based on the application of rules that govern how the domain is affected when socially-defined and identified causal events occur. Emerging applications of information technologies evaluate such business rules, learn from experience, and adapt to changes in the domain. Conceptual modeling grammars aimed at representing their system requirements must include conceptual objects, socially-defined events, and the rules pertaining to them. We identify challenges to conceptual modeling research and pose an ontology of the artificial as a step toward meeting them.
Prediction of HIV Sexual Risk Behaviors among Disadvantaged African American Adults using a Syndemic Conceptual Framework

PubMed Central

Nehl, Eric J.; Klein, Hugh; Sterk, Claire E.; Elifson, Kirk W.

2015-01-01

The focus of this paper is on HIV sexual risk taking among a community-based sample of disadvantaged African American adults. The objective is to examine multiple factors associated with sexual HIV risk behaviors within a syndemic conceptual framework. Face-to-face, computer-assisted, structured interviews were conducted with 1,535 individuals in Atlanta, Georgia. Bivariate analyses indicated a high level of relationships among the HIV sexual risks and other factors. Results from multivariate models indicated that gender, sexual orientation, relationship status, self-esteem, condom use self-efficacy, sex while the respondent was high, and sex while the partner was high were significant predictors of condomless sex. Additionally, a multivariate additive model of risk behaviors indicated that the number of health risks significantly increased the risk of condomless sex. This intersection of HIV sexual risk behaviors and their associations with various other behavioral, socio-demographics, and psychological functioning factors helps explain HIV risk-taking among this sample of African American adults and highlights the need for research and practice that accounts for multiple health behaviors and problems. PMID:26188618
Psychological need thwarting in the sport context: assessing the darker side of athletic experience.

PubMed

Bartholomew, Kimberley J; Ntoumanis, Nikos; Ryan, Richard M; Thøgersen-Ntoumani, Cecilie

2011-02-01

Research in self-determination theory (Ryan & Deci, 2002) has shown that satisfaction of autonomy, competence, and relatedness needs in sport contexts is associated with enhanced engagement, performance, and well-being. This article outlines the initial development of a multidimensional measure designed to assess psychological need thwarting, an under-studied area of conceptual and practical importance. Study 1 generated a pool of items designed to tap the negative experiential state that occurs when athletes perceive their needs for autonomy, competence, and relatedness to be actively undermined. Study 2 tested the factorial structure of the questionnaire using confirmatory factor analysis. The supported model comprised 3 factors, which represented the hypothesized interrelated dimensions of need thwarting. The model was refined and cross-validated using an independent sample in Study 3. Overall, the psychological need thwarting scale (PNTS) demonstrated good content, factorial, and predictive validity, as well as internal consistency and invariance across gender, sport type, competitive level, and competitive experience. The conceptualization of psychological need thwarting is discussed, and suggestions are made regarding the use of the PNTS in research pertaining to the darker side of sport participation.
Ranking malaria risk factors to guide malaria control efforts in African highlands.

PubMed

Protopopoff, Natacha; Van Bortel, Wim; Speybroeck, Niko; Van Geertruyden, Jean-Pierre; Baza, Dismas; D'Alessandro, Umberto; Coosemans, Marc

2009-11-25

Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through "classification and regression trees", an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density. In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors.
Application of the human needs conceptual model to dental hygiene practice.

PubMed

Darby, M L; Walsh, M M

2000-01-01

The Human Needs Conceptual Model is relevant to dental hygiene because of the need for dental hygienists to be client focused, humanistic, and accountable in practice. Application of the Human Needs Conceptual Model provides a formal framework for identifying and understanding the unique needs of the client that can be met through dental hygiene care. Practitioners find that the Human Needs Conceptual Model can not only help them in assessment and diagnosis, but also in client education, decision-making, care implementation, and the evaluation of treatment outcomes. By using the model, the dental hygienist is able to manage client care humanistically and holistically, and ensure that care is client-centered rather than task-oriented. With the model, a professional practice can be made operational.
Conceptualizing race in economic models of medical utilization: a case study of community-based elders and the emergency room.

PubMed Central

White-Means, S I

1995-01-01

There is no consensus on the appropriate conceptualization of race in economic models of health care. This is because race is rarely the primary focus for analysis of the market. This article presents an alternative framework for conceptualizing race in health economic models. A case study is analyzed to illustrate the value of the alternative conceptualization. The case study findings clearly document the importance of model stratification according to race. Moreover, the findings indicate that empirical results are improved when medical utilization models are refined in a way that reflects the unique experiences of the population that is studied. PMID:7721593
Transport and concentration controls for chloride, strontium, potassium and lead in Uvas Creek, a small cobble-bed stream in Santa Clara County, California, U.S.A. 2. Mathematical modeling

USGS Publications Warehouse

Jackman, A.P.; Walters, R.A.; Kennedy, V.C.

1984-01-01

Three models describing solute transport of conservative ion species and another describing transport of species which adsorb linearly and reversibly on bed sediments are developed and tested. The conservative models are based on three different conceptual models of the transient storage of solute in the bed. One model assumes the bed to be a well-mixed zone with flux of solute into the bed proportional to the difference between stream concentration and bed concentration. The second model assumes solute in the bed is transported by a vertical diffusion process described by Fick's law. The third model assumes that convection occurs in a selected portion of the bed while the mechanism of the first model functions everywhere. The model for adsorbing species assumes that the bed consists of particles of uniform size with the rate of uptake controlled by an intraparticle diffusion process. All models are tested using data collected before, during and after a 24-hr. pulse injection of chloride, strontium, potassium and lead ions into Uvas Creek near Morgan Hill, California, U.S.A. All three conservative models accurately predict chloride ion concentrations in the stream. The model employing the diffusion mechanism for bed transport predicts better than the others. The adsorption model predicts both strontium and potassium ion concentrations well during the injection of the pulse but somewhat overestimates the observed concentrations after the injection ceases. The overestimation may be due to the convection of solute deep into the bed where it is retained longer than the 3-week post-injection observation period. The model, when calibrated for strontium, predicts potassium equally well when the adsorption equilibrium constant for strontium is replaced by that for potassium. ?? 1984.
A Probabilistic Performance Assessment Study of Potential Low-Level Radioactive Waste Disposal Sites in Taiwan

NASA Astrophysics Data System (ADS)

Knowlton, R. G.; Arnold, B. W.; Mattie, P. D.; Kuo, M.; Tien, N.

2006-12-01

For several years now, Taiwan has been engaged in a process to select a low-level radioactive waste (LLW) disposal site. Taiwan is generating LLW from operational and decommissioning wastes associated with nuclear power reactors, as well as research, industrial, and medical radioactive wastes. The preliminary selection process has narrowed the search to four potential candidate sites. These sites are to be evaluated in a performance assessment analysis to determine the likelihood of meeting the regulatory criteria for disposal. Sandia National Laboratories and Taiwan's Institute of Nuclear Energy Research have been working together to develop the necessary performance assessment methodology and associated computer models to perform these analyses. The methodology utilizes both deterministic (e.g., single run) and probabilistic (e.g., multiple statistical realizations) analyses to achieve the goals. The probabilistic approach provides a means of quantitatively evaluating uncertainty in the model predictions and a more robust basis for performing sensitivity analyses to better understand what is driving the dose predictions from the models. Two types of disposal configurations are under consideration: a shallow land burial concept and a cavern disposal concept. The shallow land burial option includes a protective cover to limit infiltration potential to the waste. Both conceptual designs call for the disposal of 55 gallon waste drums within concrete lined trenches or tunnels, and backfilled with grout. Waste emplaced in the drums may be solidified. Both types of sites are underlain or placed within saturated fractured bedrock material. These factors have influenced the conceptual model development of each site, as well as the selection of the models to employ for the performance assessment analyses. Several existing codes were integrated in order to facilitate a comprehensive performance assessment methodology to evaluate the potential disposal sites. First, a need existed to simulate the failure processes of the waste containers, with subsequent leaching of the waste form to the underlying host rock. The Breach, Leach, and Transport Multiple Species (BLT-MS) code was selected to meet these needs. BLT-MS also has a 2-D finite-element advective-dispersive transport module, with radionuclide in-growth and decay. BLT-MS does not solve the groundwater flow equation, but instead requires the input of Darcy flow velocity terms. These terms were abstracted from a groundwater flow model using the FEHM code. For the shallow land burial site, the HELP code was also used to evaluate the performance of the protective cover. The GoldSim code was used for two purposes: quantifying uncertainties in the predictions, and providing a platform to evaluate an alternative conceptual model involving matrix-diffusion transport. Results of the preliminary performance assessment analyses using examples to illustrate the computational framework will be presented. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE AC04 94AL85000.

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