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Goal importance within planned behaviour theory as 'the' predictor of study behaviour in college.

PubMed

Sideridis, G D; Kaissidis-Rodafinos, A

2001-12-01

The theory of planned behaviour has been rarely used for the explanation of student study behaviour and achievement. Although successful, the theory has been criticised for not including important cognitions, so goal importance was added in the present study. Goal importance refers to the weight-importance an individual assigns towards achieving a specific goal (Hollenbeck & Williams, 1987). The purpose of Study 1 was to explain the study behaviour habits of first year college students, using a) Ajzen and Madden's (1986) theory of planned behaviour, and b) planned behaviour with the addition of goal importance. The purpose of Study 2 was to replicate the findings of Study 1. The sample of Study 1 included 149 first year students of an American College located in northern Greece. Study 2 included 85 first year students of the same institution. The students in Study 1 were given a questionnaire four weeks prior to the end of the spring 1998 semester, and those in Study 2 in the autumn of 1998, including all elements of the theory of planned behaviour and goal importance. The data were modelled using Covariance Structural Modelling (CSM) and EQS 5.7b (Bentler, 1998). The planned behaviour model was not well supported in Study 1 providing a Comparative Fit Index (CFI) of.83. However, when goal importance was included in the equation, the resulting structural model produced a CFI of.94. The final structural model of Study 1 was re-tested with the sample of Study 2 and produced a CFI =.95. Findings suggest that goal importance is the causal agent in directing all elements necessary to achieve high levels of study behaviour. Future studies should examine the role of goal importance with other behaviours as well.
Ionospheric Outflow in the Magnetosphere: Circulation and Consequences

NASA Astrophysics Data System (ADS)

Welling, D. T.; Liemohn, M. W.

2017-12-01

Including ionospheric outflow in global magnetohydrodynamic models of near-Earth outer space has become an important step towards understanding the role of this plasma source in the magnetosphere. Such simulations have revealed the importance of outflow in populating the plasma sheet and inner magnetosphere as a function of outflow source characteristics. More importantly, these experiments have shown how outflow can control global dynamics, including tail dynamics and dayside reconnection rate. The broad impact of light and heavy ion outflow can create non-linear feedback loops between outflow and the magnetosphere. This paper reviews some of the most important revelations from global magnetospheric modeling that includes ionospheric outflow of light and heavy ions. It also introduces new advances in outflow modeling and coupling outflow to the magnetosphere.
Modeling the rejection probability in plant imports.

PubMed

Surkov, I V; van der Werf, W; van Kooten, O; Lansink, A G J M Oude

2008-06-01

Phytosanitary inspection of imported plants and flowers is a major means for preventing pest invasions through international trade, but in a majority of countries availability of resources prevents inspection of all imports. Prediction of the likelihood of pest infestation in imported shipments could help maximize the efficiency of inspection by targeting inspection on shipments with the highest likelihood of infestation. This paper applies a multinomial logistic (MNL) regression model to data on import inspections of ornamental plant commodities in the Netherlands from 1998 to 2001 to investigate whether it is possible to predict the probability that a shipment will be (i) accepted for import, (ii) rejected for import because of detected pests, or (iii) rejected due to other reasons. Four models were estimated: (i) an all-species model, including all plant imports (136,251 shipments) in the data set, (ii) a four-species model, including records on the four ornamental commodities that accounted for 28.9% of inspected and 49.5% of rejected shipments, and two models for single commodities with large import volumes and percentages of rejections, (iii) Dianthus (16.9% of inspected and 46.3% of rejected shipments), and (iv) Chrysanthemum (6.9 and 8.6%, respectively). All models were highly significant (P < 0.001). The models for Dianthus and Chrysanthemum and for the set of four ornamental commodities showed a better fit to data than the model for all ornamental commodities. Variables that characterized the imported shipment's region of origin, the shipment's size, the company that imported the shipment, and season and year of import, were significant in most of the estimated models. The combined results of this study suggest that the MNL model can be a useful tool for modeling the probability of rejecting imported commodities even with a small set of explanatory variables. The MNL model can be helpful in better targeting of resources for import inspection. The inspecting agencies could enable development of these models by appropriately recording inspection results.
Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system

USGS Publications Warehouse

Tiedeman, C.R.; Hill, M.C.; D'Agnese, F. A.; Faunt, C.C.

2003-01-01

Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new "value of improved information" (VOII) method presented here, which includes the effects of parameter correlation in addition to individual parameter uncertainty and prediction sensitivity. In this work, the PSS and VOII methods are demonstrated and evaluated using a model of the Death Valley regional groundwater flow system. The predictions of interest are advective transport paths originating at sites of past underground nuclear testing. Results show that for two paths evaluated the most important parameters include a subset of five or six of the 23 defined model parameters. Some of the parameters identified as most important are associated with flow system attributes that do not lie in the immediate vicinity of the paths. Results also indicate that the PSS and VOII methods can identify different important parameters. Because the methods emphasize somewhat different criteria for parameter importance, it is suggested that parameters identified by both methods be carefully considered in subsequent data collection efforts aimed at improving model predictions.
Analysis Monthly Import of Palm Oil Products Using Box-Jenkins Model

NASA Astrophysics Data System (ADS)

Ahmad, Nurul F. Y.; Khalid, Kamil; Saifullah Rusiman, Mohd; Ghazali Kamardan, M.; Roslan, Rozaini; Che-Him, Norziha

2018-04-01

The palm oil industry has been an important component of the national economy especially the agriculture sector. The aim of this study is to identify the pattern of import of palm oil products, to model the time series using Box-Jenkins model and to forecast the monthly import of palm oil products. The method approach is included in the statistical test for verifying the equivalence model and statistical measurement of three models, namely Autoregressive (AR) model, Moving Average (MA) model and Autoregressive Moving Average (ARMA) model. The model identification of all product import palm oil is different in which the AR(1) was found to be the best model for product import palm oil while MA(3) was found to be the best model for products import palm kernel oil. For the palm kernel, MA(4) was found to be the best model. The results forecast for the next four months for products import palm oil, palm kernel oil and palm kernel showed the most significant decrease compared to the actual data.
Mouse Models for Unraveling the Importance of Diet in Colon Cancer Prevention

PubMed Central

Tammariello, Alexandra E.; Milner, John A.

2010-01-01

Diet and genetics are both considered important risk determinants for colorectal cancer, a leading cause of death worldwide. Several genetically engineered mouse models have been created, including the ApcMin mouse, to aid in the identification of key cancer related processes and to assist with the characterization of environmental factors, including the diet, which influence risk. Current research using these models provides evidence that several bioactive food components can inhibit genetically predisposed colorectal cancer, while others increase risk. Specifically, calorie restriction or increased exposure to n-3 fatty acids, sulforaphane, chafuroside, curcumin, and dibenzoylmethane were reported protective. Total fat, calories and all-trans retinoic acid are associated with an increased risk. Unraveling the importance of specific dietary components in these models is complicated by the basal diet used, the quantity of test components provided, and interactions among food components. Newer models are increasingly available to evaluate fundamental cellular processes, including DNA mismatch repair, immune function and inflammation as markers for colon cancer risk. Unfortunately, these models have been used infrequently to examine the influence of specific dietary components. The enhanced use of these models can shed mechanistic insights about the involvement of specific bioactive food and components and energy as determinants of colon cancer risk. However, the use of available mouse models to exactly represent processes important to human gastrointestinal cancers will remain a continued scientific challenge. PMID:20122631
Using Models to Understand Sea Level Rise

ERIC Educational Resources Information Center

Barth-Cohen, Lauren; Medina, Edwing

2017-01-01

Important science phenomena--such as atomic structure, evolution, and climate change--are often hard to observe directly. That's why an important scientific practice is to use scientific models to represent one's current understanding of a system. Using models has been included as an essential science and engineering practice in the "Next…
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.
The Importance of State and Context in Safe Interoperable Medical Systems

PubMed Central

Jaffe, Michael B.; Robkin, Michael; Rausch, Tracy; Arney, David; Goldman, Julian M.

2016-01-01

This paper describes why “device state” and “patient context” information are necessary components of device models for safe interoperability. This paper includes a discussion of the importance of describing the roles of devices with respect to interactions (including human user workflows involving devices, and device to device communication) within a system, particularly those intended for use at the point-of-care, and how this role information is communicated. In addition, it describes the importance of clinical scenarios in creating device models for interoperable devices. PMID:27730013
Estimation of source locations of total gaseous mercury measured in New York State using trajectory-based models

NASA Astrophysics Data System (ADS)

Han, Young-Ji; Holsen, Thomas M.; Hopke, Philip K.

Ambient gaseous phase mercury concentrations (TGM) were measured at three locations in NY State including Potsdam, Stockton, and Sterling from May 2000 to March 2005. Using these data, three hybrid receptor models incorporating backward trajectories were used to identify source areas for TGM. The models used were potential source contribution function (PSCF), residence time weighted concentration (RTWC), and simplified quantitative transport bias analysis (SQTBA). Each model was applied using multi-site measurements to resolve the locations of important mercury sources for New York State. PSCF results showed that southeastern New York, Ohio, Indiana, Tennessee, Louisiana, and Virginia were important TGM source areas for these sites. RTWC identified Canadian sources including the metal production facilities in Ontario and Quebec, but US regional sources including the Ohio River Valley were also resolved. Sources in southeastern NY, Massachusetts, western Pennsylvania, Indiana, and northern Illinois were identified to be significant by SQTBA. The three modeling results were combined to locate the most important probable source locations, and those are Ohio, Indiana, Illinois, and Wisconsin. The Atlantic Ocean was suggested to be a possible source as well.
Effects of agri-environmental schemes on farmland birds: do food availability measurements improve patterns obtained from simple habitat models?

PubMed Central

Ponce, Carlos; Bravo, Carolina; Alonso, Juan Carlos

2014-01-01

Studies evaluating agri-environmental schemes (AES) usually focus on responses of single species or functional groups. Analyses are generally based on simple habitat measurements but ignore food availability and other important factors. This can limit our understanding of the ultimate causes determining the reactions of birds to AES. We investigated these issues in detail and throughout the main seasons of a bird's annual cycle (mating, postfledging and wintering) in a dry cereal farmland in a Special Protection Area for farmland birds in central Spain. First, we modeled four bird response parameters (abundance, species richness, diversity and “Species of European Conservation Concern” [SPEC]-score), using detailed food availability and vegetation structure measurements (food models). Second, we fitted new models, built using only substrate composition variables (habitat models). Whereas habitat models revealed that both, fields included and not included in the AES benefited birds, food models went a step further and included seed and arthropod biomass as important predictors, respectively, in winter and during the postfledging season. The validation process showed that food models were on average 13% better (up to 20% in some variables) in predicting bird responses. However, the cost of obtaining data for food models was five times higher than for habitat models. This novel approach highlighted the importance of food availability-related causal processes involved in bird responses to AES, which remained undetected when using conventional substrate composition assessment models. Despite their higher costs, measurements of food availability add important details to interpret the reactions of the bird community to AES interventions and thus facilitate evaluating the real efficiency of AES programs. PMID:25165523
Stochasticity and determinism in models of hematopoiesis.

PubMed

Kimmel, Marek

2014-01-01

This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.
Issues and Importance of "Good" Starting Points for Nonlinear Regression for Mathematical Modeling with Maple: Basic Model Fitting to Make Predictions with Oscillating Data

ERIC Educational Resources Information Center

Fox, William

2012-01-01

The purpose of our modeling effort is to predict future outcomes. We assume the data collected are both accurate and relatively precise. For our oscillating data, we examined several mathematical modeling forms for predictions. We also examined both ignoring the oscillations as an important feature and including the oscillations as an important…
Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519
The role of non-epistemic values in engineering models.

PubMed

Diekmann, Sven; Peterson, Martin

2013-03-01

We argue that non-epistemic values, including moral ones, play an important role in the construction and choice of models in science and engineering. Our main claim is that non-epistemic values are not only "secondary values" that become important just in case epistemic values leave some issues open. Our point is, on the contrary, that non-epistemic values are as important as epistemic ones when engineers seek to develop the best model of a process or problem. The upshot is that models are neither value-free, nor depend exclusively on epistemic values or use non-epistemic values as tie-breakers.
Population pharmacokinetic characterization of BAY 81-8973, a full-length recombinant factor VIII: lessons learned - importance of including samples with factor VIII levels below the quantitation limit.

PubMed

Garmann, D; McLeay, S; Shah, A; Vis, P; Maas Enriquez, M; Ploeger, B A

2017-07-01

The pharmacokinetics (PK), safety and efficacy of BAY 81-8973, a full-length, unmodified, recombinant human factor VIII (FVIII), were evaluated in the LEOPOLD trials. The aim of this study was to develop a population PK model based on pooled data from the LEOPOLD trials and to investigate the importance of including samples with FVIII levels below the limit of quantitation (BLQ) to estimate half-life. The analysis included 1535 PK observations (measured by the chromogenic assay) from 183 male patients with haemophilia A aged 1-61 years from the 3 LEOPOLD trials. The limit of quantitation was 1.5 IU dL -1 for the majority of samples. Population PK models that included or excluded BLQ samples were used for FVIII half-life estimations, and simulations were performed using both estimates to explore the influence on the time below a determined FVIII threshold. In the data set used, approximately 16.5% of samples were BLQ, which is not uncommon for FVIII PK data sets. The structural model to describe the PK of BAY 81-8973 was a two-compartment model similar to that seen for other FVIII products. If BLQ samples were excluded from the model, FVIII half-life estimations were longer compared with a model that included BLQ samples. It is essential to assess the importance of BLQ samples when performing population PK estimates of half-life for any FVIII product. Exclusion of BLQ data from half-life estimations based on population PK models may result in an overestimation of half-life and underestimation of time under a predetermined FVIII threshold, resulting in potential underdosing of patients. © 2017 Bayer AG. Haemophilia Published by John Wiley & Sons Ltd.
From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

PubMed Central

Kreft, Jan-Ulrich; Plugge, Caroline M.; Prats, Clara; Leveau, Johan H. J.; Zhang, Weiwen; Hellweger, Ferdi L.

2017-01-01

Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy. PMID:29230200
Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...
Titan I propulsion system modeling and possible performance improvements

NASA Astrophysics Data System (ADS)

Giusti, Oreste

This thesis features the Titan I propulsion systems and offers data-supported suggestions for improvements to increase performance. The original propulsion systems were modeled both graphically in CAD and via equations. Due to the limited availability of published information, it was necessary to create a more detailed, secondary set of models. Various engineering equations---pertinent to rocket engine design---were implemented in order to generate the desired extra detail. This study describes how these new models were then imported into the ESI CFD Suite. Various parameters are applied to these imported models as inputs that include, for example, bi-propellant combinations, pressure, temperatures, and mass flow rates. The results were then processed with ESI VIEW, which is visualization software. The output files were analyzed for forces in the nozzle, and various results were generated, including sea level thrust and ISP. Experimental data are provided to compare the original engine configuration models to the derivative suggested improvement models.
EDMS Multi-year Validation Plan

DOT National Transportation Integrated Search

2001-06-01

The Emissions and Dispersion Modeling System (EDMS) is the air quality model required for use on airport projects by the Federal Aviation Administration (FAA). This model has continued to be improved and recently has included several important enhanc...

A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities.

PubMed

Kwok, Kin On; Read, Jonathan M; Tang, Arthur; Chen, Hong; Riley, Steven; Kam, Kai Man

2018-04-18

Non-hospital residential facilities are important reservoirs for MRSA transmission. However, conclusions and public health implications drawn from the many mathematical models depicting nosocomial MRSA transmission may not be applicable to these settings. Therefore, we reviewed the MRSA transmission dynamics studies in defined non-hospital residential facilities to: (1) provide an overview of basic epidemiology which has been addressed; (2) identify future research direction; and (3) improve future model implementation. A review was conducted by searching related keywords in PUBMED without time restriction as well as internet searches via Google search engine. We included only articles describing the epidemiological transmission pathways of MRSA/community-associated MRSA within and between defined non-hospital residential settings. Among the 10 included articles, nursing homes (NHs) and correctional facilities (CFs) were two settings considered most frequently. Importation of colonized residents was a plausible reason for MRSA outbreaks in NHs, where MRSA was endemic without strict infection control interventions. The importance of NHs over hospitals in increasing nosocomial MRSA prevalence was highlighted. Suggested interventions in NHs included: appropriate staffing level, screening and decolonizing, and hand hygiene. On the other hand, the small population amongst inmates in CFs has no effect on MRSA community transmission. Included models ranged from system-level compartmental models to agent-based models. There was no consensus over the course of disease progression in these models, which were mainly featured with NH residents /CF inmates/ hospital patients as transmission pathways. Some parameters used by these models were outdated or unfit. Importance of NHs has been highlighted from these current studies addressing scattered aspects of MRSA epidemiology. However, the wide variety of non-hospital residential settings suggest that more work is needed before robust conclusions can be drawn. Learning from existing work for hospitals, we identified critical future research direction in this area from infection control, ecological and economic perspectives. From current model deficiencies, we suggest more transmission pathways be specified to depict MRSA transmission, and further empirical studies be stressed to support evidence-based mathematical models of MRSA in non-hospital facilities. Future models should be ready to cope with the aging population structure.
Evaluation of the Community Multiscale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2016, CMAQ version 5.1.1 will be released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.1 (the current public release version of the CMAQ model), and additionally include updates to other portions of the code. Some specific model updates include a new implementation of the wind-blown dust calculation in CMAQv5.1.1 which fixes several bugs that were identified in the current implementation of wind-blown dust in CMAQv5.1. Several other major updates to the model include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry), which is particularly important for hemispheric applications of the CMAQ model, as halogen chemistry is need to accurately simulation the destruction of ozone over the ocean; and the new carbon bond 6 (CB6) chemical mechanism. Several annual, and numerous episodic, CMAQv5.1.1 simulations will be performed to assess the impact of these
Transcriptome analysis of Stagonospora nodorum: gene models, effectors, metabolism and pantothenate dispensability

USDA-ARS?s Scientific Manuscript database

The wheat pathogen Stagonospora nodorum, causal organism of the wheat disease Stagonospora nodorum blotch, has emerged as a model for the Dothideomycetes, a large fungal taxon that includes many important plant pathogens. The initial annotation of the genome assembly included 16 586 nuclear gene mod...
Transcriptome analysis of Stagonospora nodorum; gene models, effectors, metabolism and pantothenate dispensability

USDA-ARS?s Scientific Manuscript database

The wheat pathogen Stagonospora nodorum, causal organism of the wheat disease Stagonospora nodorum blotch, has emerged as a model for the Dothideomycetes, a large fungal taxon that includes many important plant pathogens. The initial annotation of the genome assembly included 16 586 nuclear gene mod...
A Multivariate Model of Parent-Adolescent Relationship Variables in Early Adolescence

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2011-01-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle…
Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model

USGS Publications Warehouse

Benoy, Glenn A.; Jenkinson, R. Wayne; Robertson, Dale M.; Saad, David A.

2016-01-01

Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.
Fluid dynamic modeling of junctions in internal combustion engine inlet and exhaust systems

NASA Astrophysics Data System (ADS)

Chalet, David; Chesse, Pascal

2010-10-01

The modeling of inlet and exhaust systems of internal combustion engine is very important in order to evaluate the engine performance. This paper presents new pressure losses models which can be included in a one dimensional engine simulation code. In a first part, a CFD analysis is made in order to show the importance of the density in the modeling approach. Then, the CFD code is used, as a numerical test bench, for the pressure losses models development. These coefficients depend on the geometrical characteristics of the junction and an experimental validation is made with the use of a shock tube test bench. All the models are then included in the engine simulation code of the laboratory. The numerical calculation of unsteady compressible flow, in each pipe of the inlet and exhaust systems, is made and the calculated engine torque is compared with experimental measurements.
Finite-element modeling of the human neurocranium under functional anatomical aspects.

PubMed

Mall, G; Hubig, M; Koebke, J; Steinbuch, R

1997-08-01

Due to its functional significance the human skull plays an important role in biomechanical research. The present work describes a new Finite-Element model of the human neurocranium. The dry skull of a middle-aged woman served as a pattern. The model was developed using only the preprocessor (Mentat) of a commercial FE-system (Marc). Unlike that of other FE models of the human skull mentioned in the literature, the geometry in this model was designed according to functional anatomical findings. Functionally important morphological structures representing loci minoris resistentiae, especially the foramina and fissures of the skull base, were included in the model. The results of two linear static loadcase analyses in the region of the skull base underline the importance of modeling from the functional anatomical point of view.
Hydraulic modeling analysis of the Middle Rio Grande - Escondida Reach, New Mexico

Treesearch

Amanda K. Larsen

2007-01-01

Human influence on the Middle Rio Grande has resulted in major changes throughout the Middle Rio Grande region in central New Mexico, including problems with erosion and sedimentation. Hydraulic modeling analyses have been performed on the Middle Rio Grande to determine changes in channel morphology and other important parameters. Important changes occurring in the...
Mountaintop island age determines species richness of boreal mammals in the American Southwest

USGS Publications Warehouse

Frey, J.K.; Bogan, M.A.; Yates, Terry L.

2007-01-01

Models that describe the mechanisms responsible for insular patterns of species richness include the equilibrium theory of island biogeography and the nonequilibrium vicariance model. The relative importance of dispersal or vicariance in structuring insular distribution patterns can be inferred from these models. Predictions of the alternative models were tested for boreal mammals in the American Southwest. Age of mountaintop islands of boreal habitat was determined by constructing a geographic cladogram based on characteristics of intervening valley barriers. Other independent variables included area and isolation of mountaintop islands. Island age was the most important predictor of species richness. In contrast with previous studies of species richness patterns in this system, these results supported the nonequilibrium vicariance model, which indicates that vicariance has been the primary determinant of species distribution patterns in this system.
AgMIP: Next Generation Models and Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

Next steps in developing next-generation crop models fall into several categories: significant improvements in simulation of important crop processes and responses to stress; extension from simplified crop models to complex cropping systems models; and scaling up from site-based models to landscape, national, continental, and global scales. Crop processes that require major leaps in understanding and simulation in order to narrow uncertainties around how crops will respond to changing atmospheric conditions include genetics; carbon, temperature, water, and nitrogen; ozone; and nutrition. The field of crop modeling has been built on a single crop-by-crop approach. It is now time to create a new paradigm, moving from 'crop' to 'cropping system.' A first step is to set up the simulation technology so that modelers can rapidly incorporate multiple crops within fields, and multiple crops over time. Then the response of these more complex cropping systems can be tested under different sustainable intensification management strategies utilizing the updated simulation environments. Model improvements for diseases, pests, and weeds include developing process-based models for important diseases, frameworks for coupling air-borne diseases to crop models, gathering significantly more data on crop impacts, and enabling the evaluation of pest management strategies. Most smallholder farming in the world involves integrated crop-livestock systems that cannot be represented by crop modeling alone. Thus, next-generation cropping system models need to include key linkages to livestock. Livestock linkages to be incorporated include growth and productivity models for grasslands and rangelands as well as the usual annual crops. There are several approaches for scaling up, including use of gridded models and development of simpler quasi-empirical models for landscape-scale analysis. On the assessment side, AgMIP is leading a community process for coordinated contributions to IPCC AR6 that involves the key modeling groups from around the world including North America, Europe, South America, Sub-Saharan Africa, South Asia, East Asia, and Australia and Oceania. This community process will lead to mutually agreed protocols for coordinated global and regional assessments.
The Planetary Data System Information Model for Geometry Metadata

NASA Astrophysics Data System (ADS)

Guinness, E. A.; Gordon, M. K.

2014-12-01

The NASA Planetary Data System (PDS) has recently developed a new set of archiving standards based on a rigorously defined information model. An important part of the new PDS information model is the model for geometry metadata, which includes, for example, attributes of the lighting and viewing angles of observations, position and velocity vectors of a spacecraft relative to Sun and observing body at the time of observation and the location and orientation of an observation on the target. The PDS geometry model is based on requirements gathered from the planetary research community, data producers, and software engineers who build search tools. A key requirement for the model is that it fully supports the breadth of PDS archives that include a wide range of data types from missions and instruments observing many types of solar system bodies such as planets, ring systems, and smaller bodies (moons, comets, and asteroids). Thus, important design aspects of the geometry model are that it standardizes the definition of the geometry attributes and provides consistency of geometry metadata across planetary science disciplines. The model specification also includes parameters so that the context of values can be unambiguously interpreted. For example, the reference frame used for specifying geographic locations on a planetary body is explicitly included with the other geometry metadata parameters. The structure and content of the new PDS geometry model is designed to enable both science analysis and efficient development of search tools. The geometry model is implemented in XML, as is the main PDS information model, and uses XML schema for validation. The initial version of the geometry model is focused on geometry for remote sensing observations conducted by flyby and orbiting spacecraft. Future releases of the PDS geometry model will be expanded to include metadata for landed and rover spacecraft.
Mathematical modelling as a proof of concept for MPNs as a human inflammation model for cancer development.

PubMed

Andersen, Morten; Sajid, Zamra; Pedersen, Rasmus K; Gudmand-Hoeyer, Johanne; Ellervik, Christina; Skov, Vibe; Kjær, Lasse; Pallisgaard, Niels; Kruse, Torben A; Thomassen, Mads; Troelsen, Jesper; Hasselbalch, Hans Carl; Ottesen, Johnny T

2017-01-01

The chronic Philadelphia-negative myeloproliferative neoplasms (MPNs) are acquired stem cell neoplasms which ultimately may transform to acute myelogenous leukemia. Most recently, chronic inflammation has been described as an important factor for the development and progression of MPNs in the biological continuum from early cancer stage to the advanced myelofibrosis stage, the MPNs being described as "A Human Inflammation Model for Cancer Development". This novel concept has been built upon clinical, experimental, genomic, immunological and not least epidemiological studies. Only a few studies have described the development of MPNs by mathematical models, and none have addressed the role of inflammation for clonal evolution and disease progression. Herein, we aim at using mathematical modelling to substantiate the concept of chronic inflammation as an important trigger and driver of MPNs.The basics of the model describe the proliferation from stem cells to mature cells including mutations of healthy stem cells to become malignant stem cells. We include a simple inflammatory coupling coping with cell death and affecting the basic model beneath. First, we describe the system without feedbacks or regulatory interactions. Next, we introduce inflammatory feedback into the system. Finally, we include other feedbacks and regulatory interactions forming the inflammatory-MPN model. Using mathematical modeling, we add further proof to the concept that chronic inflammation may be both a trigger of clonal evolution and an important driving force for MPN disease progression. Our findings support intervention at the earliest stage of cancer development to target the malignant clone and dampen concomitant inflammation.
A systematic review of model-based economic evaluations of diagnostic and therapeutic strategies for lower extremity artery disease.

PubMed

Vaidya, Anil; Joore, Manuela A; ten Cate-Hoek, Arina J; Kleinegris, Marie-Claire; ten Cate, Hugo; Severens, Johan L

2014-01-01

Lower extremity artery disease (LEAD) is a sign of wide spread atherosclerosis also affecting coronary, cerebral and renal arteries and is associated with increased risk of cardiovascular events. Many economic evaluations have been published for LEAD due to its clinical, social and economic importance. The aim of this systematic review was to assess modelling methods used in published economic evaluations in the field of LEAD. Our review appraised and compared the general characteristics, model structure and methodological quality of published models. Electronic databases MEDLINE and EMBASE were searched until February 2013 via OVID interface. Cochrane database of systematic reviews, Health Technology Assessment database hosted by National Institute for Health research and National Health Services Economic Evaluation Database (NHSEED) were also searched. The methodological quality of the included studies was assessed by using the Philips' checklist. Sixteen model-based economic evaluations were identified and included. Eleven models compared therapeutic health technologies; three models compared diagnostic tests and two models compared a combination of diagnostic and therapeutic options for LEAD. Results of this systematic review revealed an acceptable to low methodological quality of the included studies. Methodological diversity and insufficient information posed a challenge for valid comparison of the included studies. In conclusion, there is a need for transparent, methodologically comparable and scientifically credible model-based economic evaluations in the field of LEAD. Future modelling studies should include clinically and economically important cardiovascular outcomes to reflect the wider impact of LEAD on individual patients and on the society.
Airloads Correlation of the UH-60A Rotor Inside the 40- by 80-Foot Wind Tunnel

NASA Technical Reports Server (NTRS)

Chang, I-Chung; Norman, Thomas R.; Romander, Ethan A.

2013-01-01

The presented research validates the capability of a loosely-coupled computational fluid dynamics (CFD) and comprehensive rotorcraft analysis (CRA) code to calculate the flowfield around a rotor and test stand mounted inside a wind tunnel. The CFD/CRA predictions for the full-scale UH-60A Airloads Rotor inside the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel at NASA Ames Research Center are compared with the latest measured airloads and performance data. The studied conditions include a speed sweep at constant lift up to an advance ratio of 0.4 and a thrust sweep at constant speed up to and including stall. For the speed sweep, wind tunnel modeling becomes important at advance ratios greater than 0.37 and test stand modeling becomes increasingly important as the advance ratio increases. For the thrust sweep, both the wind tunnel and test stand modeling become important as the rotor approaches stall. Despite the beneficial effects of modeling the wind tunnel and test stand, the new models do not completely resolve the current airload discrepancies between prediction and experiment.
Modeling of the nearshore marine ecosystem with the AQUATOX model

EPA Science Inventory

Process-based models can be used to forecast the responses of coastal ecosystems to changes under future scenarios. However, most models applied to coastal systems do not include higher trophic levels, which are important providers of ecosystem services. AQUATOX is a mechanistic...
Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

PubMed

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.
A concentrated parameter model for the human cardiovascular system including heart valve dynamics and atrioventricular interaction.

PubMed

Korakianitis, Theodosios; Shi, Yubing

2006-09-01

Numerical modeling of the human cardiovascular system has always been an active research direction since the 19th century. In the past, various simulation models of different complexities were proposed for different research purposes. In this paper, an improved numerical model to study the dynamic function of the human circulation system is proposed. In the development of the mathematical model, the heart chambers are described with a variable elastance model. The systemic and pulmonary loops are described based on the resistance-compliance-inertia concept by considering local effects of flow friction, elasticity of blood vessels and inertia of blood in different segments of the blood vessels. As an advancement from previous models, heart valve dynamics and atrioventricular interaction, including atrial contraction and motion of the annulus fibrosus, are specifically modeled. With these improvements the developed model can predict several important features that were missing in previous numerical models, including regurgitant flow on heart valve closure, the value of E/A velocity ratio in mitral flow, the motion of the annulus fibrosus (called the KG diaphragm pumping action), etc. These features have important clinical meaning and their changes are often related to cardiovascular diseases. Successful simulation of these features enhances the accuracy of simulations of cardiovascular dynamics, and helps in clinical studies of cardiac function.
The importance of diverse data types to calibrate a watershed model of the Trout Lake Basin, Northern Wisconsin, USA

USGS Publications Warehouse

Hunt, R.J.; Feinstein, D.T.; Pint, C.D.; Anderson, M.P.

2006-01-01

As part of the USGS Water, Energy, and Biogeochemical Budgets project and the NSF Long-Term Ecological Research work, a parameter estimation code was used to calibrate a deterministic groundwater flow model of the Trout Lake Basin in northern Wisconsin. Observations included traditional calibration targets (head, lake stage, and baseflow observations) as well as unconventional targets such as groundwater flows to and from lakes, depth of a lake water plume, and time of travel. The unconventional data types were important for parameter estimation convergence and allowed the development of a more detailed parameterization capable of resolving model objectives with well-constrained parameter values. Independent estimates of groundwater inflow to lakes were most important for constraining lakebed leakance and the depth of the lake water plume was important for determining hydraulic conductivity and conceptual aquifer layering. The most important target overall, however, was a conventional regional baseflow target that led to correct distribution of flow between sub-basins and the regional system during model calibration. The use of an automated parameter estimation code: (1) facilitated the calibration process by providing a quantitative assessment of the model's ability to match disparate observed data types; and (2) allowed assessment of the influence of observed targets on the calibration process. The model calibration required the use of a 'universal' parameter estimation code in order to include all types of observations in the objective function. The methods described in this paper help address issues of watershed complexity and non-uniqueness common to deterministic watershed models. ?? 2005 Elsevier B.V. All rights reserved.
Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

NASA Astrophysics Data System (ADS)

Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

2017-12-01

Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

Probabilistic-Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

developed to determine the relative importance of structural components of the vehicle under differnet crash and blast scenarios. With the integration of...the vehicle under different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the...parameter variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment
Balancing the seen and unseen: Nurse educator as role model for critical thinking.

PubMed

Raymond, Christy; Profetto-McGrath, Joanne; Myrick, Florence; Strean, William B

2018-05-04

Critical thinking is an important indicator of student learning and is an essential outcome of baccalaureate nursing education. The role of nurse educators in the development of students' critical thinking has been overlooked despite the importance of their actions to facilitate critical thinking in nursing education. We used a constructivist grounded theory approach within a larger mixed methods triangulation study to explore how nurse educators revealed their critical thinking in practice. From the grounded theory approach, a model emerged from our research, outlining the important aspects of nurse educators' critical thinking and how it is revealed in the clinical setting. The important categories of this model include: a) fostering the student-educator relationship; b) role modeling critical thinking; c) mobilizing and operationalizing resources; as well as d) balancing factors that impact nurse educators' critical thinking. Our findings inform what is known about nurse educators' critical thinking and how it can be implemented in nurse educators' teaching practice. Given our findings, we offer recommendations for future nursing education practice and research, including the need to apply our findings in additional settings and further develop nurse educators' awareness of their own critical thinking. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.
Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

NASA Astrophysics Data System (ADS)

Jiang, J. H.; Su, H.

2016-12-01

Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.
Propagation Effects of Importance to the NASA/JPL Deep Space Network (DSN)

NASA Technical Reports Server (NTRS)

Slobin, Steve

1999-01-01

This paper presents Propagation Effects of Importance To The NASA/JPL Deep Space Network (DSN). The topics include: 1) DSN Antennas; 2) Deep Space Telecom Link Basics; 3) DSN Propagation Region of Interest; 4) Ka-Band Weather Effects Models and Examples; 5) Existing Goldstone Ka-Band Atmosphere Attenuation Model; 6) Existing Goldstone Atmosphere Noise Temperature Model; and 7) Ka-Band delta (G/T) Relative to Vacuum Condition. This paper summarizes the topics above.
Simple theoretical models for composite rotor blades

NASA Technical Reports Server (NTRS)

Valisetty, R. R.; Rehfield, L. W.

1984-01-01

The development of theoretical rotor blade structural models for designs based upon composite construction is discussed. Care was exercised to include a member of nonclassical effects that previous experience indicated would be potentially important to account for. A model, representative of the size of a main rotor blade, is analyzed in order to assess the importance of various influences. The findings of this model study suggest that for the slenderness and closed cell construction considered, the refinements are of little importance and a classical type theory is adequate. The potential of elastic tailoring is dramatically demonstrated, so the generality of arbitrary ply layup in the cell wall is needed to exploit this opportunity.
Evolution of an Implementation-Ready Interprofessional Pain Assessment Reference Model

PubMed Central

Collins, Sarah A; Bavuso, Karen; Swenson, Mary; Suchecki, Christine; Mar, Perry; Rocha, Roberto A.

2017-01-01

Standards to increase consistency of comprehensive pain assessments are important for safety, quality, and analytics activities, including meeting Joint Commission requirements and learning the best management strategies and interventions for the current prescription Opioid epidemic. In this study we describe the development and validation of a Pain Assessment Reference Model ready for implementation on EHR forms and flowsheets. Our process resulted in 5 successive revisions of the reference model, which more than doubled the number of data elements to 47. The organization of the model evolved during validation sessions with panels totaling 48 subject matter experts (SMEs) to include 9 sets of data elements, with one set recommended as a minimal data set. The reference model also evolved when implemented into EHR forms and flowsheets, indicating specifications such as cascading logic that are important to inform secondary use of data. PMID:29854125
Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.
Assessing medication effects in the MTA study using neuropsychological outcomes.

PubMed

Epstein, Jeffery N; Conners, C Keith; Hervey, Aaron S; Tonev, Simon T; Arnold, L Eugene; Abikoff, Howard B; Elliott, Glen; Greenhill, Laurence L; Hechtman, Lily; Hoagwood, Kimberly; Hinshaw, Stephen P; Hoza, Betsy; Jensen, Peter S; March, John S; Newcorn, Jeffrey H; Pelham, William E; Severe, Joanne B; Swanson, James M; Wells, Karen; Vitiello, Benedetto; Wigal, Timothy

2006-05-01

While studies have increasingly investigated deficits in reaction time (RT) and RT variability in children with attention deficit/hyperactivity disorder (ADHD), few studies have examined the effects of stimulant medication on these important neuropsychological outcome measures. 316 children who participated in the Multimodal Treatment Study of Children with ADHD (MTA) completed the Conners' Continuous Performance Test (CPT) at the 24-month assessment point. Outcome measures included standard CPT outcomes (e.g., errors of commission, mean hit reaction time (RT)) and RT indicators derived from an Ex-Gaussian distributional model (i.e., mu, sigma, and tau). Analyses revealed significant effects of medication across all neuropsychological outcome measures. Results on the Ex-Gaussian outcome measures revealed that stimulant medication slows RT and reduces RT variability. This demonstrates the importance of including analytic strategies that can accurately model the actual distributional pattern, including the positive skew. Further, the results of the study relate to several theoretical models of ADHD.
Parent Education within a Relationship-Focused Model.

ERIC Educational Resources Information Center

Kelly, Jean F.; Barnard, Kathryn E.

1999-01-01

This response to Mahoney et al. (EC 623 392) agrees that parent education should be an important component of early intervention programs and proposes that parent education be included in a relationship-focused early-intervention model. This model is illustrated, explained, and compared with the previous child-focused model and the current…
Grazing experiments and model simulations of the role of zooplankton in Phaeocystis food webs

NASA Astrophysics Data System (ADS)

Verity, P. G.

2000-08-01

A combined empirical and modelling study was conducted to further examine the potential importance of grazing by zooplankton in pelagic food webs in which Phaeocystis is a significant or dominant component. Laboratory experiments were designed to measure ingestion of Phaeocystis and other potential prey items which co-occur with Phaeocystis. Grazers included copepods and ciliates, and prey included Phaeocystis colonies and solitary cells, diatoms, ciliates, bacteria, and detritus. These data were expressed in the model currency of nitrogen units, and fit to hyperbolic tangent equations which included minimum prey thresholds. These equations and literature data were used to constrain a food web model whose purpose was to investigate trophic interactions rather than to mimic actual events. Nevertheless, the model output was similar to the general pattern and magnitude of development of Phaeocystis-diatom communities in some environments where they occur, e.g. north Norwegian waters. The model included three forms of nitrogen, three phytoplankton groups, bacteria, two zooplankton groups, and detritus, with detailed flows between compartments. An important component of the model was inclusion of variable prey preferences for zooplankton. The experiments and model simulations suggest several salient conclusions. Phaeocystis globosa colonies were eaten by a medium-sized copepod species, but ingestion appeared to be strongly dependent upon a proper size match between grazer and prey. If not, colonies were eaten little if at all. Phaeocystis solitary cells were ingested rapidly by ciliate microzooplankton, in agreement with prior literature observations. In contrast, detritus was eaten comparatively slowly by both ciliates and copepods. Both types of zooplankton exhibited apparent minimum prey thresholds below which grazing did not occur or was inconsequential. Model simulations implied that transitions between life cycle stages of Phaeocystis may potentially be important to phytoplankton-zooplankton interactions, and that relative rates of ingestion of Phaeocystis by various zooplankton may have significant impacts upon material fluxes through and out of Phaeocystis-diatom ecosystems. Indirect effects of trophic interactions appear to be equally significant as direct effects.
The Effects of Media Reports on Disease Spread and Important Public Health Measurements

PubMed Central

Collinson, Shannon; Khan, Kamran; Heffernan, Jane M.

2015-01-01

Controlling the spread of influenza to reduce the effects of infection on a population is an important mandate of public health. Mass media reports on an epidemic or pandemic can provide important information to the public, and in turn, can induce positive healthy behaviour practices (i.e., handwashing, social distancing) in the individuals, that will reduce the probability of contracting the disease. Mass media fatigue, however, can dampen these effects. Mathematical models can be used to study the effects of mass media reports on epidemic/pandemic outcomes. In this study we employ a stochastic agent based model to provide a quantification of mass media reports on the variability in important public health measurements. We also include mass media report data compiled by the Global Public Health Intelligence Network, to study the effects of mass media reports in the 2009 H1N1 pandemic. We find that the report rate and the rate at which individuals relax their healthy behaviours (media fatigue) greatly affect the variability in important public health measurements. When the mass media reporting data is included in the model, two peaks of infection result. PMID:26528909
Modeling greenhouse gas emissions from dairy farms

USDA-ARS?s Scientific Manuscript database

Evaluation and mitigation of greenhouse gas emissions from dairy farms requires a comprehensive approach that integrates the impacts and interactions of all important sources and sinks. This approach requires some form of modeling. Types of models commonly used include empirical emission factors, pr...
Per Aspera ad Astra: Through Complex Population Modeling to Predictive Theory.

PubMed

Topping, Christopher J; Alrøe, Hugo Fjelsted; Farrell, Katharine N; Grimm, Volker

2015-11-01

Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam's razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam's razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.
Fruit and vegetable consumption - the influence of aspects associated with trust in food and safety and quality of food.

PubMed

Taylor, Anne W; Coveney, John; Ward, Paul R; Henderson, Julie; Meyer, Samantha B; Pilkington, Rhiannon; Gill, Tiffany K

2012-02-01

To profile adults who eat less than the recommended servings of fruit and vegetables per day. Australia-wide population telephone survey on a random sample of the Australian population, with results analysed by univariate and multivariate models. Australia. One thousand one hundred and eight interviews, respondents' (49·3 % males) mean age was 45·12 (sd 17·63) years. Overall 54·8 % and 10·7 % were eating the recommended number of servings of fruit and vegetables. Variables included in the multivariate model indicating low fruit consumption included gender, age, employment, education and those who were less likely to consider the safety and quality of food as important. In regard to low vegetable consumption, people who were more likely to do the food shopping only 'some of the time' and have a high level of trust in groups of people such as immediate family, neighbours, doctors and different levels of government were included in the final model. They were also less likely to neither consider the safety and quality of food as important nor trust organisations/institutions such as the press, television and politicians. In the final model depicting both low fruit and low vegetable servings, sex, age and a low level of importance with regard to safety and quality of food were included. To increase fruit and vegetable consumption, research into a broad range of determinants associated with behaviours should be coupled with a deeper understanding of the process associated with changing behaviours. While levels of trust are related to behaviour change, knowledge and attitudes about aspects associated with safety and quality of food are also of importance.
Assessment of the Draft AIAA S-119 Flight Dynamic Model Exchange Standard

NASA Technical Reports Server (NTRS)

Jackson, E. Bruce; Murri, Daniel G.; Hill, Melissa A.; Jessick, Matthew V.; Penn, John M.; Hasan, David A.; Crues, Edwin Z.; Falck, Robert D.; McCarthy, Thomas G.; Vuong, Nghia;

2011-01-01

An assessment of a draft AIAA standard for flight dynamics model exchange, ANSI/AIAA S-119-2011, was conducted on behalf of NASA by a team from the NASA Engineering and Safety Center. The assessment included adding the capability of importing standard models into real-time simulation facilities at several NASA Centers as well as into analysis simulation tools. All participants were successful at importing two example models into their respective simulation frameworks by using existing software libraries or by writing new import tools. Deficiencies in the libraries and format documentation were identified and fixed; suggestions for improvements to the standard were provided to the AIAA. An innovative tool to generate C code directly from such a model was developed. Performance of the software libraries compared favorably with compiled code. As a result of this assessment, several NASA Centers can now import standard models directly into their simulations. NASA is considering adopting the now-published S-119 standard as an internal recommended practice.

Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model

EPA Science Inventory

A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...
Importance of scale, land cover, and weather on the abundance of bird species in a managed forest

USGS Publications Warehouse

Grinde, Alexis R.; Hiemi, Gerald J.; Sturtevant, Brian R.; Panci, Hannah; Thogmartin, Wayne E.; Wolter, Peter

2017-01-01

Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.
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.
An Interdisciplinary Guided Inquiry on Estuarine Transport Using a Computer Model in High School Classrooms

ERIC Educational Resources Information Center

Chan, Kit Yu Karen; Yang, Sylvia; Maliska, Max E.; Grunbaum, Daniel

2012-01-01

The National Science Education Standards have highlighted the importance of active learning and reflection for contemporary scientific methods in K-12 classrooms, including the use of models. Computer modeling and visualization are tools that researchers employ in their scientific inquiry process, and often computer models are used in…
EIA model documentation: Petroleum market model of the national energy modeling system

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

NONE

1995-12-28

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. Documentation of the model is in accordance with EIA`s legal obligation to provide adequate documentation in support of its models. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions, the production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supplymore » for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcohols and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level.« less

On a basic model of circulatory, fluid, and electrolyte regulation in the human system based upon the model of Guyton

NASA Technical Reports Server (NTRS)

White, R. J.

1973-01-01

A detailed description of Guyton's model and modifications are provided. Also included are descriptions of several typical experiments which the model can simulate to illustrate the model's general utility. A discussion of the problems associated with the interfacing of the model to other models such as respiratory and thermal regulation models which is prime importance since these stimuli are not present in the current model is also included. A user's guide for the operation of the model on the Xerox Sigma 3 computer is provided and two programs are described. A verification plan and procedure for performing experiments is also presented.
The dynamics of life stressors and depressive symptoms in early adolescence: a test of six theoretical models.

PubMed

Clements, Margaret; Aber, J Lawrence; Seidman, Edward

2008-01-01

Structural equation modeling was used to compare 6 competing theoretically based psychosocial models of the longitudinal association between life stressors and depressive symptoms in a sample of early adolescents (N= 907; 40% Hispanic, 32% Black, and 19% White; mean age at Time 1 = 11.4 years). Only two models fit the data, both of which included paths modeling the effect of depressive symptoms on stressors recall: The mood-congruent cognitive bias model included only depressive symptoms to life stressors paths (DS-->S), whereas the fully transactional model included paths representing both the DS-->S and stressors to depressive symptoms (S-->DS) effects. Social causation models and the stress generation model did not fit the data. Findings demonstrate the importance of accounting for mood-congruent cognitive bias in stressors-depressive symptoms investigations.
Importance of Ambipolar Electric Field in the Ion Loss from Mars- Results from a Multi-fluid MHD Model with the Electron Pressure Equation Included

NASA Astrophysics Data System (ADS)

Ma, Y.; Dong, C.; van der Holst, B.; Nagy, A. F.; Bougher, S. W.; Toth, G.; Cravens, T.; Yelle, R. V.; Jakosky, B. M.

2017-12-01

The multi-fluid (MF) magnetohydrodynamic (MHD) model of Mars is further improved by solving an additional electron pressure equation. Through the electron pressure equation, the electron temperature is calculated based on the effects from various electrons related heating and cooling processes (e.g. photo-electron heating, electron-neutral collision and electron-ion collision), and thus the improved model is able to calculate the electron temperature and the electron pressure force self-consistently. Electron thermal conductivity is also considered in the calculation. Model results of a normal case with electron pressure equation included (MFPe) are compared in detail to an identical case using the regular MF model to identify the effect of the improved physics. We found that when the electron pressure equation is included, the general interaction patterns are similar to that of the case with no electron pressure equation. The model with electron pressure equation predicts that electron temperature is much larger than the ion temperature in the ionosphere, consistent with both Viking and MAVEN observations. The inclusion of electron pressure equation significantly increases the total escape fluxes predicted by the model, indicating the importance of the ambipolar electric field(electron pressure gradient) in driving the ion loss from Mars.
A Review of Metacognition in Psychological Models of Obsessive-Compulsive Disorder

ERIC Educational Resources Information Center

Rees, Clare S.; Anderson, Rebecca A.

2013-01-01

Cognitive-behavioural models and interventions for obsessive-compulsive disorder (OCD) have always included some metacognitive elements but until recently these have been predominantly construed of as cognitive as opposed to metacognitive processes. Increasingly, psychological models of OCD are now recognising the importance of metacognitive…
Analysis of the Lenticular Jointed MARSIS Antenna Deployment

NASA Technical Reports Server (NTRS)

Mobrem, Mehran; Adams, Douglas S.

2006-01-01

This paper summarizes important milestones in a yearlong comprehensive effort which culminated in successful deployments of the MARSIS antenna booms in May and June of 2005. Experimentally measured straight section and hinge properties are incorporated into specialized modeling techniques that are used to simulate the boom lenticular joints. System level models are exercised to understand the boom deployment dynamics and spacecraft level implications. Discussion includes a comparison of ADAMS simulation results to measured flight data taken during the three boom deployments. Important parameters that govern lenticular joint behavior are outlined and a short summary of lessons learned and recommendations is included to better understand future applications of this technology.
Temporal self-regulation theory: a neurobiologically informed model for physical activity behavior

PubMed Central

Hall, Peter A.; Fong, Geoffrey T.

2015-01-01

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

PubMed

Jones, Wendy; Haslam, Roger; Haslam, Cheryl

2017-01-01

This paper proposes a model of job quality, developed from interviews with blue collar workers: bus drivers, manufacturing operatives and cleaners (n = 80). The model distinguishes between core features, important for almost all workers, and 'job fit' features, important to some but not others, or where individuals might have different preferences. Core job features found important for almost all interviewees included job security, personal safety and having enough pay to meet their needs. 'Job fit' features included autonomy and the opportunity to form close relationships. These showed more variation between participants; priorities were influenced by family commitments, stage of life and personal preference. The resulting theoretical perspective indicates the features necessary for a job to be considered 'good' by the person doing it, whilst not adversely affecting their health. The model should have utility as a basis for measuring and improving job quality and the laudable goal of creating 'good jobs'. Practitioner Summary: Good work can contribute positively to health and well-being, but there is a lack of agreement regarding the concept of a 'good' job. A model of job quality has been constructed based on semi-structured worker interviews (n = 80). The model emphasises the need to take into account variation between individuals in their preferred work characteristics.
Predicting the biological condition of streams: Use of geospatial indicators of natural and anthropogenic characteristics of watersheds

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Meador, M.R.

2009-01-01

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments. ?? Springer Science+Business Media B.V. 2008.
Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses

PubMed Central

Soares, Marta O.; Palmer, Stephen; Ades, Anthony E.; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M.

2015-01-01

Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. PMID:25712447
Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses.

PubMed

Welton, Nicky J; Soares, Marta O; Palmer, Stephen; Ades, Anthony E; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M

2015-07-01

Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. © The Author(s) 2015.
Knowledge, transparency, and refutability in groundwater models, an example from the Death Valley regional groundwater flow system

USGS Publications Warehouse

Hill, Mary C.; Faunt, Claudia C.; Belcher, Wayne; Sweetkind, Donald; Tiedeman, Claire; Kavetski, Dmitri

2013-01-01

This work demonstrates how available knowledge can be used to build more transparent and refutable computer models of groundwater systems. The Death Valley regional groundwater flow system, which surrounds a proposed site for a high level nuclear waste repository of the United States of America, and the Nevada National Security Site (NNSS), where nuclear weapons were tested, is used to explore model adequacy, identify parameters important to (and informed by) observations, and identify existing old and potential new observations important to predictions. Model development is pursued using a set of fundamental questions addressed with carefully designed metrics. Critical methods include using a hydrogeologic model, managing model nonlinearity by designing models that are robust while maintaining realism, using error-based weighting to combine disparate types of data, and identifying important and unimportant parameters and observations and optimizing parameter values with computationally frugal schemes. The frugal schemes employed in this study require relatively few (10–1000 s), parallelizable model runs. This is beneficial because models able to approximate the complex site geology defensibly tend to have high computational cost. The issue of model defensibility is particularly important given the contentious political issues involved.
Land-use planning for nearshore ecosystem services—the Puget Sound Ecosystem Portfolio Model

USGS Publications Warehouse

Byrd, Kristin

2011-01-01

The 2,500 miles of shoreline and nearshore areas of Puget Sound, Washington, provide multiple benefits to people—"ecosystem services"—including important fishing, shellfishing, and recreation industries. To help resource managers plan for expected growth in coming decades, the U.S. Geological Survey Western Geographic Science Center has developed the Puget Sound Ecosystem Portfolio Model (PSEPM). Scenarios of urban growth and shoreline modifications serve as model inputs to develop alternative futures of important nearshore features such as water quality and beach habitats. Model results will support regional long-term planning decisions for the Puget Sound region.
Enhanced Framework for Modeling Urban Truck Trips

DOT National Transportation Integrated Search

1998-09-16

Recently there has been renewed interest in modeling urban truck movements. : This is potentially important for improving traffic forecasts as well as for a : host of other applications including ITS. There are unique aspects of urban : freight movem...
Funding medical education: should we follow a different model to general higher education? Commentary.

PubMed

Walsh, Kieran

2015-01-01

There has been much recent discussion on the funding of medical education. There has also been much discussion about the funding of higher education more generally. The topics of discussion have included the rising costs of education; who should pay; the various potential models of funding; and how best to ensure maximum returns from investment. Medical education has largely followed the emerging models of funding for higher education. However there are important reasons why the funding models for higher education may not suit medical education. These reasons include the fact that medical education is as important to the public as it is to the learner; the range of funding sources available to medical schools; the strict regulation of medical education; and the fact that the privatisation and commercialisation of higher education may not been in keeping with the social goals of medical schools and the agenda of diversification within the medical student population.
Linear complementarity formulation for 3D frictional sliding problems

USGS Publications Warehouse

Kaven, Joern; Hickman, Stephen H.; Davatzes, Nicholas C.; Mutlu, Ovunc

2012-01-01

Frictional sliding on quasi-statically deforming faults and fractures can be modeled efficiently using a linear complementarity formulation. We review the formulation in two dimensions and expand the formulation to three-dimensional problems including problems of orthotropic friction. This formulation accurately reproduces analytical solutions to static Coulomb friction sliding problems. The formulation accounts for opening displacements that can occur near regions of non-planarity even under large confining pressures. Such problems are difficult to solve owing to the coupling of relative displacements and tractions; thus, many geomechanical problems tend to neglect these effects. Simple test cases highlight the importance of including friction and allowing for opening when solving quasi-static fault mechanics models. These results also underscore the importance of considering the effects of non-planarity in modeling processes associated with crustal faulting.
What are the Starting Points? Evaluating Base-Year Assumptions in the Asian Modeling Exercise

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

Chaturvedi, Vaibhav; Waldhoff, Stephanie; Clarke, Leon E.

2012-12-01

A common feature of model inter-comparison efforts is that the base year numbers for important parameters such as population and GDP can differ substantially across models. This paper explores the sources and implications of this variation in Asian countries across the models participating in the Asian Modeling Exercise (AME). Because the models do not all have a common base year, each team was required to provide data for 2005 for comparison purposes. This paper compares the year 2005 information for different models, noting the degree of variation in important parameters, including population, GDP, primary energy, electricity, and CO2 emissions. Itmore » then explores the difference in these key parameters across different sources of base-year information. The analysis confirms that the sources provide different values for many key parameters. This variation across data sources and additional reasons why models might provide different base-year numbers, including differences in regional definitions, differences in model base year, and differences in GDP transformation methodologies, are then discussed in the context of the AME scenarios. Finally, the paper explores the implications of base-year variation on long-term model results.« less
Modelling utility-scale wind power plants. Part 1: Economics

NASA Astrophysics Data System (ADS)

Milligan, Michael R.

1999-10-01

As the worldwide use of wind turbine generators continues to increase in utility-scale applications, it will become increasingly important to assess the economic and reliability impact of these intermittent resources. Although the utility industry in the United States appears to be moving towards a restructured environment, basic economic and reliability issues will continue to be relevant to companies involved with electricity generation. This article is the first of two which address modelling approaches and results obtained in several case studies and research projects at the National Renewable Energy Laboratory (NREL). This first article addresses the basic economic issues associated with electricity production from several generators that include large-scale wind power plants. An important part of this discussion is the role of unit commitment and economic dispatch in production cost models. This paper includes overviews and comparisons of the prevalent production cost modelling methods, including several case studies applied to a variety of electric utilities. The second article discusses various methods of assessing capacity credit and results from several reliability-based studies performed at NREL.
Teacher Perceptions about the Importance of Parental Involvement for Included Students with Learning Disabilities in New York Metropolitan Area Orthodox Yeshivas and Day Schools

ERIC Educational Resources Information Center

Grossman, Goldie Eichorn

2010-01-01

The population of students attending Jewish day schools includes an increasing number of students with exceptional needs. How Jewish schools meet the needs of these students is an important question. Inclusive education is a service model predicated on legal and philosophical mores as well as pedagogical and psychological findings. The quality of…
Parallel Optimization of an Earth System Model (100 Gigaflops and Beyond?)

NASA Technical Reports Server (NTRS)

Drummond, L. A.; Farrara, J. D.; Mechoso, C. R.; Spahr, J. A.; Chao, Y.; Katz, S.; Lou, J. Z.; Wang, P.

1997-01-01

We are developing an Earth System Model (ESM) to be used in research aimed to better understand the interactions between the components of the Earth System and to eventually predict their variations. Currently, our ESM includes models of the atmosphere, oceans and the important chemical tracers therein.
Different Approaches to Covariate Inclusion in the Mixture Rasch Model

ERIC Educational Resources Information Center

Li, Tongyun; Jiao, Hong; Macready, George B.

2016-01-01

The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…

Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies

ERIC Educational Resources Information Center

Smith, Carrie E.; Cribbie, Robert A.

2013-01-01

When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
Relationships Between Teacher Aptitudes, Teaching Behaviors, and Pupil Outcomes.

ERIC Educational Resources Information Center

Ekstrom, Ruth B.

A model of elementary school teacher behavior affecting pupil outcomes is presented, and research based upon that model is discussed. A portion of the model, the relationship between teacher aptitudes and knowledge, teaching behavior, and pupil outcomes is focused upon. Aptitudes considered important included verbal and reasoning ability, memory,…
Empowering Prospective Teachers to Become Active Sense-Makers: Multimodal Modeling of the Seasons

ERIC Educational Resources Information Center

Kim, Mi Song

2015-01-01

Situating science concepts in concrete and authentic contexts, using information and communications technologies, including multimodal modeling tools, is important for promoting the development of higher-order thinking skills in learners. However, teachers often struggle to integrate emergent multimodal models into a technology-rich informal…
Caring School Leadership: A Multidisciplinary, Cross-Occupational Model

ERIC Educational Resources Information Center

Smylie, Mark A.; Murphy, Joseph; Louis, Karen Seashore

2016-01-01

This article examines the importance of caring in schools and school leadership. It analyzes the concept of caring and how it functions and introduces a model of caring school leadership situated within this broader exposition. The analysis and model are informed by literature including academic and professional works from education and…
River Export of Plastic from Land to Sea: A Global Modeling Approach

NASA Astrophysics Data System (ADS)

Siegfried, Max; Gabbert, Silke; Koelmans, Albert A.; Kroeze, Carolien; Löhr, Ansje; Verburg, Charlotte

2016-04-01

Plastic is increasingly considered a serious cause of water pollution. It is a threat to aquatic ecosystems, including rivers, coastal waters and oceans. Rivers transport considerable amounts of plastic from land to sea. The quantity and its main sources, however, are not well known. Assessing the amount of macro- and microplastic transport from river to sea is, therefore, important for understanding the dimension and the patterns of plastic pollution of aquatic ecosystems. In addition, it is crucial for assessing short- and long-term impacts caused by plastic pollution. Here we present a global modelling approach to quantify river export of plastic from land to sea. Our approach accounts for different types of plastic, including both macro- and micro-plastics. Moreover, we distinguish point sources and diffuse sources of plastic in rivers. Our modelling approach is inspired by global nutrient models, which include more than 6000 river basins. In this paper, we will present our modelling approach, as well as first model results for micro-plastic pollution in European rivers. Important sources of micro-plastics include personal care products, laundry, household dust and car tyre wear. We combine information on these sources with information on sewage management, and plastic retention during river transport for the largest European rivers. Our modelling approach may help to better understand and prevent water pollution by plastic , and at the same time serves as 'proof of concept' for future application on global scale.
A transport model for computer simulation of wildfires

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

Linn, R.

1997-12-31

Realistic self-determining simulation of wildfires is a difficult task because of a large variety of important length scales (including scales on the size of twigs or grass and the size of large trees), imperfect data, complex fluid mechanics and heat transfer, and very complicated chemical reactions. The author uses a transport approach to produce a model that exhibits a self-determining propagation rate. The transport approach allows him to represent a large number of environments such as those with nonhomogeneous vegetation and terrain. He accounts for the microscopic details of a fire with macroscopic resolution by dividing quantities into mean andmore » fluctuating parts similar to what is done in traditional turbulence modeling. These divided quantities include fuel, wind, gas concentrations, and temperature. Reaction rates are limited by the mixing process and not the chemical kinetics. The author has developed a model that includes the transport of multiple gas species, such as oxygen and volatile hydrocarbons, and tracks the depletion of various fuels and other stationary solids and liquids. From this model he develops a simplified local burning model with which he performs a number of simulations that demonstrate that he is able to capture the important physics with the transport approach. With this simplified model he is able to pick up the essence of wildfire propagation, including such features as acceleration when transitioning to upsloping terrain, deceleration of fire fronts when they reach downslopes, and crowning in the presence of high winds.« less
COSP for Windows: Strategies for Rapid Analyses of Cyclic Oxidation Behavior

NASA Technical Reports Server (NTRS)

Smialek, James L.; Auping, Judith V.

2002-01-01

COSP is a publicly available computer program that models the cyclic oxidation weight gain and spallation process. Inputs to the model include the selection of an oxidation growth law and a spalling geometry, plus oxide phase, growth rate, spall constant, and cycle duration parameters. Output includes weight change, the amounts of retained and spalled oxide, the total oxygen and metal consumed, and the terminal rates of weight loss and metal consumption. The present version is Windows based and can accordingly be operated conveniently while other applications remain open for importing experimental weight change data, storing model output data, or plotting model curves. Point-and-click operating features include multiple drop-down menus for input parameters, data importing, and quick, on-screen plots showing one selection of the six output parameters for up to 10 models. A run summary text lists various characteristic parameters that are helpful in describing cyclic behavior, such as the maximum weight change, the number of cycles to reach the maximum weight gain or zero weight change, the ratio of these, and the final rate of weight loss. The program includes save and print options as well as a help file. Families of model curves readily show the sensitivity to various input parameters. The cyclic behaviors of nickel aluminide (NiAl) and a complex superalloy are shown to be properly fitted by model curves. However, caution is always advised regarding the uniqueness claimed for any specific set of input parameters,
Effect of current federal regulations on handgun safety features.

PubMed

Milne, John S; Hargarten, Stephen W; Kellermann, Arthur L; Wintemute, Garen J

2003-01-01

In the late 1960s, the Bureau of Alcohol, Tobacco, and Firearms implemented the "factoring criteria," a set of minimum size and safety standards required for any handgun imported into the United States. These standards, however, were not applied to guns manufactured domestically. We determine whether extending the factoring criteria to all handguns sold in the United States, as has been proposed in Congress, would increase the likelihood that safety devices would be included in new handgun designs. Imported and domestic handgun models produced in 1996 were examined to determine the prevalence of 4 passively acting safety devices on pistols and 1 passive safety device on revolvers. Domestic models were also scored against the factoring criteria. Compared with domestic pistol models, imported pistols were more likely to include a firing pin block (odds ratio [OR] 2.43; 95% confidence interval [CI] 1.54 to 3.85) and a loaded chamber indicator (OR 1.59; 95% CI 0.98 to 2.56). Domestic pistol models that already met the factoring criteria were more likely to include a loaded chamber indicator (OR 12.05; 95% CI 2.74 to 53.02), a grip safety (OR 24.12; 95% CI 7.8 to 74.33), and a firing pin block (OR 4.92; 95% CI 2.35 to 10.29) than domestic models that did not meet the criteria. Although pistol models that meet the factoring criteria are more likely to contain safety devices than those that do not, the net effect is modest. Thus, the factoring criteria alone are insufficient to ensure consistent incorporation of safety features into new handgun designs.
Testing a Model of Diabetes Self-Care Management: A Causal Model Analysis with LISREL.

ERIC Educational Resources Information Center

Nowacek, George A.; And Others

1990-01-01

A diabetes-management model is presented, which includes an attitudinal element and depicts relationships among causal elements. LISREL-VI was used to analyze data from 115 Type-I and 105 Type-II patients. The data did not closely fit the model. Results support the importance of the personal meaning of diabetes. (TJH)
Demographic, Maltreatment, and Neurobiological Correlates of PTSD Symptoms in Children and Adolescents

PubMed Central

Hooper, Stephen R.; Woolley, Donald P.; Shenk, Chad E.

2010-01-01

Objective To examine the relationships of demographic, maltreatment, neurostructural and neuropsychological measures with total posttraumatic stress disorder (PTSD) symptoms. Methods Participants included 216 children with maltreatment histories (N = 49), maltreatment and PTSD (N = 49), or no maltreatment (N = 118). Participants received diagnostic interviews, brain imaging, and neuropsychological evaluations. Results We examined a hierarchical regression model comprised of independent variables including demographics, trauma and maltreatment-related variables, and hippocampal volumes and neuropsychological measures to model PTSD symptoms. Important independent contributors to this model were SES, and General Maltreatment and Sexual Abuse Factors. Although hippocampal volumes were not significant, Visual Memory was a significant contributor to this model. Conclusions Similar to adult PTSD, pediatric PTSD symptoms are associated with lower Visual Memory performance. It is an important correlate of PTSD beyond established predictors of PTSD symptoms. These results support models of developmental traumatology and suggest that treatments which enhance visual memory may decrease symptoms of PTSD. PMID:20008084
Innovative research of AD HOC network mobility model

NASA Astrophysics Data System (ADS)

Chen, Xin

2017-08-01

It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.
Petroleum Market Model of the National Energy Modeling System. Part 1

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

NONE

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions, the production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcoholsmore » and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level.« less
NASTRAN thermal analyzer: Theory and application including a guide to modeling engineering problems, volume 2. [sample problem library guide

NASA Technical Reports Server (NTRS)

Jackson, C. E., Jr.

1977-01-01

A sample problem library containing 20 problems covering most facets of Nastran Thermal Analyzer modeling is presented. Areas discussed include radiative interchange, arbitrary nonlinear loads, transient temperature and steady-state structural plots, temperature-dependent conductivities, simulated multi-layer insulation, and constraint techniques. The use of the major control options and important DMAP alters is demonstrated.
Team Resilience as a Second-Order Emergent State: A Theoretical Model and Research Directions

PubMed Central

Bowers, Clint; Kreutzer, Christine; Cannon-Bowers, Janis; Lamb, Jerry

2017-01-01

Resilience has been recognized as an important phenomenon for understanding how individuals overcome difficult situations. However, it is not only individuals who face difficulties; it is not uncommon for teams to experience adversity. When they do, they must be able to overcome these challenges without performance decrements.This manuscript represents a theoretical model that might be helpful in conceptualizing this important construct. Specifically, it describes team resilience as a second-order emergent state. We also include research propositions that follow from the model. PMID:28861013
Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.

PubMed

Klenk, Jochen; Becker, Clemens; Palumbo, Pierpaolo; Schwickert, Lars; Rapp, Kilan; Helbostad, Jorunn L; Todd, Chris; Lord, Stephen R; Kerse, Ngaire

2017-11-01

Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
Extension and comparison of neoclassical models for poloidal rotation in tokamaks

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

Stacey, W. M.

2008-01-15

Several neoclassical models for the calculation of poloidal rotation in tokamaks were rederived within a common framework, extended to include additional physics and numerically compared. The importance of new physics phenomena not usually included in poloidal rotation calculations (e.g., poloidal electric field, VxB force resulting from enhanced radial particle flow arising from the ionization of recycling neutrals) was examined. Extensions of the Hirshman-Sigmar, Kim-Diamond-Groebner, and Stacey-Sigmar poloidal rotation models are presented.
Modelling of capillary-driven flow for closed paper-based microfluidic channels

NASA Astrophysics Data System (ADS)

Songok, Joel; Toivakka, Martti

2017-06-01

Paper-based microfluidics is an emerging field focused on creating inexpensive devices, with simple fabrication methods for applications in various fields including healthcare, environmental monitoring and veterinary medicine. Understanding the flow of liquid is important in achieving consistent operation of the devices. This paper proposes capillary models to predict flow in paper-based microfluidic channels, which include a flow accelerating hydrophobic top cover. The models, which consider both non-absorbing and absorbing substrates, are in good agreement with the experimental results.
A review of mechanisms and modelling procedures for landslide tsunamis

NASA Astrophysics Data System (ADS)

Løvholt, Finn; Harbitz, Carl B.; Glimsdal, Sylfest

2017-04-01

Landslides, including volcano flank collapses or volcanically induced flows, constitute the second-most important cause of tsunamis after earthquakes. Compared to earthquakes, landslides are more diverse with respect to how they generation tsunamis. Here, we give an overview over the main tsunami generation mechanisms for landslide tsunamis. In the presentation, a mix of results using analytical models, numerical models, laboratory experiments, and case studies are used to illustrate the diversity, but also to point out some common characteristics. Different numerical modelling techniques for the landslide evolution, and the tsunami generation and propagation, as well as the effect of frequency dispersion, are also briefly discussed. Basic tsunami generation mechanisms for different types of landslides, including large submarine translational landslide, to impulsive submarine slumps, and violent subaerial landslides and volcano flank collapses, are reviewed. The importance of the landslide kinematics is given attention, including the interplay between landslide acceleration, landslide velocity to depth ratio (Froude number) and dimensions. Using numerical simulations, we demonstrate how landslide deformation and retrogressive failure development influence tsunamigenesis. Generation mechanisms for subaerial landslides, are reviewed by means of scaling relations from laboratory experiments and numerical modelling. Finally, it is demonstrated how the different degree of complexity in the landslide tsunamigenesis needs to be reflected by increased sophistication in numerical models.
What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.
FACTORS INFLUENCING TOTAL DIETARY EXPOSURE OF YOUNG CHILDREN

EPA Science Inventory

A deterministic model was developed to identify critical input parameters to assess dietary intake of young children. The model was used as a framework for understanding important factors in data collection and analysis. Factors incorporated included transfer efficiencies of pest...

Individual Resistance to Change

DTIC Science & Technology

2012-09-13

important aspects of the model that were not included elsewhere. As expressed by Burke and Litwin (1992), leadership is a cornerstone in understanding...The Study of Leadership Danvilie, IL: Interstate Printers and Publishers Burke W., Litwin G. (1992). A Causal Model of Organizational Performance
Modeling surface-water flow and sediment mobility with the Multi-Dimensional Surface-Water Modeling System (MD_SWMS)

USGS Publications Warehouse

McDonald, Richard; Nelson, Jonathan; Kinzel, Paul; Conaway, Jeffrey S.

2006-01-01

The Multi-Dimensional Surface-Water Modeling System (MD_SWMS) is a Graphical User Interface for surface-water flow and sediment-transport models. The capabilities of MD_SWMS for developing models include: importing raw topography and other ancillary data; building the numerical grid and defining initial and boundary conditions; running simulations; visualizing results; and comparing results with measured data.
Development of mathematical models of environmental physiology

NASA Technical Reports Server (NTRS)

Stolwijk, J. A. J.; Mitchell, J. W.; Nadel, E. R.

1971-01-01

Selected articles concerned with mathematical or simulation models of human thermoregulation are presented. The articles presented include: (1) development and use of simulation models in medicine, (2) model of cardio-vascular adjustments during exercise, (3) effective temperature scale based on simple model of human physiological regulatory response, (4) behavioral approach to thermoregulatory set point during exercise, and (5) importance of skin temperature in sweat regulation.
Army College Fund Cost-Effectiveness Study

DTIC Science & Technology

1990-11-01

Section A.2 presents a theory of enlistment supply to provide a basis for specifying the regression model , The model Is specified in Section A.3, which...Supplementary materials are included in the final four sections. Section A.6 provides annual trends in the regression model variables. Estimates of the model ...millions, A.S. ESTIMATION OF A YOUTH EARNINGS FORECASTING MODEL Civilian pay is an important explanatory variable in the regression model . Previous
Trade Agreements: Impact on the U.S. Economy

DTIC Science & Technology

2009-11-10

model is consistent with the Ricardian and Heckscher- Ohlin models . An important drawback of the model is that it can estimate only the aggregate...24 Now known as the Michigan Brown-Deardorff-Stern Model , the Michigan Model of World Production and Trade includes data on 29...economy in the model . Input- output accounts trace the flow of input commodities into the production processes of industries, the flow of intermediate
Effect of Network-Assisted Language Teaching Model on Undergraduate English Skills

ERIC Educational Resources Information Center

He, Chunyan

2013-01-01

With the coming of the information age, computer-based teaching model has had an important impact on English teaching. Since 2004, the trial instruction on Network-assisted Language Teaching (NALT) Model integrating the English instruction and computer technology has been launched at some universities in China, including China university of…
BehavePlus fire modeling system: Past, present, and future

Treesearch

Patricia L. Andrews

2007-01-01

Use of mathematical fire models to predict fire behavior and fire effects plays an important supporting role in wildland fire management. When used in conjunction with personal fire experience and a basic understanding of the fire models, predictions can be successfully applied to a range of fire management activities including wildfire behavior prediction, prescribed...
A NONSTEADY-STATE ANALYTICAL MODEL TO PREDICT GASEOUS EMISSIONS OF VOLATILE ORGANIC COMPOUNDS FROM LANDFILLS. (R825689C072)

EPA Science Inventory

Abstract
A general mathematical model is developed to predict emissions of volatile organic compounds (VOCs) from hazardous or sanitary landfills. The model is analytical in nature and includes important mechanisms occurring in unsaturated subsurface landfill environme...
The Importance of Teaching Methodology in Moral Education of Sport Populations.

ERIC Educational Resources Information Center

Stoll, Sharon Kay; And Others

Three approaches to teaching moral reasoning were implemented by expert teachers in classes at three small colleges and outcomes were compared. Teaching models included the following: Model A, a "good reasoned" approach in which students discussed scenarios and determined the best course of action; Model B, a teacher-centered lecture,…
Predicting performance: relative importance of students' background and past performance.

PubMed

Stegers-Jager, Karen M; Themmen, Axel P N; Cohen-Schotanus, Janke; Steyerberg, Ewout W

2015-09-01

Despite evidence for the predictive value of both pre-admission characteristics and past performance at medical school, their relative contribution to predicting medical school performance has not been thoroughly investigated. This study was designed to determine the relative importance of pre-admission characteristics and past performance in medical school in predicting student performance in pre-clinical and clinical training. This longitudinal prospective study followed six cohorts of students admitted to a Dutch, 6-year, undergraduate medical course during 2002-2007 (n = 2357). Four prediction models were developed using multivariate logistic regression analysis. Main outcome measures were 'Year 1 course completion within 1 year' (models 1a, 1b), 'Pre-clinical course completion within 4 years' (model 2) and 'Achievement of at least three of five clerkship grades of ≥ 8.0' (model 3). Pre-admission characteristics (models 1a, 1b, 2, 3) and past performance at medical school (models 1b, 2, 3) were included as predictor variables. In model 1a - including pre-admission characteristics only - the strongest predictor for Year 1 course completion was pre-university grade point average (GPA). Success factors were 'selected by admission testing' and 'age > 21 years'; risk factors were 'Surinamese/Antillean background', 'foreign pre-university degree', 'doctor parent' and male gender. In model 1b, number of attempts and GPA at 4 months were the strongest predictors for Year 1 course completion, and male gender remained a risk factor. Year 1 GPA was the strongest predictor for pre-clinical course completion, whereas being male or aged 19-21 years were risk factors. Pre-clinical course GPA positively predicted clinical performance, whereas being non-Dutch or a first-generation university student were important risk factors for lower clinical grades. Nagelkerke's R(2) ranged from 0.16 to 0.62. This study not only confirms the importance of past performance as a predictor of future performance in pre-clinical training, but also reveals the importance of a student's background as a predictor in clinical training. These findings have important practical implications for selection and support during medical school. © 2015 John Wiley & Sons Ltd.
Women at the top: powerful leaders define success as work + family in a culture of gender.

PubMed

Cheung, Fanny M; Halpern, Diane F

2010-04-01

How do women rise to the top of their professions when they also have significant family care responsibilities? This critical question has not been addressed by existing models of leadership. In a review of recent research, we explore an alternative model to the usual notion of a Western male as the prototypical leader. The model includes (a) relationship-oriented leadership traits, (b) the importance of teamwork and consensus building, and (c) an effective work-family interface that women with family care responsibilities create and use to break through the glass ceiling. We adopted a cross-cultural perspective to highlight the importance of relational orientation and work-family integration in collectivistic cultures, which supplements models of leadership based on Western men. Our expanded model of leadership operates in the context of a "culture of gender" that defines expectations for women and men as leaders. This complex model includes women in diverse global contexts and enriches our understanding of the interplay among personal attributes, processes, and environments in leadership. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
Modern Perspectives on Numerical Modeling of Cardiac Pacemaker Cell

PubMed Central

Maltsev, Victor A.; Yaniv, Yael; Maltsev, Anna V.; Stern, Michael D.; Lakatta, Edward G.

2015-01-01

Cardiac pacemaking is a complex phenomenon that is still not completely understood. Together with experimental studies, numerical modeling has been traditionally used to acquire mechanistic insights in this research area. This review summarizes the present state of numerical modeling of the cardiac pacemaker, including approaches to resolve present paradoxes and controversies. Specifically we discuss the requirement for realistic modeling to consider symmetrical importance of both intracellular and cell membrane processes (within a recent “coupled-clock” theory). Promising future developments of the complex pacemaker system models include the introduction of local calcium control, mitochondria function, and biochemical regulation of protein phosphorylation and cAMP production. Modern numerical and theoretical methods such as multi-parameter sensitivity analyses within extended populations of models and bifurcation analyses are also important for the definition of the most realistic parameters that describe a robust, yet simultaneously flexible operation of the coupled-clock pacemaker cell system. The systems approach to exploring cardiac pacemaker function will guide development of new therapies, such as biological pacemakers for treating insufficient cardiac pacemaker function that becomes especially prevalent with advancing age. PMID:24748434
Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

ERIC Educational Resources Information Center

Carey, Cayelan C.; Gougis, Rebekka Darner

2017-01-01

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing)…
An Overview of Atmospheric Chemistry and Air Quality Modeling

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.

2017-01-01

This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.
Leveraging organismal biology to forecast the effects of climate change.

PubMed

Buckley, Lauren B; Cannistra, Anthony F; John, Aji

2018-04-26

Despite the pressing need for accurate forecasts of ecological and evolutionary responses to environmental change, commonly used modelling approaches exhibit mixed performance because they omit many important aspects of how organisms respond to spatially and temporally variable environments. Integrating models based on organismal phenotypes at the physiological, performance and fitness levels can improve model performance. We summarize current limitations of environmental data and models and discuss potential remedies. The paper reviews emerging techniques for sensing environments at fine spatial and temporal scales, accounting for environmental extremes, and capturing how organisms experience the environment. Intertidal mussel data illustrate biologically important aspects of environmental variability. We then discuss key challenges in translating environmental conditions into organismal performance including accounting for the varied timescales of physiological processes, for responses to environmental fluctuations including the onset of stress and other thresholds, and for how environmental sensitivities vary across lifecycles. We call for the creation of phenotypic databases to parameterize forecasting models and advocate for improved sharing of model code and data for model testing. We conclude with challenges in organismal biology that must be solved to improve forecasts over the next decade.acclimation, biophysical models, ecological forecasting, extremes, microclimate, spatial and temporal variability.
Strengthening the weak link: Built Environment modelling for loss analysis

NASA Astrophysics Data System (ADS)

Millinship, I.

2012-04-01

Methods to analyse insured losses from a range of natural perils, including pricing by primary insurers and catastrophe modelling by reinsurers, typically lack sufficient exposure information. Understanding the hazard intensity in terms of spatial severity and frequency is only the first step towards quantifying the risk of a catastrophic event. For any given event we need to know: Are any structures affected? What type of buildings are they? How much damaged occurred? How much will the repairs cost? To achieve this, detailed exposure information is required to assess the likely damage and to effectively calculate the resultant loss. Modelling exposures in the Built Environment therefore plays as important a role in understanding re/insurance risk as characterising the physical hazard. Across both primary insurance books and aggregated reinsurance portfolios, the location of a property (a risk) and its monetary value is typically known. Exactly what that risk is in terms of detailed property descriptors including structure type and rebuild cost - and therefore its vulnerability to loss - is often omitted. This data deficiency is a primary source of variations between modelled losses and the actual claims value. Built Environment models are therefore required at a high resolution to describe building attributes that relate vulnerability to property damage. However, national-scale household-level datasets are often not computationally practical in catastrophe models and data must be aggregated. In order to provide more accurate risk analysis, we have developed and applied a methodology for Built Environment modelling for incorporation into a range of re/insurance applications, including operational models for different international regions and different perils and covering residential, commercial and industry exposures. Illustrated examples are presented, including exposure modelling suitable for aggregated reinsurance analysis for the UK and bespoke high resolution modelling for industrial sites in Germany. A range of attributes are included following detailed claims analysis and engineering research with property type, age and condition identified as important differentiators of damage from flood, wind and freeze events.
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Modeling the Magnetopause Shadowing and Drift Orbit Bifurcation Loss during the June 2015 Dropout Event

NASA Astrophysics Data System (ADS)

Tu, W.; Cunningham, G.

2017-12-01

The relativistic electron flux in Earth's radiation belt are observed to drop by orders of magnitude on timescale of a few hours. Where do the electrons go during the dropout? This is one of the most important outstanding questions in radiation belt studies. Here we will study the 22 June 2015 dropout event which occurred during one of the largest geomagnetic storms in the last decade. A sudden and nearly complete loss of all the outer zone relativistic and ultra-relativistic electrons were observed after a strong interplanetary shock. The Last Closed Drift Shell (LCDS) calculated using the TS04 model reached as low as L*=3.7 during the shock and stay below L*=4 for 1 hour. The unusually low LCDS values suggest that magnetopause shadowing and the associated outward radial diffusion can contribute significantly to the observed dropout. In addition, Drift Orbit Bifurcation (DOB) has been suggested as an important loss mechanism for radiation belt electrons, especially when the solar wind dynamic pressure is high, but its relative importance has not been quantified. Here, we will model the June 2015 dropout event using a radial diffusion model that includes physical and event-specific inputs. First, we will trace electron drift shells based on TS04 model to identify the LCDS and bifurcation regions as a function of the 2nd adiabatic invariant (K) and time. To model magnetopause shadowing, electron lifetimes in our model will be set to electron drift periods at L*>LCDS. Electron lifetimes inside the bifurcation region have been estimated by Ukhorskiy et al. [JGR 2011, doi:10.1029/2011JA016623] as a function of L* and K, which will also be implemented in the model. This will be the first effort to include the DOB loss in a comprehensive radiation belt model. Furthermore, to realistically simulate outward radial diffusion, the new radial diffusion coefficients that are calculated based on the realistic TS04 model and include physical K dependence [Cunningham, JGR 2016, doi:10.1002/2015JA021981] will be achieved and included here. With these event-specific and physical model inputs, we will test how well the observed fast dropout during the June 2015 event can be reproduced by our model, and quantify the relative contribution of magnetopause shadowing, outward radial diffusion, and DOB to the fast electron depletion.
Computational Modeling of Space Physiology

NASA Technical Reports Server (NTRS)

Lewandowski, Beth E.; Griffin, Devon W.

2016-01-01

The Digital Astronaut Project (DAP), within NASAs Human Research Program, develops and implements computational modeling for use in the mitigation of human health and performance risks associated with long duration spaceflight. Over the past decade, DAP developed models to provide insights into space flight related changes to the central nervous system, cardiovascular system and the musculoskeletal system. Examples of the models and their applications include biomechanical models applied to advanced exercise device development, bone fracture risk quantification for mission planning, accident investigation, bone health standards development, and occupant protection. The International Space Station (ISS), in its role as a testing ground for long duration spaceflight, has been an important platform for obtaining human spaceflight data. DAP has used preflight, in-flight and post-flight data from short and long duration astronauts for computational model development and validation. Examples include preflight and post-flight bone mineral density data, muscle cross-sectional area, and muscle strength measurements. Results from computational modeling supplement space physiology research by informing experimental design. Using these computational models, DAP personnel can easily identify both important factors associated with a phenomenon and areas where data are lacking. This presentation will provide examples of DAP computational models, the data used in model development and validation, and applications of the model.

How Animal Models Inform Child and Adolescent Psychiatry

PubMed Central

Stevens, Hanna E.; Vaccarino, Flora M.

2015-01-01

Objective Every available approach should be utilized to advance the field of child and adolescent psychiatry. Biological systems are important for the behavioral problems of children. Close examination of non-human animals and the biology and behavior they share with humans is an approach that must be used to advance the clinical work of child psychiatry. Method We review here how model systems are used to contribute to significant insights into childhood psychiatric disorders. Model systems have not only demonstrated causality of risk factors for psychiatric pathophysiology but have also allowed child psychiatrists to think in different ways about risks for psychiatric disorders and multiple levels that might be the basis of recovery and prevention. Results We present examples of how animal systems are utilized to benefit child psychiatry, including through environmental, genetic, and acute biological manipulations. Animal model work has been essential in our current thinking about childhood disorders, including the importance of dose and timing of risk factors, specific features of risk factors that are significant, neurochemistry involved in brain functioning, molecular components of brain development, and the importance of cellular processes previously neglected in psychiatric theories. Conclusion Animal models have clear advantages and disadvantages that must both be considered for these systems to be useful. Coupled with increasingly sophisticated methods for investigating human behavior and biology, animal model systems will continue to make essential contributions to our field. PMID:25901771
Creating High Reliability in Health Care Organizations

PubMed Central

Pronovost, Peter J; Berenholtz, Sean M; Goeschel, Christine A; Needham, Dale M; Sexton, J Bryan; Thompson, David A; Lubomski, Lisa H; Marsteller, Jill A; Makary, Martin A; Hunt, Elizabeth

2006-01-01

Objective The objective of this paper was to present a comprehensive approach to help health care organizations reliably deliver effective interventions. Context Reliability in healthcare translates into using valid rate-based measures. Yet high reliability organizations have proven that the context in which care is delivered, called organizational culture, also has important influences on patient safety. Model for Improvement Our model to improve reliability, which also includes interventions to improve culture, focuses on valid rate-based measures. This model includes (1) identifying evidence-based interventions that improve the outcome, (2) selecting interventions with the most impact on outcomes and converting to behaviors, (3) developing measures to evaluate reliability, (4) measuring baseline performance, and (5) ensuring patients receive the evidence-based interventions. The comprehensive unit-based safety program (CUSP) is used to improve culture and guide organizations in learning from mistakes that are important, but cannot be measured as rates. Conclusions We present how this model was used in over 100 intensive care units in Michigan to improve culture and eliminate catheter-related blood stream infections—both were accomplished. Our model differs from existing models in that it incorporates efforts to improve a vital component for system redesign—culture, it targets 3 important groups—senior leaders, team leaders, and front line staff, and facilitates change management—engage, educate, execute, and evaluate for planned interventions. PMID:16898981
Importance of Dissolved Organic Nitrogen to Water Quality in Narragansett Bay

EPA Science Inventory

This preliminary analysis of the importance of the dissolved organic nitrogen (DON) pool in Narragansett Bay is being conducted as part of a five-year study of Narragansett Bay and its watershed. This larger study includes water quality and ecological modeling components that foc...
Increasing Effectiveness in Teaching Ethics to Undergraduate Business Students.

ERIC Educational Resources Information Center

Lampe, Marc

1997-01-01

Traditional approaches to teaching business ethics (philosophical analysis, moral quandaries, executive cases) may not be effective in persuading undergraduates of the importance of ethical behavior. Better techniques include values education, ethical decision-making models, analysis of ethical conflicts, and role modeling. (SK)
Maturity of hospital information systems: Most important influencing factors.

PubMed

Vidal Carvalho, João; Rocha, Álvaro; Abreu, António

2017-07-01

Maturity models facilitate organizational management, including information systems management, with hospital organizations no exception. This article puts forth a study carried out with a group of experts in the field of hospital information systems management with a view to identifying the main influencing factors to be included in an encompassing maturity model for hospital information systems management. This study is based on the results of a literature review, which identified maturity models in the health field and relevant influencing factors. The development of this model is justified to the extent that the available maturity models for the hospital information systems management field reveal multiple limitations, including lack of detail, absence of tools to determine their maturity and lack of characterization for stages of maturity structured by different influencing factors.
mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach

PubMed Central

2014-01-01

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology. PMID:24576337
Simulation of the Burridge-Knopoff model of earthquakes with variable range stress transfer.

PubMed

Xia, Junchao; Gould, Harvey; Klein, W; Rundle, J B

2005-12-09

Simple models of earthquake faults are important for understanding the mechanisms for their observed behavior, such as Gutenberg-Richter scaling and the relation between large and small events, which is the basis for various forecasting methods. Although cellular automaton models have been studied extensively in the long-range stress transfer limit, this limit has not been studied for the Burridge-Knopoff model, which includes more realistic friction forces and inertia. We find that the latter model with long-range stress transfer exhibits qualitatively different behavior than both the long-range cellular automaton models and the usual Burridge-Knopoff model with nearest-neighbor springs, depending on the nature of the velocity-weakening friction force. These results have important implications for our understanding of earthquakes and other driven dissipative systems.
Surface Adsorption in Nonpolarizable Atomic Models.

PubMed

Whitmer, Jonathan K; Joshi, Abhijeet A; Carlton, Rebecca J; Abbott, Nicholas L; de Pablo, Juan J

2014-12-09

Many ionic solutions exhibit species-dependent properties, including surface tension and the salting-out of proteins. These effects may be loosely quantified in terms of the Hofmeister series, first identified in the context of protein solubility. Here, our interest is to develop atomistic models capable of capturing Hofmeister effects rigorously. Importantly, we aim to capture this dependence in computationally cheap "hard" ionic models, which do not exhibit dynamic polarization. To do this, we have performed an investigation detailing the effects of the water model on these properties. Though incredibly important, the role of water models in simulation of ionic solutions and biological systems is essentially unexplored. We quantify this via the ion-dependent surface attraction of the halide series (Cl, Br, I) and, in so doing, determine the relative importance of various hypothesized contributions to ionic surface free energies. Importantly, we demonstrate surface adsorption can result in hard ionic models combined with a thermodynamically accurate representation of the water molecule (TIP4Q). The effect observed in simulations of iodide is commensurate with previous calculations of the surface potential of mean force in rigid molecular dynamics and polarizable density-functional models. Our calculations are direct simulation evidence of the subtle but sensitive role of water thermodynamics in atomistic simulations.
Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

PubMed Central

Huang, Jian; Zhang, Cun-Hui

2013-01-01

The ℓ1-penalized method, or the Lasso, has emerged as an important tool for the analysis of large data sets. Many important results have been obtained for the Lasso in linear regression which have led to a deeper understanding of high-dimensional statistical problems. In this article, we consider a class of weighted ℓ1-penalized estimators for convex loss functions of a general form, including the generalized linear models. We study the estimation, prediction, selection and sparsity properties of the weighted ℓ1-penalized estimator in sparse, high-dimensional settings where the number of predictors p can be much larger than the sample size n. Adaptive Lasso is considered as a special case. A multistage method is developed to approximate concave regularized estimation by applying an adaptive Lasso recursively. We provide prediction and estimation oracle inequalities for single- and multi-stage estimators, a general selection consistency theorem, and an upper bound for the dimension of the Lasso estimator. Important models including the linear regression, logistic regression and log-linear models are used throughout to illustrate the applications of the general results. PMID:24348100
Learning Layouts for Single-Page Graphic Designs.

PubMed

O'Donovan, Peter; Agarwala, Aseem; Hertzmann, Aaron

2014-08-01

This paper presents an approach for automatically creating graphic design layouts using a new energy-based model derived from design principles. The model includes several new algorithms for analyzing graphic designs, including the prediction of perceived importance, alignment detection, and hierarchical segmentation. Given the model, we use optimization to synthesize new layouts for a variety of single-page graphic designs. Model parameters are learned with Nonlinear Inverse Optimization (NIO) from a small number of example layouts. To demonstrate our approach, we show results for applications including generating design layouts in various styles, retargeting designs to new sizes, and improving existing designs. We also compare our automatic results with designs created using crowdsourcing and show that our approach performs slightly better than novice designers.
Studying Individual Differences in Predictability with Gamma Regression and Nonlinear Multilevel Models

ERIC Educational Resources Information Center

Culpepper, Steven Andrew

2010-01-01

Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…
A PBPK MODEL FOR EVALUATING THE IMPACT OF ALDEHYDE DEHYDROGENASE POLYMORPHISMS ON COMPARATIVE RAT AND HUMAN NASAL TISSUE ACETALDEHYDE DOSIMETRY

EPA Science Inventory

ABSTRACT: Acetaldehyde is an important intermediate in chemical synthesis and a byproduct of normal oxidative metabolism of several industrially important compounds including ethanol, ethyl acetate and vinyl acetate. Chronic inhalation of acetaldehyde leads to degeneratio...
Modeling greenhouse gas emissions from dairy farms

USDA-ARS?s Scientific Manuscript database

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric methane (CH4) from the animals, CH4 and nitrous oxide (N2O) from manure in housing facilities, during long-term storage and during field application, and N2O from...
The Importance of Music in Early Childhood.

ERIC Educational Resources Information Center

Levinowitz, Lili M.

1998-01-01

Surveys some of the research in music education that validates the inclusion of music for its own sake in models for early childhood learning. Focuses on topics that include, but are not limited to, child and vocal development, the importance of movement for children, and adult involvement in music education. (CMK)
A PBPK model for evaluating the impact of aldehyde dehydrogenase polymorphisms on comparative rat and human nasal tissue acetaldehyde dosimetry*

EPA Science Inventory

Acetaldehyde is an important intermediate in the chemical synthesis and normal oxidative metabolism of several industrially important compounds, including ethanol, ethyl acetate, and vinyl acetate. Chronic inhalation of acetaldehyde leads to degeneration of the olfactory and resp...
Effects of stochastic sodium channels on extracellular excitation of myelinated nerve fibers.

PubMed

Mino, Hiroyuki; Grill, Warren M

2002-06-01

The effects of the stochastic gating properties of sodium channels on the extracellular excitation properties of mammalian nerve fibers was determined by computer simulation. To reduce computation time, a hybrid multicompartment cable model including five central nodes of Ranvier containing stochastic sodium channels and 16 flanking nodes containing detenninistic membrane dynamics was developed. The excitation properties of the hybrid cable model were comparable with those of a full stochastic cable model including 21 nodes of Ranvier containing stochastic sodium channels, indicating the validity of the hybrid cable model. The hybrid cable model was used to investigate whether or not the excitation properties of extracellularly activated fibers were influenced by the stochastic gating of sodium channels, including spike latencies, strength-duration (SD), current-distance (IX), and recruitment properties. The stochastic properties of the sodium channels in the hybrid cable model had the greatest impact when considering the temporal dynamics of nerve fibers, i.e., a large variability in latencies, while they did not influence the SD, IX, or recruitment properties as compared with those of the conventional deterministic cable model. These findings suggest that inclusion of stochastic nodes is not important for model-based design of stimulus waveforms for activation of motor nerve fibers. However, in cases where temporal fine structure is important, for example in sensory neural prostheses in the auditory and visual systems, the stochastic properties of the sodium channels may play a key role in the design of stimulus waveforms.
Job Loss: An Individual Level Review and Model.

ERIC Educational Resources Information Center

DeFrank, Richard S.; Ivancevich, John M.

1986-01-01

Reviews behavioral, medical, and social science literature to illustrate the complexity and multidisciplinary nature of the job loss experience and provides a conceptual model to examine individual responses to job loss. Emphasizes the importance of including organizational-relevant variables in individual level conceptualizations and proposed…
MODELING FISH AND SHELLFISH DISTRIBUTIONS IN THE MOBILE BAY ESTUARY, USA

EPA Science Inventory

Estuaries in the Gulf of Mexico provide rich habitat for many fish and shellfish, including those that have been identified as economically and ecologically important. For the Mobile Bay estuary, we developed statistical models to relate distributions of individual species and sp...
Modeling the current and future role of particulate organic nitrates in the southeastern United States

EPA Science Inventory

Organic nitrates are an important aerosol constituent in locations where biogenic hydrocarbon emissions mix with anthropogenic NOx sources. While regional and global chemical transport models may include a representation of organic aerosol from monoterpene reactions with nitrate ...
Equations of state for hydrogen and deuterium.

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

Kerley, Gerald Irwin

2003-12-01

This report describes the complete revision of a deuterium equation of state (EOS) model published in 1972. It uses the same general approach as the 1972 EOS, i.e., the so-called 'chemical model,' but incorporates a number of theoretical advances that have taken place during the past thirty years. Three phases are included: a molecular solid, an atomic solid, and a fluid phase consisting of both molecular and atomic species. Ionization and the insulator-metal transition are also included. The most important improvements are in the liquid perturbation theory, the treatment of molecular vibrations and rotations, and the ionization equilibrium and mixturemore » models. In addition, new experimental data and theoretical calculations are used to calibrate certain model parameters, notably the zero-Kelvin isotherms for the molecular and atomic solids, and the quantum corrections to the liquid phase. The report gives a general overview of the model, followed by detailed discussions of the most important theoretical issues and extensive comparisons with the many experimental data that have been obtained during the last thirty years. Questions about the validity of the chemical model are also considered. Implications for modeling the 'giant planets' are also discussed.« less

Modelling C₃ photosynthesis from the chloroplast to the ecosystem.

PubMed

Bernacchi, Carl J; Bagley, Justin E; Serbin, Shawn P; Ruiz-Vera, Ursula M; Rosenthal, David M; Vanloocke, Andy

2013-09-01

Globally, photosynthesis accounts for the largest flux of CO₂ from the atmosphere into ecosystems and is the driving process for terrestrial ecosystem function. The importance of accurate predictions of photosynthesis over a range of plant growth conditions led to the development of a C₃ photosynthesis model by Farquhar, von Caemmerer & Berry that has become increasingly important as society places greater pressures on vegetation. The photosynthesis model has played a major role in defining the path towards scientific understanding of photosynthetic carbon uptake and the role of photosynthesis on regulating the earth's climate and biogeochemical systems. In this review, we summarize the photosynthesis model, including its continued development and applications. We also review the implications these developments have on quantifying photosynthesis at a wide range of spatial and temporal scales, and discuss the model's role in determining photosynthetic responses to changes in environmental conditions. Finally, the review includes a discussion of the larger-scale modelling and remote-sensing applications that rely on the leaf photosynthesis model and are likely to open new scientific avenues to address the increasing challenges to plant productivity over the next century. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
Challenges for Preclinical Investigations of Human Biofield Modalities

PubMed Central

Gronowicz, Gloria; Bengston, William

2015-01-01

Preclinical models for studying the effects of the human biofield have great potential to advance our understanding of human biofield modalities, which include external qigong, Johrei, Reiki, therapeutic touch, healing touch, polarity therapy, pranic healing, and other practices. A short history of Western biofield studies using preclinical models is presented and demonstrates numerous and consistent examples of human biofields significantly affecting biological systems both in vitro and in vivo. Methodological issues arising from these studies and practical solutions in experimental design are presented. Important questions still left unanswered with preclinical models include variable reproducibility, dosing, intentionality of the practitioner, best preclinical systems, and mechanisms. Input from the biofield practitioners in the experimental design is critical to improving experimental outcomes; however, the development of standard criteria for uniformity of practice and for inclusion of multiple practitioners is needed. Research in human biofield studies involving preclinical models promises a better understanding of the mechanisms underlying the efficacy of biofield therapies and will be important in guiding clinical protocols and integrating treatments with conventional medical therapies. PMID:26665042
A descriptivist approach to trait conceptualization and inference.

PubMed

Jonas, Katherine G; Markon, Kristian E

2016-01-01

In their recent article, How Functionalist and Process Approaches to Behavior Can Explain Trait Covariation, Wood, Gardner, and Harms (2015) underscore the need for more process-based understandings of individual differences. At the same time, the article illustrates a common error in the use and interpretation of latent variable models: namely, the misuse of models to arbitrate issues of causation and the nature of latent variables. Here, we explain how latent variables can be understood simply as parsimonious summaries of data, and how statistical inference can be based on choosing those summaries that minimize information required to represent the data using the model. Although Wood, Gardner, and Harms acknowledge this perspective, they underestimate its significance, including its importance to modeling and the conceptualization of psychological measurement. We believe this perspective has important implications for understanding individual differences in a number of domains, including current debates surrounding the role of formative versus reflective latent variables. (c) 2015 APA, all rights reserved).
Modeling our understanding of the His-Purkinje system.

PubMed

Vigmond, Edward J; Stuyvers, Bruno D

2016-01-01

The His-Purkinje System (HPS) is responsible for the rapid electric conduction in the ventricles. It relays electrical impulses from the atrioventricular node to the muscle cells and, thus, coordinates the contraction of ventricles in order to ensure proper cardiac pump function. The HPS has been implicated in the genesis of ventricular tachycardia and fibrillation as a source of ectopic beats, as well as forming distinct portions of reentry circuitry. Despite its importance, it remains much less well characterized, structurally and functionally, than the myocardium. Notably, important differences exist with regard to cell structure and electrophysiology, including ion channels, intracellular calcium handling, and gap junctions. Very few computational models address the HPS, and the majority of organ level modeling studies omit it. This review will provide an overview of our current knowledge of structure and function (including electrophysiology) of the HPS. We will review the most recent advances in modeling of the system from the single cell to the organ level, with considerations for relevant interspecies distinctions. Copyright © 2015 Elsevier Ltd. All rights reserved.
A smoothed particle hydrodynamics framework for modelling multiphase interactions at meso-scale

NASA Astrophysics Data System (ADS)

Li, Ling; Shen, Luming; Nguyen, Giang D.; El-Zein, Abbas; Maggi, Federico

2018-01-01

A smoothed particle hydrodynamics (SPH) framework is developed for modelling multiphase interactions at meso-scale, including the liquid-solid interaction induced deformation of the solid phase. With an inter-particle force formulation that mimics the inter-atomic force in molecular dynamics, the proposed framework includes the long-range attractions between particles, and more importantly, the short-range repulsive forces to avoid particle clustering and instability problems. Three-dimensional numerical studies have been conducted to demonstrate the capabilities of the proposed framework to quantitatively replicate the surface tension of water, to model the interactions between immiscible liquids and solid, and more importantly, to simultaneously model the deformation of solid and liquid induced by the multiphase interaction. By varying inter-particle potential magnitude, the proposed SPH framework has successfully simulated various wetting properties ranging from hydrophobic to hydrophilic surfaces. The simulation results demonstrate the potential of the proposed framework to genuinely study complex multiphase interactions in wet granular media.
Importance of fish behaviour in modelling conservation problems: food limitation as an example

Treesearch

Steven Railsback; Bret Harvey

2011-01-01

Simulation experiments using the inSTREAM individual-based brown trout Salmo trutta population model explored the role of individual adaptive behaviour in food limitation, as an example of how behaviour can affect managersâ understanding of conservation problems. The model includes many natural complexities in habitat (spatial and temporal variation in characteristics...
Production of Accurate Skeletal Models of Domestic Animals Using Three-Dimensional Scanning and Printing Technology

ERIC Educational Resources Information Center

Li, Fangzheng; Liu, Chunying; Song, Xuexiong; Huan, Yanjun; Gao, Shansong; Jiang, Zhongling

2018-01-01

Access to adequate anatomical specimens can be an important aspect in learning the anatomy of domestic animals. In this study, the authors utilized a structured light scanner and fused deposition modeling (FDM) printer to produce highly accurate animal skeletal models. First, various components of the bovine skeleton, including the femur, the…
A smoothed residual based goodness-of-fit statistic for nest-survival models

Treesearch

Rodney X. Sturdivant; Jay J. Rotella; Robin E. Russell

2008-01-01

Estimating nest success and identifying important factors related to nest-survival rates is an essential goal for many wildlife researchers interested in understanding avian population dynamics. Advances in statistical methods have led to a number of estimation methods and approaches to modeling this problem. Recently developed models allow researchers to include a...
Animal models of fibromyalgia

PubMed Central

2013-01-01

Animal models of disease states are valuable tools for developing new treatments and investigating underlying mechanisms. They should mimic the symptoms and pathology of the disease and importantly be predictive of effective treatments. Fibromyalgia is characterized by chronic widespread pain with associated co-morbid symptoms that include fatigue, depression, anxiety and sleep dysfunction. In this review, we present different animal models that mimic the signs and symptoms of fibromyalgia. These models are induced by a wide variety of methods that include repeated muscle insults, depletion of biogenic amines, and stress. All potential models produce widespread and long-lasting hyperalgesia without overt peripheral tissue damage and thus mimic the clinical presentation of fibromyalgia. We describe the methods for induction of the model, pathophysiological mechanisms for each model, and treatment profiles. PMID:24314231
Constraining the Magmatic System at Mount St. Helens (2004-2008) Using Bayesian Inversion With Physics-Based Models Including Gas Escape and Crystallization

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

Wong, Ying -Qi; Segall, Paul; Bradley, Andrew

Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock andmore » magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5 wt %) total volatiles and that the magma permeability scale is well constrained at ~10 –11.4m 2 to reproduce observed dome rock porosities. Here, compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.« less
Constraining the Magmatic System at Mount St. Helens (2004-2008) Using Bayesian Inversion With Physics-Based Models Including Gas Escape and Crystallization

NASA Astrophysics Data System (ADS)

Wong, Ying-Qi; Segall, Paul; Bradley, Andrew; Anderson, Kyle

2017-10-01

Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock and magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5 wt %) total volatiles and that the magma permeability scale is well constrained at ˜10-11.4m2 to reproduce observed dome rock porosities. Compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.
Constraining the Magmatic System at Mount St. Helens (2004-2008) Using Bayesian Inversion With Physics-Based Models Including Gas Escape and Crystallization

DOE PAGES

Wong, Ying -Qi; Segall, Paul; Bradley, Andrew; ...

2017-10-04

Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock andmore » magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5 wt %) total volatiles and that the magma permeability scale is well constrained at ~10 –11.4m 2 to reproduce observed dome rock porosities. Here, compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.« less
Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization

USGS Publications Warehouse

Wong, Ying-Qi; Segall, Paul; Bradley, Andrew; Anderson, Kyle R.

2017-01-01

Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock and magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5wt%) total volatiles and that the magma permeability scale is well constrained at ~10-11.4 m2 to reproduce observed dome rock porosities. Compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.
Command Process Modeling & Risk Analysis

NASA Technical Reports Server (NTRS)

Meshkat, Leila

2011-01-01

Commanding Errors may be caused by a variety of root causes. It's important to understand the relative significance of each of these causes for making institutional investment decisions. One of these causes is the lack of standardized processes and procedures for command and control. We mitigate this problem by building periodic tables and models corresponding to key functions within it. These models include simulation analysis and probabilistic risk assessment models.
MicroRNAs and complex diseases: from experimental results to computational models.

PubMed

Chen, Xing; Xie, Di; Zhao, Qi; You, Zhu-Hong

2017-10-17

Plenty of microRNAs (miRNAs) were discovered at a rapid pace in plants, green algae, viruses and animals. As one of the most important components in the cell, miRNAs play a growing important role in various essential and important biological processes. For the recent few decades, amounts of experimental methods and computational models have been designed and implemented to identify novel miRNA-disease associations. In this review, the functions of miRNAs, miRNA-target interactions, miRNA-disease associations and some important publicly available miRNA-related databases were discussed in detail. Specially, considering the important fact that an increasing number of miRNA-disease associations have been experimentally confirmed, we selected five important miRNA-related human diseases and five crucial disease-related miRNAs and provided corresponding introductions. Identifying disease-related miRNAs has become an important goal of biomedical research, which will accelerate the understanding of disease pathogenesis at the molecular level and molecular tools design for disease diagnosis, treatment and prevention. Computational models have become an important means for novel miRNA-disease association identification, which could select the most promising miRNA-disease pairs for experimental validation and significantly reduce the time and cost of the biological experiments. Here, we reviewed 20 state-of-the-art computational models of predicting miRNA-disease associations from different perspectives. Finally, we summarized four important factors for the difficulties of predicting potential disease-related miRNAs, the framework of constructing powerful computational models to predict potential miRNA-disease associations including five feasible and important research schemas, and future directions for further development of computational models. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Lutein and Zeaxanthin—Food Sources, Bioavailability and Dietary Variety in Age-Related Macular Degeneration Protection

PubMed Central

Eisenhauer, Bronwyn; Natoli, Sharon; Liew, Gerald; Flood, Victoria M.

2017-01-01

Lutein and zeaxanthin (L/Z) are the predominant carotenoids which accumulate in the retina of the eye. The impact of L/Z intake on the risk and progression of age-related macular degeneration (AMD), a leading cause of blindness in the developed world, has been investigated in cohort studies and clinical trials. The aims of this review were to critically examine the literature and evaluate the current evidence relating to L/Z intake and AMD, and describe important food sources and factors that increase the bioavailability of L/Z, to inform dietary models. Cohort studies generally assessed L/Z from dietary sources, while clinical trials focused on providing L/Z as a supplement. Important considerations to take into account in relation to dietary L/Z include: nutrient-rich sources of L/Z, cooking methods, diet variety and the use of healthy fats. Dietary models include examples of how suggested effective levels of L/Z can be achieved through diet alone, with values of 5 mg and 10 mg per day described. These diet models depict a variety of food sources, not only from dark green leafy vegetables, but also include pistachio nuts and other highly bioavailable sources of L/Z such as eggs. This review and the diet models outlined provide information about the importance of diet variety among people at high risk of AMD or with early signs and symptoms of AMD. PMID:28208784
The Atmospheric Tomography Mission (ATom): Comparing the Chemical Climatology of Reactive Species and Air Parcels from Measurements and Global Models

NASA Astrophysics Data System (ADS)

Prather, M. J.; Flynn, C.; Wennberg, P. O.; Kim, M. J.; Ryerson, T. B.; Hanisco, T. F.; Diskin, G. S.; Daube, B. C.; Commane, R.; McKain, K.; Apel, E. C.; Blake, N. J.; Blake, D. R.; Elkins, J. W.; Hall, S.; Steenrod, S.; Strahan, S. E.; Lamarque, J. F.; Fiore, A. M.; Horowitz, L. W.; Murray, L. T.; Mao, J.; Shindell, D. T.; Wofsy, S. C.

2017-12-01

The NASA Atmospheric Tomography Mission (ATom) is building a photochemical climatology of the remote troposphere based on objective sampling and profiling transects over the Pacific and Atlantic Oceans. These statistics provide direct tests of chemistry-climate models. The choice of species focuses on those controlling primary reactivity (a.k.a. oxidative state) of the troposphere, specifically chemical tendencies of O3 and CH4. These key species include, inter alia, O3, CH4, CO, C2H6, other alkanes, alkenes, aromatics, NOx, HNO3, HO2NO2, PAN, other organic nitrates, H2O, HCHO, H2O2, CH3OOH. Three of the four ATom deployments are now complete, and data from the first two (ATom-1 & -2) have been released as of this talk (see espoarchive.nasa.gov/archive/browse/atom). The statistical distributions of key species are presented as 1D and 2D probability densities (PDs) and we focus here on the tropical and mid-latitude regions of the Pacific during ATom-1 (Aug) and -2 (Feb). PDs are computed from ATom observations and 6 global chemistry models over the tropospheric depth (0-12 km) and longitudinal extent of the observations. All data are weighted to achieve equal mass-weighting by latitude regimes to account for spatial sampling biases. The models are used to calculate the reactivity in each ATom air parcel. Reweighting parcels with loss of CH4 or production of O3, for example, allows us to identify which air parcels are most influential, including assessment of the importance of fine pollution layers in the most remote troposphere. Another photochemical climatology developed from ATom, and used to test models, includes the effect of clouds on photolysis rates. The PDs and reactivity-weighted PDs reveal important seasonal differences and similarities between the two campaigns and also show which species may be most important in controlling reactivities. They clearly identify some very specific failings in the modeled climatologies and help us evaluate the chemical importance of fine-scale laminae with distinct chemical composition that are beyond model simulations.
Model-experiment interaction to improve representation of phosphorus limitation in land models

NASA Astrophysics Data System (ADS)

Norby, R. J.; Yang, X.; Cabugao, K. G. M.; Childs, J.; Gu, L.; Haworth, I.; Mayes, M. A.; Porter, W. S.; Walker, A. P.; Weston, D. J.; Wright, S. J.

2015-12-01

Carbon-nutrient interactions play important roles in regulating terrestrial carbon cycle responses to atmospheric and climatic change. None of the CMIP5 models has included routines to represent the phosphorus (P) cycle, although P is commonly considered to be the most limiting nutrient in highly productive, lowland tropical forests. Model simulations with the Community Land Model (CLM-CNP) show that inclusion of P coupling leads to a smaller CO2 fertilization effect and warming-induced CO2 release from tropical ecosystems, but there are important uncertainties in the P model, and improvements are limited by a dearth of data. Sensitivity analysis identifies the relative importance of P cycle parameters in determining P availability and P limitation, and thereby helps to define the critical measurements to make in field campaigns and manipulative experiments. To improve estimates of P supply, parameters that describe maximum amount of labile P in soil and sorption-desorption processes are necessary for modeling the amount of P available for plant uptake. Biochemical mineralization is poorly constrained in the model and will be improved through field observations that link root traits to mycorrhizal activity, phosphatase activity, and root depth distribution. Model representation of P demand by vegetation, which currently is set by fixed stoichiometry and allometric constants, requires a different set of data. Accurate carbon cycle modeling requires accurate parameterization of the photosynthetic machinery: Vc,max and Jmax. Relationships between the photosynthesis parameters and foliar nutrient (N and P) content are being developed, and by including analysis of covariation with other plant traits (e.g., specific leaf area, wood density), we can provide a basis for more dynamic, trait-enabled modeling. With this strong guidance from model sensitivity and uncertainty analysis, field studies are underway in Puerto Rico and Panama to collect model-relevant data on P supply and demand functions. New FACE and soil warming experiments in P-limited ecosystems in subtropical Australia, and tropical Brazil, Puerto Rico, and Panama will provide important benchmarks for the performance of P-enabled models under future conditions.
Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth

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

Atul Jain, University of Illinois, Urbana-Champaign, IL

2009-10-14

The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full projectmore » period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.« less
Peer Models in Mental Health for Caregivers and Families.

PubMed

Acri, Mary; Hooley, Cole D; Richardson, Nicole; Moaba, Lily B

2017-02-01

Peer-delivered mental health models may hold important benefits for family members, yet their prevalence, components, and outcomes are unknown. We conducted a review of peer-delivered services for families of children and adults with mental health problems. Randomized studies of interventions published between 1990 and 2014 were included if the intervention contained a component for family members and examined familial outcomes. Of 77 studies that were assessed for their eligibility, six met criteria. Familial components included coping and parenting skills, knowledge about mental health, and emotional support. Outcomes were uneven, although significant improvements in family functioning, knowledge about mental illness, parental concerns about their child, and parenting skills were associated with the intervention. Peer-delivered services for family members may have important benefits to family members and individuals with mental health problems; however, the research base remains thin. A research agenda to develop and examine these models is discussed.

A multivariate model of parent-adolescent relationship variables in early adolescence.

PubMed

McKinney, Cliff; Renk, Kimberly

2011-08-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle school in a Southeastern state. The parents of a subset of these adolescents (i.e., 487 mother-father pairs) participated in this study as well. Correlational analyses indicate that authoritative and authoritarian parenting, family cohesion and adaptability, and conflict are significant predictors of early adolescents' internalizing and externalizing problems. Structural equation modeling analyses indicate that fathers' parenting may not predict directly externalizing problems in male and female adolescents but instead may act through conflict. More direct relationships exist when examining mothers' parenting. The impact of parenting, family environment, and conflict on early adolescents' internalizing and externalizing problems and the importance of both gender and cross-informant ratings are emphasized.
Analysis of functional importance of binding sites in the Drosophila gap gene network model.

PubMed

Kozlov, Konstantin; Gursky, Vitaly V; Kulakovskiy, Ivan V; Dymova, Arina; Samsonova, Maria

2015-01-01

The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.
Screen and clean: a tool for identifying interactions in genome-wide association studies.

PubMed

Wu, Jing; Devlin, Bernie; Ringquist, Steven; Trucco, Massimo; Roeder, Kathryn

2010-04-01

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.
Latent heat sink in soil heat flux measurements

USDA-ARS?s Scientific Manuscript database

The surface energy balance includes a term for soil heat flux. Soil heat flux is difficult to measure because it includes conduction and convection heat transfer processes. Accurate representation of soil heat flux is an important consideration in many modeling and measurement applications. Yet, the...
Latent Heat in Soil Heat Flux Measurements

USDA-ARS?s Scientific Manuscript database

The surface energy balance includes a term for soil heat flux. Soil heat flux is difficult to measure because it includes conduction and convection heat transfer processes. Accurate representation of soil heat flux is an important consideration in many modeling and measurement applications. Yet, the...
Trauma and Juvenile Delinquency: Theory, Research, and Interventions.

ERIC Educational Resources Information Center

Greenwald, Ricky, Ed.

This book addresses the connection between childhood trauma and juvenile delinquency. It includes theoretical models of this relationship and examinations of its most important aspects, explorations of trauma-related assessment issues, and practical therapeutic interventions for use with juvenile delinquents. Chapters include: (1) "The Role…
Computational Insights into the O2-evolving complex of photosystem II

PubMed Central

Sproviero, Eduardo M.; McEvoy, James P.; Gascón, José A.; Brudvig, Gary W.; Batista, Victor S.

2009-01-01

Mechanistic investigations of the water-splitting reaction of the oxygen-evolving complex (OEC) of photosystem II (PSII) are fundamentally informed by structural studies. Many physical techniques have provided important insights into the OEC structure and function, including X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS) spectroscopy as well as mass spectrometry (MS), electron paramagnetic resonance (EPR) spectroscopy and Fourier transform infrared spectroscopy applied in conjunction with mutagenesis studies. However, experimental studies have yet to yield consensus as to the exact configuration of the catalytic metal cluster and its ligation scheme. Computational modeling studies, including density functional (DFT) theory combined with quantum mechanics/molecular mechanics (QM/MM) hybrid methods for explicitly including the influence of the surrounding protein, have proposed chemically satisfactory models of the fully ligated OEC within PSII that are maximally consistent with experimental results. The inorganic core of these models is similar to the crystallographic model upon which they were based but comprises important modifications due to structural refinement, hydration and proteinaceous ligation which improve agreement with a wide range of experimental data. The computational models are useful for rationalizing spectroscopic and crystallographic results and for building a complete structure-based mechanism of water-splitting in PSII as described by the intermediate oxidation states of the OEC. This review summarizes these recent advances in QM/MM modeling of PSII within the context of recent experimental studies. PMID:18483777
Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China.

PubMed

Zhai, Binxu; Chen, Jianguo

2018-04-18

A stacked ensemble model is developed for forecasting and analyzing the daily average concentrations of fine particulate matter (PM 2.5 ) in Beijing, China. Special feature extraction procedures, including those of simplification, polynomial, transformation and combination, are conducted before modeling to identify potentially significant features based on an exploratory data analysis. Stability feature selection and tree-based feature selection methods are applied to select important variables and evaluate the degrees of feature importance. Single models including LASSO, Adaboost, XGBoost and multi-layer perceptron optimized by the genetic algorithm (GA-MLP) are established in the level 0 space and are then integrated by support vector regression (SVR) in the level 1 space via stacked generalization. A feature importance analysis reveals that nitrogen dioxide (NO 2 ) and carbon monoxide (CO) concentrations measured from the city of Zhangjiakou are taken as the most important elements of pollution factors for forecasting PM 2.5 concentrations. Local extreme wind speeds and maximal wind speeds are considered to extend the most effects of meteorological factors to the cross-regional transportation of contaminants. Pollutants found in the cities of Zhangjiakou and Chengde have a stronger impact on air quality in Beijing than other surrounding factors. Our model evaluation shows that the ensemble model generally performs better than a single nonlinear forecasting model when applied to new data with a coefficient of determination (R 2 ) of 0.90 and a root mean squared error (RMSE) of 23.69μg/m 3 . For single pollutant grade recognition, the proposed model performs better when applied to days characterized by good air quality than when applied to days registering high levels of pollution. The overall classification accuracy level is 73.93%, with most misclassifications made among adjacent categories. The results demonstrate the interpretability and generalizability of the stacked ensemble model. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Modelling Parameters Characterizing Selected Water Supply Systems in Lower Silesia Province

NASA Astrophysics Data System (ADS)

Nowogoński, Ireneusz; Ogiołda, Ewa

2017-12-01

The work presents issues of modelling water supply systems in the context of basic parameters characterizing their operation. In addition to typical parameters, such as water pressure and flow rate, assessing the age of the water is important, as a parameter of assessing the quality of the distributed medium. The analysis was based on two facilities, including one with a diverse spectrum of consumers, including residential housing and industry. The carried out simulations indicate the possibility of the occurrence of water quality degradation as a result of excessively long periods of storage in the water supply network. Also important is the influence of the irregularity of water use, especially in the case of supplying various kinds of consumers (in the analysed case - mining companies).
Factors Influencing Cerebral Plasticity in the Normal and Injured Brain

PubMed Central

Kolb, Bryan; Teskey, G. Campbell; Gibb, Robbin

2010-01-01

An important development in behavioral neuroscience in the past 20 years has been the demonstration that it is possible to stimulate functional recovery after cerebral injury in laboratory animals. Rodent models of cerebral injury provide an important tool for developing such rehabilitation programs. The models include analysis at different levels including detailed behavioral paradigms, electrophysiology, neuronal morphology, protein chemistry, and epigenetics. A significant challenge for the next 20 years will be the translation of this work to improve the outcome from brain injury and disease in humans. Our goal in the article will be to synthesize the multidisciplinary laboratory work on brain plasticity and behavior in the injured brain to inform the development of rehabilitation programs. PMID:21120136
Infection prevention behaviour and infectious disease modelling: a review of the literature and recommendations for the future.

PubMed

Weston, Dale; Hauck, Katharina; Amlôt, Richard

2018-03-09

Given the importance of person to person transmission in the spread of infectious diseases, it is critically important to ensure that human behaviour with respect to infection prevention is appropriately represented within infectious disease models. This paper presents a large scale scoping review regarding the incorporation of infection prevention behaviour in infectious disease models. The outcomes of this review are contextualised within the psychological literature concerning health behaviour and behaviour change, resulting in a series of key recommendations for the incorporation of human behaviour in future infectious disease models. The search strategy focused on terms relating to behaviour, infectious disease and mathematical modelling. The selection criteria were developed iteratively to focus on original research articles that present an infectious disease model with human-human spread, in which individuals' self-protective health behaviour varied endogenously within the model. Data extracted included: the behaviour that is modelled; how this behaviour is modelled; any theoretical background for the modelling of behaviour, and; any behavioural data used to parameterise the models. Forty-two papers from an initial total of 2987 were retained for inclusion in the final review. All of these papers were published between 2002 and 2015. Many of the included papers employed a multiple, linked models to incorporate infection prevention behaviour. Both cognitive constructs (e.g., perceived risk) and, to a lesser extent, social constructs (e.g., social norms) were identified in the included papers. However, only five papers made explicit reference to psychological health behaviour change theories. Finally, just under half of the included papers incorporated behavioural data in their modelling. By contextualising the review outcomes within the psychological literature on health behaviour and behaviour change, three key recommendations for future behavioural modelling are made. First, modellers should consult with the psychological literature on health behaviour/ behaviour change when developing new models. Second, modellers interested in exploring the relationship between behaviour and disease spread should draw on social psychological literature to increase the complexity of the social world represented within infectious disease models. Finally, greater use of context-specific behavioural data (e.g., survey data, observational data) is recommended to parameterise models.
A modeling study examining the impact of nutrient boundaries ...

EPA Pesticide Factsheets

A mass balance eutrophication model, Gulf of Mexico Dissolved Oxygen Model (GoMDOM), has been developed and applied to describe nitrogen, phosphorus and primary production in the Louisiana shelf of the Gulf of Mexico. Features of this model include bi-directional boundary exchanges, an empirical site-specific light attenuation equation, estimates of 56 river loads and atmospheric loads. The model was calibrated for 2006 by comparing model output to observations in zones that represent different locations in the Gulf. The model exhibited reasonable skill in simulating the phosphorus and nitrogen field data and primary production observations. The model was applied to generate a nitrogen mass balance estimate, to perform sensitivity analysis to compare the importance of the nutrient boundary concentrations versus the river loads on nutrient concentrations and primary production within the shelf, and to provide insight into the relative importance of different limitation factors on primary production. The mass budget showed the importance of the rivers as the major external nitrogen source while the atmospheric load contributed approximately 2% of the total external load. Sensitivity analysis showed the importance of accurate estimates of boundary nitrogen concentrations on the nitrogen levels on the shelf, especially at regions further away from the river influences. The boundary nitrogen concentrations impacted primary production less than nitrogen concent
General Equilibrium Models: Improving the Microeconomics Classroom

ERIC Educational Resources Information Center

Nicholson, Walter; Westhoff, Frank

2009-01-01

General equilibrium models now play important roles in many fields of economics including tax policy, environmental regulation, international trade, and economic development. The intermediate microeconomics classroom has not kept pace with these trends, however. Microeconomics textbooks primarily focus on the insights that can be drawn from the…
Advances in statistics

Treesearch

Howard Stauffer; Nadav Nur

2005-01-01

The papers included in the Advances in Statistics section of the Partners in Flight (PIF) 2002 Proceedings represent a small sample of statistical topics of current importance to Partners In Flight research scientists: hierarchical modeling, estimation of detection probabilities, and Bayesian applications. Sauer et al. (this volume) examines a hierarchical model...
Multidimensional Model of Trauma and Correlated Antisocial Personality Disorder

ERIC Educational Resources Information Center

Martens, Willem H. J.

2005-01-01

Many studies have revealed an important relationship between psychosocial trauma and antisocial personality disorder. A multidimensional model is presented which describes the psychopathological route from trauma to antisocial development. A case report is also included that can illustrate the etiological process from trauma to severe antisocial…
CFD Code Development for Combustor Flows

NASA Technical Reports Server (NTRS)

Norris, Andrew

2003-01-01

During the lifetime of this grant, work has been performed in the areas of model development, code development, code validation and code application. For model development, this has included the PDF combustion module, chemical kinetics based on thermodynamics, neural network storage of chemical kinetics, ILDM chemical kinetics and assumed PDF work. Many of these models were then implemented in the code, and in addition many improvements were made to the code, including the addition of new chemistry integrators, property evaluation schemes, new chemistry models and turbulence-chemistry interaction methodology. Validation of all new models and code improvements were also performed, while application of the code to the ZCET program and also the NPSS GEW combustor program were also performed. Several important items remain under development, including the NOx post processing, assumed PDF model development and chemical kinetic development. It is expected that this work will continue under the new grant.
Modeling procedures for handling qualities evaluation of flexible aircraft

NASA Technical Reports Server (NTRS)

Govindaraj, K. S.; Eulrich, B. J.; Chalk, C. R.

1981-01-01

This paper presents simplified modeling procedures to evaluate the impact of flexible modes and the unsteady aerodynamic effects on the handling qualities of Supersonic Cruise Aircraft (SCR). The modeling procedures involve obtaining reduced order transfer function models of SCR vehicles, including the important flexible mode responses and unsteady aerodynamic effects, and conversion of the transfer function models to time domain equations for use in simulations. The use of the modeling procedures is illustrated by a simple example.
From bench to patient: model systems in drug discovery

PubMed Central

Breyer, Matthew D.; Look, A. Thomas; Cifra, Alessandra

2015-01-01

ABSTRACT Model systems, including laboratory animals, microorganisms, and cell- and tissue-based systems, are central to the discovery and development of new and better drugs for the treatment of human disease. In this issue, Disease Models & Mechanisms launches a Special Collection that illustrates the contribution of model systems to drug discovery and optimisation across multiple disease areas. This collection includes reviews, Editorials, interviews with leading scientists with a foot in both academia and industry, and original research articles reporting new and important insights into disease therapeutics. This Editorial provides a summary of the collection's current contents, highlighting the impact of multiple model systems in moving new discoveries from the laboratory bench to the patients' bedsides. PMID:26438689
pyres: a Python wrapper for electrical resistivity modeling with R2

NASA Astrophysics Data System (ADS)

Befus, Kevin M.

2018-04-01

A Python package, pyres, was written to handle common as well as specialized input and output tasks for the R2 electrical resistivity (ER) modeling program. Input steps including handling field data, creating quadrilateral or triangular meshes, and data filtering allow repeatable and flexible ER modeling within a programming environment. pyres includes non-trivial routines and functions for locating and constraining specific known or separately-parameterized regions in both quadrilateral and triangular meshes. Three basic examples of how to run forward and inverse models with pyres are provided. The importance of testing mesh convergence and model sensitivity are also addressed with higher-level examples that show how pyres can facilitate future research-grade ER analyses.
A multidimensional approach to understanding the potential risk factors and covariates of adult picky eating.

PubMed

Ellis, Jordan M; Schenk, Rebecca R; Galloway, Amy T; Zickgraf, Hana F; Webb, Rose Mary; Martz, Denise M

2018-06-01

Adult picky eating (PE) has received increased attention in the eating behavior literature due to its important association with adult avoidant-restrictive food intake disorder (ARFID). The current study tested a model of potential risk factors of adult PE behavior, including perceived early parental feeding practices. An exploratory model was also utilized to understand associations with different aspects of adult PE behaviors. A sample of 1339 US adults recruited through Amazon's MTurk completed an online survey that included the recently developed Adult Picky Eating Questionnaire (APEQ), retrospective reports of parental feeding practices, and other measures of eating behavior and demographic variables. A structural equation modeling procedure tested a series of regression models that included BMI and disordered eating behaviors as covariates. SEM modeling indicated that retrospective reports of greater parental pressure to eat, higher disgust sensitivity, lower PE age of onset, and experiencing an aversive food event were associated with general adult PE behavior. Results also indicated parental encouragement of healthy eating may be a protective factor, and that men endorsed higher levels of adult PE. Exploratory analyses indicated that cross-sectional predictors and covariates were differentially related to specific aspects of PE as measured by the APEQ subscales. Early experiences, including parental approaches to feeding, appear to be potential risk factors of PE behavior in adults. A nuanced understanding of adult PE is important for the prevention and treatment of severe PE behaviors, related psychosocial impairment, and ARFID. Copyright © 2018 Elsevier Ltd. All rights reserved.

MISTRA mechanism development: A new mechanism focused on marine environments

NASA Astrophysics Data System (ADS)

Bräuer, Peter; Sommariva, Roberto; von Glasow, Roland

2015-04-01

The tropospheric multiphase chemistry of halogen compounds plays a key role in marine environments. Moreover, halogen compounds have an impact on the tropospheric oxidation capacity and climate. With more than two thirds of the Earth's surface covered with oceans, effects are of global importance. Various conditions are found in marine environments ranging from pristine regions to polluted regimes in the continental outflow. Furthermore, there are important sources for halogen compounds over land, such as volcanoes, salt lakes, or emissions from industrial processes. To assess the impact of halogen chemistry with numerical models under these distinct conditions, a multiphase mechanism has been developed in the last decades and applied successfully in numerous box and 1D model studies. Contributions from these model studies helped to identify important chemical cycles affecting the composition and chemistry of the troposphere. However, several discrepancies between model results and field measurements remain. Therefore, a major revision of the chemical mechanism has been performed including an update of the kinetic data and the addition of new reaction cycles. The extended mechansims have been evaluated in several model studies with the 1D model MISTRA. Current work focuses at the identification of the most important reaction cycles, which led to significant changes in the concentration-time profiles of several halogen species. Subsequently, the mechanism will be reduced to the most imporatant reactions, which are currently investigated. As regional and global model studies become more important to identify the importance of tropospheric halogen multiphase chemistry, the goal is to derive parameterisations for the most important halogen chemistry cycles, which can than be implemented in regional and global 3D models. In the reduction process, the extented MISTRA version will serve as a benchmark to assess the quality and accuracy of the reduced mechansim versions.
Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.
Paired and interacting galaxies: Conference summary

NASA Technical Reports Server (NTRS)

Norman, Colin A.

1990-01-01

The author gives a summary of the conference proceedings. The conference began with the presentation of the basic data sets on pairs, groups, and interacting galaxies with the latter being further discussed with respect to both global properties and properties of the galactic nuclei. Then followed the theory, modelling and interpretation using analytic techniques, simulations and general modelling for spirals and ellipticals, starbursts and active galactic nuclei. Before the conference the author wrote down the three questions concerning pairs, groups and interacting galaxies that he hoped would be answered at the meeting: (1) How do they form, including the role of initial conditions, the importance of subclustering, the evolution of groups to compact groups, and the fate of compact groups; (2) How do they evolve, including issues such as relevant timescales, the role of halos and the problem of overmerging, the triggering and enhancement of star formation and activity in the galactic nuclei, and the relative importance of dwarf versus giant encounters; and (3) Are they important, including the frequency of pairs and interactions, whether merging and interactions are very important aspects of the life of a normal galaxy at formation, during its evolution, in forming bars, shells, rings, bulges, etc., and in the formation and evolution of active galaxies? Where possible he focuses on these three central issues in the summary.
The Importance of Neighborhood Scheme Selection in Agent-based Tumor Growth Modeling.

PubMed

Tzedakis, Georgios; Tzamali, Eleftheria; Marias, Kostas; Sakkalis, Vangelis

2015-01-01

Modeling tumor growth has proven a very challenging problem, mainly due to the fact that tumors are highly complex systems that involve dynamic interactions spanning multiple scales both in time and space. The desire to describe interactions in various scales has given rise to modeling approaches that use both continuous and discrete variables, known as hybrid approaches. This work refers to a hybrid model on a 2D square lattice focusing on cell movement dynamics as they play an important role in tumor morphology, invasion and metastasis and are considered as indicators for the stage of malignancy used for early prognosis and effective treatment. Considering various distributions of the microenvironment, we explore how Neumann vs. Moore neighborhood schemes affects tumor growth and morphology. The results indicate that the importance of neighborhood selection is critical under specific conditions that include i) increased hapto/chemo-tactic coefficient, ii) a rugged microenvironment and iii) ECM degradation.
A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.
Petroleum Market Model of the National Energy Modeling System

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

NONE

1997-01-01

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions. The production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcoholsmore » and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level. This report is organized as follows: Chapter 2, Model Purpose; Chapter 3, Model Overview and Rationale; Chapter 4, Model Structure; Appendix A, Inventory of Input Data, Parameter Estimates, and Model Outputs; Appendix B, Detailed Mathematical Description of the Model; Appendix C, Bibliography; Appendix D, Model Abstract; Appendix E, Data Quality; Appendix F, Estimation methodologies; Appendix G, Matrix Generator documentation; Appendix H, Historical Data Processing; and Appendix I, Biofuels Supply Submodule.« less
Patients' mental models and adherence to outpatient physical therapy home exercise programs.

PubMed

Rizzo, Jon

2015-05-01

Within physical therapy, patient adherence usually relates to attending appointments, following advice, and/or undertaking prescribed exercise. Similar to findings for general medical adherence, patient adherence to physical therapy home exercise programs (HEP) is estimated between 35 and 72%. Adherence to HEPs is a multifactorial and poorly understood phenomenon, with no consensus regarding a common theoretical framework that best guides empirical or clinical efforts. Mental models, a construct used to explain behavior and decision-making in the social sciences, may serve as this framework. Mental models comprise an individual's tacit thoughts about how the world works. They include assumptions about new experiences and expectations for the future based on implicit comparisons between current and past experiences. Mental models play an important role in decision-making and guiding actions. This professional theoretical article discusses empirical research demonstrating relationships among mental models, prior experience, and adherence decisions in medical and physical therapy contexts. Specific issues related to mental models and physical therapy patient adherence are discussed, including the importance of articulation of patients' mental models, assessment of patients' mental models that relate to exercise program adherence, discrepancy between patient and provider mental models, and revision of patients' mental models in ways that enhance adherence. The article concludes with practical implications for physical therapists and recommendations for further research to better understand the role of mental models in physical therapy patient adherence behavior.
Study of Varying Boundary Layer Height on Turret Flow Structures

DTIC Science & Technology

2011-06-01

fluid dynamics. The difficulties of the problem arise in modeling several complex flow features including separation, reattachment, three-dimensional...impossible. In this case, the approach is to create a model to calculate the properties of interest. The main issue with resolving turbulent flows...operation and their effect is modeled through subgrid scale models . As a result, the the most important turbulent scales are resolved and the
Library of Advanced Materials for Engineering (LAME) 4.44.

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

Scherzinger, William M.; Lester, Brian T.

Accurate and efficient constitutive modeling remains a cornerstone issues for solid mechanics analysis. Over the years, the LAME advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to s ti ff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco) plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization ofmore » the LAME library in application, this effort seeks to document and verify the various models in the LAME library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.« less
Library of Advanced Materials for Engineering (LAME) 4.48.

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

Scherzinger, William M.; Lester, Brian T.

Accurate and efficient constitutive modeling remains a cornerstone issues for solid mechanics analysis. Over the years, the LAME advanced material model library has grown to address this challenge by implement- ing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting imple- mentation. Therefore, to enhance confidence and enable the utilization of themore » LAME library in application, this effort seeks to document and verify the various models in the LAME library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verifi- cation tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.« less
Black carbon inclusive multichemical modeling of PBDE and PCB biomagnification and -transformation in estuarine food webs.

PubMed

Di Paolo, Carolina; Gandhi, Nilima; Bhavsar, Satyendra P; Van den Heuvel-Greve, Martine; Koelmans, Albert A

2010-10-01

Bioavailability and bioaccumulation of polybrominated diphenylethers (PBDEs) are affected by adsorption on black carbon (BC) and metabolism in biota, respectively. Recent studies have addressed these two processes separately, illustrating their importance in assessing contaminant dynamics. In order to properly examine biomagnification of polychlorinated biphenyls (PCBs) and PBDEs in an estuarine food-web, here we set up a black carbon inclusive multichemical model. A dual domain sorption model, which accounted for sorption to organic matter (OM) and black carbon (BC), was used to estimate aqueous phase concentrations from the measured chemical concentrations in suspended solids. We adapted a previously published multichemical model that tracks the movement of a parent compound and its metabolites in each organism and within its food web. First, the model was calibrated for seven PCB congeners assuming negligible metabolism. Subsequently, PBDE biomagnification was modeled, including biotransformation and bioformation of PBDE congeners, keeping the other model parameters the same. The integrated model was capable of predicting trophic magnification factors (TMF) within error limits. PBDE metabolic half-lives ranged 21-415 days and agreed to literature data. The results showed importance of including BC as an adsorbing phase, and biotransformation and bioformation of PBDEs for a proper assessment of their dynamics in aquatic systems.
SYSTEMS MODELING OF PROSTATE REGULATION AND ...

EPA Pesticide Factsheets

The prostate is an androgen-dependent tissue that is an important site of disease in human males as well as an important indicator of androgen status in animals. The rat prostate is used for studying antiandrogenic drugs as well as for evaluation of endocrine disruption (e.g., Hershberger Assay). Pubertal changes in the prostate have been observed to be as sensitive to environmental antiandrogens as in utero effects. The goal of this research is to model the biology of prostate androgen function on a systems level to determine the factors responsible for the dose-response observable with androgens and antiandrogens in the male rat. This includes investigation of the roles of positive and negative feedback loops in prostatic response following castration and dosing with testosterone and/or antiandrogens. A biologically-based, systems-level model will be developed describing the regulation of the prostate by androgens. The model will extend an existing model for the male rat central axis, which describes feedback between luteinizing hormone and testosterone production in the testes, to include the prostate and conversion of testosterone to dihydrotestosterone (DHT). The prostate model will describe binding of androgens to the androgen receptor, 5α-reductase catalyzed production of DHT, and gene regulation affecting cell proliferation, apoptosis, and prostatic fluid production. The model will combine pharmacokinetic models for endogenous hormones (i.e., testost
Modeling large woody debris recruitment for small streams of the Central Rocky Mountains

Treesearch

Don C. Bragg; Jeffrey L. Kershner; David W. Roberts

2000-01-01

As our understanding of the importance of large woody debris (LWD) evolves, planning for its production in riparian forest management is becoming more widely recognized. This report details the development of a model (CWD, version 1.4) that predicts LWD inputs, including descriptions of the field sampling used to parameterize parts of the model, the theoretical and...
DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooker, A.; Gonder, J.; Lopp, S.

The Automotive Deployment Option Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy’s Vehicle Technologies Office. It estimates technology improvement impacts on U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method estimate sales. Specifically, it estimates sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution ofmore » importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced. The sales feed into the ADOPT stock model. It captures key aspects for summing petroleum use and greenhouse gas emissions This includes capturing the change in vehicle miles traveled by vehicle age, the creation of new model options based on the success of existing vehicles, new vehicle option introduction rate limits, and survival rates by vehicle age. ADOPT has been extensively validated with historical sales data. It matches in key dimensions including sales by fuel economy, acceleration, price, vehicle size class, and powertrain across multiple years. A graphical user interface provides easy and efficient use. It manages the inputs, simulation, and results.« less
Performance-Based Accountability in Qatar: A State in Progress

ERIC Educational Resources Information Center

Jaafar, Sonia Ben

2011-01-01

It has become a normative practice to include Performance-Based Accountability (PBA) policies in educational reforms to foster school changes that enhance student learning and success. There is considerable variation in PBA models that have an important impact on how they operate in schools. It is, therefore, important to characterize PBA models…
How animal models inform child and adolescent psychiatry.

PubMed

Stevens, Hanna E; Vaccarino, Flora M

2015-05-01

Every available approach should be used to advance the field of child and adolescent psychiatry. Biological systems are important for the behavioral problems of children. Close examination of nonhuman animals and the biology and behavior that they share with humans is an approach that must be used to advance the clinical work of child psychiatry. We review here how model systems are used to contribute to significant insights into childhood psychiatric disorders. Model systems have not only demonstrated causality of risk factors for psychiatric pathophysiology, but have also allowed child psychiatrists to think in different ways about risks for psychiatric disorders and multiple levels that might be the basis of recovery and prevention. We present examples of how animal systems are used to benefit child psychiatry, including through environmental, genetic, and acute biological manipulations. Animal model work has been essential in our current thinking about childhood disorders, including the importance of dose and timing of risk factors, specific features of risk factors that are significant, neurochemistry involved in brain functioning, molecular components of brain development, and the importance of cellular processes previously neglected in psychiatric theories. Animal models have clear advantages and disadvantages that must be considered for these systems to be useful. Coupled with increasingly sophisticated methods for investigating human behavior and biology, animal model systems will continue to make essential contributions to our field. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Modeling Nutrient Loading to Watersheds in the Great Lakes Basin: A Detailed Source Model at the Regional Scale

NASA Astrophysics Data System (ADS)

Luscz, E.; Kendall, A. D.; Martin, S. L.; Hyndman, D. W.

2011-12-01

Watershed nutrient loading models are important tools used to address issues including eutrophication, harmful algal blooms, and decreases in aquatic species diversity. Such approaches have been developed to assess the level and source of nutrient loading across a wide range of scales, yet there is typically a tradeoff between the scale of the model and the level of detail regarding the individual sources of nutrients. To avoid this tradeoff, we developed a detailed source nutrient loading model for every watershed in Michigan's lower peninsula. Sources considered include atmospheric deposition, septic tanks, waste water treatment plants, combined sewer overflows, animal waste from confined animal feeding operations and pastured animals, as well as fertilizer from agricultural, residential, and commercial sources and industrial effluents . Each source is related to readily-available GIS inputs that may vary through time. This loading model was used to assess the importance of sources and landscape factors in nutrient loading rates to watersheds, and how these have changed in recent decades. The results showed the value of detailed source inputs, revealing regional trends while still providing insight to the existence of variability at smaller scales.
Images of smokers and willingness to smoke among African American pre-adolescents: an application of the prototype/willingness model of adolescent health risk behavior to smoking initiation.

PubMed

Gerrard, Meg; Gibbons, Frederick X; Stock, Michelle L; Lune, Linda S Vande; Cleveland, Michael J

2005-06-01

This study used the prototype/willingness model of adolescent health risk behavior to examine factors related to onset of smoking. Two waves of data were collected from a panel of 742 African American children (mean age=10.5 at Wave 1) and their primary caregivers. Measures included cognitions outlined by the prototype model as well as self-reports of smoking by the parent and child. Structural equation modeling revealed a pattern consistent with expectations generated by the prototype model. The relation between contextual, familial, and dispositional factors-including neighborhood risk, parental smoking, and children's academic orientation-and the initiation of smoking at Wave 2, two years later, was mediated by the children's cognitions. Primary among these cognitions were the children's images of smokers and children's willingness to smoke. Smoking cognitions mediate the impact of important distal factors (such as context, family environment, and disposition) on the onset of smoking in children. Perhaps more important, it is possible to predict onset of smoking in African American children as young as age 10 by assessing the cognitive factors suggested by the prototype model.
Systems, Shocks and Time Bombs

NASA Astrophysics Data System (ADS)

Winder, Nick

The following sections are included: * Introduction * Modelling strategies * Are time-bomb phenomena important? * Heuristic approaches to time-bomb phenomena * Three rational approaches to TBP * Two irrational approaches * Conclusions * References
Seteria viridis as a model for pathogen resistance in the Poaceae

USDA-ARS?s Scientific Manuscript database

Seteria viridis is an effective model system for functional genetics in the C4 Poaceae grasses, which include important crops like maize, sorghum, and sugar cane. The small genome size, short stature, rapid life cycle, and the availability of genetic transformation protocols, make Seteria an attract...

Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact

Treesearch

James A. Powell; Barbara J. Bentz

2014-01-01

For species with irruptive population behavior, dispersal is an important component of outbreak dynamics. We developed and parameterized a mechanistic model describing mountain pine beetle (Dendroctonus ponderosae Hopkins) population demographics and dispersal across a landscape. Model components include temperature-dependent phenology, host tree colonization...
Conceptualizations of Creativity: Comparing Theories and Models of Giftedness

ERIC Educational Resources Information Center

Miller, Angie L.

2012-01-01

This article reviews seven different theories of giftedness that include creativity as a component, comparing and contrasting how each one conceptualizes creativity as a part of giftedness. The functions of creativity vary across the models, suggesting that while the field of gifted education often cites the importance of creativity, the…
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…
EVALUATING THE SENSITIVITY OF A SUBSURFACE MULTICOMPONENT REACTIVE TRANSPORT MODEL WITH RESPECT TO TRANSPORT AND REACTION PARAMETERS

EPA Science Inventory

The input variables for a numerical model of reactive solute transport in groundwater include both transport parameters, such as hydraulic conductivity and infiltration, and reaction parameters that describe the important chemical and biological processes in the system. These pa...
The importance of data curation on QSAR Modeling - PHYSPROP open data as a case study. (QSAR 2016)

EPA Science Inventory

During the last few decades many QSAR models and tools have been developed at the US EPA, including the widely used EPISuite. During this period the arsenal of computational capabilities supporting cheminformatics has broadened dramatically with multiple software packages. These ...
Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models.

PubMed

Liang, Shih-Hsiung; Walther, Bruno Andreas; Shieh, Bao-Sen

2017-01-01

Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies.
Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models

PubMed Central

Liang, Shih-Hsiung; Walther, Bruno Andreas

2017-01-01

Background Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. Methods We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. Results The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Discussion Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies. PMID:28316893
Trust, but verify: On the importance of chemical structure curation in cheminformatics and QSAR modeling research

PubMed Central

Fourches, Denis; Muratov, Eugene; Tropsha, Alexander

2010-01-01

Molecular modelers and cheminformaticians typically analyze experimental data generated by other scientists. Consequently, when it comes to data accuracy, cheminformaticians are always at the mercy of data providers who may inadvertently publish (partially) erroneous data. Thus, dataset curation is crucial for any cheminformatics analysis such as similarity searching, clustering, QSAR modeling, virtual screening, etc., especially nowadays when the availability of chemical datasets in public domain has skyrocketed in recent years. Despite the obvious importance of this preliminary step in the computational analysis of any dataset, there appears to be no commonly accepted guidance or set of procedures for chemical data curation. The main objective of this paper is to emphasize the need for a standardized chemical data curation strategy that should be followed at the onset of any molecular modeling investigation. Herein, we discuss several simple but important steps for cleaning chemical records in a database including the removal of a fraction of the data that cannot be appropriately handled by conventional cheminformatics techniques. Such steps include the removal of inorganic and organometallic compounds, counterions, salts and mixtures; structure validation; ring aromatization; normalization of specific chemotypes; curation of tautomeric forms; and the deletion of duplicates. To emphasize the importance of data curation as a mandatory step in data analysis, we discuss several case studies where chemical curation of the original “raw” database enabled the successful modeling study (specifically, QSAR analysis) or resulted in a significant improvement of model's prediction accuracy. We also demonstrate that in some cases rigorously developed QSAR models could be even used to correct erroneous biological data associated with chemical compounds. We believe that good practices for curation of chemical records outlined in this paper will be of value to all scientists working in the fields of molecular modeling, cheminformatics, and QSAR studies. PMID:20572635
Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.
Bayesian Spatiotemporal Pattern and Eco-climatological Drivers of Striped Skunk Rabies in the North Central Plains

PubMed Central

Raghavan, Ram K.; Hanlon, Cathleen A.; Goodin, Douglas G.; Anderson, Gary A.

2016-01-01

Striped skunks are one of the most important terrestrial reservoirs of rabies virus in North America, and yet the prevalence of rabies among this host is only passively monitored and the disease among this host remains largely unmanaged. Oral vaccination campaigns have not efficiently targeted striped skunks, while periodic spillovers of striped skunk variant viruses to other animals, including some domestic animals, are routinely recorded. In this study we evaluated the spatial and spatio-temporal patterns of infection status among striped skunk cases submitted for rabies testing in the North Central Plains of US in a Bayesian hierarchical framework, and also evaluated potential eco-climatological drivers of such patterns. Two Bayesian hierarchical models were fitted to point-referenced striped skunk rabies cases [n = 656 (negative), and n = 310 (positive)] received at a leading rabies diagnostic facility between the years 2007–2013. The first model included only spatial and temporal terms and a second covariate model included additional covariates representing eco-climatic conditions within a 4km2 home-range area for striped skunks. The better performing covariate model indicated the presence of significant spatial and temporal trends in the dataset and identified higher amounts of land covered by low-intensity developed areas [Odds ratio (OR) = 3.41; 95% Bayesian Credible Intervals (CrI) = 2.08, 3.85], higher level of patch fragmentation (OR = 1.70; 95% CrI = 1.25, 2.89), and diurnal temperature range (OR = 0.54; 95% CrI = 0.27, 0.91) to be important drivers of striped skunk rabies incidence in the study area. Model validation statistics indicated satisfactory performance for both models; however, the covariate model fared better. The findings of this study are important in the context of rabies management among striped skunks in North America, and the relevance of physical and climatological factors as risk factors for skunk to human rabies transmission and the space-time patterns of striped skunk rabies are discussed. PMID:27127994
Probing heat transfer, fluid flow and microstructural evolution during fusion welding of alloys

NASA Astrophysics Data System (ADS)

Zhang, Wei

The composition, geometry, structure and properties of the welded joints are affected by the various physical processes that take place during fusion welding. Understanding these processes has been an important goal in the contemporary welding research to achieve structurally sound and reliable welds. In the present thesis research, several important physical processes including the heat transfer, fluid flow and microstructural evolution in fusion welding were modeled based on the fundamentals of transport phenomena and phase transformation theory. The heat transfer and fluid flow calculation is focused on the predictions of the liquid metal convection in the weld pool, the temperature distribution in the entire weldment, and the shape and size of the fusion zone (FZ) and heat affected zone (HAZ). The modeling of microstructural evolution is focused on the quantitative understanding of phase transformation kinetics during welding of several important alloys under both low and high heating and cooling conditions. Three numerical models were developed in the present thesis work: (1) a three-dimensional heat transfer and free surface flow model for the gas metal arc (GMA) fillet welding considering the complex weld joint geometry, (2) a phase transformation model based on the Johnson-Mehl-Avrami (JMA) theory, and (3) a one-dimensional numerical diffusion model considering multiple moving interfaces. To check the capabilities of the developed models, several cases were investigated, in which the predictions from the models were compared with the experimental results. The cases studied are the follows. For the modeling of heat transfer and fluid flow, the welding processes studied included gas tungsten arc (GTA) linear welding, GTA transient spot welding, and GMA fillet welding. The calculated weldment geometry and thermal cycles was validated against the experimental data under various welding conditions. For the modeling of microstructural evolution, the welded materials investigated included AISI 1005 low-carbon steel, 1045 medium-carbon steel, 2205 duplex stainless steel (DSS) and Ti-6Al-4V alloy. The calculated phase transformation kinetics were compared with the experimental results obtained using an x-ray diffraction technique by Dr. John W. Elmer of Lawrence Livermore National Laboratory. (Abstract shortened by UMI.)
Detecting biodiversity hotspots by species-area relationships: a case study of Mediterranean beetles.

PubMed

Fattorini, Simone

2006-08-01

Any method of identifying hotspots should take into account the effect of area on species richness. I examined the importance of the species-area relationship in determining tenebrionid (Coleoptera: Tenebrionidae) hotspots on the Aegean Islands (Greece). Thirty-two islands and 170 taxa (species and subspecies) were included in this study. I tested several species-area relationship models with linear and nonlinear regressions, including power exponential, negative exponential, logistic, Gompertz, Weibull, Lomolino, and He-Legendre functions. Islands with positive residuals were identified as hotspots. I also analyzed the values of the C parameter of the power function and the simple species-area ratios. Species richness was significantly correlated with island area for all models. The power function model was the most convenient one. Most functions, however identified certain islands as hotspots. The importance of endemics in insular biotas should be evaluated carefully because they are of high conservation concern. The simple use of the species-area relationship can be problematic when areas with no endemics are included. Therefore the importance of endemics should be evaluated according to different methods, such as percentages, to take into account different levels of endemism and different kinds of "endemics" (e.g., endemic to single islands vs. endemic to the archipelago). Because the species-area relationship is a key pattern in ecology, my findings can be applied at broader scales.
Development and Application of a Process-based River System Model at a Continental Scale

NASA Astrophysics Data System (ADS)

Kim, S. S. H.; Dutta, D.; Vaze, J.; Hughes, J. D.; Yang, A.; Teng, J.

2014-12-01

Existing global and continental scale river models, mainly designed for integrating with global climate model, are of very course spatial resolutions and they lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing streamflow forecast at fine spatial resolution and water accounts at sub-catchment levels, which are important for water resources planning and management at regional and national scale. A large-scale river system model has been developed and implemented for water accounting in Australia as part of the Water Information Research and Development Alliance between Australia's Bureau of Meteorology (BoM) and CSIRO. The model, developed using node-link architecture, includes all major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. It includes an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. An auto-calibration tool has been built within the modelling system to automatically calibrate the model in large river systems using Shuffled Complex Evolution optimiser and user-defined objective functions. The auto-calibration tool makes the model computationally efficient and practical for large basin applications. The model has been implemented in several large basins in Australia including the Murray-Darling Basin, covering more than 2 million km2. The results of calibration and validation of the model shows highly satisfactory performance. The model has been operalisationalised in BoM for producing various fluxes and stores for national water accounting. This paper introduces this newly developed river system model describing the conceptual hydrological framework, methods used for representing different hydrological processes in the model and the results and evaluation of the model performance. The operational implementation of the model for water accounting is discussed.
Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.

PubMed

Rochau, U; Jahn, B; Qerimi, V; Burger, E A; Kurzthaler, C; Kluibenschaedl, M; Willenbacher, E; Gastl, G; Willenbacher, W; Siebert, U

2015-05-01

The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM). We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures. Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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.
Computer Model Inversion and Uncertainty Quantification in the Geosciences

NASA Astrophysics Data System (ADS)

White, Jeremy T.

The subject of this dissertation is use of computer models as data analysis tools in several different geoscience settings, including integrated surface water/groundwater modeling, tephra fallout modeling, geophysical inversion, and hydrothermal groundwater modeling. The dissertation is organized into three chapters, which correspond to three individual publication manuscripts. In the first chapter, a linear framework is developed to identify and estimate the potential predictive consequences of using a simple computer model as a data analysis tool. The framework is applied to a complex integrated surface-water/groundwater numerical model with thousands of parameters. Several types of predictions are evaluated, including particle travel time and surface-water/groundwater exchange volume. The analysis suggests that model simplifications have the potential to corrupt many types of predictions. The implementation of the inversion, including how the objective function is formulated, what minimum of the objective function value is acceptable, and how expert knowledge is enforced on parameters, can greatly influence the manifestation of model simplification. Depending on the prediction, failure to specifically address each of these important issues during inversion is shown to degrade the reliability of some predictions. In some instances, inversion is shown to increase, rather than decrease, the uncertainty of a prediction, which defeats the purpose of using a model as a data analysis tool. In the second chapter, an efficient inversion and uncertainty quantification approach is applied to a computer model of volcanic tephra transport and deposition. The computer model simulates many physical processes related to tephra transport and fallout. The utility of the approach is demonstrated for two eruption events. In both cases, the importance of uncertainty quantification is highlighted by exposing the variability in the conditioning provided by the observations used for inversion. The worth of different types of tephra data to reduce parameter uncertainty is evaluated, as is the importance of different observation error models. The analyses reveal the importance using tephra granulometry data for inversion, which results in reduced uncertainty for most eruption parameters. In the third chapter, geophysical inversion is combined with hydrothermal modeling to evaluate the enthalpy of an undeveloped geothermal resource in a pull-apart basin located in southeastern Armenia. A high-dimensional gravity inversion is used to define the depth to the contact between the lower-density valley fill sediments and the higher-density surrounding host rock. The inverted basin depth distribution was used to define the hydrostratigraphy for the coupled groundwater-flow and heat-transport model that simulates the circulation of hydrothermal fluids in the system. Evaluation of several different geothermal system configurations indicates that the most likely system configuration is a low-enthalpy, liquid-dominated geothermal system.
Curbing the Financial Exploitation of the Poor: Financial Literacy and Social Work Education

ERIC Educational Resources Information Center

Karger, Howard

2015-01-01

The article investigates the importance of financial literacy content for social work students who at some point in their career will encounter financially-excluded clients. Financial literacy content can include understanding how fringe economy businesses operate, including their business model, knowledge of local and national nonpredatory…
Perspectives on Cultural Geography in AP® Human Geography

ERIC Educational Resources Information Center

Hall, Christopher; Johnston-Anumonwo, Ibipo

2016-01-01

This article provides an overview of selected current concerns in cultural geography and the way it is taught. It includes coverage of cultural convergence and divergence, race and gender as culturally defined topics, and best teaching practices, including those related to analyzing controversial issues. Two important geographical models are laid…
Team Modelling: Review of Experimental Scenarios and Computational Models

DTIC Science & Technology

2006-09-01

les auteurs ont réuni et examiné des scénarios ayant servi dans le cadre d’études antérieures sur les équipes, ils ont développé d’importants...cognition, perception, sensation, motor action and knowledge, that embody a principled underlying theory or framework for human information...Processing) integrates Qinetiq’s (POP) model with DRDC’s IP/PCT (Perceptual Control Theory ) models. In particular, the POP/IP model includes the
Populational Growth Models Proportional to Beta Densities with Allee Effect

NASA Astrophysics Data System (ADS)

Aleixo, Sandra M.; Rocha, J. Leonel; Pestana, Dinis D.

2009-05-01

We consider populations growth models with Allee effect, proportional to beta densities with shape parameters p and 2, where the dynamical complexity is related with the Malthusian parameter r. For p>2, these models exhibit a population dynamics with natural Allee effect. However, in the case of 1

An investigation of the astronomical theory of the ice ages using a simple climate-ice sheet model

NASA Technical Reports Server (NTRS)

Pollard, D.

1978-01-01

The astronomical theory of the Quaternary ice ages is incorporated into a simple climate model for global weather; important features of the model include the albedo feedback, topography and dynamics of the ice sheets. For various parameterizations of the orbital elements, the model yields realistic assessments of the northern ice sheet. Lack of a land-sea heat capacity contrast represents one of the chief difficulties of the model.
Modeling low-temperature geochemical processes: Chapter 2

USGS Publications Warehouse

Nordstrom, D. Kirk; Campbell, Kate M.

2014-01-01

This chapter provides an overview of geochemical modeling that applies to water–rock interactions under ambient conditions of temperature and pressure. Topics include modeling definitions, historical background, issues of activity coefficients, popular codes and databases, examples of modeling common types of water–rock interactions, and issues of model reliability. Examples include speciation, microbial redox kinetics and ferrous iron oxidation, calcite dissolution, pyrite oxidation, combined pyrite and calcite dissolution, dedolomitization, seawater–carbonate groundwater mixing, reactive-transport modeling in streams, modeling catchments, and evaporation of seawater. The chapter emphasizes limitations to geochemical modeling: that a proper understanding and ability to communicate model results well are as important as completing a set of useful modeling computations and that greater sophistication in model and code development is not necessarily an advancement. If the goal is to understand how a particular geochemical system behaves, it is better to collect more field data than rely on computer codes.
Fun with maths: exploring implications of mathematical models for malaria eradication.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A

2014-12-11

Mathematical analyses and modelling have an important role informing malaria eradication strategies. Simple mathematical approaches can answer many questions, but it is important to investigate their assumptions and to test whether simple assumptions affect the results. In this note, four examples demonstrate both the effects of model structures and assumptions and also the benefits of using a diversity of model approaches. These examples include the time to eradication, the impact of vaccine efficacy and coverage, drug programs and the effects of duration of infections and delays to treatment, and the influence of seasonality and migration coupling on disease fadeout. An excessively simple structure can miss key results, but simple mathematical approaches can still achieve key results for eradication strategy and define areas for investigation by more complex models.
Tabulated Combustion Model Development For Non-Premixed Flames

NASA Astrophysics Data System (ADS)

Kundu, Prithwish

Turbulent non-premixed flames play a very important role in the field of engineering ranging from power generation to propulsion. The coupling of fluid mechanics and complicated combustion chemistry of fuels pose a challenge for the numerical modeling of these type of problems. Combustion modeling in Computational Fluid Dynamics (CFD) is one of the most important tools used for predictive modeling of complex systems and to understand the basic fundamentals of combustion. Traditional combustion models solve a transport equation of each species with a source term. In order to resolve the complex chemistry accurately it is important to include a large number of species. However, the computational cost is generally proportional to the cube of number of species. The presence of a large number of species in a flame makes the use of CFD computationally expensive and beyond reach for some applications or inaccurate when solved with simplified chemistry. For highly turbulent flows, it also becomes important to incorporate the effects of turbulence chemistry interaction (TCI). The aim of this work is to develop high fidelity combustion models based on the flamelet concept and to significantly advance the existing capabilities. A thorough investigation of existing models (Finite-rate chemistry and Representative Interactive Flamelet (RIF)) and comparative study of combustion models was done initially on a constant volume combustion chamber with diesel fuel injection. The CFD modeling was validated with experimental results and was also successfully applied to a single cylinder diesel engine. The effect of number of flamelets on the RIF model and flamelet initialization strategies were studied. The RIF model with multiple flamelets is computationally expensive and a model was proposed on the frame work of RIF. The new model was based on tabulated chemistry and incorporated TCI effects. A multidimensional tabulated chemistry database generation code was developed based on the 1D diffusion flame solver. The proposed model did not use progress variables like the traditional chemistry tabulation methods. The resulting model demonstrated an order of magnitude computational speed up over the RIF model. The results were validated across a wide range of operating conditions for diesel injections and the results were in close agreement to those of the experimental data. History of scalar dissipation rates plays a very important role in non premixed flames. However, tabulated methods have not been able to incorporate this physics in their models. A comparative approach is developed that can quantify these effects and find correlations with flow variables. A new model is proposed to include these effects in tabulated combustion models. The model is initially validated for 1D counterflow diffusion flame problems at engine conditions. The model is further implemented and validated in a 3D RANS code across a range of operating conditions for spray flames.
Bootstrap investigation of the stability of a Cox regression model.

PubMed

Altman, D G; Andersen, P K

1989-07-01

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Disk flexibility effects on the rotordynamics of the SSME high pressure turbopumps

NASA Technical Reports Server (NTRS)

Flowers, George T.

1990-01-01

Rotordynamical analyses are typically performed using rigid disk models. Studies of rotor models in which the effects of disk flexibility were included indicate that it may be an important effect for many systems. This issue is addressed with respect to the Space Shuttle Main Engine high pressure turbopumps. Finite element analyses were performed for a simplified free-free flexible disk rotor models and the modes and frequencies compared to those of a rigid disk model. Equations were developed to account for disk flexibility in rotordynamical analysis. Simulation studies were conducted to assess the influence of disk flexibility on the HPOTP. Some recommendations are given as to the importance of disk flexibility and for how this project should proceed.
Ferroelectric Material Application: Modeling Ferroelectric Field Effect Transistor Characteristics from Micro to Nano

NASA Technical Reports Server (NTRS)

MacLeod, Todd, C.; Ho, Fat Duen

2006-01-01

All present ferroelectric transistors have been made on the micrometer scale. Existing models of these devices do not take into account effects of nanoscale ferroelectric transistors. Understanding the characteristics of these nanoscale devices is important in developing a strategy for building and using future devices. This paper takes an existing microscale ferroelectric field effect transistor (FFET) model and adds effects that become important at a nanoscale level, including electron velocity saturation and direct tunneling. The new model analyzed FFETs ranging in length from 40,000 nanometers to 4 nanometers and ferroelectric thickness form 200 nanometers to 1 nanometer. The results show that FFETs can operate on the nanoscale but have some undesirable characteristics at very small dimensions.
Plant growth modelling and applications: the increasing importance of plant architecture in growth models.

PubMed

Fourcaud, Thierry; Zhang, Xiaopeng; Stokes, Alexia; Lambers, Hans; Körner, Christian

2008-05-01

Modelling plant growth allows us to test hypotheses and carry out virtual experiments concerning plant growth processes that could otherwise take years in field conditions. The visualization of growth simulations allows us to see directly and vividly the outcome of a given model and provides us with an instructive tool useful for agronomists and foresters, as well as for teaching. Functional-structural (FS) plant growth models are nowadays particularly important for integrating biological processes with environmental conditions in 3-D virtual plants, and provide the basis for more advanced research in plant sciences. In this viewpoint paper, we ask the following questions. Are we modelling the correct processes that drive plant growth, and is growth driven mostly by sink or source activity? In current models, is the importance of soil resources (nutrients, water, temperature and their interaction with meristematic activity) considered adequately? Do classic models account for architectural adjustment as well as integrating the fundamental principles of development? Whilst answering these questions with the available data in the literature, we put forward the opinion that plant architecture and sink activity must be pushed to the centre of plant growth models. In natural conditions, sinks will more often drive growth than source activity, because sink activity is often controlled by finite soil resources or developmental constraints. PMA06: This viewpoint paper also serves as an introduction to this Special Issue devoted to plant growth modelling, which includes new research covering areas stretching from cell growth to biomechanics. All papers were presented at the Second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06), held in Beijing, China, from 13-17 November, 2006. Although a large number of papers are devoted to FS models of agricultural and forest crop species, physiological and genetic processes have recently been included and point the way to a new direction in plant modelling research.
Modeling of unit operating considerations in generating-capacity reliability evaluation. Volume 1. Mathematical models, computing methods, and results. Final report. [GENESIS, OPCON and OPPLAN

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

Patton, A.D.; Ayoub, A.K.; Singh, C.

1982-07-01

Existing methods for generating capacity reliability evaluation do not explicitly recognize a number of operating considerations which may have important effects in system reliability performance. Thus, current methods may yield estimates of system reliability which differ appreciably from actual observed reliability. Further, current methods offer no means of accurately studying or evaluating alternatives which may differ in one or more operating considerations. Operating considerations which are considered to be important in generating capacity reliability evaluation include: unit duty cycles as influenced by load cycle shape, reliability performance of other units, unit commitment policy, and operating reserve policy; unit start-up failuresmore » distinct from unit running failures; unit start-up times; and unit outage postponability and the management of postponable outages. A detailed Monte Carlo simulation computer model called GENESIS and two analytical models called OPCON and OPPLAN have been developed which are capable of incorporating the effects of many operating considerations including those noted above. These computer models have been used to study a variety of actual and synthetic systems and are available from EPRI. The new models are shown to produce system reliability indices which differ appreciably from index values computed using traditional models which do not recognize operating considerations.« less
Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment.

PubMed

Beca, Jaclyn; Husereau, Don; Chan, Kelvin K W; Hawkins, Neil; Hoch, Jeffrey S

2018-01-01

In evaluating new oncology medicines, two common modeling approaches are state transition (e.g., Markov and semi-Markov) and partitioned survival. Partitioned survival models have become more prominent in oncology health technology assessment processes in recent years. Our experience in conducting and evaluating models for economic evaluation has highlighted many important and practical pitfalls. As there is little guidance available on best practices for those who wish to conduct them, we provide guidance in the form of 'Key steps for busy analysts,' who may have very little time and require highly favorable results. Our guidance highlights the continued need for rigorous conduct and transparent reporting of economic evaluations regardless of the modeling approach taken, and the importance of modeling that better reflects reality, which includes better approaches to considering plausibility, estimating relative treatment effects, dealing with post-progression effects, and appropriate characterization of the uncertainty from modeling itself.
Preceptors' understanding and use of role modeling to develop the CanMEDS competencies in residents.

PubMed

Côté, Luc; Laughrea, Patricia-Ann

2014-06-01

Role modeling by preceptors is a key strategy for training residents in the competencies defined within the CanMEDS conceptual framework. However, little is known about the extent to which preceptors are aware of the importance of role modeling or how they perceive and enact it in their daily interactions with residents. The purpose of this study was to describe how preceptors understand and use role modeling to develop CanMEDS competencies in residents. In 2010, the authors conducted a descriptive qualitative study with preceptors in medical, surgical, and laboratory specialties who supervised residents on a regular basis at the Université Laval Faculty of Medicine (Québec, Canada). Respondents participated in semistructured, individual interviews. An inductive thematic analysis of interview transcripts was conducted using triangulation. Most participants highlighted the importance of role modeling to support residents' development of the CanMEDS competencies, particularly communication, collaboration, and professionalism, which preceptors perceived as "less scientific" and the most difficult to teach. Although most participants reported using an implicit, unstructured role modeling process, some described more explicit strategies. Eight types of educational challenges in role modeling the CanMEDS competencies were identified, including encouraging reflective practice, understanding the competencies and their importance in one's specialty, and being aware of one's strengths and weaknesses as a clinical teacher. Preceptors are aware of the importance of role modeling competencies for residents, but many do so only implicitly. This study's findings are important for improving strategies for role modeling and for the professional development of preceptors.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Dobson, Ian; Hiskens, Ian; Linderoth, Jeffrey

Building on models of electrical power systems, and on powerful mathematical techniques including optimization, model predictive control, and simluation, this project investigated important issues related to the stable operation of power grids. A topic of particular focus was cascading failures of the power grid: simulation, quantification, mitigation, and control. We also analyzed the vulnerability of networks to component failures, and the design of networks that are responsive to and robust to such failures. Numerous other related topics were investigated, including energy hubs and cascading stall of induction machines
Analysis of Crystallization Kinetics

NASA Technical Reports Server (NTRS)

Kelton, Kenneth F.

1997-01-01

A realistic computer model for polymorphic crystallization (i.e., initial and final phases with identical compositions), which includes time-dependent nucleation and cluster-size-dependent growth rates, is developed and tested by fits to experimental data. Model calculations are used to assess the validity of two of the more common approaches for the analysis of crystallization data. The effects of particle size on transformation kinetics, important for the crystallization of many systems of limited dimension including thin films, fine powders, and nanoparticles, are examined.
Extending radiative transfer models by use of Bayes rule. [in atmospheric science

NASA Technical Reports Server (NTRS)

Whitney, C.

1977-01-01

This paper presents a procedure that extends some existing radiative transfer modeling techniques to problems in atmospheric science where curvature and layering of the medium and dynamic range and angular resolution of the signal are important. Example problems include twilight and limb scan simulations. Techniques that are extended include successive orders of scattering, matrix operator, doubling, Gauss-Seidel iteration, discrete ordinates and spherical harmonics. The procedure for extending them is based on Bayes' rule from probability theory.
VOC Reactivity and the Ozone Climate Penalty: Modeled Impacts of Updated Aromatic and Monoterpene Chemistry on the Ozone-temperature Connection

NASA Astrophysics Data System (ADS)

Porter, W. C.; Heald, C. L.; Safieddine, S.

2016-12-01

Rising temperatures associated with global warming can increase concentrations of tropospheric ozone (O3) in many regions worldwide, a correlation often described as the "ozone climate penalty". This effect is driven by a variety of underlying chemical, physical, and biological mechanisms, including temperature-dependent reaction rates, emissions of volatile organic compounds (VOCs) from trees and other plant life, and correlations with other meteorological variables. While many of the most important O3-producing VOCs, such as isoprene, are represented in typical chemical transport models such as GEOS-Chem, others - including aromatics from fires and human activity and monoterpenes from natural sources - are not always included in gas-phase chemistry. Here we examine the impact of increased VOC reactivity on the ozone climate penalty due to a more comprehensive treatment of aromatics and monoterpenes in the chemical transport model GEOS-Chem, finding regional impacts not only on daily O3 levels themselves, but also on the O3/temperature relationship. While many uncertainties related to the emissions and chemistry of these species remain, the impact of their inclusion on both current simulations and future projections indicates their importance towards the overall goal of more accurately modeled surface O3.
Optics at langley research center.

PubMed

Crumbly, K H

1970-02-01

The specialized tools of optics have played an important part in Langley's history of aeronautical and space research. Schlieren systems for photographing aeronautics and space models in wind-tunnel investigations have contributed to the available knowledge of aerodynamics. Optics continues to be an important part of Langley's research program, including new techniques for measuring the sensitivity of photomultiplier tubes, spectrographic techniques for radiation measurements of wind-tunnel models, research into large orbiting telescopes, horizon definition by ir radiation measurements, spectra of natural and artificial meteors, measurement of clear air turbulence utilizing lasers, and many others.
Adaptive Non-Interventional Heuristics for Covariation Detection in Causal Induction: Model Comparison and Rational Analysis

ERIC Educational Resources Information Center

Hattori, Masasi; Oaksford, Mike

2007-01-01

In this article, 41 models of covariation detection from 2 x 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in…
Mapping migratory flyways in Asia using dynamic Brownian bridge movement models

USGS Publications Warehouse

Palm, E.C.; Newman, S.H.; Prosser, Diann J.; Xiao, Xiangming; Luo, Ze; Batbayar, Nyambayar; Balachandran, Sivananinthaperumal; Takekawa, John Y.

2015-01-01

The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.
The Collective Impact Model and Its Potential for Health Promotion: Overview and Case Study of a Healthy Retail Initiative in San Francisco

ERIC Educational Resources Information Center

Flood, Johnna; Minkler, Meredith; Lavery, Susana Hennessey; Estrada, Jessica; Falbe, Jennifer

2015-01-01

As resources for health promotion become more constricted, it is increasingly important to collaborate across sectors, including the private sector. Although many excellent models for cross-sector collaboration have shown promise in the health field, collective impact (CI), an emerging model for creating larger scale change, has yet to receive…

Using video self- and peer modeling to facilitate reading fluency in children with learning disabilities.

PubMed

Decker, Martha M; Buggey, Tom

2014-01-01

The authors compared the effects of video self-modeling and video peer modeling on oral reading fluency of elementary students with learning disabilities. A control group was also included to gauge general improvement due to reading instruction and familiarity with researchers. The results indicated that both interventions resulted in improved fluency. Students in both experimental groups improved their reading fluency. Two students in the self-modeling group made substantial and immediate gains beyond any of the other students. Discussion is included that focuses on the importance that positive imagery can have on student performance and the possible applications of both forms of video modeling with students who have had negative experiences in reading.
From bench to patient: model systems in drug discovery.

PubMed

Breyer, Matthew D; Look, A Thomas; Cifra, Alessandra

2015-10-01

Model systems, including laboratory animals, microorganisms, and cell- and tissue-based systems, are central to the discovery and development of new and better drugs for the treatment of human disease. In this issue, Disease Models & Mechanisms launches a Special Collection that illustrates the contribution of model systems to drug discovery and optimisation across multiple disease areas. This collection includes reviews, Editorials, interviews with leading scientists with a foot in both academia and industry, and original research articles reporting new and important insights into disease therapeutics. This Editorial provides a summary of the collection's current contents, highlighting the impact of multiple model systems in moving new discoveries from the laboratory bench to the patients' bedsides. © 2015. Published by The Company of Biologists Ltd.
Modeling Jupiter's Great Red Spot with an Active Hydrological Cycle

NASA Astrophysics Data System (ADS)

Palotai, C. J.; Dowling, T. E.; Morales-Juberías, R.

2003-05-01

We are studying the interaction of Jupiter's hydrological cycle with the formation and maintenance of its long-lived vortices and jet streams using numerical simulations. We are particularly interested in establishing the importance of the large convective storm system to the northwest of Jupiter's Great Red Spot (GRS). We have adapted into the EPIC model the cloud microphysics scheme used at Colorado State University (Fowler et al. 1996, J. Cli. 9, 489), which contains prognostic equations for vapor, liquid cloud, ice cloud, rain and snow. We are focussing on the role of water, but the EPIC model can also handle multiple species (water, ammonia, etc.). Processes that are currently working in the microphysics model include large-scale condensation/deposition, cloud evaporation, melting/freezing, and Bergeron-Findeisen diffusional growth of ice from supercooled liquid. The form of precipitation on gas giants is a major unknown. We are currently using a simple scheme for precipitation, but are studying the effect that processes known to be important in terrestrial models have on our results, including formation and accretion of rain and snow, preciptation evaporation, detrainment and cloud-top entrainment. We will present comparisons of ``dry'' and ``wet'' runs of a channel Jupiter EPIC simulation covering -40S to the equator that includes various initial water-vapor profiles and a GRS model. The effects of latent heating on the energy budget and vertical transport will be discussed. This research is funded by NASA's Planetary Atmospheres and EPSCoR Programs.
Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.

PubMed

Acosta-Pech, Rocío; Crossa, José; de Los Campos, Gustavo; Teyssèdre, Simon; Claustres, Bruno; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino

2017-07-01

A new genomic model that incorporates genotype × environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype × environment interaction (G × E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G × E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G × E in the prediction of untested maize hybrids increases the accuracy of genomic models.
The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.
The importance of different frequency bands in predicting subcutaneous glucose concentration in type 1 diabetic patients.

PubMed

Lu, Yinghui; Gribok, Andrei V; Ward, W Kenneth; Reifman, Jaques

2010-08-01

We investigated the relative importance and predictive power of different frequency bands of subcutaneous glucose signals for the short-term (0-50 min) forecasting of glucose concentrations in type 1 diabetic patients with data-driven autoregressive (AR) models. The study data consisted of minute-by-minute glucose signals collected from nine deidentified patients over a five-day period using continuous glucose monitoring devices. AR models were developed using single and pairwise combinations of frequency bands of the glucose signal and compared with a reference model including all bands. The results suggest that: for open-loop applications, there is no need to explicitly represent exogenous inputs, such as meals and insulin intake, in AR models; models based on a single-frequency band, with periods between 60-120 min and 150-500 min, yield good predictive power (error <3 mg/dL) for prediction horizons of up to 25 min; models based on pairs of bands produce predictions that are indistinguishable from those of the reference model as long as the 60-120 min period band is included; and AR models can be developed on signals of short length (approximately 300 min), i.e., ignoring long circadian rhythms, without any detriment in prediction accuracy. Together, these findings provide insights into efficient development of more effective and parsimonious data-driven models for short-term prediction of glucose concentrations in diabetic patients.
Choice modeling: public preferences for enhancing benefits from private forests in the Adirondacks

Treesearch

Donald F. Dennis; Mark J. Twery

2007-01-01

Recognizing the importance of private land in meeting society's needs for forest-related benefits, public agencies fund programs that provide aid to private landowners to enhance public benefits derived from these lands. This may include technical help, education, tax incentives, and cost-share programs for various management activities. It is important that...
Vegetation of Upper Coastal Plain Depression Wetlands: Environmental Templates and Wetland Dynamics Within A Landscape Framework

Treesearch

Diane De Steven; Maureen M. Toner

2004-01-01

Reference wetlands play an important role in efforts to protect wetlands and assess wetland condition. Because wetland vegetation integrates the influence of many ecological factors, a useful reference system would identify natural vegetation types and include models relating vegetation to important regional geomorphic, hydrologic, and geochemical properties. Across...
A Cognitive Multimedia Environment and Its Importance: A Conceptual Model for Effective E-Learning and Development

ERIC Educational Resources Information Center

Phan, Huy P.

2011-01-01

Multimedia learning is innovative and has revolutionised the way we learn online. It is important to create a multimedia learning environment that stimulates active participation and effective learning. The significance of multimedia learning extends to include the cultivation of professional and personal experiences that reflect the reality of a…
Important parameters for smoke plume rise simulation with Daysmoke

Treesearch

L. Liu; G.L. Achtemeier; S.L. Goodrick; W. Jackson

2010-01-01

Daysmoke is a local smoke transport model and has been used to provide smoke plume rise information. It includes a large number of parameters describing the dynamic and stochastic processes of particle upward movement, fallout, fluctuation, and burn emissions. This study identifies the important parameters for Daysmoke simulations of plume rise and seeks to understand...
Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis.

PubMed

Zador, Zsolt; Sperrin, Matthew; King, Andrew T

2016-01-01

Traumatic brain injury remains a global health problem. Understanding the relative importance of outcome predictors helps optimize our treatment strategies by informing assessment protocols, clinical decisions and trial designs. In this study we establish importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models. We then explore the associations between key outcome predictors using Bayesian networks to gain further insight into predictor importance. We analyzed the corticosteroid randomization after significant head injury (CRASH) trial database of 10008 patients and included patients for whom demographics, injury characteristics, computer tomography (CT) findings and Glasgow Outcome Scale (GCS) were recorded (total of 13 predictors, which would be available to clinicians within a few hours following the injury in 6945 patients). Predictions of clinical outcome (death or severe disability at 6 months) were performed using logistic regression models with 5-fold cross validation. Predictive performance was measured using standardized partial area (pAUC) under the receiver operating curve (ROC) and we used Delong test for comparisons. Variable importance ranking was based on pAUC targeted at specificity (pAUCSP) and sensitivity (pAUCSE) intervals of 90-100%. Probabilistic associations were depicted using Bayesian networks. Complete AUC analysis showed very good predictive power (AUC = 0.8237, 95% CI: 0.8138-0.8336) for the complete model. Specificity focused importance ranking highlighted age, pupillary, motor responses, obliteration of basal cisterns/3rd ventricle and midline shift. Interestingly when targeting model sensitivity, the highest-ranking variables were age, severe extracranial injury, verbal response, hematoma on CT and motor response. Simplified models, which included only these key predictors, had similar performance (pAUCSP = 0.6523, 95% CI: 0.6402-0.6641 and pAUCSE = 0.6332, 95% CI: 0.62-0.6477) compared to the complete models (pAUCSP = 0.6664, 95% CI: 0.6543-0.679, pAUCSE = 0.6436, 95% CI: 0.6289-0.6585, de Long p value 0.1165 and 0.3448 respectively). Bayesian networks showed the predictors that did not feature in the simplified models were associated with those that did. We demonstrate that importance based variable selection allows simplified predictive models to be created while maintaining prediction accuracy. Variable selection targeting specificity confirmed key components of clinical assessment in TBI whereas sensitivity based ranking suggested extracranial injury as one of the important predictors. These results help refine our approach to head injury assessment, decision-making and outcome prediction targeted at model sensitivity and specificity. Bayesian networks proved to be a comprehensive tool for depicting probabilistic associations for key predictors giving insight into why the simplified model has maintained accuracy.
A gamma variate model that includes stretched exponential is a better fit for gastric emptying data from mice

PubMed Central

Bajzer, Željko; Gibbons, Simon J.; Coleman, Heidi D.; Linden, David R.

2015-01-01

Noninvasive breath tests for gastric emptying are important techniques for understanding the changes in gastric motility that occur in disease or in response to drugs. Mice are often used as an animal model; however, the gamma variate model currently used for data analysis does not always fit the data appropriately. The aim of this study was to determine appropriate mathematical models to better fit mouse gastric emptying data including when two peaks are present in the gastric emptying curve. We fitted 175 gastric emptying data sets with two standard models (gamma variate and power exponential), with a gamma variate model that includes stretched exponential and with a proposed two-component model. The appropriateness of the fit was assessed by the Akaike Information Criterion. We found that extension of the gamma variate model to include a stretched exponential improves the fit, which allows for a better estimation of T1/2 and Tlag. When two distinct peaks in gastric emptying are present, a two-component model is required for the most appropriate fit. We conclude that use of a stretched exponential gamma variate model and when appropriate a two-component model will result in a better estimate of physiologically relevant parameters when analyzing mouse gastric emptying data. PMID:26045615
Impact Of Three-Phase Relative Permeability and Hysteresis Models On Forecasts of Storage Associated with CO2-EOR

NASA Astrophysics Data System (ADS)

Jia, W.; Pan, F.; McPherson, B. J. O. L.

2015-12-01

Due to the presence of multiple phases in a given system, CO2 sequestration with enhanced oil recovery (CO2-EOR) includes complex multiphase flow processes compared to CO2 sequestration in deep saline aquifers (no hydrocarbons). Two of the most important factors are three-phase relative permeability and hysteresis effects, both of which are difficult to measure and are usually represented by numerical interpolation models. The purposes of this study included quantification of impacts of different three-phase relative permeability models and hysteresis models on CO2 sequestration simulation results, and associated quantitative estimation of uncertainty. Four three-phase relative permeability models and three hysteresis models were applied to a model of an active CO2-EOR site, the SACROC unit located in western Texas. To eliminate possible bias of deterministic parameters on the evaluation, a sequential Gaussian simulation technique was utilized to generate 50 realizations to describe heterogeneity of porosity and permeability, initially obtained from well logs and seismic survey data. Simulation results of forecasted pressure distributions and CO2 storage suggest that (1) the choice of three-phase relative permeability model and hysteresis model have noticeable impacts on CO2 sequestration simulation results; (2) influences of both factors are observed in all 50 realizations; and (3) the specific choice of hysteresis model appears to be somewhat more important relative to the choice of three-phase relative permeability model in terms of model uncertainty.
Assessing the importance of rainfall uncertainty on hydrological models with different spatial and temporal scale

NASA Astrophysics Data System (ADS)

Nossent, Jiri; Pereira, Fernando; Bauwens, Willy

2015-04-01

Precipitation is one of the key inputs for hydrological models. As long as the values of the hydrological model parameters are fixed, a variation of the rainfall input is expected to induce a change in the model output. Given the increased awareness of uncertainty on rainfall records, it becomes more important to understand the impact of this input - output dynamic. Yet, modellers often still have the intention to mimic the observed flow, whatever the deviation of the employed records from the actual rainfall might be, by recklessly adapting the model parameter values. But is it actually possible to vary the model parameter values in such a way that a certain (observed) model output can be generated based on inaccurate rainfall inputs? Thus, how important is the rainfall uncertainty for the model output with respect to the model parameter importance? To address this question, we apply the Sobol' sensitivity analysis method to assess and compare the importance of the rainfall uncertainty and the model parameters on the output of the hydrological model. In order to be able to treat the regular model parameters and input uncertainty in the same way, and to allow a comparison of their influence, a possible approach is to represent the rainfall uncertainty by a parameter. To tackle the latter issue, we apply so called rainfall multipliers on hydrological independent storm events, as a probabilistic parameter representation of the possible rainfall variation. As available rainfall records are very often point measurements at a discrete time step (hourly, daily, monthly,…), they contain uncertainty due to a latent lack of spatial and temporal variability. The influence of the latter variability can also be different for hydrological models with different spatial and temporal scale. Therefore, we perform the sensitivity analyses on a semi-distributed model (SWAT) and a lumped model (NAM). The assessment and comparison of the importance of the rainfall uncertainty and the model parameters is achieved by considering different scenarios for the included parameters and the state of the models.
Adaptation of Acoustic Model Experiments of STM via Smartphones and Tablets

ERIC Educational Resources Information Center

Thees, Michael; Hochberg, Katrin; Kuhn, Jochen; Aeschlimann, Martin

2017-01-01

The importance of Scanning Tunneling Microscopy (STM) in today's research and industry leads to the question of how to include such a key technology in physics education. Manfred Euler has developed an acoustic model experiment to illustrate the fundamental measuring principles based on an analogy between quantum mechanics and acoustics. Based on…
77 FR 41266 - Extension of Import Restrictions on Archaeological Objects and Ecclesiastical and Ritual...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-13

... figurines; warrior figures; animals such as birds, bulls and pigs; tubular figurines; boat models; and human masks. In the Cypro-Archaic period, terra cotta models illustrate a variety of daily activities.... Illustrated examples include the head of a woman decorated with rosettes and a bearded male with spiral...
Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…
Validation of an Evaluation Model for Learning Management Systems

ERIC Educational Resources Information Center

Kim, S. W.; Lee, M. G.

2008-01-01

This study aims to validate a model for evaluating learning management systems (LMS) used in e-learning fields. A survey of 163 e-learning experts, regarding 81 validation items developed through literature review, was used to ascertain the importance of the criteria. A concise list of explanatory constructs, including two principle factors, was…
Quality Assurance in E-Learning: PDPP Evaluation Model and Its Application

ERIC Educational Resources Information Center

Zhang, Weiyuan; Cheng, Y. L.

2012-01-01

E-learning has become an increasingly important teaching and learning mode in educational institutions and corporate training. The evaluation of e-learning, however, is essential for the quality assurance of e-learning courses. This paper constructs a four-phase evaluation model for e-learning courses, which includes planning, development,…
A growing social network model in geographical space

NASA Astrophysics Data System (ADS)

Antonioni, Alberto; Tomassini, Marco

2017-09-01

In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

Modeling asthma: Pitfalls, promises, and the road ahead.

PubMed

Rosenberg, Helene F; Druey, Kirk M

2018-02-16

Asthma is a chronic, heterogeneous, and recurring inflammatory disease of the lower airways, with exacerbations that feature airway inflammation and bronchial hyperresponsiveness. Asthma has been modeled extensively via disease induction in both wild-type and genetically manipulated laboratory mice (Mus musculus). Antigen sensitization and challenge strategies have reproduced numerous important features of airway inflammation characteristic of human asthma, notably the critical roles of type 2 T helper cell cytokines. Recent models of disease induction have advanced to include physiologic aeroallergens with prolonged respiratory challenge without systemic sensitization; others incorporate tobacco, respiratory viruses, or bacteria as exacerbants. Nonetheless, differences in lung size, structure, and physiologic responses limit the degree to which airway dynamics measured in mice can be compared to human subjects. Other rodent allergic airways models, including those featuring the guinea pig (Cavia porcellus) might be considered for lung function studies. Finally, domestic cats (Feline catus) and horses (Equus caballus) develop spontaneous obstructive airway disorders with clinical and pathologic features that parallel human asthma. Information on pathogenesis and treatment of these disorders is an important resource. ©2018 Society for Leukocyte Biology.
Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.
Effects of rail dynamics and friction characteristics on curve squeal

NASA Astrophysics Data System (ADS)

Ding, B.; Squicciarini, G.; Thompson, D. J.

2016-09-01

Curve squeal in railway vehicles is an instability mechanism that arises in tight curves under certain running and environmental conditions. In developing a model the most important elements are the characterisation of friction coupled with an accurate representation of the structural dynamics of the wheel. However, the role played by the dynamics of the rail is not fully understood and it is unclear whether this should be included in a model or whether it can be safely neglected. This paper makes use of previously developed time domain and frequency domain curve squeal models to assess whether the presence of the rail and the falling characteristics of the friction force can modify the instability mechanisms and the final response. For this purpose, the time-domain model has been updated to include the rail dynamics in terms of its state space representation in various directions. Frequency domain and time domain analyses results show that falling friction is not the only reason for squeal and rail dynamics can play an important role, especially under constant friction conditions.
Quantitative microbiological risk assessment in food industry: Theory and practical application.

PubMed

Membré, Jeanne-Marie; Boué, Géraldine

2018-04-01

The objective of this article is to bring scientific background as well as practical hints and tips to guide risk assessors and modelers who want to develop a quantitative Microbiological Risk Assessment (MRA) in an industrial context. MRA aims at determining the public health risk associated with biological hazards in a food. Its implementation in industry enables to compare the efficiency of different risk reduction measures, and more precisely different operational settings, by predicting their effect on the final model output. The first stage in MRA is to clearly define the purpose and scope with stakeholders, risk assessors and modelers. Then, a probabilistic model is developed; this includes schematically three important phases. Firstly, the model structure has to be defined, i.e. the connections between different operational processing steps. An important step in food industry is the thermal processing leading to microbial inactivation. Growth of heat-treated surviving microorganisms and/or post-process contamination during storage phase is also important to take into account. Secondly, mathematical equations are determined to estimate the change of microbial load after each processing step. This phase includes the construction of model inputs by collecting data or eliciting experts. Finally, the model outputs are obtained by simulation procedures, they have to be interpreted and communicated to targeted stakeholders. In this latter phase, tools such as what-if scenarios provide an essential added value. These different MRA phases are illustrated through two examples covering important issues in industry. The first one covers process optimization in a food safety context, the second one covers shelf-life determination in a food quality context. Although both contexts required the same methodology, they do not have the same endpoint: up to the human health in the foie gras case-study illustrating here a safety application, up to the food portion in the brioche case-study illustrating here a quality application. Copyright © 2017 Elsevier Ltd. All rights reserved.
A new model for yaw attitude of Global Positioning System satellites

NASA Technical Reports Server (NTRS)

Bar-Sever, Y. E.

1995-01-01

Proper modeling of the Global Positioning System (GPS) satellite yaw attitude is important in high-precision applications. A new model for the GPS satellite yaw attitude is introduced that constitutes a significant improvement over the previously available model in terms of efficiency, flexibility, and portability. The model is described in detail, and implementation issues, including the proper estimation strategy, are addressed. The performance of the new model is analyzed, and an error budget is presented. This is the first self-contained description of the GPS yaw attitude model.
A new interpretation and validation of variance based importance measures for models with correlated inputs

NASA Astrophysics Data System (ADS)

Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

2013-05-01

In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.
Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

DOE PAGES

Wang, Yan; Swiler, Laura

2017-09-07

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.
Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

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

Wang, Yan; Swiler, Laura

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.
Parents and friends both matter: simultaneous and interactive influences of parents and friends on European schoolchildren's energy balance-related behaviours - the ENERGY cross-sectional study.

PubMed

te Velde, Saskia J; ChinAPaw, Mai J M; De Bourdeaudhuij, Ilse; Bere, Elling; Maes, Lea; Moreno, Luis; Jan, Nataša; Kovacs, Eva; Manios, Yannis; Brug, Johannes

2014-07-08

The family, and parents in particular, are considered the most important influencers regarding children's energy-balance related behaviours (EBRBs). When children become older and gain more behavioural autonomy regarding different behaviours, the parental influences may become less important and peer influences may gain importance. Therefore the current study aims to investigate simultaneous and interactive associations of family rules, parent and friend norms and modelling with soft drink intake, TV viewing, daily breakfast consumption and sport participation among schoolchildren across Europe. A school-based cross-sectional survey in eight countries across Europe among 10-12 year old schoolchildren. Child questionnaires were used to assess EBRBs (soft drink intake, TV viewing, breakfast consumption, sport participation), and potential determinants of these behaviours as perceived by the child, including family rules, parental and friend norms and modelling. Linear and logistic regression analyses (n = 7811) were applied to study the association of parental (norms, modelling and rules) and friend influences (norm and modelling) with the EBRBs. In addition, potential moderating effects of parental influences on the associations of friend influences with the EBRBs were studied by including interaction terms. Children reported more unfavourable friend norms and modelling regarding soft drink intake and TV viewing, while they reported more favourable friend and parental norms and modelling for breakfast consumption and physical activity. Perceived friend and parental norms and modelling were significantly positively associated with soft drink intake, breakfast consumption, physical activity (only modelling) and TV time. Across the different behaviours, ten significant interactions between parental and friend influencing variables were found and suggested a weaker association of friend norms and modelling when rules were in place. Parental and friends norm and modelling are associated with schoolchildren's energy balance-related behaviours. Having family rules or showing favourable parental modelling and norms seems to reduce the potential unfavourable associations of friends' norms and modelling with the EBRBs.
ModelTest Server: a web-based tool for the statistical selection of models of nucleotide substitution online

PubMed Central

Posada, David

2006-01-01

ModelTest server is a web-based application for the selection of models of nucleotide substitution using the program ModelTest. The server takes as input a text file with likelihood scores for the set of candidate models. Models can be selected with hierarchical likelihood ratio tests, or with the Akaike or Bayesian information criteria. The output includes several statistics for the assessment of model selection uncertainty, for model averaging or to estimate the relative importance of model parameters. The server can be accessed at . PMID:16845102
Role of seasonality on predator-prey-subsidy population dynamics.

PubMed

Levy, Dorian; Harrington, Heather A; Van Gorder, Robert A

2016-05-07

The role of seasonality on predator-prey interactions in the presence of a resource subsidy is examined using a system of non-autonomous ordinary differential equations (ODEs). The problem is motivated by the Arctic, inhabited by the ecological system of arctic foxes (predator), lemmings (prey), and seal carrion (subsidy). We construct two nonlinear, nonautonomous systems of ODEs named the Primary Model, and the n-Patch Model. The Primary Model considers spatial factors implicitly, and the n-Patch Model considers space explicitly as a "Stepping Stone" system. We establish the boundedness of the dynamics, as well as the necessity of sufficiently nutritional food for the survival of the predator. We investigate the importance of including the resource subsidy explicitly in the model, and the importance of accounting for predator mortality during migration. We find a variety of non-equilibrium dynamics for both systems, obtaining both limit cycles and chaotic oscillations. We were then able to discuss relevant implications for biologically interesting predator-prey systems including subsidy under seasonal effects. Notably, we can observe the extinction or persistence of a species when the corresponding autonomous system might predict the opposite. Copyright © 2016 Elsevier Ltd. All rights reserved.
Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

PubMed Central

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θ s - θ r), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process. PMID:24672332
Analysis of rainfall infiltration law in unsaturated soil slope.

PubMed

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.
The Missing Stakeholder Group: Why Patients Should be Involved in Health Economic Modelling.

PubMed

van Voorn, George A K; Vemer, Pepijn; Hamerlijnck, Dominique; Ramos, Isaac Corro; Teunissen, Geertruida J; Al, Maiwenn; Feenstra, Talitha L

2016-04-01

Evaluations of healthcare interventions, e.g. new drugs or other new treatment strategies, commonly include a cost-effectiveness analysis (CEA) that is based on the application of health economic (HE) models. As end users, patients are important stakeholders regarding the outcomes of CEAs, yet their knowledge of HE model development and application, or their involvement therein, is absent. This paper considers possible benefits and risks of patient involvement in HE model development and application for modellers and patients. An exploratory review of the literature has been performed on stakeholder-involved modelling in various disciplines. In addition, Dutch patient experts have been interviewed about their experience in, and opinion about, the application of HE models. Patients have little to no knowledge of HE models and are seldom involved in HE model development and application. Benefits of becoming involved would include a greater understanding and possible acceptance by patients of HE model application, improved model validation, and a more direct infusion of patient expertise. Risks would include patient bias and increased costs of modelling. Patient involvement in HE modelling seems to carry several benefits as well as risks. We claim that the benefits may outweigh the risks and that patients should become involved.
Noise Suppression Based on Multi-Model Compositions Using Multi-Pass Search with Multi-Label N-gram Models

NASA Astrophysics Data System (ADS)

Jitsuhiro, Takatoshi; Toriyama, Tomoji; Kogure, Kiyoshi

We propose a noise suppression method based on multi-model compositions and multi-pass search. In real environments, input speech for speech recognition includes many kinds of noise signals. To obtain good recognized candidates, suppressing many kinds of noise signals at once and finding target speech is important. Before noise suppression, to find speech and noise label sequences, we introduce multi-pass search with acoustic models including many kinds of noise models and their compositions, their n-gram models, and their lexicon. Noise suppression is frame-synchronously performed using the multiple models selected by recognized label sequences with time alignments. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. The proposed method obtained higher performance than the conventional method.
Alternative Payment Models in Radiology: The Legislative and Regulatory Roadmap for Reform.

PubMed

Silva, Ezequiel; McGinty, Geraldine B; Hughes, Danny R; Duszak, Richard

2016-10-01

The Medicare Access and CHIP Reauthorization Act (MACRA) replaces the sustainable growth rate with a payment system based on the Merit-Based Incentive Payment System and incentives for alternative payment model participation. It is important that radiologists understand the statutory requirements of MACRA. This includes the nature of the Merit-Based Incentive Payment System composite performance score and its impact on payments. The timeline for MACRA implementation is fairly aggressive and includes a robust effort to define episode groups, which include radiologic services. A number of organizations, including the ACR, are commenting on the structure of MACRA-directed initiatives. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.
How Measurement and Modeling of Attendance Matter to Assessing Dimensions of Inequality

ERIC Educational Resources Information Center

Dougherty, Shaun M.

2018-01-01

Each iteration of high stakes accountability has included requirements to include measures of attendance in their accountability programs, thereby increasing the salience of this measure. Researchers too have turned to attendance and chronic absence as important outcomes in evaluations and policy studies. Often, too little attention is paid to the…
Parallel Computing for Brain Simulation.

PubMed

Pastur-Romay, L A; Porto-Pazos, A B; Cedron, F; Pazos, A

2017-01-01

The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not been understood yet how and why most of these abilities are produced. For decades, researchers have been trying to make computers reproduce these abilities, focusing on both understanding the nervous system and, on processing data in a more efficient way than before. Their aim is to make computers process information similarly to the brain. Important technological developments and vast multidisciplinary projects have allowed creating the first simulation with a number of neurons similar to that of a human brain. This paper presents an up-to-date review about the main research projects that are trying to simulate and/or emulate the human brain. They employ different types of computational models using parallel computing: digital models, analog models and hybrid models. This review includes the current applications of these works, as well as future trends. It is focused on various works that look for advanced progress in Neuroscience and still others which seek new discoveries in Computer Science (neuromorphic hardware, machine learning techniques). Their most outstanding characteristics are summarized and the latest advances and future plans are presented. In addition, this review points out the importance of considering not only neurons: Computational models of the brain should also include glial cells, given the proven importance of astrocytes in information processing. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Recent advances in understanding secondary organic aerosols: implications for global climate forcing

NASA Astrophysics Data System (ADS)

Shrivastava, Manish

2017-04-01

Anthropogenic emissions and land-use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding pre-industrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features 1) influence estimates of aerosol radiative forcing and 2) can confound estimates of the historical response of climate to increases in greenhouse gases (e.g. the 'climate sensitivity'). Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This presentation is based on a US Department of Energy Atmospheric Systems Research sponsored workshop, which highlighted key SOA processes overlooked in climate models that could greatly affect climate forcing estimates. We will highlight the importance of processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including: formation of extremely low-volatility organics in the gas-phase; isoprene epoxydiols (IEPOX) multi-phase chemistry; particle-phase oligomerization; and physical properties such as viscosity. We also highlight some of the recently discovered important processes that involve interactions between natural biogenic emissions and anthropogenic emissions such as effects of sulfur and NOx emissions on SOA. We will present examples of integrated model-measurement studies that relate the observed evolution of organic aerosol mass and number with knowledge of particle properties such as volatility and viscosity. We will also highlight the importance of continuing efforts to rank the most influential SOA processes that affect climate forcing, but are often missing in climate models. Ultimately, gas- and particle-phase chemistry processes that capture the dynamic evolution of number and mass concentrations of SOA particles need to be accurately and efficiently represented in regional and global atmospheric chemistry-climate models.
The importance of considering shifts in seasonal changes in discharges when predicting future phosphorus loads in streams

USGS Publications Warehouse

LaBeau, Meredith B.; Mayer, Alex S.; Griffis, Veronica; Watkins, David Jr.; Robertson, Dale M.; Gyawali, Rabi

2015-01-01

In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.

[Emotional regulation and motivation in children with ADHD].

PubMed

Høvik, Marie Farstad; Plessen, Kerstin J

2010-12-02

Impaired cognitive control functions have long been regarded as the main problem in the development of Attention-Deficit/Hyperactivity Disorder (ADHD). A more recent model emphasizes the importance of emotional and motivational problems. We have reviewed the evidence for this model, which may have important implications for clinical practice. The article is based on literature identified through a non-systematic search in PubMed. Although limited research was carried out in this topic earlier, studies are currently emerging. Persons with ADHD react differently than controls on tasks that include rewards and on tasks that stress their capacity to regulate emotions. Abnormal signals during examination with electroencephalography (EEG) and anatomical and functional magnetic resonance imaging (fMRI) reflect problems with emotional regulation in patients with ADHD. Neurobiological research supports a model that includes emotional and motivational problems in the development of ADHD. Increased knowledge about emotional and motivational problems may improve treatment of these patients through development of more individually adapted therapy.
Upstream and downstream correlates of older people's engagement in social networks: what are their effects on health over time?

PubMed

Stephens, Christine; Noone, Jack; Alpass, Fiona

2014-01-01

This study tested the effects of social network engagement and social support on the health of older people moving into retirement, using a model which includes social context variables. A prospective survey of a New Zealand population sample aged 54-70 at baseline (N = 2,282) was used to assess the effects on mental and physical health across time. A structural equation model assessed pathways from the social context variables through network engagement to social support and then to mental and physical health 2 years later. The proposed model of effects on mental health was supported when gender, economic living standards, and ethnicity were included along with the direct effects of these variables on social support. These findings confirm the importance of taking social context variables into account when considering social support networks. Social engagement appears to be an important aspect of social network functioning which could be investigated further.
Multidimensional Modeling of Atmospheric Effects and Surface Heterogeneities on Remote Sensing

NASA Technical Reports Server (NTRS)

Gerstl, S. A. W.; Simmer, C.; Zardecki, A. (Principal Investigator)

1985-01-01

The overall goal of this project is to establish a modeling capability that allows a quantitative determination of atmospheric effects on remote sensing including the effects of surface heterogeneities. This includes an improved understanding of aerosol and haze effects in connection with structural, angular, and spatial surface heterogeneities. One important objective of the research is the possible identification of intrinsic surface or canopy characteristics that might be invariant to atmospheric perturbations so that they could be used for scene identification. Conversely, an equally important objective is to find a correction algorithm for atmospheric effects in satellite-sensed surface reflectances. The technical approach is centered around a systematic model and code development effort based on existing, highly advanced computer codes that were originally developed for nuclear radiation shielding applications. Computational techniques for the numerical solution of the radiative transfer equation are adapted on the basis of the discrete-ordinates finite-element method which proved highly successful for one and two-dimensional radiative transfer problems with fully resolved angular representation of the radiation field.
Particle-based modeling of heterogeneous chemical kinetics including mass transfer.

PubMed

Sengar, A; Kuipers, J A M; van Santen, Rutger A; Padding, J T

2017-08-01

Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.
Particle-based modeling of heterogeneous chemical kinetics including mass transfer

NASA Astrophysics Data System (ADS)

Sengar, A.; Kuipers, J. A. M.; van Santen, Rutger A.; Padding, J. T.

2017-08-01

Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.
Analysis of precision and accuracy in a simple model of machine learning

NASA Astrophysics Data System (ADS)

Lee, Julian

2017-12-01

Machine learning is a procedure where a model for the world is constructed from a training set of examples. It is important that the model should capture relevant features of the training set, and at the same time make correct prediction for examples not included in the training set. I consider the polynomial regression, the simplest method of learning, and analyze the accuracy and precision for different levels of the model complexity.
Utility of arterial blood gas, CBC, biochemistry and cardiac hormones as evaluation parameters of cardiovascular disease in nonhuman primates.

PubMed

Nakayama, Shunya; Koie, Hiroshi; Kanayama, Kiichi; Katakai, Yuko; Ito-Fujishiro, Yasuyo; Sankai, Tadashi; Yasutomi, Yasuhiro; Ageyama, Naohide

2018-06-11

Cardiovascular disease (CVD) has a tremendous impact on the quality of life of humans. While experimental animals are valuable to medical research as models of human diseases, cardiac systems differ widely across various animal species. Thus, we examined a CVD model in cynomolgus monkeys. Laboratory primates are precious resources, making it imperative that symptoms of diseases and disorders are detected as early as possible. Thus, in this study we comprehensively examined important indicators of CVD in cynomolgus monkeys, including arterial blood gas, complete blood count (CBC), biochemistry, and cardiac hormones. The control group included 20 healthy macaques showing non-abnormal findings in screening tests, whereas the CVD group included 20 macaques with valvular disease and cardiomyopathy. An increase of red blood cell distribution width was observed in the CBC, indicating chronic inflammation related to CVD. An increase of HCO 3 was attributed to the correction of acidosis. Furthermore, development of the CVD model was supported by significant increases in natriuretic peptides. It is suggested that these results indicated a correlation between human CVD and the model in monkeys. Moreover, blood tests including arterial blood gas are non-invasive and can be performed more easily than other technical tests. CVD affected animals easily change their condition by anesthesia and surgical invasion. Pay attention to arterial blood gas and proper respond to their condition are important for research. This data may facilitate human research and aid in the management and veterinary care of nonhuman primates.
The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

USGS Publications Warehouse

Larocque, Guy R.; Bhatti, Jagtar S.; Liu, Jinxun; Ascough, James C.; Gordon, Andrew M.

2008-01-01

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models (Smith and Heath, 2001 and Allen et al., 2004). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.
A study of the effects of disk flexibility on the rotordynamics of the space shuttle main engine turbo-pumps

NASA Technical Reports Server (NTRS)

Flowers, George T.

1989-01-01

Rotor dynamical analyses are typically performed using rigid disk models. Studies of rotor models in which the effects of disk flexibility were included indicate that is may be an important effect for many systems. This issue is addressed with respect to the Space Shuttle Main Engine high pressure turbo-pumps. Finite element analyses have been performed for a simplified free-free flexible disk rotor model and the modes and frequencies compared to those of a rigid disk model. The simple model was then extended to a more sophisticated HPTOP rotor model and similar results were observed. Equations were developed that are suitable for modifying the current rotordynamical analysis program to account for disk flexibility. Some conclusions are drawn from the results of this work as to the importance of disk flexibility on the HPTOP rotordynamics and some recommendations are given for follow-up research in this area.
What Can the Diffusion Model Tell Us About Prospective Memory?

PubMed Central

Horn, Sebastian S.; Bayen, Ute J.; Smith, Rebekah E.

2011-01-01

Cognitive process models, such as Ratcliff’s (1978) diffusion model, are useful tools for examining cost- or interference effects in event-based prospective memory (PM). The diffusion model includes several parameters that provide insight into how and why ongoing-task performance may be affected by a PM task and is ideally suited to analyze performance because both reaction time and accuracy are taken into account. Separate analyses of these measures can easily yield misleading interpretations in cases of speed-accuracy tradeoffs. The diffusion model allows us to measure possible criterion shifts and is thus an important methodological improvement over standard analyses. Performance in an ongoing lexical decision task (Smith, 2003) was analyzed with the diffusion model. The results suggest that criterion shifts play an important role when a PM task is added, but do not fully explain the cost effect on RT. PMID:21443332
Poststroke Seizures and Epilepsy: Clinical Studies and Animal Models

PubMed Central

Kelly, Kevin M.

2002-01-01

Poststroke seizures and epilepsy have been described in numerous clinical studies for many years. Most studies are retrospective in design, include relatively small numbers of patients, have limited periods of follow-up, and report a diversity of findings. Well-designed clinical trials and population studies in the recent past addressed several critical clinical issues and generated important findings regarding the occurrence of poststroke seizures and epilepsy. In contrast, the pathophysiologic events of injured brain that establish poststroke epileptogenesis are not well understood, and animal modeling has had limited development. Reviews of several important clinical studies and animal models that hold promise for a better understanding of poststroke epileptogenesis are presented. PMID:15309107
A Brief Survey of Modern Optimization for Statisticians

PubMed Central

Lange, Kenneth; Chi, Eric C.; Zhou, Hua

2014-01-01

Modern computational statistics is turning more and more to high-dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include nondifferentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience. PMID:25242858
Using Radiation Risk Models in Cancer Screening Simulations: Important Assumptions and Effects on Outcome Projections

PubMed Central

Lee, Janie M.; McMahon, Pamela M.; Lowry, Kathryn P.; Omer, Zehra B.; Eisenberg, Jonathan D.; Pandharipande, Pari V.; Gazelle, G. Scott

2012-01-01

Purpose: To evaluate the effect of incorporating radiation risk into microsimulation (first-order Monte Carlo) models for breast and lung cancer screening to illustrate effects of including radiation risk on patient outcome projections. Materials and Methods: All data used in this study were derived from publicly available or deidentified human subject data. Institutional review board approval was not required. The challenges of incorporating radiation risk into simulation models are illustrated with two cancer screening models (Breast Cancer Model and Lung Cancer Policy Model) adapted to include radiation exposure effects from mammography and chest computed tomography (CT), respectively. The primary outcome projected by the breast model was life expectancy (LE) for BRCA1 mutation carriers. Digital mammographic screening beginning at ages 25, 30, 35, and 40 years was evaluated in the context of screenings with false-positive results and radiation exposure effects. The primary outcome of the lung model was lung cancer–specific mortality reduction due to annual screening, comparing two diagnostic CT protocols for lung nodule evaluation. The Metropolis-Hastings algorithm was used to estimate the mean values of the results with 95% uncertainty intervals (UIs). Results: Without radiation exposure effects, the breast model indicated that annual digital mammography starting at age 25 years maximized LE (72.03 years; 95% UI: 72.01 years, 72.05 years) and had the highest number of screenings with false-positive results (2.0 per woman). When radiation effects were included, annual digital mammography beginning at age 30 years maximized LE (71.90 years; 95% UI: 71.87 years, 71.94 years) with a lower number of screenings with false-positive results (1.4 per woman). For annual chest CT screening of 50-year-old females with no follow-up for nodules smaller than 4 mm in diameter, the lung model predicted lung cancer–specific mortality reduction of 21.50% (95% UI: 20.90%, 22.10%) without radiation risk and 17.75% (95% UI: 16.97%, 18.41%) with radiation risk. Conclusion: Because including radiation exposure risk can influence long-term projections from simulation models, it is important to include these risks when conducting modeling-based assessments of diagnostic imaging. © RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11110352/-/DC1 PMID:22357897
New insights into epididymal biology and function.

PubMed

Cornwall, Gail A

2009-01-01

The epididymis performs an important role in the maturation of spermatozoa including their acquisition of progressive motility and fertilizing ability. However, the molecular mechanisms that govern these maturational events are still poorly defined. This review focuses on recent progress in our understanding of epididymal function including its development, role of the luminal microenvironment in sperm maturation, regulation and novel mechanisms the epididymis utilizes to carry out some of its functions. A systematic search of Pubmed was carried out using the search term 'epididymis'. Articles that were published in the English language until the end of August 2008 and that focused on the specific topics described above were included. Additional papers cited in the primary reference were also included. While the majority of these findings were the result of studies in animal models, recent studies in the human epididymis are also presented including gene profiling studies to examine regionalized expression in normal epididymides as well as in those from vasectomized patients. Significant progress has been made in our understanding of epididymal function providing new insights that ultimately could improve human health. The data also indicate that the human epididymis plays an important role in sperm maturation but has unique properties compared with animal models.
Relationships between host viremia and vector susceptibility for arboviruses.

PubMed

Lord, Cynthia C; Rutledge, C Roxanne; Tabachnick, Walter J

2006-05-01

Using a threshold model where a minimum level of host viremia is necessary to infect vectors affects our assessment of the relative importance of different host species in the transmission and spread of these pathogens. Other models may be more accurate descriptions of the relationship between host viremia and vector infection. Under the threshold model, the intensity and duration of the viremia above the threshold level is critical in determining the potential numbers of infected mosquitoes. A probabilistic model relating host viremia to the probability distribution of virions in the mosquito bloodmeal shows that the threshold model will underestimate the significance of hosts with low viremias. A probabilistic model that includes avian mortality shows that the maximum number of mosquitoes is infected by feeding on hosts whose viremia peaks just below the lethal level. The relationship between host viremia and vector infection is complex, and there is little experimental information to determine the most accurate model for different arthropod-vector-host systems. Until there is more information, the ability to distinguish the relative importance of different hosts in infecting vectors will remain problematic. Relying on assumptions with little support may result in erroneous conclusions about the importance of different hosts.
Relationships Between Host Viremia and Vector Susceptibility for Arboviruses

PubMed Central

Lord, Cynthia C.; Rutledge, C. Roxanne; Tabachnick, Walter J.

2010-01-01

Using a threshold model where a minimum level of host viremia is necessary to infect vectors affects our assessment of the relative importance of different host species in the transmission and spread of these pathogens. Other models may be more accurate descriptions of the relationship between host viremia and vector infection. Under the threshold model, the intensity and duration of the viremia above the threshold level is critical in determining the potential numbers of infected mosquitoes. A probabilistic model relating host viremia to the probability distribution of virions in the mosquito bloodmeal shows that the threshold model will underestimate the significance of hosts with low viremias. A probabilistic model that includes avian mortality shows that the maximum number of mosquitoes is infected by feeding on hosts whose viremia peaks just below the lethal level. The relationship between host viremia and vector infection is complex, and there is little experimental information to determine the most accurate model for different arthropod–vector–host systems. Until there is more information, the ability to distinguish the relative importance of different hosts in infecting vectors will remain problematic. Relying on assumptions with little support may result in erroneous conclusions about the importance of different hosts. PMID:16739425
Impacts of increasing the aerosol complexity in the Met Office global numerical weather prediction model

NASA Astrophysics Data System (ADS)

Mulcahy, J. P.; Walters, D. N.; Bellouin, N.; Milton, S. F.

2014-05-01

The inclusion of the direct and indirect radiative effects of aerosols in high-resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three-dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing long-wave radiation over West Africa due to a better representation of dust. However, uncertainties in dust optical properties propagate to its direct effect and the subsequent model response. Inclusion of the indirect aerosol effects improves surface radiation biases at the North Slope of Alaska ARM site due to lower cloud amounts in high-latitude clean-air regions. This leads to improved temperature and height forecasts in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short-range forecasts. However, the indirect aerosol effect leads to a strengthening of the low-level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. Regional impacts on the African Easterly Jet (AEJ) are also presented with the large dust loading in the aerosol climatology enhancing of the heat low over West Africa and weakening the AEJ. This study highlights the importance of including a more realistic treatment of aerosol-cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes.
Impacts of increasing the aerosol complexity in the Met Office global NWP model

NASA Astrophysics Data System (ADS)

Mulcahy, J. P.; Walters, D. N.; Bellouin, N.; Milton, S. F.

2013-11-01

Inclusion of the direct and indirect radiative effects of aerosols in high resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing longwave radiation over West Africa due to a better representation of dust. However, uncertainties in dust optical properties propogate to its direct effect and the subsequent model response. Inclusion of the indirect aerosol effects improves surface radiation biases at the North Slope of Alaska ARM site due to lower cloud amounts in high latitude clean air regions. This leads to improved temperature and height forecasts in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short range forecasts. However, the indirect aerosol effect leads to a strengthening of the low level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. Regional impacts on the African Easterly Jet (AEJ) are also presented with the large dust loading in the aerosol climatology enhancing of the heat low over West Africa and weakening the AEJ. This study highlights the importance of including a~more realistic treatment of aerosol-cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes.
Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist.

PubMed

Doble, Brett; Tan, Marcus; Harris, Anthony; Lorgelly, Paula

2015-02-01

The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics of companion diagnostics into model-based economic evaluations to ensure consistent and transparent reimbursement decisions are made.
Groundwater Withdrawals under Drought: Reconciling GRACE and Models in the United States High Plains Aquifer

NASA Astrophysics Data System (ADS)

Nie, W.; Zaitchik, B. F.; Kumar, S.; Rodell, M.

2017-12-01

Advanced Land Surface Models (LSM) offer a powerful tool for studying and monitoring hydrological variability. Highly managed systems, however, present a challenge for these models, which typically have simplified or incomplete representations of human water use, if the process is represented at all. GRACE, meanwhile, detects the total change in water storage, including change due to human activities, but does not resolve the source of these changes. Here we examine recent groundwater declines in the US High Plains Aquifer (HPA), a region that is heavily utilized for irrigation and that is also affected by episodic drought. To understand observed decline in groundwater (well observation) and terrestrial water storage (GRACE) during a recent multi-year drought, we modify the Noah-MP LSM to include a groundwater pumping irrigation scheme. To account for seasonal and interannual variability in active irrigated area we apply a monthly time-varying greenness vegetation fraction (GVF) dataset to the model. A set of five experiments were performed to study the impact of irrigation with groundwater withdrawal on the simulated hydrological cycle of the HPA and to assess the importance of time-varying GVF when simulating drought conditions. The results show that including the groundwater pumping irrigation scheme in Noah-MP improves model agreement with GRACE mascon solutions for TWS and well observations of groundwater anomaly in the southern HPA, including Texas and Kansas, and that accounting for time-varying GVF is important for model realism under drought. Results for the HPA in Nebraska are mixed, likely due to misrepresentation of the recharge process. This presentation will highlight the value of the GRACE constraint for model development, present estimates of the relative contribution of climate variability and irrigation to declining TWS in the HPA under drought, and identify opportunities to integrate GRACE-FO with models for water resource monitoring in heavily irrigated regions.

Does Attainment of Piaget's Formal Operational Level of Cognitive Development Predict Student Understanding of Scientific Models?

ERIC Educational Resources Information Center

Lahti, Richard Dennis, II.

2012-01-01

Knowledge of scientific models and their uses is a concept that has become a key benchmark in many of the science standards of the past 30 years, including the proposed Next Generation Science Standards. Knowledge of models is linked to other important nature of science concepts such as theory change which are also rising in prominence in newer…
Bond Graph Model of Cerebral Circulation: Toward Clinically Feasible Systemic Blood Flow Simulations.

PubMed

Safaei, Soroush; Blanco, Pablo J; Müller, Lucas O; Hellevik, Leif R; Hunter, Peter J

2018-01-01

We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data.
Machine Learning Predictions of a Multiresolution Climate Model Ensemble

NASA Astrophysics Data System (ADS)

Anderson, Gemma J.; Lucas, Donald D.

2018-05-01

Statistical models of high-resolution climate models are useful for many purposes, including sensitivity and uncertainty analyses, but building them can be computationally prohibitive. We generated a unique multiresolution perturbed parameter ensemble of a global climate model. We use a novel application of a machine learning technique known as random forests to train a statistical model on the ensemble to make high-resolution model predictions of two important quantities: global mean top-of-atmosphere energy flux and precipitation. The random forests leverage cheaper low-resolution simulations, greatly reducing the number of high-resolution simulations required to train the statistical model. We demonstrate that high-resolution predictions of these quantities can be obtained by training on an ensemble that includes only a small number of high-resolution simulations. We also find that global annually averaged precipitation is more sensitive to resolution changes than to any of the model parameters considered.
Commentary on the shifting processes model: a conceptual model for weight management.

PubMed

Pagoto, Sherry; Rodrigues, Stephanie

2013-12-01

Macchi and colleagues propose a theoretical model that merges concepts from the biopsychosocial model and family systems theory to produce a broader framework for understanding weight loss and maintenance (see record 2013-28564-001). The Shifting Processes Model views individual weight loss and maintenance in the context of family dynamics, including family eating and exercise habits, home environment, and family relationships. The authors reason that traditional models put the burden of change on the individual rather than the family system, when the latter is an important context of individual behavior.
Cloud-based calculators for fast and reliable access to NOAA's geomagnetic field models

NASA Astrophysics Data System (ADS)

Woods, A.; Nair, M. C.; Boneh, N.; Chulliat, A.

2017-12-01

While the Global Positioning System (GPS) provides accurate point locations, it does not provide pointing directions. Therefore, the absolute directional information provided by the Earth's magnetic field is of primary importance for navigation and for the pointing of technical devices such as aircrafts, satellites and lately, mobile phones. The major magnetic sources that affect compass-based navigation are the Earth's core, its magnetized crust and the electric currents in the ionosphere and magnetosphere. NOAA/CIRES Geomagnetism (ngdc.noaa.gov/geomag/) group develops and distributes models that describe all these important sources to aid navigation. Our geomagnetic models are used in variety of platforms including airplanes, ships, submarines and smartphones. While the magnetic field from Earth's core can be described in relatively fewer parameters and is suitable for offline computation, the magnetic sources from Earth's crust, ionosphere and magnetosphere require either significant computational resources or real-time capabilities and are not suitable for offline calculation. This is especially important for small navigational devices or embedded systems, where computational resources are limited. Recognizing the need for a fast and reliable access to our geomagnetic field models, we developed cloud-based application program interfaces (APIs) for NOAA's ionospheric and magnetospheric magnetic field models. In this paper we will describe the need for reliable magnetic calculators, the challenges faced in running geomagnetic field models in the cloud in real-time and the feedback from our user community. We discuss lessons learned harvesting and validating the data which powers our cloud services, as well as our strategies for maintaining near real-time service, including load-balancing, real-time monitoring, and instance cloning. We will also briefly talk about the progress we achieved on NOAA's Big Earth Data Initiative (BEDI) funded project to develop API interface to our Enhanced Magnetic Model (EMM).
[Global Atmospheric Chemistry/Transport Modeling and Data-Analysis

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

1999-01-01

This grant supported a global atmospheric chemistry/transport modeling and data- analysis project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for trace gases; (b) utilization of these inverse methods which use either the Model for Atmospheric Chemistry and Transport (MATCH) which is based on analyzed observed winds or back- trajectories calculated from these same winds for determining regional and global source and sink strengths for long-lived trace gases important in ozone depletion and the greenhouse effect; (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple "titrating" gases; and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important ultimate goals included determination of regional source strengths of important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements, and hydrohalocarbons now used as alternatives to the above restricted halocarbons.
Research advances and challenges in one-dimensional modeling of secondary settling tanks--a critical review.

PubMed

Li, Ben; Stenstrom, M K

2014-11-15

Sedimentation is one of the most important processes that determine the performance of the activated sludge process (ASP), and secondary settling tanks (SSTs) have been frequently investigated with the mathematical models for design and operation optimization. Nevertheless their performance is often far from satisfactory. The starting point of this paper is a review of the development of settling theory, focusing on batch settling and the development of flux theory, since they played an important role in the early stage of SST investigation. The second part is an explicit review of the established 1-D SST models, including the relevant physical law, various settling behaviors (hindered, transient, and compression settling), the constitutive functions, and their advantages and disadvantages. The third part is a discussion of numerical techniques required to solve the governing equation, which is usually a partial differential equation. Finally, the most important modeling challenges, such as settleability description, settling behavior understanding, are presented. Copyright © 2014 Elsevier Ltd. All rights reserved.
Interpretation of Trace Gas Data Using Inverse Methods and Global Chemical Transport Models

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

1997-01-01

This is a theoretical research project aimed at: (1) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (2) utilization of inverse methods to determine these source/sink strengths which use the NCAR/Boulder CCM2-T42 3-D model and a global 3-D Model for Atmospheric Transport and Chemistry (MATCH) which is based on analyzed observed wind fields (developed in collaboration by MIT and NCAR/Boulder), (3) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and, (4) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3-D models. Important goals include determination of regional source strengths of methane, nitrous oxide, and other climatically and chemically important biogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements and hydrohalocarbons used as alternatives to the restricted halocarbons.
A stochastic spatial model of HIV dynamics with an asymmetric battle between the virus and the immune system

NASA Astrophysics Data System (ADS)

Lin, Hai; Shuai, J. W.

2010-04-01

A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.
Response Surface Modeling of Combined-Cycle Propulsion Components using Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.

2002-01-01

Three examples of response surface modeling with CFD are presented for combined cycle propulsion components. The examples include a mixed-compression-inlet during hypersonic flight, a hydrogen-fueled scramjet combustor during hypersonic flight, and a ducted-rocket nozzle during all-rocket flight. Three different experimental strategies were examined, including full factorial, fractionated central-composite, and D-optimal with embedded Plackett-Burman designs. The response variables have been confined to integral data extracted from multidimensional CFD results. Careful attention to uncertainty assessment and modeling bias has been addressed. The importance of automating experimental setup and effectively communicating statistical results are emphasized.
[Review of dynamic global vegetation models (DGVMs)].

PubMed

Che, Ming-Liang; Chen, Bao-Zhang; Wang, Ying; Guo, Xiang-Yun

2014-01-01

Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology. Then the future research directions of DGVMs were pointed out, i. e. improving the PFT scheme, refining the vegetation dynamic mechanism, and implementing a model inter-comparison project.
A simulation model for studying the role of pre-slaughter factors on the exposure of beef carcasses to human microbial hazards.

PubMed

Jordan, D; McEwen, S A; Lammerding, A M; McNab, W B; Wilson, J B

1999-06-29

A Monte Carlo simulation model was constructed for assessing the quantity of microbial hazards deposited on cattle carcasses under different pre-slaughter management regimens. The model permits comparison of industry-wide and abattoir-based mitigation strategies and is suitable for studying pathogens such as Escherichia coli O157:H7 and Salmonella spp. Simulations are based on a hierarchical model structure that mimics important aspects of the cattle population prior to slaughter. Stochastic inputs were included so that uncertainty about important input assumptions (such as prevalence of a human pathogen in the live cattle-population) would be reflected in model output. Control options were built into the model to assess the benefit of having prior knowledge of animal or herd-of-origin pathogen status (obtained from the use of a diagnostic test). Similarly, a facility was included for assessing the benefit of re-ordering the slaughter sequence based on the extent of external faecal contamination. Model outputs were designed to evaluate the performance of an abattoir in a 1-day period and included outcomes such as the proportion of carcasses contaminated with a pathogen, the daily mean and selected percentiles of pathogen counts per carcass, and the position of the first infected animal in the slaughter run. A measure of the time rate of introduction of pathogen into the abattoir was provided by assessing the median, 5th percentile, and 95th percentile cumulative pathogen counts at 10 equidistant points within the slaughter run. Outputs can be graphically displayed as frequency distributions, probability densities, cumulative distributions or x-y plots. The model shows promise as an inexpensive method for evaluating pathogen control strategies such as those forming part of a Hazard Analysis and Critical Control Point (HACCP) system.
[On comparison of hospital performance].

PubMed

Kjekshus, L E

2000-10-20

The motivation to identify the causes of rising health care cost and variations across providers has intensified in all industrialized countries. These countries have an ongoing debate on efficiency and effectiveness in hospital production. In this debate, national and international comparative studies are important. There are very few international comparative studies that include Norwegian hospitals. Actually we know very little about how Norwegian hospitals are performing compared to others. This paper gives an introduction to comparative studies and to the DEA model which is often used in such studies and also a multilevel model which is not so common. A short review is given of a comparative study of Norwegian and North American hospitals. I also discuss the feasibility of comparative studies of hospitals from the Nordic countries, with references to several comparative studies performed in these countries. Comparative studies are often closely linked to national health politics, policy making and reforms; thus the outcome of such studies is important for the hospitals included. This makes such studies a sensitive field of research. It is important to be aware of the strength and weaknesses of comparative studies and acknowledge their importance beyond the development of new knowledge.
Key factors associated with postoperative complications in patients undergoing colorectal surgery.

PubMed

Manilich, E; Vogel, J D; Kiran, R P; Church, J M; Seyidova-Khoshknabi, Dilara; Remzi, F H

2013-01-01

Surgical outcomes are determined by complex interactions among a variety of factors including patient characteristics, diagnosis, and type of procedure. The aim of this study was to prioritize the effect and relative importance of the surgeon (in terms of identity of a surgeon and surgeon volume), patient characteristics, and the intraoperative details on complications of colorectal surgery including readmission, reoperation, sepsis, anastomotic leak, small-bowel obstruction, surgical site infection, abscess, need for transfusion, and portal and deep vein thrombosis. This study uses a novel classification methodology to measure the influence of various risk factors on postoperative complications in a large outcomes database. Using prospectively collected information from the departmental outcomes database from 2010 to 2011, we examined the records of 3552 patients who underwent colorectal surgery. Instead of traditional statistical methods, we used a family of 7000 bootstrap classification models to examine and quantify the impact of various factors on the most common serious surgical complications. For each complication, an ensemble of multivariate classification models was designed to determine the relative importance of potential factors that may influence outcomes of surgery. This is a new technique for analyzing outcomes data that produces more accurate results and a more reliable ranking of study variables in order of their importance in producing complications. Patients who underwent colorectal surgery in 2010 and 2011 were included. This study was conducted at a tertiary referral department at a major medical center. Postoperative complications were the primary outcomes measured. Factors sorted themselves into 2 groups: a highly important group (operative time, BMI, age, identity of the surgeon, type of surgery) and a group of low importance (sex, comorbidity, laparoscopy, and emergency). ASA score and diagnosis were of intermediate importance. The outcomes most influenced by variations in the highly important factors included readmission, transfusion, surgical site infection, and abscesses. This study was limited by the use of data from a single tertiary referral department at a major medical center. Body mass index, operative time, and the surgeon who performed the operation are the 3 most important factors influencing readmission rates, rates of transfusions, and surgical site infection. Identification of these contributing factors can help minimize complications.
On Subsurface Fracture Opening and Closure

NASA Astrophysics Data System (ADS)

Wang, Y.

2016-12-01

Mechanistic understanding of fracture opening and closure in geologic media is of significant importance to nature resource extraction and waste management, such as geothermal energy extraction, oil/gas production, radioactive waste disposal, and carbon sequestration and storage). A dynamic model for subsurface fracture opening and closure has been formulated. The model explicitly accounts for the stress concentration around individual aperture channels and the stress-activated mineral dissolution and precipitation. A preliminary model analysis has demonstrated the importance of the stress-activated dissolution mechanism in the evolution of fracture aperture in a stressed geologic medium. The model provides a reasonable explanation for some key features of fracture opening and closure observed in laboratory experiments, including a spontaneous switch from a net permeability reduction to a net permeability increase with no changes in a limestone fracture experiment.
Sound for Film: Audio Education for Filmmakers.

ERIC Educational Resources Information Center

Lazar, Wanda

1998-01-01

Identifies the specific, unique, and important elements of audio education required by film professionals. Presents a model unit to be included in a film studies program, either as a separate course or as part of a film production or introduction to film course. Offers a model syllabus for such a course or unit on sound in film. (SR)
Combining fire and erosion modeling to target forest management activities

Treesearch

William J. Elliot; Mary Ellen Miller; Nic Enstice

2015-01-01

Forests deliver a number of important ecosystem services including clean water. When forests are disturbed by wildfire, the timing, quantity and quality of runoff are altered. A modeling study was carried out in a forested watershed in California to determine the risk of wildfire, and the potential post-fire sediment delivery from approximately 6-ha hillslope polygons...
Targeting forest management through fire and erosion modeling

Treesearch

William J. Elliot; Mary Ellen Miller; Nic Enstice

2016-01-01

Forests deliver a number of important ecosystem services, including clean water. When forests are disturbed by wildfire, the timing, quantity and quality of runoff are altered. A modelling study was conducted in a forested watershed in California, USA, to determine the risk of wildfire, and the potential post-fire sediment delivery from ~4-ha hillslope polygons within...
User Acceptance of YouTube for Procedural Learning: An Extension of the Technology Acceptance Model

ERIC Educational Resources Information Center

Lee, Doo Young; Lehto, Mark R.

2013-01-01

The present study was framed using the Technology Acceptance Model (TAM) to identify determinants affecting behavioral intention to use YouTube. Most importantly, this research emphasizes the motives for using YouTube, which is notable given its extrinsic task goal of being used for procedural learning tasks. Our conceptual framework included two…
Vocabulary and Experiences to Develop a Center of Mass Model

ERIC Educational Resources Information Center

Kaar, Taylor; Pollack, Linda B.; Lerner, Michael E.; Engels, Robert J.

2017-01-01

The use of systems in many introductory courses is limited and often implicit. Modeling two or more objects as a system and tracking the center of mass of that system is usually not included. Thinking in terms of the center of mass facilitates problem solving while exposing the importance of using conservation laws. We present below three…

What Qualifications and Skills Are Important for Digital Librarian Positions in Academic Libraries? A Job Advertisement Analysis

ERIC Educational Resources Information Center

Choi, Youngok; Rasmussen, Edie

2009-01-01

As academic library functions and activities continue to evolve, libraries have broadened the traditional library model, which focuses on management of physical resources and activities, to include a digital library model, transforming resources and services into digital formats to support teaching, learning, and research. This transition has…
Scholarly Use of E-Books in a Virtual Academic Environment: A Case Study

ERIC Educational Resources Information Center

Ahmad, Pervaiz; Brogan, Mark

2012-01-01

From a fledgling technology with no proven business models, electronic books (e-books) have grown in importance usurping traditional formats as an acquisitions budget line in many academic library contexts. Business models include purchase, subscription, and pay per use. In academic and research libraries, web based e-book delivery is the dominant…
Boreal soil carbon dynamics under a changing climate: a model inversion approach

Treesearch

Zhaosheng Fan; Jason C. Neff; Jennifer W. Harden; Kimberly P. Wickland

2008-01-01

Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and...
Metal Ion Modeling Using Classical Mechanics

PubMed Central

2017-01-01

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems. PMID:28045509
Constitutive modeling of superalloy single crystals with verification testing

NASA Technical Reports Server (NTRS)

Jordan, Eric; Walker, Kevin P.

1985-01-01

The goal is the development of constitutive equations to describe the elevated temperature stress-strain behavior of single crystal turbine blade alloys. The program includes both the development of a suitable model and verification of the model through elevated temperature-torsion testing. A constitutive model is derived from postulated constitutive behavior on individual crystallographic slip systems. The behavior of the entire single crystal is then arrived at by summing up the slip on all the operative crystallographic slip systems. This type of formulation has a number of important advantages, including the prediction orientation dependence and the ability to directly represent the constitutive behavior in terms which metallurgists use in describing the micromechanisms. Here, the model is briefly described, followed by the experimental set-up and some experimental findings to date.
A review of telavancin activity in in vitro biofilms and animal models of biofilm-associated infections.

PubMed

Chan, Cynthia; Hardin, Thomas C; Smart, Jennifer I

2015-01-01

Tissue- and device-associated biofilm infections are important medical problems. These infections are difficult to treat due to a high-level of tolerance to antibiotics. Telavancin has been studied in several in vitro biofilm models and has demonstrated efficacy against staphylococcal and enterococcal-associated biofilm infections, including those formed by methicillin-resistant Staphylococcus aureus. Telavancin was effective against the difficult-to-treat vancomycin- and glycopeptide-intermediate strains of S. aureus in these models. Furthermore, the efficacy of telavancin has been evaluated in several biofilm-related in vivo models, including osteomyelitis, endocarditis and device-associated infections in rabbits. Overall, telavancin exhibited similar or greater efficacy than vancomycin and other comparators in these animal models and maintained activity against vancomycin-intermediate and daptomycin nonsusceptible strains of S. aureus.
Overview and Evaluation of the Community Multiscale Air ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In late 2016 or early 2017, CMAQ version 5.2 will be released. This new version of CMAQ will contain important updates from the current CMAQv5.1 modeling system, along with several instrumented versions of the model (e.g. decoupled direct method and sulfur tracking). Some specific model updates include the implementation of a new wind-blown dust treatment in CMAQv5.2, a significant improvement over the treatment in v5.1 which can severely overestimate wind-blown dust under certain conditions. Several other major updates to the modeling system include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry); the new carbon bond 6 (CB6) chemical mechanism; updates to cloud model in CMAQ; and a new lightning assimilation scheme for the WRF model which significant improves the placement and timing of convective precipitation in the WRF precipitation fields. Numerous other updates to the modeling system will also be available in v5.2.
Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

NASA Astrophysics Data System (ADS)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.
Distress and adjustment among adolescents and young adults with cancer: an empirical and conceptual review

PubMed Central

Wakefield, Claire E.

2013-01-01

Adolescents and young adults (AYAs) with cancer must simultaneously navigate the challenges associated with their cancer experience, whilst striving to achieve a number of important developmental milestones at the cusp of adulthood. The disruption caused by their cancer experience at this critical life-stage is assumed to be responsible for significant distress among AYAs living with cancer. The quality and severity of psychological outcomes among AYAs remain poorly documented, however. This review examined the existing literature on psychological outcomes among AYAs living with cancer. All psychological outcomes (both distress and positive adjustment) were included, and AYAs were included across the cancer trajectory, ranging from newly-diagnosed patients, to long-term cancer survivors. Four key research questions were addressed. Section 1 answered the question, “What is the nature and prevalence of distress (and other psychological outcomes) among AYAs living with cancer?” and documented rates of clinical distress, as well as evidence for the trajectory of this distress over time. Section 2 examined the individual, cancer/treatment-related and socio-demographic factors that have been identified as predictors of these outcomes in this existing literature. Section 3 examined current theoretical models relevant to explaining psychological outcomes among AYAs, including developmental models, socio-cognitive and family-systems models, stress-coping frameworks, and cognitive appraisal models (including trauma and meaning making models). The mechanisms implicated in each model were discussed, as was the existing evidence for each model. Converging evidence implicating the potential role of autobiographical memory and future thinking systems in how AYAs process and integrate their cancer experience into their current sense of self and future goals are highlighted. Finally, Section 4 addressed the future of psycho-oncology in understanding and conceptualizing psychological outcomes among AYAs living with cancer, by discussing recent empirical advancements in adjacent, non-oncology fields that might improve our understanding of psychological outcomes in AYAs living with cancer. Included in these were models of memory and future thinking drawn from the broader psychology literature that identify important mechanisms involved in adjustment, as well as experimental paradigms for the study of these mechanisms within analogue, non-cancer AYA samples. PMID:26835313
A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease.

PubMed

Manore, Carrie A; Hickmann, Kyle S; Hyman, James M; Foppa, Ivo M; Davis, Justin K; Wesson, Dawn M; Mores, Christopher N

2015-01-01

Mosquito-borne diseases cause significant public health burden and are widely re-emerging or emerging. Understanding, predicting, and mitigating the spread of mosquito-borne disease in diverse populations and geographies are ongoing modelling challenges. We propose a hybrid network-patch model for the spread of mosquito-borne pathogens that accounts for individual movement through mosquito habitats, extending the capabilities of existing agent-based models (ABMs) to include vector-borne diseases. The ABM are coupled with differential equations representing 'clouds' of mosquitoes in patches accounting for mosquito ecology. We adapted an ABM for humans using this method and investigated the importance of heterogeneity in pathogen spread, motivating the utility of models of individual behaviour. We observed that the final epidemic size is greater in patch models with a high risk patch frequently visited than in a homogeneous model. Our hybrid model quantifies the importance of the heterogeneity in the spread of mosquito-borne pathogens, guiding mitigation strategies.
Theoretical and methodological issues with testing the SCCT and RIASEC models: Comment on Lent, Sheu, and Brown (2010) and Lubinski (2010).

PubMed

Armstrong, Patrick Ian; Vogel, David L

2010-04-01

The current article replies to comments made by Lent, Sheu, and Brown (2010) and Lubinski (2010) regarding the study "Interpreting the Interest-Efficacy Association From a RIASEC Perspective" (Armstrong & Vogel, 2009). The comments made by Lent et al. and Lubinski highlight a number of important theoretical and methodological issues, including the process of defining and differentiating between constructs, the assumptions underlying Holland's (1959, 1997) RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, and Conventional types) model and interrelations among constructs specified in social cognitive career theory (SCCT), the importance of incremental validity for evaluating constructs, and methodological considerations when quantifying interest-efficacy correlations and for comparing models using multivariate statistical methods. On the basis of these comments and previous research on the SCCT and Holland models, we highlight the importance of considering multiple theoretical perspectives in vocational research and practice. Alternative structural models are outlined for examining the role of interests, self-efficacy, learning experiences, outcome expectations, personality, and cognitive abilities in the career choice and development process. PsycINFO Database Record (c) 2010 APA, all rights reserved.
A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063
DOE Office of Scientific and Technical Information (OSTI.GOV)

M.A. Wasiolek

Inhalation exposure pathway modeling has recently been investigated as one of the tasks of the BIOPROTA Project (BIOPROTA 2005). BIOPROTA was set up to address the key uncertainties in long term assessments of contaminant releases into the environment arising from radioactive waste disposal. Participants of this international Project include national authorities and agencies, both regulators and operators, with responsibility for achieving safe and acceptable radioactive waste management. The objective of the inhalation task was to investigate the calculation of doses arising from inhalation of particles suspended from soils within which long-lived radionuclides, particularly alpha emitters, had accumulated. It was recognizedmore » that site-specific conditions influence the choice of conceptual model and input parameter values. Therefore, one of the goals of the task was to identify the circumstances in which different processes included in specific inhalation exposure pathway models were important. This paper discusses evaluation of processes and modeling assumptions specific to the proposed repository at Yucca Mountain as compared to the typical approaches and other models developed for different assessments and project specific contexts. Inhalation of suspended particulates that originate from contaminated soil is an important exposure pathway, particularly for exposure to actinides such as uranium, neptunium and plutonium. Radionuclide accumulation in surface soil arises from irrigation of soil with contaminated water over many years. The level of radionuclide concentration in surface soil depends on the assumed duration of irrigation. Irrigation duration is one of the parameters used on biosphere models and it depends on a specific assessment context. It is one of the parameters addressed in this paper from the point of view of assessment context for the proposed repository at Yucca Mountain. The preferred model for the assessment of inhalation exposure uses atmospheric mass loading approach, which is based on the mass of airborne particulates per unit volume of air that is inhaled by the receptor. This type of model was used by the majority of the BIOPROTA inhalation task participants and is also used in the Yucca Mountain model. Although the mass loading model is conceptually straightforward, there are some considerations that need to be included when using this model. Small particles have larger surface to volume ratio than large particles and this ratio increases in inverse proportion to the particle size. This is particularly important for elements such as plutonium, which have high sorption coefficients, and thus are preferentially attached to small particles of soil. Suspended particulates originating from soil are composed of particles smaller than average soil particles and thus, on average, have larger available surface area, and consequently activity, per unit mass than that of soil. The increase of radionuclide concentration of suspended particulates compared with that of underlying soil is quantified in terms of the enhancement factor, which is included in the inhalation model for the Yucca Mountain repository. In this paper, the use of the enhancement factor in the inhalation exposure models is discussed. Then, enhancement factor values used in the Yucca Mountain model are discussed from the perspective of site-specific conditions as well as the microenvironmental approach to modeling inhalation exposure of the receptor: The receptor can spend specified time in several environments, each of them characterized by an occupancy time, suspended particulate level, enhancement factor and breathing rate. The environment where inhalation exposure is the highest is associated with the receptor being active outdoors and involved in activities that generate high levels of dust by using farm equipment, walking, or conducting other outdoor activities. I n summary, it is important to recognize that site-specific conditions play an important role in constructing conceptual and mathematical models of inhalation exposure.« less
Evaluating indices of lipid and protein content in lesser snow and Ross's geese during spring migration

USGS Publications Warehouse

Webb, Elisabeth B.; Fowler, Drew N.; Woodall, Brendan A.; Vrtiska, Mark P.

2018-01-01

Assessing nutrient stores in avian species is important for understanding the extent to which body condition influences success or failure in life‐history events. We evaluated predictive models using morphometric characteristics to estimate total body lipids (TBL) and total body protein (TBP), based on traditional proximate analyses, in spring migrating lesser snow geese (Anser caerulescens caerulescens) and Ross's geese (A. rossii). We also compared performance of our lipid model with a previously derived predictive equation for TBL developed for nesting lesser snow geese. We used external and internal measurements on 612 lesser snow and 125 Ross's geese collected during spring migration in 2015 and 2016 within the Central and Mississippi flyways to derive and evaluate predictive models. Using a validation data set, our best performing lipid model for snow geese better predicted TBL (root mean square error [RMSE] of 23.56) compared with a model derived from nesting individuals (RMSE = 48.60), suggesting the importance of season‐specific models for accurate lipid estimation. Models that included body mass and abdominal fat deposit best predicted TBL determined by proximate analysis in both species (lesser snow goose, R2 = 0.87, RMSE = 23.56: Ross's geese, R2 = 0.89, RMSE = 13.75). Models incorporating a combination of external structural measurements in addition to internal muscle and body mass best predicted protein values (R2 = 0.85, RMSE = 19.39 and R2 = 0.85, RMSE = 7.65, lesser snow and Ross's geese, respectively), but protein models including only body mass and body size were also competitive and provided extended utility to our equations for field applications. Therefore, our models indicated the importance of specimen dissection and measurement of the abdominal fat pad to provide the most accurate lipid estimates and provide alternative dissection‐free methods for estimating protein.
Understanding anode and cathode behaviour in high-pressure discharge lamps

NASA Astrophysics Data System (ADS)

Flesch, P.; Neiger, M.

2005-09-01

High-intensity discharge (HID) lamps have widespread and modern areas of application including general lighting, video/movie projection (e.g. UHP lamp), street/industrial lighting, and automotive headlight lamps (D2/xenon lamp). Even though HID lamps have been known for several decades now, the important plasma-electrode interactions are still not well understood. Because HID lamps are usually operated on ac (electrodes switch alternately from anode to cathode phase), time-dependent simulations including realistic and verified anode and cathode models are essential. Therefore, a recently published investigation of external laser heating of an electrode during anode and cathode phase in an operating HID lamp [28] provided the basis for our present paper. These measurements revealed impressive influences of the external laser heating on electrode fall voltage and electrode temperature. Fortunately, the effects are very different during anode and cathode phase. Thus, by comparing the experimental findings with results from our numerical simulations we can learn much about the principles of electrode behaviour and explain in detail the differences between anode and cathode phase. Furthermore, we can verify our model (which includes plasma column, hot plasma spots in front of the electrodes, constriction zones and near-electrode non-local thermal equilibrium-plasma as well as anode and cathode) that accounts for all relevant physical processes concerning plasma, electrodes and interactions between them. Moreover, we investigate the influence of two different notions concerning ionization and recombination in the near electrode plasma on the numerical results. This improves our physical understanding of near-electrode plasma likewise and further increases the confidence in the model under consideration. These results are important for the understanding and the further development of HID lamps which, due to their small dimensions, are often experimentally inaccessible. Thus, modelling becomes more and more important.
Caenorhabditis elegans: An Emerging Model in Biomedical and Environmental Toxicology

PubMed Central

Leung, Maxwell C. K.; Williams, Phillip L.; Benedetto, Alexandre; Au, Catherine; Helmcke, Kirsten J.; Aschner, Michael; Meyer, Joel N.

2008-01-01

The nematode Caenorhabditis elegans has emerged as an important animal model in various fields including neurobiology, developmental biology, and genetics. Characteristics of this animal model that have contributed to its success include its genetic manipulability, invariant and fully described developmental program, well-characterized genome, ease of maintenance, short and prolific life cycle, and small body size. These same features have led to an increasing use of C. elegans in toxicology, both for mechanistic studies and high-throughput screening approaches. We describe some of the research that has been carried out in the areas of neurotoxicology, genetic toxicology, and environmental toxicology, as well as high-throughput experiments with C. elegans including genome-wide screening for molecular targets of toxicity and rapid toxicity assessment for new chemicals. We argue for an increased role for C. elegans in complementing other model systems in toxicological research. PMID:18566021
Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs

NASA Astrophysics Data System (ADS)

Jayathilake, D. I.; Smith, T. J.

2017-12-01

Many watersheds of interest are confronted with insufficient data and poor process understanding. Therefore, understanding the relative importance of input data types and the impact of different qualities on model performance, parameterization, and fidelity is critically important to improving hydrologic models. In this paper, the change in model parameterization and performance are explored with respect to four different potential evapotranspiration (PET) products of varying quality. For each PET product, two widely used, conceptual rainfall-runoff models are calibrated with multiple objective functions to a sample of 20 basins included in the MOPEX data set and analyzed to understand how model behavior varied. Model results are further analyzed by classifying catchments as energy- or water-limited using the Budyko framework. The results demonstrated that model fit was largely unaffected by the quality of the PET inputs. However, model parameterizations were clearly sensitive to PET inputs, as their production parameters adjusted to counterbalance input errors. Despite this, changes in model robustness were not observed for either model across the four PET products, although robustness was affected by model structure.
Understanding the impact of relapses in the overall course of MS; refinement of the 2 stage natural history model.

PubMed

Scott, Thomas F

2017-04-15

Recent studies suggest a need for refinement of the traditional two phase model of relapse onset multiple sclerosis (RMS) to include dynamically changing subgroups within the broad category of secondary progressive MS (SPMS). These studies challenge the traditional notion that relapses play a minor role in comparison to a secondary progressive (perhaps degenerative) process. Patients fulfilling the broad definition for SPMS may take several courses, including variable rates and patterns of overall worsening. New paradigms or models for mapping the trajectory of disability in RMS and SPMS (clinical phenotyping), including periods of remission, may impact our understanding of the underlying pathology, and will be important in assessing treatments. Copyright © 2017 Elsevier B.V. All rights reserved.
Microdosimetric study for nanosecond pulsed electric fields on a cell circuit model with nucleus.

PubMed

Denzi, Agnese; Merla, Caterina; Camilleri, Paola; Paffi, Alessandra; d'Inzeo, Guglielmo; Apollonio, Francesca; Liberti, Micaela

2013-10-01

Recently, scientific interest in electric pulses, always more intense and shorter and able to induce biological effects on both plasma and nuclear membranes, has greatly increased. Hence, microdosimetric models that include internal organelles like the nucleus have assumed increasing importance. In this work, a circuit model of the cell including the nucleus is proposed, which accounts for the dielectric dispersion of all cell compartments. The setup of the dielectric model of the nucleus is of fundamental importance in determining the transmembrane potential (TMP) induced on the nuclear membrane; here, this is demonstrated by comparing results for three different sets of nuclear dielectric properties present in the literature. The results have been compared, even including or disregarding the dielectric dispersion of the nucleus. The main differences have been found when using pulses shorter than 10 ns. This is due to the fact that the high spectral components of the shortest pulses are differently taken into account by the nuclear membrane transfer functions computed with and without nuclear dielectric dispersion. The shortest pulses are also the most effective in porating the intracellular structures, as confirmed by the time courses of the TMP calculated across the plasma and nuclear membranes. We show how dispersive nucleus models are unavoidable when dealing with pulses shorter than 10 ns because of the large spectral contents arriving above 100 MHz, i.e., over the typical relaxation frequencies of the dipolar mechanism of the molecules constituting the nuclear membrane and the subcellular cell compartments.
Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing

USGS Publications Warehouse

Marshall, Michael T.; Thenkabail, Prasad S.

2015-01-01

Ground-based estimates of aboveground wet (fresh) biomass (AWB) are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H), fraction of absorbed photosynthetically active radiation (FAPAR), leaf area index (LAI), and fraction of vegetation cover (FVC). The spectral predictors included 196 hyperspectral narrowbands (HNBs) from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR); H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

Venous thromboembolism prevention guidelines for medical inpatients: mind the (implementation) gap.

PubMed

Maynard, Greg; Jenkins, Ian H; Merli, Geno J

2013-10-01

Hospital-associated nonsurgical venous thromboembolism (VTE) is an important problem addressed by new guidelines from the American College of Physicians (ACP) and American College of Chest Physicians (AT9). Narrative review and critique. Both guidelines discount asymptomatic VTE outcomes and caution against overprophylaxis, but have different methodologies and estimates of risk/benefit. Guideline complexity and lack of consensus on VTE risk assessment contribute to an implementation gap. Methods to estimate prophylaxis benefit have significant limitations because major trials included mostly screening-detected events. AT9 relies on a single Italian cohort study to conclude that those with a Padua score ≥4 have a very high VTE risk, whereas patients with a score <4 (60% of patients) have a very small risk. However, the cohort population has less comorbidity than US inpatients, and over 1% of patients with a score of 3 suffered pulmonary emboli. The ACP guideline does not endorse any risk-assessment model. AT9 includes the Padua model and Caprini point-based system for nonsurgical inpatients and surgical inpatients, respectively, but there is no evidence they are more effective than simpler risk-assessment models. New VTE prevention guidelines provide varied guidance on important issues including risk assessment. If Padua is used, a threshold of 3, as well as 4, should be considered. Simpler VTE risk-assessment models may be superior to complicated point-based models in environments without sophisticated clinical decision support. © 2013 Society of Hospital Medicine.
Heterogenous Combustion of Porous Graphite Particles in Normal and Microgravity

NASA Technical Reports Server (NTRS)

Chelliah, Harsha K.; Miller, Fletcher J.; Delisle, Andrew J.

2001-01-01

Combustion of solid fuel particles has many important applications, including power generation and space propulsion systems. The current models available for describing the combustion process of these particles, especially porous solid particles, include various simplifying approximations. One of the most limiting approximations is the lumping of the physical properties of the porous fuel with the heterogeneous chemical reaction rate constants. The primary objective of the present work is to develop a rigorous model that could decouple such physical and chemical effects from the global heterogeneous reaction rates. For the purpose of validating this model, experiments with porous graphite particles of varying sizes and porosity are being performed. The details of this experimental and theoretical model development effort are described.
Policy Implications Learning from Sociohydrological Modelling

NASA Astrophysics Data System (ADS)

Tian, F.

2016-12-01

Sociohydrology focuses on the interplays between natural variability and social activities. Policy is one of important social activities, which drives the evolution of sociohydrological system at annual to decadal scales. A conceptual sociohydrological model can be a useful tool to explore how policy functions. In this study, we developed a coupled socio-hydrological model which includes water and land policies, irrigated land area, irrigation water use and an environmental indicator.The model is used to analyze the agriculture water-conservation development during 1998—2010 in Bayinguoleng Mongol Autonomous Prefecture, Xinjiang as an example with four policy scenarios including weak irrigation land control,low irrigation land control,medium irrigation land control and strong irrigation land control to analyze how agriculture water-conservation develops with different policies.
Parental IQ and cognitive development of malnourished Indonesian children.

PubMed

Webb, K E; Horton, N J; Katz, D L

2005-04-01

A cross-sectional study of children in West Kalimantan, Indonesia, was conducted to examine the relationship between malnutrition history, child IQ, school attendance, socioeconomic status, parental education and parental IQ. In unadjusted analyses, severely stunted children had significantly lower IQ scores than mild-moderately stunted children. This effect was significant when stunting, school attendance and parental education were included in multivariable models but was attenuated when parental IQ was included. Our research underscores the importance of accounting for parental IQ as a critical covariate when modeling the association between childhood stunting and IQ.
A model for Huanglongbing spread between citrus plants including delay times and human intervention

NASA Astrophysics Data System (ADS)

Vilamiu, Raphael G. d'A.; Ternes, Sonia; Braga, Guilherme A.; Laranjeira, Francisco F.

2012-09-01

The objective of this work was to present a compartmental deterministic mathematical model for representing the dynamics of HLB disease in a citrus orchard, including delay in the disease's incubation phase in the plants, and a delay period on the nymphal stage of Diaphorina citri, the most important HLB insect vector in Brazil. Numerical simulations were performed to assess the possible impacts of human detection efficiency of symptomatic plants, as well as the influence of a long incubation period of HLB in the plant.
Acoustic Modeling of Lightweight Structures: A Literature Review

NASA Astrophysics Data System (ADS)

Yang, Shasha; Shen, Cheng

2017-10-01

This paper gives an overview of acoustic modeling for three kinds of typical lightweight structures including double-leaf plate system, stiffened single (or double) plate and porous material. Classical models are citied to provide frame work of theoretical modeling for acoustic property of lightweight structures; important research advances derived by our research group and other authors are introduced to describe the current state of art for acoustic research. Finally, remaining problems and future research directions are concluded and prospected briefly
[The emphases and basic procedures of genetic counseling in psychotherapeutic model].

PubMed

Zhang, Yuan-Zhi; Zhong, Nanbert

2006-11-01

The emphases and basic procedures of genetic counseling are all different with those in old models. In the psychotherapeutic model, genetic counseling will not only focus on counselees' genetic disorders and birth defects, but also their psychological problems. "Client-centered therapy" termed by Carl Rogers plays an important role in genetic counseling process. The basic procedures of psychotherapeutic model of genetic counseling include 7 steps: initial contact, introduction, agendas, inquiry of family history, presenting information, closing the session and follow-up.
Thermal modeling of carbon-epoxy laminates in fire environments.

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

McGurn, Matthew T.; DesJardin, Paul Edward; Dodd, Amanda B.

2010-10-01

A thermal model is developed for the response of carbon-epoxy composite laminates in fire environments. The model is based on a porous media description that includes the effects of gas transport within the laminate along with swelling. Model comparisons are conducted against the data from Quintere et al. Simulations are conducted for both coupon level and intermediate scale one-sided heating tests. Comparisons of the heat release rate (HRR) as well as the final products (mass fractions, volume percentages, porosity, etc.) are conducted. Overall, the agreement between available the data and model is excellent considering the simplified approximations to account formore » flame heat flux. A sensitivity study using a newly developed swelling model shows the importance of accounting for laminate expansion for the prediction of burnout. Excellent agreement is observed between the model and data of the final product composition that includes porosity, mass fractions and volume expansion ratio.« less
An Introduction to System-Level, Steady-State and Transient Modeling and Optimization of High-Power-Density Thermoelectric Generator Devices Made of Segmented Thermoelectric Elements

NASA Astrophysics Data System (ADS)

Crane, D. T.

2011-05-01

High-power-density, segmented, thermoelectric (TE) elements have been intimately integrated into heat exchangers, eliminating many of the loss mechanisms of conventional TE assemblies, including the ceramic electrical isolation layer. Numerical models comprising simultaneously solved, nonlinear, energy balance equations have been created to simulate these novel architectures. Both steady-state and transient models have been created in a MATLAB/Simulink environment. The models predict data from experiments in various configurations and applications over a broad range of temperature, flow, and current conditions for power produced, efficiency, and a variety of other important outputs. Using the validated models, devices and systems are optimized using advanced multiparameter optimization techniques. Devices optimized for particular steady-state operating conditions can then be dynamically simulated in a transient operating model. The transient model can simulate a variety of operating conditions including automotive and truck drive cycles.
Mentoring and role models in recruitment and retention: a study of junior medical faculty perceptions.

PubMed

Steele, Margaret M; Fisman, Sandra; Davidson, Brenda

2013-05-01

This study explored the views of junior faculty toward informing mentorship program development. Mixed sampling methodologies including questionnaires (n = 175), focus groups (female, n = 4; male, n = 4), and individual interviews (female n = 10; male, n = 9) of junior faculty were conducted in clinical departments at one academic health sciences center. Questionnaire results indicated that having role models increased commitment to an academic career; mentorship experience during residency training was a high incentive to pursue an academic career; and junior faculty did have identifiable mentorship experiences. Focus group results revealed that mentoring as well as the presence of role models a few years ahead of the junior faculty would promote career development. Females preferred similar age role models who spoke the same language, particularly in the area of promotion. Females identified several challenges and issues including a lack of researcher role models, a range of perceptions regarding the merits of formal versus informal mentoring, and the idea that mentors should provide advice on promotion and grants. Males valued advice on finances while females wanted advice on work-life balance. Mentorship emerged as an important factor in academic faculty recruitment and retention, with varying perceptions of how it should be institutionalized. Role models were viewed as important for retention, and a paucity of mid-career, female researcher role models suggests a gap to be filled in future programmatic efforts.
Modelling Short-Term Maximum Individual Exposure from Airborne Hazardous Releases in Urban Environments. Part ΙI: Validation of a Deterministic Model with Wind Tunnel Experimental Data.

PubMed

Efthimiou, George C; Bartzis, John G; Berbekar, Eva; Hertwig, Denise; Harms, Frank; Leitl, Bernd

2015-06-26

The capability to predict short-term maximum individual exposure is very important for several applications including, for example, deliberate/accidental release of hazardous substances, odour fluctuations or material flammability level exceedance. Recently, authors have proposed a simple approach relating maximum individual exposure to parameters such as the fluctuation intensity and the concentration integral time scale. In the first part of this study (Part I), the methodology was validated against field measurements, which are governed by the natural variability of atmospheric boundary conditions. In Part II of this study, an in-depth validation of the approach is performed using reference data recorded under truly stationary and well documented flow conditions. For this reason, a boundary-layer wind-tunnel experiment was used. The experimental dataset includes 196 time-resolved concentration measurements which detect the dispersion from a continuous point source within an urban model of semi-idealized complexity. The data analysis allowed the improvement of an important model parameter. The model performed very well in predicting the maximum individual exposure, presenting a factor of two of observations equal to 95%. For large time intervals, an exponential correction term has been introduced in the model based on the experimental observations. The new model is capable of predicting all time intervals giving an overall factor of two of observations equal to 100%.
A reduced-form approach for representing the impacts of wind and solar PV deployment on the structure and operation of the electricity system

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

Johnson, Nils; Strubegger, Manfred; McPherson, Madeleine

In many climate change mitigation scenarios, integrated assessment models of the energy and climate systems rely heavily on renewable energy technologies with variable and uncertain generation, such as wind and solar PV, to achieve substantial decarbonization of the electricity sector. However, these models often include very little temporal resolution and thus have difficulty in representing the integration costs that arise from mismatches between electricity supply and demand. The global integrated assessment model, MESSAGE, has been updated to explicitly model the trade-offs between variable renewable energy (VRE) deployment and its impacts on the electricity system, including the implications for electricity curtailment,more » backup capacity, and system flexibility. These impacts have been parameterized using a reduced-form approach, which allows VRE integration impacts to be quantified on a regional basis. In addition, thermoelectric technologies were updated to include two modes of operation, baseload and flexible, to better account for the cost, efficiency, and availability penalties associated with flexible operation. In this paper, the modeling approach used in MESSAGE is explained and the implications for VRE deployment in mitigation scenarios are assessed. Three important stylized facts associated with integrating high VRE shares are successfully reproduced by our modeling approach: (1) the significant reduction in the utilization of non-VRE power plants; (2) the diminishing role for traditional baseload generators, such as nuclear and coal, and the transition to more flexible technologies; and (3) the importance of electricity storage and hydrogen electrolysis in facilitating the deployment of VRE.« less
Importance of agricultural landscapes to nesting burrowing owls in the Northern Great Plains, USA

USGS Publications Warehouse

Restani, M.; Davies, J.M.; Newton, W.E.

2008-01-01

Anthropogenic habitat loss and fragmentation are the principle factors causing declines of grassland birds. Declines in burrowing owl (Athene cunicularia) populations have been extensive and have been linked to habitat loss, primarily the decline of black-tailed prairie dog (Cynomys ludovicianus) colonies. Development of habitat use models is a research priority and will aid conservation of owls inhabiting human-altered landscapes. From 2001 to 2004 we located 160 burrowing owl nests on prairie dog colonies on the Little Missouri National Grassland in North Dakota. We used multiple linear regression and Akaike's Information Criterion to estimate the relationship between cover type characteristics surrounding prairie dog colonies and (1) number of owl pairs per colony and (2) reproductive success. Models were developed for two spatial scales, within 600 m and 2,000 m radii of nests for cropland, crested wheatgrass (Agropyron cristatum), grassland, and prairie dog colonies. We also included number of patches as a metric of landscape fragmentation. Annually, fewer than 30% of prairie dog colonies were occupied by owls. None of the models at the 600 m scale explained variation in number of owl pairs or reproductive success. However, models at the 2,000 m scale did explain number of owl pairs and reproductive success. Models included cropland, crested wheatgrass, and prairie dog colonies. Grasslands were not included in any of the models and had low importance values, although percentage grassland surrounding colonies was high. Management that protects prairie dog colonies bordering cropland and crested wheatgrass should be implemented to maintain nesting habitat of burrowing owls. ?? 2008 Springer Science+Business Media B.V.
Assessing NARCCAP climate model effects using spatial confidence regions.

PubMed

French, Joshua P; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.
DigitalHuman (DH): An Integrative Mathematical Model ofHuman Physiology

NASA Technical Reports Server (NTRS)

Hester, Robert L.; Summers, Richard L.; lIescu, Radu; Esters, Joyee; Coleman, Thomas G.

2010-01-01

Mathematical models and simulation are important tools in discovering the key causal relationships governing physiological processes and improving medical intervention when physiological complexity is a central issue. We have developed a model of integrative human physiology called DigitalHuman (DH) consisting of -5000 variables modeling human physiology describing cardiovascular, renal, respiratory, endocrine, neural and metabolic physiology. Users can view time-dependent solutions and interactively introduce perturbations by altering numerical parameters to investigate new hypotheses. The variables, parameters and quantitative relationships as well as all other model details are described in XML text files. All aspects of the model, including the mathematical equations describing the physiological processes are written in XML open source, text-readable files. Model structure is based upon empirical data of physiological responses documented within the peer-reviewed literature. The model can be used to understand proposed physiological mechanisms and physiological interactions that may not be otherwise intUitively evident. Some of the current uses of this model include the analyses of renal control of blood pressure, the central role of the liver in creating and maintaining insulin resistance, and the mechanisms causing orthostatic hypotension in astronauts. Additionally the open source aspect of the modeling environment allows any investigator to add detailed descriptions of human physiology to test new concepts. The model accurately predicts both qualitative and more importantly quantitative changes in clinically and experimentally observed responses. DigitalHuman provides scientists a modeling environment to understand the complex interactions of integrative physiology. This research was supported by.NIH HL 51971, NSF EPSCoR, and NASA
A cross-national analysis of how economic inequality predicts biodiversity loss.

PubMed

Holland, Tim G; Peterson, Garry D; Gonzalez, Andrew

2009-10-01

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.
Evapotranspiration information reporting: II. Recommended documentation

USDA-ARS?s Scientific Manuscript database

Researchers and journal authors, reviewers, and readers can benefit from more complete documentation of published evapotranspiration (ET) information, including a description of field procedures, instrumentation, data filtering, model parameterization, and site review. This information is important ...
GENETICS AND POPULATION-LEVEL RISK ASSESSMENT

EPA Science Inventory

Genetic variation defines population structure and provides the mechanism for populations to adapt to novel stressors. Despite its fundamental importance in understanding populations, genetic information has been included rarely in models of population dynamics (endangered speci...
Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data

NASA Astrophysics Data System (ADS)

Karamchandani, Prakash; Long, Yoann; Pirovano, Guido; Balzarini, Alessandra; Yarwood, Greg

2017-05-01

Source apportionment modeling provides valuable information on the contributions of different source sectors and/or source regions to ozone (O3) or fine particulate matter (PM2.5) concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. The Comprehensive Air quality Model with Extensions (CAMx) offers unique source attribution tools, called the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT), which track source contributions. We present results from a CAMx source attribution modeling study for a summer month and a winter month using a recently evaluated European CAMx modeling database developed for Phase 3 of the Air Quality Model Evaluation International Initiative (AQMEII). The contributions of several source sectors (including model boundary conditions of chemical species representing transport of emissions from outside the modeling domain as well as initial conditions of these species) to O3 or PM2.5 concentrations in Europe were calculated using OSAT and PSAT, respectively. A 1-week spin-up period was used to reduce the influence of initial conditions. Evaluation focused on 16 major cities and on identifying source sectors that contributed above 5 %. Boundary conditions have a large impact on summer and winter ozone in Europe and on summer PM2.5, but they are only a minor contributor to winter PM2.5. Biogenic emissions are important for summer ozone and PM2.5. The important anthropogenic sectors for summer ozone are transportation (both on-road and non-road), energy production and conversion, and industry. In two of the 16 cities, solvent and product also contributed above 5 % to summertime ozone. For summertime PM2.5, the important anthropogenic source sectors are energy, transportation, industry, and agriculture. Residential wood combustion is an important anthropogenic sector in winter for PM2.5 over most of Europe, with larger contributions in central and eastern Europe and the Nordic cities. Other anthropogenic sectors with large contributions to wintertime PM2.5 include energy, transportation, and agriculture.
Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

Interactions between Flight Dynamics and Propulsion Systems of Air-Breathing Hypersonic Vehicles

DTIC Science & Technology

2013-01-01

coupled with combustor – Combustor, component for subsonic or supersonic combustion – Nozzle , expands flow for high thrust and may provide lift... supersonic solution method that is used for both the inlet and nozzle components. The supersonic model SAMURI is a substantial improvement over previous models...purely supersonic inviscid flow. As a result, the model is also appropriate for other applications, including the nozzle , which is important 19 Figure
Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation modelORCHIDEE - Part 1: Simulating historical global burned area and fire regimes

Treesearch

C. Yue; P. Ciais; P. Cadule; K. Thonicke; S. Archibald; B. Poulter; W. M. Hao; S. Hantson; F. Mouillot; P. Friedlingstein; F. Maignan; N. Viovy

2014-01-01

Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE...
Including resonances in the multiperipheral model

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

Pinsky, S.S.; Snider, D.R.; Thomas, G.H.

1973-10-01

A simple generalization of the multiperipheral model (MPM) and the Mueller--Regge Model (MRM) is given which has improved phenomenological capabilities by explicitly incorporating resonance phenomena, and still is simple enough to be an important theoretical laboratory. The model is discussed both with and without charge. In addition, the one channel, two channel, three channel and N channel cases are explicitly treated. Particular attention is paid to the constraints of charge conservation and positivity in the MRM. The recently proven equivalence between the MRM and MPM is extended to this model, and is used extensively. (auth)
Electromagnetic Launch Vehicle Fairing and Acoustic Blanket Model of Received Power Using FEKO

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Stanley, James E.; Wahid, Parveen F.

2011-01-01

Evaluating the impact of radio frequency transmission in vehicle fairings is important to sensitive spacecraft. This paper employees the Multilevel Fast Multipole Method (MLFMM) feature of a commercial electromagnetic tool to model the fairing electromagnetic environment in the presence of an internal transmitter. This work is an extension of the perfect electric conductor model that was used to represent the bare aluminum internal fairing cavity. This fairing model includes typical acoustic blanketing commonly used in vehicle fairings. Representative material models within FEKO were successfully used to simulate the test case.
A Comparison of One-Dimensional Hydrologic Models Using Soil Moisture Observations under Urban Irrigation in a Desert Climate

NASA Astrophysics Data System (ADS)

Volo, T. J.; Vivoni, E. R.; Martin, C. A.; Wang, Z.; Ruddell, B.

2012-12-01

Through the past several decades, rapid population growth in the arid American Southwest has dramatically changed patterns of plant-available water through municipal and residential irrigation systems that provide supplemental water to designed and managed urban landscape vegetation. Urban irrigation, including diversion of rainwater and addition of imported water, has thereby enabled the transformation of areas once covered by bare soil and low water-use, native desert plant species to large tracts of exotic, high water-use turf grass and shade trees. Despite the large percentage of residential water appropriated to irrigation purposes, models of urban hydrology often fail to include the impact that this anthropogenic input has on water, energy, and biomass conditions. This study utilizes two one-dimensional soil moisture models to examine the importance of representing different processes in a quantitative urban ecohydrology model under irrigation scenarios. Such processes include sub-daily energy fluxes, vertical redistribution of soil moisture, saturation- and infiltration-excess runoff mechanisms, seasonally variable irrigation scheduling, and soil moisture control on evapotranspiration rates. The analysis is informed by soil moisture observations from an experimental sensor network in the Phoenix, Arizona metropolitan area. The network includes data from several different landscape and irrigation treatments representative of pre- and post-development conditions in the region. By interpreting soil moisture levels in terms of plant water stress, this study analyzes the effectiveness of urban irrigation practices in arid climates. Furthermore, by identifying the necessary hydrologic processes to represent in an urban ecohydrology model, our results inform future work in adapting a distributed hydrologic model to desert urban settings where irrigation plays a significant role in minimizing plant water stress. An appropriate model of water and energy balances, calibrated using local meteorological forcing, can facilitate discussions with water managers and homeowners regarding optimal irrigation frequency, volume, duration, and seasonality for individual landscapes, while also aiding in water-efficient landscape design for growing cities in desert regions.
The relative influence of nutrients and habitat on stream metabolism in agricultural streams

USGS Publications Warehouse

Frankforter, J.D.; Weyers, H.S.; Bales, J.D.; Moran, P.W.; Calhoun, D.L.

2010-01-01

Stream metabolism was measured in 33 streams across a gradient of nutrient concentrations in four agricultural areas of the USA to determine the relative influence of nutrient concentrations and habitat on primary production (GPP) and respiration (CR-24). In conjunction with the stream metabolism estimates, water quality and algal biomass samples were collected, as was an assessment of habitat in the sampling reach. When data for all study areas were combined, there were no statistically significant relations between gross primary production or community respiration and any of the independent variables. However, significant regression models were developed for three study areas for GPP (r 2 = 0.79-0.91) and CR-24 (r 2 = 0.76-0.77). Various forms of nutrients (total phosphorus and area-weighted total nitrogen loading) were significant for predicting GPP in two study areas, with habitat variables important in seven significant models. Important physical variables included light availability, precipitation, basin area, and in-stream habitat cover. Both benthic and seston chlorophyll were not found to be important explanatory variables in any of the models; however, benthic ash-free dry weight was important in two models for GPP. ?? 2009 The Author(s).
Anticancer activity of seaweeds.

PubMed

Gutiérrez-Rodríguez, Anllely G; Juárez-Portilla, Claudia; Olivares-Bañuelos, Tatiana; Zepeda, Rossana C

2018-02-01

Cancer is a major health problem worldwide and still lacks fully effective treatments. Therefore, alternative therapies, using natural products, have been proposed. Marine algae are an important component of the marine environment, with high biodiversity, and contain a huge number of functional compounds, including terpenes, polyphenols, phlorotannins, and polysaccharides, among others. These compounds have complex structures that have shown several biological activities, including anticancer activity, using in vitro and in vivo models. Moreover, seaweed-derived compounds target important molecules that regulate cancer processes. Here, we review our current understanding of the anticancer activity of seaweeds. Copyright © 2017 Elsevier Ltd. All rights reserved.
Impacts of increasing the aerosol complexity in the Met Office global NWP model

NASA Astrophysics Data System (ADS)

Mulcahy, Jane; Walters, David; Bellouin, Nicolas; Milton, Sean

2014-05-01

Inclusion of the direct and indirect radiative effects of aerosols in high resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing longwave radiation over West Africa due to a better representation of dust. Inclusion of the indirect aerosol effects has significant impacts on the SW radiation particularly at high latitudes due to lower cloud amounts in high latitude clean air regions. This leads to improved surface radiation biases at the North Slope of Alaska ARM site. Verification of temperature and height forecasts is also improved in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short range forecasts. However, the indirect aerosol effect leads to a strengthening of the low level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. This study highlights the importance of including a more realistic treatment of aerosol-cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.
Cost-benefit analysis model of badger (Meles meles) culling to reduce cattle herd tuberculosis breakdowns in Britain, with particular reference to badger perturbation.

PubMed

Wilkinson, D; Bennett, R; McFarlane, I; Rushton, S; Shirley, M; Smith, G C

2009-10-01

Bovine tuberculosis (TB) is an important economic disease. Badgers (Meles meles) are the wildlife source implicated in many cattle outbreaks of TB in Britain, and extensive badger control is a controversial option to reduce the disease. A badger and cattle population model was developed, simulating TB epidemiology; badger ecology, including postcull social perturbation; and TB-related farm management. An economic cost-benefit module was integrated into the model to assess whether badger control offers economic benefits. Model results strongly indicate that although, if perturbation were restricted, extensive badger culling could reduce rates in cattle, overall an economic loss would be more likely than a benefit. Perturbation of the badger population was a key factor determining success or failure of control. The model highlighted some important knowledge gaps regarding both the spatial and temporal characteristics of perturbation that warrant further research.
Silkworm: A Promising Model Organism in Life Science.

PubMed

Meng, Xu; Zhu, Feifei; Chen, Keping

2017-09-01

As an important economic insect, silkworm Bombyx mori (L.) (Lepidoptera: Bombycidae) has numerous advantages in life science, such as low breeding cost, large progeny size, short generation time, and clear genetic background. Additionally, there are rich genetic resources associated with silkworms. The completion of the silkworm genome has further accelerated it to be a modern model organism in life science. Genomic studies showed that some silkworm genes are highly homologous to certain genes related to human hereditary disease and, therefore, are a candidate model for studying human disease. In this article, we provided a review of silkworm as an important model in various research areas, including human disease, screening of antimicrobial agents, environmental safety monitoring, and antitumor studies. In addition, the application potentiality of silkworm model in life sciences was discussed. © The Author 2017. Published by Oxford University Press on behalf of Entomological Society of America.
Some guidance on preparing validation plans for the DART Full System Models.

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

Gray, Genetha Anne; Hough, Patricia Diane; Hills, Richard Guy

2009-03-01

Planning is an important part of computational model verification and validation (V&V) and the requisite planning document is vital for effectively executing the plan. The document provides a means of communicating intent to the typically large group of people, from program management to analysts to test engineers, who must work together to complete the validation activities. This report provides guidelines for writing a validation plan. It describes the components of such a plan and includes important references and resources. While the initial target audience is the DART Full System Model teams in the nuclear weapons program, the guidelines are generallymore » applicable to other modeling efforts. Our goal in writing this document is to provide a framework for consistency in validation plans across weapon systems, different types of models, and different scenarios. Specific details contained in any given validation plan will vary according to application requirements and available resources.« less
Codigestion of solid wastes: a review of its uses and perspectives including modeling.

PubMed

Mata-Alvarez, Joan; Dosta, Joan; Macé, Sandra; Astals, Sergi

2011-06-01

The last two years have witnessed a dramatic increase in the number of papers published on the subject of codigestion, highlighting the relevance of this topic within anaerobic digestion research. Consequently, it seems appropriate to undertake a review of codigestion practices starting from the late 1970s, when the first papers related to this concept were published, and continuing to the present day, demonstrating the exponential growth in the interest shown in this approach in recent years. Following a general analysis of the situation, state-of-the-art codigestion is described, focusing on the two most important areas as regards publication: codigestion involving sewage sludge and the organic fraction of municipal solid waste (including a review of the secondary advantages for wastewater treatment plant related to biological nutrient removal), and codigestion in the agricultural sector, that is, including agricultural - farm wastes, and energy crops. Within these areas, a large number of oversized digesters appear which can be used to codigest other substrates, resulting in economic and environmental advantages. Although the situation may be changing, there is still a need for good examples on an industrial scale, particularly with regard to wastewater treatment plants, in order to extend this beneficial practice. In the last section, a detailed analysis of papers addressing the important aspect of modelisation is included. This analysis includes the first codigestion models to be developed as well as recent applications of the standardised anaerobic digestion model ADM1 to codigestion. (This review includes studies ranging from laboratory to industrial scale.).
Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

NASA Astrophysics Data System (ADS)

O'Hagan, Joseph J.; Samani, Abbas

2009-04-01

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C11 showing the most significant difference. Furthermore, statistical analysis indicates that C02 of the Yeoh model, and C11 and C20 of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.
The impact of lianas on the carbon cycle of tropical forests: a modeling study using the Ecosystem Demography model

NASA Astrophysics Data System (ADS)

di Porcia e Brugnera, M.; Longo, M.; Verbeek, H.

2017-12-01

Lianas are an important component of tropical forests, constituting up to 40% of the woody stems and about 35% of the woody species. Tropical forests have been experiencing large-scale structural changes, including an increase in liana abundance and biomass. This may eventually reduce the projected carbon sink of tropical forests. Despite their crucial role no single terrestrial ecosystem model has included lianas so far. Here, we present the very first implementation of lianas in the Ecosystem Demography model (ED2). ED2 is able to represent the competition for water and light between different vegetation types at the regional level. Our new implementation of ED2 is hence suitable to address important questions such as the impact of lianas on the tropical forest carbon balance. We validated the model against forest inventory and eddy covariance flux data at a dry seasonal site (Barro Colorado Island, Panama), and at a wet rainforest site (Paracou, French Guiana). The model was able to represent size structure and carbon accumulation rates. We also evaluated the impact of the unique allocation strategy of lianas on their competitive ability. Lianas invest only a small fraction of their carbon for structural tissues when compared to trees. As a result, lianas benefit from an extra amount of available carbon, however the trade-offs of low allocation on structural tissues are not yet well understood. We are currently investigating a number of hypotheses, including the possibility for lianas to have high turnover rates for leaves and fine roots, or to have high mortality rates due to the loss of structural support when trees die. As such our model allows us to get a better understanding of the role of lianas in the tropical forest carbon cycle.
Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.
Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529
The use of typed lambda calculus for comprehension and construction of simulation models in the domain of ecology

NASA Technical Reports Server (NTRS)

Uschold, Michael

1992-01-01

We are concerned with two important issues in simulation modelling: model comprehension and model construction. Model comprehension is limited because many important choices taken during the modelling process are not documented. This makes it difficult for models to be modified or used by others. A key factor hindering model construction is the vast modelling search space which must be navigated. This is exacerbated by the fact that many modellers are unfamiliar with the terms and concepts catered to by current tools. The root of both problems is the lack of facilities for representing or reasoning about domain concepts in current simulation technology. The basis for our achievements in both of these areas is the development of a language with two distinct levels; one for representing domain information, and the other for representing the simulation model. Of equal importance, is the fact that we make formal connections between these two levels. The domain we are concerned with is ecological modelling. This language, called Elklogic, is based on the typed lambda calculus. Important features include a rich type structure, the use of various higher order functions, and semantics. This enables complex expressions to be constructed from relatively few primitives. The meaning of each expression can be determined in terms of the domain, the simulation model, or the relationship between the two. We describe a novel representation for sets and substructure, and a variety of other general concepts that are especially useful in the ecological domain. We use the type structure in a novel way: for controlling the modelling search space, rather than a proof search space. We facilitate model comprehension by representing modelling decisions that are embodied in the simulation model. We represent the simulation model separately from, but in terms of a domain mode. The explicit links between the two models constitute the modelling decisions. The semantics of Elklogic enables English text to be generated to explain the simulation model in domain terms.
Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.
A 15 year legacy of cloud and atmosphere observations in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shupe, M.

2012-12-01

For the past 15 years, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program has operated the North Slope of Alaska (NSA) atmospheric observatory in Barrow, Alaska. Barrow offers many valuable perspectives on the Arctic environment that complement observations at lower latitudes. Unique features of the Arctic region include cold and dry atmospheric conditions, strong annual variability in sun light, a seasonally high-reflective surface, and persistent clouds that involve mixed-phase processes. ARM's ultimate objective with its flagship observatory at the northernmost point in U.S. territory is to provide measurements that can be used to improve the understanding of these atmospheric physical and radiative properties and processes such that they can be better represented in climate models. The NSA is the most detailed and long-lasting cloud-radiation-atmosphere observatory in the Arctic, providing continuous, sophisticated measurements of climate-relevant parameters. Instrument suites include active radars and lidars at various frequencies, passive radiometers monitoring radiation in microwave, infrared, visible and ultraviolet wavelengths, meteorological towers, and sounding systems. Together these measurements are used to characterize many of the important properties of clouds, aerosols, atmospheric radiation, dynamics, thermodynamics, and the surface. The coordinated nature of these measurements offers important multi-dimensional insight into many fundamental processes linking these different elements of the climate system. Moreover, the continuous operations of the facility support these observations over the full diurnal cycle and in all seasons of the year. This presentation will highlight a number of important studies and key findings that have been facilitated by the NSA observations during the first 15 years in operation. Some of these include: a thorough documentation of clouds, their occurrence frequency, phase, microphysical properties, and impacts on surface radiation; the indirect effect of aerosols on the surface longwave radiative effects of Arctic clouds; improved measurements of low amounts of atmospheric water vapor and their impacts on atmospheric radiation; dynamical and microphysical processes that are responsible for long-lived Arctic stratiform clouds; evaluation of satellite observations in extreme and observationally-difficult regimes; and assessment of model performance for models ranging from very high resolution to climate model simulations in the Arctic. The observational legacy at Barrow continues as ARM works to expand and enhance its impact. Plans are underway to install observational capabilities at a sister location in Oliktok Point to the east of Barrow, including enhanced capabilities of tethered balloon profiling and flying unmanned aerial vehicles over the adjacent Arctic Ocean. A new set of scanning cloud and precipitation radars have recently come online at Barrow that will allow for new insights on the spatial context of measurements at Barrow, including important information on the variability of atmospheric processes associated with the coastline. And lastly, there are many opportunities for the intensive observations at Barrow to inform important regional research on permafrost and sea-ice loss, while also serving as an unmatched, long-term record for evaluating atmospheric processes in regional and global climate models.
Intrinsic and extrinsic influences on children's acceptance of new foods.

PubMed

Blissett, Jackie; Fogel, Anna

2013-09-10

The foods that tend to be rejected by children include those which may have greatest importance for later health. This paper reviews some of the intrinsic and extrinsic influences on preschool children's eating behavior, with particular reference to their acceptance of new foods into their diet. Factors conceptualized as intrinsic to the child in this review include sensory processing, taste perception, neophobia, and temperament. The important extrinsic determinants of children's food acceptance which are reviewed include parental and peer modeling, the family food environment, infant feeding practices including breastfeeding and age at weaning, concurrent feeding practices including restriction, pressure to eat, prompting and reward, and the taste & energy content of foods. Children's willingness to accept new foods is influenced by a wide range of factors that likely have individual and also interactive effects on children's willingness to taste, and then continue to eat, new foods. The literature lacks longitudinal and experimental studies, which will be particularly important in determining interventions most likely to be effective in facilitating children's acceptance of healthy foods. Copyright © 2013 Elsevier Inc. All rights reserved.

Theory of Planned Behavior including self-stigma and perceived barriers explain help-seeking behavior for sexual problems in Iranian women suffering from epilepsy.

PubMed

Lin, Chung-Ying; Oveisi, Sonia; Burri, Andrea; Pakpour, Amir H

2017-03-01

To apply the Theory of Planned Behavior (TPB) and the two additional concepts self-stigma and perceived barriers to the help-seeking behavior for sexual problems in women with epilepsy. In this 18-month follow-up study, TPB elements, including attitude, subjective norm, perceived behavioral control, and behavioral intention along with self-stigma and perceived barriers in seeking help for sexual problems were assessed in n=818 women with epilepsy (94.0% aged ≤40years). The basic TPB model (model 1) and the TPB model additionally including self-stigma and perceived barriers (Model 2) were analyzed using structural equation modeling (SEM). Both SEM models showed satisfactory model fits. According to model, attitude, subjective norms, perceived behavioral control, and intention explained 63.1% of the variance in help-seeking behavior. Variance was slightly higher (64.5%) when including self-stigma and perceived barriers (model 2). In addition, the fit indices of the models were better highlighting the importance of self-stigma and perceived barriers in help-seeking behavior for sexual problems. Theory of Planned Behavior is useful in explaining help-seeking behavior for sexual problems in women with epilepsy. Self-stigma and perceived barriers are additional factors that should be considered in future interventions aiming to adopt TPB to improve help-seeking behavior for sexual problems. Copyright © 2017 Elsevier Inc. All rights reserved.
Regional impacts of iron-light colimitation in a global biogeochemical model

NASA Astrophysics Data System (ADS)

Galbraith, E. D.; Gnanadesikan, A.; Dunne, J. P.; Hiscock, M. R.

2009-07-01

Laboratory and field studies have revealed that iron has multiple roles in phytoplankton physiology, with particular importance for light-harvesting cellular machinery. However, although iron-limitation is explicitly included in numerous biogeochemical/ecosystem models, its implementation varies, and its effect on the efficiency of light harvesting is often ignored. Given the complexity of the ocean environment, it is difficult to predict the consequences of applying different iron limitation schemes. Here we explore the interaction of iron and nutrient cycles using a new, streamlined model of ocean biogeochemistry. Building on previously published parameterizations of photoadaptation and export production, the Biogeochemistry with Light Iron Nutrients and Gasses (BLING) model is constructed with only three explicit tracers but including macronutrient and micronutrient limitation, light limitation, and an implicit treatment of community structure. The structural simplicity of this computationally inexpensive model allows us to clearly isolate the global effects of iron availability on maximum light-saturated photosynthesis rates from those of photosynthetic efficiency. We find that the effect on light-saturated photosynthesis rates is dominant, negating the importance of photosynthetic efficiency in most regions, especially the cold waters of the Southern Ocean. The primary exceptions to this occur in iron-rich regions of the Northern Hemisphere, where high light-saturated photosynthesis rates cause photosynthetic efficiency to play a more important role. Additionally, we speculate that the small phytoplankton dominating iron-limited regions tend to have relatively high photosynthetic efficiency, such that iron-limitation has less of a deleterious effect on growth rates than would be expected from short-term iron addition experiments.
Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis.

PubMed

Knerer, Gerhart; Currie, Christine S M; Brailsford, Sally C

2015-06-01

Dengue fever is a vector-borne disease prevalent in tropical and subtropical regions. It is an important public health problem with a considerable and often under-valued disease burden in terms of frequency, cost and quality-of-life. Recent literature reviews have documented the development of mathematical models of dengue fever both to identify important characteristics for future model development as well as to assess the impact of dengue control interventions. Such reviews highlight the importance of short-term cross-protection; antibody-dependent enhancement; and seasonality (in terms of both favourable and unfavourable conditions for mosquitoes). The compartmental model extends work by Bartley (2002) and combines the following factors: seasonality, age-structure, consecutive infection by all four serotypes, cross-protection and immune enhancement, as well as combined vector-host transmission. The model is used to represent dengue transmission dynamics using parameters appropriate for Thailand and to assess the potential impact of combined vector-control and vaccination strategies including routine and catch-up vaccination strategies on disease dynamics. When seasonality and temporary cross-protection between serotypes are included, the model is able to approximate the observed incidence of dengue fever in Thailand. We find vaccination to be the most effective single intervention, albeit with imperfect efficacy (30.2 %) and limited duration of protection. However, in combination, control interventions and vaccination exhibit a marked impact on dengue fever transmission. This study shows that an imperfect vaccine can be a useful weapon in reducing disease spread within the community, although it will be most effective when promoted as one of several strategies for combating dengue fever transmission.
Modeling coupled Thermo-Hydro-Mechanical processes including plastic deformation in geological porous media

NASA Astrophysics Data System (ADS)

Kelkar, S.; Karra, S.; Pawar, R. J.; Zyvoloski, G.

2012-12-01

There has been an increasing interest in the recent years in developing computational tools for analyzing coupled thermal, hydrological and mechanical (THM) processes that occur in geological porous media. This is mainly due to their importance in applications including carbon sequestration, enhanced geothermal systems, oil and gas production from unconventional sources, degradation of Arctic permafrost, and nuclear waste isolation. Large changes in pressures, temperatures and saturation can result due to injection/withdrawal of fluids or emplaced heat sources. These can potentially lead to large changes in the fluid flow and mechanical behavior of the formation, including shear and tensile failure on pre-existing or induced fractures and the associated permeability changes. Due to this, plastic deformation and large changes in material properties such as permeability and porosity can be expected to play an important role in these processes. We describe a general purpose computational code FEHM that has been developed for the purpose of modeling coupled THM processes during multi-phase fluid flow and transport in fractured porous media. The code uses a continuum mechanics approach, based on control volume - finite element method. It is designed to address spatial scales on the order of tens of centimeters to tens of kilometers. While large deformations are important in many situations, we have adapted the small strain formulation as useful insight can be obtained in many problems of practical interest with this approach while remaining computationally manageable. Nonlinearities in the equations and the material properties are handled using a full Jacobian Newton-Raphson technique. Stress-strain relationships are assumed to follow linear elastic/plastic behavior. The code incorporates several plasticity models such as von Mises, Drucker-Prager, and also a large suite of models for coupling flow and mechanical deformation via permeability and stresses/deformations. In this work we present several example applications of such models.
Carnivore Translocations and Conservation: Insights from Population Models and Field Data for Fishers (Martes pennanti)

PubMed Central

Lewis, Jeffrey C.; Powell, Roger A.; Zielinski, William J.

2012-01-01

Translocations are frequently used to restore extirpated carnivore populations. Understanding the factors that influence translocation success is important because carnivore translocations can be time consuming, expensive, and controversial. Using population viability software, we modeled reintroductions of the fisher, a candidate for endangered or threatened status in the Pacific states of the US. Our model predicts that the most important factor influencing successful re-establishment of a fisher population is the number of adult females reintroduced (provided some males are also released). Data from 38 translocations of fishers in North America, including 30 reintroductions, 5 augmentations and 3 introductions, show that the number of females released was, indeed, a good predictor of success but that the number of males released, geographic region and proximity of the source population to the release site were also important predictors. The contradiction between model and data regarding males may relate to the assumption in the model that all males are equally good breeders. We hypothesize that many males may need to be released to insure a sufficient number of good breeders are included, probably large males. Seventy-seven percent of reintroductions with known outcomes (success or failure) succeeded; all 5 augmentations succeeded; but none of the 3 introductions succeeded. Reintroductions were instrumental in reestablishing fisher populations within their historical range and expanding the range from its most-contracted state (43% of the historical range) to its current state (68% of the historical range). To increase the likelihood of translocation success, we recommend that managers: 1) release as many fishers as possible, 2) release more females than males (55–60% females) when possible, 3) release as many adults as possible, especially large males, 4) release fishers from a nearby source population, 5) conduct a formal feasibility assessment, and 6) develop a comprehensive implementation plan that includes an active monitoring program. PMID:22479336
Importance of Foliar Nitrogen Concentration to Predict Forest Productivity in the Mid-Atlantic Region

Treesearch

Yude Pan; John Hom; Jennifer Jenkins; Richard Birdsey

2004-01-01

To assess what difference it might make to include spatially defined estimates of foliar nitrogen in the regional application of a forest ecosystem model (PnET-II), we composed model predictions of wood production from extensive ground-based forest inventory analysis data across the Mid-Atlantic region. Spatial variation in foliar N concentration was assigned based on...
The Influence of Engineers' Training Models on Ethics and Civic Education Component in Engineering Courses in Portugal

ERIC Educational Resources Information Center

Monteiro, Fátima; Leite, Carlinda; Rocha, Cristina

2017-01-01

The recognition of the need and importance of including ethical and civic education in engineering courses, as well as the training profile on ethical issues, relies heavily on the engineer's concept and the perception of the engineering action. These views are strongly related to the different engineer education model conceptions and its…
Watershed-scale evaluation of the Water Erosion Prediction Project (WEPP) model in the Lake Tahoe basin

Treesearch

Erin S. Brooks; Mariana Dobre; William J. Elliot; Joan Q. Wu; Jan Boll

2016-01-01

Forest managers need methods to evaluate the impacts of management at the watershed scale. The Water Erosion Prediction Project (WEPP) has the ability to model disturbed forested hillslopes, but has difficulty addressing some of the critical processes that are important at a watershed scale, including baseflow and water yield. In order to apply WEPP to...
A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Treesearch

LaWen T. Hollingsworth; Laurie L. Kurth; Bernard R. Parresol; Roger D. Ottmar; Susan J. Prichard

2012-01-01

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation...
Roads in landscape modeling: a case study of a road data layer and use in the interior northwest landscape analysis system.

Treesearch

Marti Aitken; Jane L. Hayes

2006-01-01

Roads are important ecological features of forest landscapes, but their cause-and effect relationships with other ecosystem components are only recently becoming included in integrated landscape analyses. Simulation models can help us to understand how forested landscapes respond over time to disturbance and socioeconomic factors, and potentially to address the...
Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The
The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species

Treesearch

Keith B. Aubry; Catherine M. Raley; Kevin S. McKelvey

2017-01-01

The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated...
Skeletal maturity determination from hand radiograph by model-based analysis

NASA Astrophysics Data System (ADS)

Vogelsang, Frank; Kohnen, Michael; Schneider, Hansgerd; Weiler, Frank; Kilbinger, Markus W.; Wein, Berthold B.; Guenther, Rolf W.

2000-06-01

Derived from a model based segmentation algorithm for hand radiographs proposed in our former work we now present a method to determine skeletal maturity by an automated analysis of regions of interest (ROI). These ROIs including the epiphyseal and carpal bones, which are most important for skeletal maturity determination, can be extracted out of the radiograph by knowledge based algorithms.
Do the Teacher and School Factors of the Dynamic Model Affect High- and Low-Achieving Student Groups to the Same Extent? A Cross-Country Study

ERIC Educational Resources Information Center

Vanlaar, Gudrun; Kyriakides, Leonidas; Panayiotou, Anastasia; Vandecandelaere, Machteld; McMahon, Léan; De Fraine, Bieke; Van Damme, Jan

2016-01-01

Background: The dynamic model of educational effectiveness (DMEE) is a comprehensive theoretical framework including factors that are important for school learning, based on consistent findings within educational effectiveness research. Purpose: This study investigates the impact of teacher and school factors of DMEE on mathematics and science…
Policy Capturing with Local Models: The Application of the AID technique in Modeling Judgment

DTIC Science & Technology

1972-12-01

or coding phases have upon the derived policy modelo . Particularly important aspects of these subtasks include: 1) Initial identification and coding of...in o c building pJha~sed a.ird the 1 50 a ~pli- atuls f the cr osi - vuljdatiof po[pulationl. Th.is iiicreasv iii aitr ilvatabl to Lxo ba sic fa ctu r
Modelling indirect interactions during failure spreading in a project activity network.

PubMed

Ellinas, Christos

2018-03-12

Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of 'hidden influentials' in large-scale spreading events, and evaluate the role of direct and subsequent exposure in their emergence. Given the evidence of the importance of subsequent exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.
Genetically engineered mouse models and human osteosarcoma

PubMed Central

2012-01-01

Osteosarcoma is the most common form of bone cancer. Pivotal insight into the genes involved in human osteosarcoma has been provided by the study of rare familial cancer predisposition syndromes. Three kindreds stand out as predisposing to the development of osteosarcoma: Li-Fraumeni syndrome, familial retinoblastoma and RecQ helicase disorders, which include Rothmund-Thomson Syndrome in particular. These disorders have highlighted the important roles of P53 and RB respectively, in the development of osteosarcoma. The association of OS with RECQL4 mutations is apparent but the relevance of this to OS is uncertain as mutations in RECQL4 are not found in sporadic OS. Application of the knowledge or mutations of P53 and RB in familial and sporadic OS has enabled the development of tractable, highly penetrant murine models of OS. These models share many of the cardinal features associated with human osteosarcoma including, importantly, a high incidence of spontaneous metastasis. The recent development of these models has been a significant advance for efforts to improve our understanding of the genetics of human OS and, more critically, to provide a high-throughput genetically modifiable platform for preclinical evaluation of new therapeutics. PMID:23036272
Iterative Methods to Solve Linear RF Fields in Hot Plasma

NASA Astrophysics Data System (ADS)

Spencer, Joseph; Svidzinski, Vladimir; Evstatiev, Evstati; Galkin, Sergei; Kim, Jin-Soo

2014-10-01

Most magnetic plasma confinement devices use radio frequency (RF) waves for current drive and/or heating. Numerical modeling of RF fields is an important part of performance analysis of such devices and a predictive tool aiding design and development of future devices. Prior attempts at this modeling have mostly used direct solvers to solve the formulated linear equations. Full wave modeling of RF fields in hot plasma with 3D nonuniformities is mostly prohibited, with memory demands of a direct solver placing a significant limitation on spatial resolution. Iterative methods can significantly increase spatial resolution. We explore the feasibility of using iterative methods in 3D full wave modeling. The linear wave equation is formulated using two approaches: for cold plasmas the local cold plasma dielectric tensor is used (resolving resonances by particle collisions), while for hot plasmas the conductivity kernel (which includes a nonlocal dielectric response) is calculated by integrating along test particle orbits. The wave equation is discretized using a finite difference approach. The initial guess is important in iterative methods, and we examine different initial guesses including the solution to the cold plasma wave equation. Work is supported by the U.S. DOE SBIR program.
PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections.

PubMed

Gillman, Ashley; Smith, Jye; Thomas, Paul; Rose, Stephen; Dowson, Nicholas

2017-12-01

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment. © 2017 American Association of Physicists in Medicine.
Epidemiological Implications of Host Biodiversity and Vector Biology: Key Insights from Simple Models.

PubMed

Dobson, Andrew D M; Auld, Stuart K J R

2016-04-01

Models used to investigate the relationship between biodiversity change and vector-borne disease risk often do not explicitly include the vector; they instead rely on a frequency-dependent transmission function to represent vector dynamics. However, differences between classes of vector (e.g., ticks and insects) can cause discrepancies in epidemiological responses to environmental change. Using a pair of disease models (mosquito- and tick-borne), we simulated substitutive and additive biodiversity change (where noncompetent hosts replaced or were added to competent hosts, respectively), while considering different relationships between vector and host densities. We found important differences between classes of vector, including an increased likelihood of amplified disease risk under additive biodiversity change in mosquito models, driven by higher vector biting rates. We also draw attention to more general phenomena, such as a negative relationship between initial infection prevalence in vectors and likelihood of dilution, and the potential for a rise in density of infected vectors to occur simultaneously with a decline in proportion of infected hosts. This has important implications; the density of infected vectors is the most valid metric for primarily zoonotic infections, while the proportion of infected hosts is more relevant for infections where humans are a primary host.

An Earth-Based Model of Microgravity Pulmonary Physiology

NASA Technical Reports Server (NTRS)

Hirschl, Ronald B.; Bull, Joseph L.; Grothberg, James B.

2004-01-01

There are currently only two practical methods of achieving micro G for experimentation: parabolic flight in an aircraft or space flight, both of which have limitations. As a result, there are many important aspects of pulmonary physiology that have not been investigated in micro G. We propose to develop an earth-based animal model of micro G by using liquid ventilation, which will allow us to fill the lungs with perfluorocarbon, and submersing the animal in water such that the density of the lungs is the same as the surrounding environment. By so doing, we will eliminate the effects of gravity on respiration. We will first validate the model by comparing measures of pulmonary physiology, including cardiac output, central venous pressures, lung volumes, and pulmonary mechanics, to previous space flight and parabolic flight measurements. After validating the model, we will investigate the impact of micro G on aspects of lung physiology that have not been previously measured. These will include pulmonary blood flow distribution, ventilation distribution, pulmonary capillary wedge pressure, ventilation-perfusion matching, and pleural pressures and flows. We expect that this earth-based model of micro G will enhance our knowledge and understanding of lung physiology in space which will increase in importance as space flights increase in time and distance.
Through their eyes: The influence of social models on attention and memory in capuchin monkeys (Sapajus apella).

PubMed

Howard, Lauren H; Festa, Cassandra; Lonsdorf, Elizabeth V

2018-05-01

The ability to learn socially is of critical importance across a wide variety of species, as it allows knowledge to be passed quickly among individuals without the need of time-consuming trial-and-error learning. Among primates, social learning research has been particularly focused on foraging tasks, including transmission dynamics and the demonstration characteristics that appear to support social learning. Less work has focused on the attentional salience of the information being viewed, especially in New World monkeys. We used a noninvasive eye-tracking paradigm previously used in human infants and great apes to examine the salience of social modeling for memory in capuchin monkeys. Like human infants and apes, capuchins were significantly more likely to remember an event that included a social model as opposed to a nonsocial model. This article provides some of the first evidence that capuchin memory is altered by the presence of a social model and presents a novel method for assessing cognitive capabilities in this species. Whether this "social memory bias" is shared across the primate order, or is present only in taxa that regularly rely on social information, is an important avenue for future research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
A Unified Framework Integrating Parent-of-Origin Effects for Association Study

PubMed Central

Xiao, Feifei; Ma, Jianzhong; Amos, Christopher I.

2013-01-01

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits. PMID:23991061
A strand graph semantics for DNA-based computation

PubMed Central

Petersen, Rasmus L.; Lakin, Matthew R.; Phillips, Andrew

2015-01-01

DNA nanotechnology is a promising approach for engineering computation at the nanoscale, with potential applications in biofabrication and intelligent nanomedicine. DNA strand displacement is a general strategy for implementing a broad range of nanoscale computations, including any computation that can be expressed as a chemical reaction network. Modelling and analysis of DNA strand displacement systems is an important part of the design process, prior to experimental realisation. As experimental techniques improve, it is important for modelling languages to keep pace with the complexity of structures that can be realised experimentally. In this paper we present a process calculus for modelling DNA strand displacement computations involving rich secondary structures, including DNA branches and loops. We prove that our calculus is also sufficiently expressive to model previous work on non-branching structures, and propose a mapping from our calculus to a canonical strand graph representation, in which vertices represent DNA strands, ordered sites represent domains, and edges between sites represent bonds between domains. We define interactions between strands by means of strand graph rewriting, and prove the correspondence between the process calculus and strand graph behaviours. Finally, we propose a mapping from strand graphs to an efficient implementation, which we use to perform modelling and simulation of DNA strand displacement systems with rich secondary structure. PMID:27293306
Automated adaptive inference of phenomenological dynamical models

NASA Astrophysics Data System (ADS)

Daniels, Bryan

Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.
Numerical Simulations of Supernova Remnant Evolution in a Cloudy Interstellar Medium

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

Slavin, Jonathan D.; Smith, Randall K.; Foster, Adam

The mixed morphology class of supernova remnants has centrally peaked X-ray emission along with a shell-like morphology in radio emission. White and Long proposed that these remnants are evolving in a cloudy medium wherein the clouds are evaporated via thermal conduction once being overrun by the expanding shock. Their analytical model made detailed predictions regarding temperature, density, and emission profiles as well as shock evolution. We present numerical hydrodynamical models in 2D and 3D including thermal conduction, testing the White and Long model and presenting results for the evolution and emission from remnants evolving in a cloudy medium. We findmore » that, while certain general results of the White and Long model hold, such as the way the remnants expand and the flattening of the X-ray surface brightness distribution, in detail there are substantial differences. In particular we find that the X-ray luminosity is dominated by emission from shocked cloud gas early on, leading to a bright peak, which then declines and flattens as evaporation becomes more important. In addition, the effects of thermal conduction on the intercloud gas, which is not included in the White and Long model, are important and lead to further flattening of the X-ray brightness profile as well as lower X-ray emission temperatures.« less
Habitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming

USGS Publications Warehouse

Fedy, Bradley C.; Doherty, Kevin E.; Aldridge, Cameron L.; O'Donnell, Michael S.; Beck, Jeffrey L.; Bedrosian, Bryan; Gummer, David; Holloran, Matthew J.; Johnson, Gregory D.; Kaczor, Nicholas W.; Kirol, Christopher P.; Mandich, Cheryl A.; Marshall, David; McKee, Gwyn; Olson, Chad; Pratt, Aaron C.; Swanson, Christopher C.; Walker, Brett L.

2014-01-01

Animal habitat selection is an important and expansive area of research in ecology. In particular, the study of habitat selection is critical in habitat prioritization efforts for species of conservation concern. Landscape planning for species is happening at ever-increasing extents because of the appreciation for the role of landscape-scale patterns in species persistence coupled to improved datasets for species and habitats, and the expanding and intensifying footprint of human land uses on the landscape. We present a large-scale collaborative effort to develop habitat selection models across large landscapes and multiple seasons for prioritizing habitat for a species of conservation concern. Greater sage-grouse (Centrocercus urophasianus, hereafter sage-grouse) occur in western semi-arid landscapes in North America. Range-wide population declines of this species have been documented, and it is currently considered as “warranted but precluded” from listing under the United States Endangered Species Act. Wyoming is predicted to remain a stronghold for sage-grouse populations and contains approximately 37% of remaining birds. We compiled location data from 14 unique radiotelemetry studies (data collected 1994–2010) and habitat data from high-quality, biologically relevant, geographic information system (GIS) layers across Wyoming. We developed habitat selection models for greater sage-grouse across Wyoming for 3 distinct life stages: 1) nesting, 2) summer, and 3) winter. We developed patch and landscape models across 4 extents, producing statewide and regional (southwest, central, northeast) models for Wyoming. Habitat selection varied among regions and seasons, yet preferred habitat attributes generally matched the extensive literature on sage-grouse seasonal habitat requirements. Across seasons and regions, birds preferred areas with greater percentage sagebrush cover and avoided paved roads, agriculture, and forested areas. Birds consistently preferred areas with higher precipitation in the summer and avoided rugged terrain in the winter. Selection for sagebrush cover varied regionally with stronger selection in the Northeast region, likely because of limited availability, whereas avoidance of paved roads was fairly consistent across regions. We chose resource selection function (RSF) thresholds for each model set (seasonal × regional combination) that delineated important seasonal habitats for sage-grouse. Each model set showed good validation and discriminatory capabilities within study-site boundaries. We applied the nesting-season models to a novel area not included in model development. The percentage of independent nest locations that fell directly within identified important habitat was not overly impressive in the novel area (49%); however, including a 500-m buffer around important habitat captured 98% of independent nest locations within the novel area. We also used leks and associated peak male counts as a proxy for nesting habitat outside of the study sites used to develop the models. A 1.5-km buffer around the important nesting habitat boundaries included 77% of males counted at leks in Wyoming outside of the study sites. Data were not available to quantitatively test the performance of the summer and winter models outside our study sites. The collection of models presented here represents large-scale resource-management planning tools that are a significant advancement to previous tools in terms of spatial and temporal resolution.
Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

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

Deutsch, Jared L., E-mail: jdeutsch@ualberta.ca; Palmer, Kevin; Deutsch, Clayton V.

High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit inmore » South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.« less
ISO Technical Specification for the Ionosphere -IRI Recent Activities

NASA Astrophysics Data System (ADS)

Bilitza, Dieter; Reinisch, Bodo; Tamara, Gulyaeva

ISO Technical Specification TS 16457 recommends the International Reference Ionosphere (IRI) for the specification of ionospheric densities and temperatures. We review the latest develop-ments towards improving the IRI model and the newest version of the model IRI-2010. IRI-2010 includes several important improvements and additions. This presentation introduces these changes and discusses their benefits. The changes affect primarily the density profiles in the bottomside ionosphere and the density and height of the F2 peak, the point of highest density in the ionosphere. An important new addition to the model is the inclusion of auroral boundaries and their movement with magnetic activity. We will also discuss the status of other ongoing IRI activities and some of the recent applications of the IRI model. The homepage for the IRI project is at http://IRI.gsfc.nasa.gov/.
Engineering Large Animal Species to Model Human Diseases.

PubMed

Rogers, Christopher S

2016-07-01

Animal models are an important resource for studying human diseases. Genetically engineered mice are the most commonly used species and have made significant contributions to our understanding of basic biology, disease mechanisms, and drug development. However, they often fail to recreate important aspects of human diseases and thus can have limited utility as translational research tools. Developing disease models in species more similar to humans may provide a better setting in which to study disease pathogenesis and test new treatments. This unit provides an overview of the history of genetically engineered large animals and the techniques that have made their development possible. Factors to consider when planning a large animal model, including choice of species, type of modification and methodology, characterization, production methods, and regulatory compliance, are also covered. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.
A dynamic vulnerability evaluation model to smart grid for the emergency response

NASA Astrophysics Data System (ADS)

Yu, Zhen; Wu, Xiaowei; Fang, Diange

2018-01-01

Smart grid shows more significant vulnerability to natural disasters and external destroy. According to the influence characteristics of important facilities suffered from typical kinds of natural disaster and external destroy, this paper built a vulnerability evaluation index system of important facilities in smart grid based on eight typical natural disasters, including three levels of static and dynamic indicators, totally forty indicators. Then a smart grid vulnerability evaluation method was proposed based on the index system, including determining the value range of each index, classifying the evaluation grade standard and giving the evaluation process and integrated index calculation rules. Using the proposed evaluation model, it can identify the most vulnerable parts of smart grid, and then help adopting targeted emergency response measures, developing emergency plans and increasing its capacity of disaster prevention and mitigation, which guarantee its safe and stable operation.
The relationship between financial strain, perceived stress, psychological symptoms, and academic and social integration in undergraduate students.

PubMed

Adams, Danielle R; Meyers, Steven A; Beidas, Rinad S

2016-07-01

Financial strain may directly or indirectly (i.e., through perceived stress) impact students' psychological symptoms and academic and social integration, yet few studies have tested these relationships. The authors explored the mediating effect of perceived stress on the relationship between financial strain and 2 important outcomes: psychological symptomology and academic and social integration. Participants were 157 undergraduate students. Data were collected from December 2013 to March 2014. Cross-sectional data collection conducted using online survey software. It was found that perceived stress mediated the relationship between financial strain and (a) psychological symptomology and (b) academic and social integration. Both models included first-generation status as a covariate. Results suggest that perceived stress is an important intervention target for reducing psychological symptoms and improving academic and social integration for undergraduate students. Implications for university health centers and mental health professionals include incorporating a public health model to minimize stress risk.
Ozone changes under solar geoengineering: implications for UV exposure and air quality

NASA Astrophysics Data System (ADS)

Nowack, P. J.; Abraham, N. L.; Braesicke, P.; Pyle, J. A.

2015-11-01

Various forms of geoengineering have been proposed to counter anthropogenic climate change. Methods which aim to modify the Earth's energy balance by reducing insolation are often subsumed under the term Solar Radiation Management (SRM). Here, we present results of a standard SRM modelling experiment in which the incoming solar irradiance is reduced to offset the global mean warming induced by a quadrupling of atmospheric carbon dioxide. For the first time in an atmosphere-ocean coupled climate model, we include atmospheric composition feedbacks such as ozone changes under this scenario. Including the composition changes, we find large reductions in surface UV-B irradiance, with implications for vitamin D production, and increases in surface ozone concentrations, both of which could be important for human health. We highlight that both tropospheric and stratospheric ozone changes should be considered in the assessment of any SRM scheme, due to their important roles in regulating UV exposure and air quality.
A Framework to Debug Diagnostic Matrices

NASA Technical Reports Server (NTRS)

Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

2013-01-01

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.
Symplectic multiparticle tracking model for self-consistent space-charge simulation

DOE PAGES

Qiang, Ji

2017-01-23

Symplectic tracking is important in accelerator beam dynamics simulation. So far, to the best of our knowledge, there is no self-consistent symplectic space-charge tracking model available in the accelerator community. In this paper, we present a two-dimensional and a three-dimensional symplectic multiparticle spectral model for space-charge tracking simulation. This model includes both the effect from external fields and the effect of self-consistent space-charge fields using a split-operator method. Such a model preserves the phase space structure and shows much less numerical emittance growth than the particle-in-cell model in the illustrative examples.
Symplectic multiparticle tracking model for self-consistent space-charge simulation

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

Qiang, Ji

Symplectic tracking is important in accelerator beam dynamics simulation. So far, to the best of our knowledge, there is no self-consistent symplectic space-charge tracking model available in the accelerator community. In this paper, we present a two-dimensional and a three-dimensional symplectic multiparticle spectral model for space-charge tracking simulation. This model includes both the effect from external fields and the effect of self-consistent space-charge fields using a split-operator method. Such a model preserves the phase space structure and shows much less numerical emittance growth than the particle-in-cell model in the illustrative examples.
Using decision trees to understand structure in missing data

PubMed Central

Tierney, Nicholas J; Harden, Fiona A; Harden, Maurice J; Mengersen, Kerrie L

2015-01-01

Objectives Demonstrate the application of decision trees—classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs)—to understand structure in missing data. Setting Data taken from employees at 3 different industrial sites in Australia. Participants 7915 observations were included. Materials and methods The approach was evaluated using an occupational health data set comprising results of questionnaires, medical tests and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the type of data (medical or environmental), the site in which it was collected, the number of visits, and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured as compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusions Researchers are encouraged to use CART and BRT models to explore and understand missing data. PMID:26124509
Proposed best practice for projects that involve modelling and simulation.

PubMed

O'Kelly, Michael; Anisimov, Vladimir; Campbell, Chris; Hamilton, Sinéad

2017-03-01

Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre-specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detail and the strictness of pre-specification should be allowed to vary, depending on the complexity and importance of the project. This best practice document does not prescribe how to develop a statistical model. Rather, it describes the elements required for the specification of a project and requires that the practitioner justify in the specification the omission of any of the elements and, in addition, justify the level of detail provided about each element. This document is an initiative of the Special Interest Group for modelling and simulation. The Special Interest Group for modelling and simulation is a body open to members of Statisticians in the Pharmaceutical Industry and the European Federation of Statisticians in the Pharmaceutical Industry. Examples of a very detailed specification and a less detailed specification are included as appendices. Copyright © 2016 John Wiley & Sons, Ltd.
Combustion Of Porous Graphite Particles In Oxygen Enriched Air

NASA Technical Reports Server (NTRS)

Delisle, Andrew J.; Miller, Fletcher J.; Chelliah, Harsha K.

2003-01-01

Combustion of solid fuel particles has many important applications, including power generation and space propulsion systems. The current models available for describing the combustion process of these particles, especially porous solid particles, include various simplifying approximations. One of the most limiting approximations is the lumping of the physical properties of the porous fuel with the heterogeneous chemical reaction rate constants [1]. The primary objective of the present work is to develop a rigorous modeling approach that could decouple such physical and chemical effects from the global heterogeneous reaction rates. For the purpose of validating this model, experiments with porous graphite particles of varying sizes and porosity are being performed under normal and micro gravity.
Modelling biogas production of solid waste: application of the BGP model to a synthetic landfill

NASA Astrophysics Data System (ADS)

Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco

2013-04-01

Production of biogas as a result of the decomposition of organic matter included on solid waste landfills is still an issue to be understood. Reports on this matter are rarely included on the engineering construction projects of solid waste landfills despite it can be an issue of critical importance while operating the landfill and after its closure. This paper presents an application of BGP (Bio-Gas-Production) model to a synthetic landfill. The evolution in time of the concentrations of the different chemical compounds of biogas is studied. Results obtained show the impact on the air quality of different management alternatives which are usually performed in real landfills.

A Stochastic Model of Space Radiation Transport as a Tool in the Development of Time-Dependent Risk Assessment

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Nounu, Hatem N.; Ponomarev, Artem L.; Cucinotta, Francis A.

2011-01-01

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and heavy ions that have been studied at the NASA Space Radiation Laboratory (NSRL) [1] for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of heavy ions in tissue and shielding materials is made with a stochastic approach that includes both ion track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model [2]. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections
Development of simplified ecosystem models for applications in Earth system studies: The Century experience

NASA Technical Reports Server (NTRS)

Parton, William J.; Ojima, Dennis S.; Schimel, David S.; Kittel, Timothy G. F.

1992-01-01

During the past decade, a growing need to conduct regional assessments of long-term trends of ecosystem behavior and the technology to meet this need have converged. The Century model is the product of research efforts initially intended to develop a general model of plant-soil ecosystem dynamics for the North American central grasslands. This model is now being used to simulate plant production, nutrient cycling, and soil organic matter dynamics for grassland, crop, forest, and shrub ecosystems in various regions of the world, including temperate and tropical ecosystems. This paper will focus on the philosophical approach used to develop the structure of Century. The steps included were model simplification, parameterization, and testing. In addition, the importance of acquiring regional data bases for model testing and the present regional application of Century in the Great Plains, which focus on regional ecosystem dynamics and the effect of altering environmental conditions, are discussed.
Comparing functional responses in predator-infected eco-epidemics models.

PubMed

Haque, Mainul; Rahman, Md Sabiar; Venturino, Ezio

2013-11-01

The current paper deals with the mathematical models of predator-prey system where a transmissible disease spreads among the predator species only. Four mathematical models are proposed and analysed with several popular predator functional responses in order to show the influence of functional response on eco-epidemic models. The existence, boundedness, uniqueness of solutions of all the models are established. Mathematical analysis including stability and bifurcation are observed. Comparison among the results of these models allows the general conclusion that relevant behaviour of the eco-epidemic predator-prey system, including switching of stability, extinction, persistence and oscillations for any species depends on four important parameters viz. the rate of infection, predator interspecies competition and the attack rate on susceptible predator. The paper ends with a discussion of the biological implications of the analytical and numerical results. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Sleep disorders, obesity, and aging: the role of orexin

PubMed Central

Nixon, Joshua P.; Mavanji, Vijayakumar; Butterick, Tammy A.; Billington, Charles J.; Kotz, Catherine M.; Teske, Jennifer A.

2015-01-01

The hypothalamic neuropeptides orexin A and B (hypocretin 1 and 2) are important homeostatic mediators of central control of energy metabolism and maintenance of sleep/wake states. Dysregulation or loss of orexin signaling has been linked to narcolepsy, obesity, and age-related disorders. In this review, we present an overview of our current understanding of orexin function, focusing on sleep disorders, energy balance, and aging, in both rodents and humans. We first discuss animal models used in studies of obesity and sleep, including loss of function using transgenic or viral-mediated approaches, gain of function models using exogenous delivery of orexin receptor agonist, and naturally-occurring models in which orexin responsiveness varies by individual. We next explore rodent models of orexin in aging, presenting evidence that orexin loss contributes to age-related changes in sleep and energy balance. In the next section, we focus on clinical importance of orexin in human obesity, sleep, and aging. We include discussion of orexin loss in narcolepsy and potential importance of orexin in insomnia, correlations between animal and human studies of age-related decline, and evidence for orexin involvement in age-related changes in cognitive performance. Finally, we present a summary of recent studies of orexin in neurodegenerative disease. We conclude that orexin acts as an integrative homeostatic signal influencing numerous brain regions, and that this pivotal role results in potential dysregulation of multiple physiological processes when orexin signaling is disrupted or lost. PMID:25462194
Sleep disorders, obesity, and aging: the role of orexin.

PubMed

Nixon, Joshua P; Mavanji, Vijayakumar; Butterick, Tammy A; Billington, Charles J; Kotz, Catherine M; Teske, Jennifer A

2015-03-01

The hypothalamic neuropeptides orexin A and B (hypocretin 1 and 2) are important homeostatic mediators of central control of energy metabolism and maintenance of sleep/wake states. Dysregulation or loss of orexin signaling has been linked to narcolepsy, obesity, and age-related disorders. In this review, we present an overview of our current understanding of orexin function, focusing on sleep disorders, energy balance, and aging, in both rodents and humans. We first discuss animal models used in studies of obesity and sleep, including loss of function using transgenic or viral-mediated approaches, gain of function models using exogenous delivery of orexin receptor agonist, and naturally-occurring models in which orexin responsiveness varies by individual. We next explore rodent models of orexin in aging, presenting evidence that orexin loss contributes to age-related changes in sleep and energy balance. In the next section, we focus on clinical importance of orexin in human obesity, sleep, and aging. We include discussion of orexin loss in narcolepsy and potential importance of orexin in insomnia, correlations between animal and human studies of age-related decline, and evidence for orexin involvement in age-related changes in cognitive performance. Finally, we present a summary of recent studies of orexin in neurodegenerative disease. We conclude that orexin acts as an integrative homeostatic signal influencing numerous brain regions, and that this pivotal role results in potential dysregulation of multiple physiological processes when orexin signaling is disrupted or lost. Published by Elsevier B.V.
Overcoming Hurdles Implementing Multi-skilling Policies

DTIC Science & Technology

2015-03-26

skilled workforce? Chapter II will communicate important concepts found in the literature on skill proficiency topics. These topics include skill...training methods that might improve learning and retention during the acquisition phase. 10 The active interlock modeling (AIM) protocol is a dyadic ...retention, as found in 43 Chapter 2. These techniques include dyadic training methods, overlearning, feedback, peer support, and managerial support
Effectiveness of chronic care models: opportunities for improving healthcare practice and health outcomes: a systematic review.

PubMed

Davy, Carol; Bleasel, Jonathan; Liu, Hueiming; Tchan, Maria; Ponniah, Sharon; Brown, Alex

2015-05-10

The increasing prevalence of chronic disease and even multiple chronic diseases faced by both developed and developing countries is of considerable concern. Many of the interventions to address this within primary healthcare settings are based on a chronic care model first developed by MacColl Institute for Healthcare Innovation at Group Health Cooperative. This systematic literature review aimed to identify and synthesise international evidence on the effectiveness of elements that have been included in a chronic care model for improving healthcare practices and health outcomes within primary healthcare settings. The review broadens the work of other similar reviews by focusing on effectiveness of healthcare practice as well as health outcomes associated with implementing a chronic care model. In addition, relevant case series and case studies were also included. Of the 77 papers which met the inclusion criteria, all but two reported improvements to healthcare practice or health outcomes for people living with chronic disease. While the most commonly used elements of a chronic care model were self-management support and delivery system design, there were considerable variations between studies regarding what combination of elements were included as well as the way in which chronic care model elements were implemented. This meant that it was impossible to clearly identify any optimal combination of chronic care model elements that led to the reported improvements. While the main argument for excluding papers reporting case studies and case series in systematic literature reviews is that they are not of sufficient quality or generalizability, we found that they provided a more detailed account of how various chronic care models were developed and implemented. In particular, these papers suggested that several factors including supporting reflective healthcare practice, sending clear messages about the importance of chronic disease care and ensuring that leaders support the implementation and sustainability of interventions may have been just as important as a chronic care model's elements in contributing to the improvements in healthcare practice or health outcomes for people living with chronic disease.
Algorithms for a Closed-Loop Artificial Pancreas: The Case for Model Predictive Control

PubMed Central

Bequette, B. Wayne

2013-01-01

The relative merits of model predictive control (MPC) and proportional-integral-derivative (PID) control are discussed, with the end goal of a closed-loop artificial pancreas (AP). It is stressed that neither MPC nor PID are single algorithms, but rather are approaches or strategies that may be implemented very differently by different engineers. The primary advantages to MPC are that (i) constraints on the insulin delivery rate (and/or insulin on board) can be explicitly included in the control calculation; (ii) it is a general framework that makes it relatively easy to include the effect of meals, exercise, and other events that are a function of the time of day; and (iii) it is flexible enough to include many different objectives, from set-point tracking (target) to zone (control to range). In the end, however, it is recognized that the control algorithm, while important, represents only a portion of the effort required to develop a closed-loop AP. Thus, any number of algorithms/approaches can be successful—the engineers involved in the design must have experience with the particular technique, including the important experience of implementing the algorithm in human studies and not simply through simulation studies. PMID:24351190
Urban growth simulation from "first principles".

PubMed

Andersson, Claes; Lindgren, Kristian; Rasmussen, Steen; White, Roger

2002-08-01

General and mathematically transparent models of urban growth have so far suffered from a lack in microscopic realism. Physical models that have been used for this purpose, i.e., diffusion-limited aggregation, dielectric breakdown models, and correlated percolation all have microscopic dynamics for which analogies with urban growth appear stretched. Based on a Markov random field formulation we have developed a model that is capable of reproducing a variety of important characteristic urban morphologies and that has realistic microscopic dynamics. The results presented in this paper are particularly important in relation to "urban sprawl," an important aspect of which is aggressively spreading low-density land uses. This type of growth is increasingly causing environmental, social, and economical problems around the world. The microdynamics of our model, or its "first principles," can be mapped to human decisions and motivations and thus potentially also to policies and regulations. We measure statistical properties of macrostates generated by the urban growth mechanism that we propose, and we compare these to empirical measurements as well as to results from other models. To showcase the open-endedness of the model and to thereby relate our work to applied urban planning we have also included a simulated city consisting of a large number of land use classes in which also topographical data have been used.
Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

NASA Astrophysics Data System (ADS)

Derwent, Richard; Beevers, Sean; Chemel, Charles; Cooke, Sally; Francis, Xavier; Fraser, Andrea; Heal, Mathew R.; Kitwiroon, Nutthida; Lingard, Justin; Redington, Alison; Sokhi, Ranjeet; Vieno, Massimo

2014-09-01

Simple emission scenarios have been implemented in eight United Kingdom air quality models with the aim of assessing how these models compared when addressing whether photochemical ozone formation in southern England was NOx- or VOC-sensitive and whether ozone precursor sources in the UK or in the Rest of Europe (RoE) were the most important during July 2006. The suite of models included three Eulerian-grid models (three implementations of one of these models), a Lagrangian atmospheric dispersion model and two moving box air parcel models. The assignments as to NOx- or VOC-sensitive and to UK- versus RoE-dominant, turned out to be highly variable and often contradictory between the individual models. However, when the assignments were filtered by model performance on each day, many of the contradictions could be eliminated. Nevertheless, no one model was found to be the 'best' model on all days, indicating that no single air quality model could currently be relied upon to inform policymakers robustly in terms of NOx- versus VOC-sensitivity and UK- versus RoE-dominance on each day. It is important to maintain a diversity in model approaches.
Relative role of pore water versus ingested sediment in bioavailability of organic contaminants in marine sediments

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

Forbes, T.L.; Hansen, R.; Kure, L.K.

Experimental data for fluoranthene and feeding selectivity in combination with reaction-diffusion modeling suggest that ingestion of contaminated sediment may often be the dominant uptake pathway for deposit-feeding invertebrates in sediments. A dietary absorption efficiency of 56% and accompanying forage ratio of 2.4 were measured using natural sediment that had been dual-labeled ({sup 14}C:{sup 51}Cr) with fluoranthene and fed to the marine deposit-feeding polychaete Capitella species I. Only 3 to 4% of the total absorption could be accounted for by desorption during gut passage. These data were then used as input into a reaction-diffusion model to calculate the importance of uptakemore » from ingested sediment relative to pore-water exposure. The calculations predict a fluoranthene dietary uptake flux that is 20 to 30 times greater than that due to pore water. Factors that act to modify or control the formation of local chemical gradients, boundary layers, or dietary absorption rates including particle selection or burrow construction will be important in determining the relative importance of potential exposure pathways. From a chemical perspective, the kinetics of the adsorption and desorption process are especially important as they will strongly influence the boundary layer immediately surrounding burrowing animals or irrigated tubes. The most important biological factors likely include irrigation behavior and burrow density and size.« less
Vehicle/Atmosphere Interaction Glows: Far Ultraviolet, Visible, and Infrared

NASA Technical Reports Server (NTRS)

Swenson, G.

1999-01-01

Spacecraft glow information has been gathered from a number of spacecraft including Atmospheric and Dynamic satellites, and Space Shuttles (numerous flights) with dedicated pallet flow observations on STS-39 (DOD) and STS-62 (NASA). In addition, a larger number of laboratory experiments with low energy oxygen beam studies have made important contributions to glow understanding. The following report provides information on three engineering models developed for spacecraft glow including the far ultraviolet to ultraviolet (1400-4000 A), and infrared (0.9-40 microns) spectral regions. The models include effects resulting from atmospheric density/altitude, spacecraft temperature, spacecraft material, and ram angle. Glow brightness would be predicted as a function of distance from surfaces for all wavelengths.
Variable-Speed Simulation of a Dual-Clutch Gearbox Tiltrotor Driveline

NASA Technical Reports Server (NTRS)

DeSmidt, Hans; Wang, Kon-Well; Smith, Edward C.; Lewicki, David G.

2012-01-01

This investigation explores the variable-speed operation and shift response of a prototypical two-speed dual-clutch transmission tiltrotor driveline in forward flight. Here, a Comprehensive Variable-Speed Rotorcraft Propulsion System Modeling (CVSRPM) tool developed under a NASA funded NRA program is utilized to simulate the drive system dynamics. In this study, a sequential shifting control strategy is analyzed under a steady forward cruise condition. This investigation attempts to build upon previous variable-speed rotorcraft propulsion studies by 1) including a fully nonlinear transient gas-turbine engine model, 2) including clutch stick-slip friction effects, 3) including shaft flexibility, 4) incorporating a basic flight dynamics model to account for interactions with the flight control system. Through exploring the interactions between the various subsystems, this analysis provides important insights into the continuing development of variable-speed rotorcraft propulsion systems.
The epidemiology of pelvic floor disorders and childbirth: an update

PubMed Central

Hallock, Jennifer L.; Handa, Victoria L.

2015-01-01

SYNOPSIS Using a life span model, this article presents new scientific findings regarding risk factors for pelvic floor disorders (PFDs), with a focus on the role of childbirth in the development of single or multiple co-existing PFDs. Phase I of the life span model includes predisposing factors such as genetic predisposition and race. Phase II of the model includes inciting factors such as obstetric events. Prolapse, urinary incontinence (UI) and fecal incontinence (FI) are more common among vaginally parous women, although the impact of vaginal delivery on risk of FI is less dramatic than for prolapse and UI. Finally, Phase III includes intervening factors such as age and obesity. Both age and obesity are associated with prevalence of PFDs. The prevention and treatment of obesity is an important component to PFD prevention. PMID:26880504
A mathematical model of insulin resistance in Parkinson's disease.

PubMed

Braatz, Elise M; Coleman, Randolph A

2015-06-01

This paper introduces a mathematical model representing the biochemical interactions between insulin signaling and Parkinson's disease. The model can be used to examine the changes that occur over the course of the disease as well as identify which processes would be the most effective targets for treatment. The model is mathematized using biochemical systems theory (BST). It incorporates a treatment strategy that includes several experimental drugs along with current treatments. In the past, BST models of neurodegeneration have used power law analysis and simulation (PLAS) to model the system. This paper recommends the use of MATLAB instead. MATLAB allows for more flexibility in both the model itself and in data analysis. Previous BST analyses of neurodegeneration began treatment at disease onset. As shown in this model, the outcomes of delayed, realistic treatment and full treatment at disease onset are significantly different. The delayed treatment strategy is an important development in BST modeling of neurodegeneration. It emphasizes the importance of early diagnosis, and allows for a more accurate representation of disease and treatment interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.
An accurate behavioral model for single-photon avalanche diode statistical performance simulation

NASA Astrophysics Data System (ADS)

Xu, Yue; Zhao, Tingchen; Li, Ding

2018-01-01

An accurate behavioral model is presented to simulate important statistical performance of single-photon avalanche diodes (SPADs), such as dark count and after-pulsing noise. The derived simulation model takes into account all important generation mechanisms of the two kinds of noise. For the first time, thermal agitation, trap-assisted tunneling and band-to-band tunneling mechanisms are simultaneously incorporated in the simulation model to evaluate dark count behavior of SPADs fabricated in deep sub-micron CMOS technology. Meanwhile, a complete carrier trapping and de-trapping process is considered in afterpulsing model and a simple analytical expression is derived to estimate after-pulsing probability. In particular, the key model parameters of avalanche triggering probability and electric field dependence of excess bias voltage are extracted from Geiger-mode TCAD simulation and this behavioral simulation model doesn't include any empirical parameters. The developed SPAD model is implemented in Verilog-A behavioral hardware description language and successfully operated on commercial Cadence Spectre simulator, showing good universality and compatibility. The model simulation results are in a good accordance with the test data, validating high simulation accuracy.
Forecasting cyanobacteria dominance in Canadian temperate lakes.

PubMed

Persaud, Anurani D; Paterson, Andrew M; Dillon, Peter J; Winter, Jennifer G; Palmer, Michelle; Somers, Keith M

2015-03-15

Predictive models based on broad scale, spatial surveys typically identify nutrients and climate as the most important predictors of cyanobacteria abundance; however these models generally have low predictive power because at smaller geographic scales numerous other factors may be equally or more important. At the lake level, for example, the ability to forecast cyanobacteria dominance is of tremendous value to lake managers as they can use such models to communicate exposure risks associated with recreational and drinking water use, and possible exposure to algal toxins, in advance of bloom occurrence. We used detailed algal, limnological and meteorological data from two temperate lakes in south-central Ontario, Canada to determine the factors that are closely linked to cyanobacteria dominance, and to develop easy to use models to forecast cyanobacteria biovolume. For Brandy Lake (BL), the strongest and most parsimonious model for forecasting % cyanobacteria biovolume (% CB) included water column stability, hypolimnetic TP, and % cyanobacteria biovolume two weeks prior. For Three Mile Lake (TML), the best model for forecasting % CB included water column stability, hypolimnetic TP concentration, and 7-d mean wind speed. The models for forecasting % CB in BL and TML are fundamentally different in their lag periods (BL = lag 1 model and TML = lag 2 model) and in some predictor variables despite the close proximity of the study lakes. We speculate that three main factors (nutrient concentrations, water transparency and lake morphometry) may have contributed to differences in the models developed, and may account for variation observed in models derived from large spatial surveys. Our results illustrate that while forecast models can be developed to determine when cyanobacteria will dominate within two temperate lakes, the models require detailed, lake-specific calibration to be effective as risk-management tools. Copyright © 2015 Elsevier Ltd. All rights reserved.
Stratosphere-resolving CMIP5 models simulate different changes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Rea, Gloria; Riccio, Angelo; Fierli, Federico; Cairo, Francesco; Cagnazzo, Chiara

2018-03-01

This work documents long-term changes in the Southern Hemisphere circulation in the austral spring-summer season in the Coupled Intercomparison Project Phase 5 models, showing that those changes are larger in magnitude and closer to ERA-Interim and other reanalyses if models include a dynamical representation of the stratosphere. Specifically, models with a high-top and included dynamical and—in some cases—chemical feedbacks within the stratosphere better simulate the lower stratospheric cooling observed over 1979-2001 and strongly driven by ozone depletion, when compared to the other models. This occurs because high-top models can fully capture the stratospheric large scale circulation response to the ozone-induced cooling. Interestingly, this difference is also found at the surface for the Southern Annular Mode (SAM) changes, even though all model categories tend to underestimate SAM trends over those decades. In this analysis, models including a proper dynamical stratosphere are more sensitive to lower stratospheric cooling in their tropospheric circulation response. After a brief discussion of two RCP scenarios, our study confirms that at least for large changes in the extratropical regions, stratospheric changes induced by external forcing have to be properly simulated, as they are important drivers of tropospheric climate variations.
Parents and friends both matter: simultaneous and interactive influences of parents and friends on European schoolchildren’s energy balance-related behaviours – the ENERGY cross-sectional study

PubMed Central

2014-01-01

Background The family, and parents in particular, are considered the most important influencers regarding children’s energy-balance related behaviours (EBRBs). When children become older and gain more behavioural autonomy regarding different behaviours, the parental influences may become less important and peer influences may gain importance. Therefore the current study aims to investigate simultaneous and interactive associations of family rules, parent and friend norms and modelling with soft drink intake, TV viewing, daily breakfast consumption and sport participation among schoolchildren across Europe. Methods A school-based cross-sectional survey in eight countries across Europe among 10–12 year old schoolchildren. Child questionnaires were used to assess EBRBs (soft drink intake, TV viewing, breakfast consumption, sport participation), and potential determinants of these behaviours as perceived by the child, including family rules, parental and friend norms and modelling. Linear and logistic regression analyses (n = 7811) were applied to study the association of parental (norms, modelling and rules) and friend influences (norm and modelling) with the EBRBs. In addition, potential moderating effects of parental influences on the associations of friend influences with the EBRBs were studied by including interaction terms. Results Children reported more unfavourable friend norms and modelling regarding soft drink intake and TV viewing, while they reported more favourable friend and parental norms and modelling for breakfast consumption and physical activity. Perceived friend and parental norms and modelling were significantly positively associated with soft drink intake, breakfast consumption, physical activity (only modelling) and TV time. Across the different behaviours, ten significant interactions between parental and friend influencing variables were found and suggested a weaker association of friend norms and modelling when rules were in place. Conclusion Parental and friends norm and modelling are associated with schoolchildren’s energy balance-related behaviours. Having family rules or showing favourable parental modelling and norms seems to reduce the potential unfavourable associations of friends’ norms and modelling with the EBRBs. PMID:25001090
A Model for the Formation and Melting of Ice on Surface Waters.

NASA Astrophysics Data System (ADS)

de Bruin, H. A. R.; Wessels, H. R. A.

1988-02-01

Ice covers have an important influence on the hydrology of surface waters. The growth of ice layer on stationary waters, such as lakes or canals, depends primarily on meteorological parameters like temperature and humidity of the air, windspeed and radiation balance. The more complicated ice formation in rapidly flowing rivers is not considered in this study. A model is described that simulates ice growth and melting utilizing observed or forecast weather data. The model includes situations with a snow cover. Special attention is given to the optimal estimation of the net radiation and to the role of the stability of the near-surface air. Since a major practical application in the Netherlands is the use of frozen waters for recreation skating, the model is extended to include artificial ice tracks.

Commonalities of nurse-designed models of health care.

PubMed

Mason, Diana J; Jones, Dorothy A; Roy, Callista; Sullivan, Cheryl G; Wood, Laura J

2015-01-01

The American Academy of Nursing has identified examples of care redesign developed by nurses who address the health needs of diverse populations. These models show important clinical and financial outcomes as summarized in the Select Edge Runner Models of Care table included in this article. A study team appointed by the Academy explored the commonalities across these models. Four commonalities emerged: health holistically defined; individual-, family-, and community-centric approaches to care; relationship-based care that enables partnerships and builds patient engagement and activation; and a shift from episodic individual care to continuous group and public health approaches. The policy implications include examining measures of an expanded definition of health, paying for visionary care, and transparency and rewards for community-level engagement. Copyright © 2015 Elsevier Inc. All rights reserved.
Lessons from the Unexpected: The Importance of Data Infrastructure, Conceptual Models, and Serendipity in Health Services Research

PubMed Central

Mechanic, David

2001-01-01

In examining the importance of data systems, conceptual models, and serendipity in understanding health services, the case is made for a vigorous and responsive data infrastructure and more emphasis on conceptual development. Particularly important is the development of data systems that can keep pace with changes in health care organization and patterns of care. Three examples—from managed care, deinstitutionalization, and physician remuneration—demonstrate the need to empirically examine seemingly obvious assumptions about health patterns and trends, and the lessons to be learned when assumptions are proved incorrect. Major future challenges include incorporating patient preferences into outcomes research, meaningful communication about treatment options and health plan choices, and understanding how organizational culture and norms affect decision processes. PMID:11565164
On the Vertical Distribution of Local and Remote Sources of Water for Precipitation

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.

2001-01-01

The vertical distribution of local and remote sources of water for precipitation and total column water over the United States are evaluated in a general circulation model simulation. The Goddard Earth Observing System (GEOS) general circulation model (GCM) includes passive constituent tracers to determine the geographical sources of the water in the column. Results show that the local percentage of precipitable water and local percentage of precipitation can be very different. The transport of water vapor from remote oceanic sources at mid and upper levels is important to the total water in the column over the central United States, while the access of locally evaporated water in convective precipitation processes is important to the local precipitation ratio. This result resembles the conceptual formulation of the convective parameterization. However, the formulations of simple models of precipitation recycling include the assumption that the ratio of the local water in the column is equal to the ratio of the local precipitation. The present results demonstrate the uncertainty in that assumption, as locally evaporated water is more concentrated near the surface.
Arcjet space thrusters

NASA Astrophysics Data System (ADS)

Keefer, Dennis; Rhodes, Robert

1993-05-01

Electrically powered arc jets which produce thrust at high specific impulse could provide a substantial cost reduction for orbital transfer and station keeping missions. There is currently a limited understanding of the complex, nonlinear interactions in the plasma propellant which has hindered the development of high efficiency arc jet thrusters by making it difficult to predict the effect of design changes and to interpret experimental results. A computational model developed at the University of Tennessee Space Institute (UTSI) to study laser powered thrusters and radio frequency gas heaters has been adapted to provide a tool to help understand the physical processes in arc jet thrusters. The approach is to include in the model those physical and chemical processes which appear to be important, and then to evaluate our judgement by the comparison of numerical simulations with experimental data. The results of this study have been presented at four technical conferences. The details of the work accomplished in this project are covered in the individual papers included in the appendix of this report. We present a brief description of the model covering its most important features followed by a summary of the effort.
The Effect and Relative Importance of Neutral Genetic Diversity for Predicting Parasitism Varies across Parasite Taxa

PubMed Central

Ruiz-López, María José; Monello, Ryan J.; Gompper, Matthew E.; Eggert, Lori S.

2012-01-01

Understanding factors that determine heterogeneity in levels of parasitism across individuals is a major challenge in disease ecology. It is known that genetic makeup plays an important role in infection likelihood, but the mechanism remains unclear as does its relative importance when compared to other factors. We analyzed relationships between genetic diversity and macroparasites in outbred, free-ranging populations of raccoons (Procyon lotor). We measured heterozygosity at 14 microsatellite loci and modeled the effects of both multi-locus and single-locus heterozygosity on parasitism using an information theoretic approach and including non-genetic factors that are known to influence the likelihood of parasitism. The association of genetic diversity and parasitism, as well as the relative importance of genetic diversity, differed by parasitic group. Endoparasite species richness was better predicted by a model that included genetic diversity, with the more heterozygous hosts harboring fewer endoparasite species. Genetic diversity was also important in predicting abundance of replete ticks (Dermacentor variabilis). This association fit a curvilinear trend, with hosts that had either high or low levels of heterozygosity harboring fewer parasites than those with intermediate levels. In contrast, genetic diversity was not important in predicting abundance of non-replete ticks and lice (Trichodectes octomaculatus). No strong single-locus effects were observed for either endoparasites or replete ticks. Our results suggest that in outbred populations multi-locus diversity might be important for coping with parasitism. The differences in the relationships between heterozygosity and parasitism for the different parasites suggest that the role of genetic diversity varies with parasite-mediated selective pressures. PMID:23049796
Improving high-altitude emp modeling capabilities by using a non-equilibrium electron swarm model to monitor conduction electron evolution

NASA Astrophysics Data System (ADS)

Pusateri, Elise Noel

An Electromagnetic Pulse (EMP) can severely disrupt the use of electronic devices in its path causing a significant amount of infrastructural damage. EMP can also cause breakdown of the surrounding atmosphere during lightning discharges. This makes modeling EMP phenomenon an important research effort in many military and atmospheric physics applications. EMP events include high-energy Compton electrons or photoelectrons that ionize air and produce low energy conduction electrons. A sufficient number of conduction electrons will damp or alter the EMP through conduction current. Therefore, it is important to understand how conduction electrons interact with air in order to accurately predict the EMP evolution and propagation in the air. It is common for EMP simulation codes to use an equilibrium ohmic model for computing the conduction current. Equilibrium ohmic models assume the conduction electrons are always in equilibrium with the local instantaneous electric field, i.e. for a specific EMP electric field, the conduction electrons instantaneously reach steady state without a transient process. An equilibrium model will work well if the electrons have time to reach their equilibrium distribution with respect to the rise time or duration of the EMP. If the time to reach equilibrium is comparable or longer than the rise time or duration of the EMP then the equilibrium model would not accurately predict the conduction current necessary for the EMP simulation. This is because transport coefficients used in the conduction current calculation will be found based on equilibrium reactions rates which may differ significantly from their non-equilibrium values. We see this deficiency in Los Alamos National Laboratory's EMP code, CHAP-LA (Compton High Altitude Pulse-Los Alamos), when modeling certain EMP scenarios at high altitudes, such as upward EMP, where the ionization rate by secondary electrons is over predicted by the equilibrium model, causing the EMP to short abruptly. The objective of the PhD research is to mitigate this effect by integrating a conduction electron model into CHAP-LA which can calculate the conduction current based on a non-equilibrium electron distribution. We propose to use an electron swarm model to monitor the time evolution of conduction electrons in the EMP environment which is characterized by electric field and pressure. Swarm theory uses various collision frequencies and reaction rates to study how the electron distribution and the resultant transport coefficients change with time, ultimately reaching an equilibrium distribution. Validation of the swarm model we develop is a necessary step for completion of the thesis work. After validation, the swarm model is integrated in the air chemistry model CHAP-LA employs for conduction electron simulations. We test high altitude EMP simulations with the swarm model option in the air chemistry model to show improvements in the computational capability of CHAP-LA. A swarm model has been developed that is based on a previous swarm model developed by Higgins, Longmire and O'Dell 1973, hereinafter HLO. The code used for the swarm model calculation solves a system of coupled differential equations for electric field, electron temperature, electron number density, and drift velocity. Important swarm parameters, including the momentum transfer collision frequency, energy transfer collision frequency, and ionization rate, are recalculated and compared to the previously reported empirical results given by HLO. These swarm parameters are found using BOLSIG+, a two term Boltzmann solver developed by Hagelaar and Pitchford 2005. BOLSIG+ utilizes updated electron scattering cross sections that are defined over an expanded energy range found in the atomic and molecular cross section database published by Phelps in the Phelps Database 2014 on the LXcat website created by Pancheshnyi et al. 2012. The swarm model is also updated from the original HLO model by including additional physical parameters such as the O2 electron attachment rate, recombination rate, and mutual neutralization rate. This necessitates tracking the positive and negative ion densities in the swarm model. Adding these parameters, especially electron attachment, is important at lower EMP altitudes where atmospheric density is high. We compare swarm model equilibrium temperatures and times using the HLO and BOLSIG+ coefficients for a uniform electric field of 1 StatV/cm for a range of atmospheric heights. This is done in order to test sensitivity to the swarm parameters used in the swarm model. It is shown that the equilibrium temperature and time are sensitive to the modifications in the collision frequency and ionization rate based on the updated electron interaction cross sections. We validate the swarm model by comparing ionization coefficients and equilibrium drift velocities to experimental results over a wide range of reduced electric field values. The final part of the PhD thesis work includes integrating the swarm model into CHAP-LA. We discuss the physics included in the CHAP-LA EMP model and demonstrate EMP damping behavior caused by the ohmic model at high altitudes. We report on numerical techniques for incorporation of the swarm model into CHAP-LA's Maxwell solver. This includes a discussion of integration techniques for Maxwell's equations in CHAP-LA using the swarm model calculated conduction current. We show improvements on EMP parameter calculations when modeling a high altitude, upward EMP scenario. This provides a novel computational capability that will have an important impact on the atmospheric and EMP research community.
Development and Application of a Three-Dimensional Finite Element Vapor Intrusion Model

PubMed Central

Pennell, Kelly G.; Bozkurt, Ozgur; Suuberg, Eric M.

2010-01-01

Details of a three-dimensional finite element model of soil vapor intrusion, including the overall modeling process and the stepwise approach, are provided. The model is a quantitative modeling tool that can help guide vapor intrusion characterization efforts. It solves the soil gas continuity equation coupled with the chemical transport equation, allowing for both advective and diffusive transport. Three-dimensional pressure, velocity, and chemical concentration fields are produced from the model. Results from simulations involving common site features, such as impervious surfaces, porous foundation sub-base material, and adjacent structures are summarized herein. The results suggest that site-specific features are important to consider when characterizing vapor intrusion risks. More importantly, the results suggest that soil gas or subslab gas samples taken without proper regard for particular site features may not be suitable for evaluating vapor intrusion risks; rather, careful attention needs to be given to the many factors that affect chemical transport into and around buildings. PMID:19418819
An Observation Analysis Tool for time-series analysis and sensor management in the FREEWAT GIS environment for water resources management

NASA Astrophysics Data System (ADS)

Cannata, Massimiliano; Neumann, Jakob; Cardoso, Mirko; Rossetto, Rudy; Foglia, Laura; Borsi, Iacopo

2017-04-01

In situ time-series are an important aspect of environmental modelling, especially with the advancement of numerical simulation techniques and increased model complexity. In order to make use of the increasing data available through the requirements of the EU Water Framework Directive, the FREEWAT GIS environment incorporates the newly developed Observation Analysis Tool for time-series analysis. The tool is used to import time-series data into QGIS from local CSV files, online sensors using the istSOS service, or MODFLOW model result files and enables visualisation, pre-processing of data for model development, and post-processing of model results. OAT can be used as a pre-processor for calibration observations, integrating the creation of observations for calibration directly from sensor time-series. The tool consists in an expandable Python library of processing methods and an interface integrated in the QGIS FREEWAT plug-in which includes a large number of modelling capabilities, data management tools and calibration capacity.
First-Order SPICE Modeling of Extreme-Temperature 4H-SiC JFET Integrated Circuits

NASA Technical Reports Server (NTRS)

Neudeck, Philip G.; Spry, David J.; Chen, Liang-Yu

2016-01-01

A separate submission to this conference reports that 4H-SiC Junction Field Effect Transistor (JFET) digital and analog Integrated Circuits (ICs) with two levels of metal interconnect have reproducibly demonstrated electrical operation at 500 C in excess of 1000 hours. While this progress expands the complexity and durability envelope of high temperature ICs, one important area for further technology maturation is the development of reasonably accurate and accessible computer-aided modeling and simulation tools for circuit design of these ICs. Towards this end, we report on development and verification of 25 C to 500 C SPICE simulation models of first order accuracy for this extreme-temperature durable 4H-SiC JFET IC technology. For maximum availability, the JFET IC modeling is implemented using the baseline-version SPICE NMOS LEVEL 1 model that is common to other variations of SPICE software and importantly includes the body-bias effect. The first-order accuracy of these device models is verified by direct comparison with measured experimental device characteristics.
Total reaction cross sections in CEM and MCNP6 at intermediate energies

DOE PAGES

Kerby, Leslie M.; Mashnik, Stepan G.

2015-05-14

Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used inmore » the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.« less
Total reaction cross sections in CEM and MCNP6 at intermediate energies

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

Kerby, Leslie M.; Mashnik, Stepan G.

Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used inmore » the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.« less
Energy Production Calculations with Field Flow Models and Windspeed Predictions with Statistical Methods

NASA Astrophysics Data System (ADS)

Rüstemoǧlu, Sevinç; Barutçu, Burak; Sibel Menteş, Å..

2010-05-01

The continuous usage of fossil fuels as primary energy source is the reason of the emission of CO and powerless economy of the country affected by the great flactuations in the unit price of energy sources. In recent years, developments in wind energy sector and the supporting new renewable energy policies of the countries allow the new wind farm owners and the firms who expect to be an owner to consider and invest on the renewable sources. In this study, the annual production of the turbines with 1.8 kW and 30 kW which are available for Istanbul Technical University in Energy Institute is calculated by Wasp and WindPro Field Flow Models and the wind characteristics of the area are analysed. The meteorological data used in calculation includes the period between 02.March.2000 and 31.May.2004 and is taken from the meteorological mast ( ) in Istanbul Technical University's campus area. The measurement data is taken from 2 m and 10 m heights with hourly means. The topography, roughness classes and shelter effects are defined in the models to make accurate extrapolation to the turbine sites. As an advantage, the region is nearly 3.5 km close to the Istanbul Bosphorous but as it can be seen from the Wasp and WindPro Model Results, the Bosphorous effect is interrupted by the new buildings and hight forestry. The shelter effect of these high buildings have a great influence on the wind flow and decrease the high wind energy potential which is produced by the Bosphorous effect. This study, which determines wind characteristics and expected annual production, is important for this Project Site and therefore gains importance before the construction of wind energy system. However, when the system is operating, developing the energy management skills, forecasting the wind speed and direction will become important. At this point, three statistical models which are Kalman Fitler, AR Model and Neural Networks models are used to determine the success of each method for correct wind prediction. Statistical methods' preditictions as time series are included and the similartiy rates are compared for each method. The algorithms which are performed in MATLAB, gave the similarity results of each model. According to the Neural Networks results which are found to be the most successful method for prediction within these three statistical models, the windspeed similarity rate between the original measurements and the prediction set which includes 1 year period between 2003 and 2004, is evaluated as % 94.7. For wind direction, the similarity rate is %81.61. High noise margin and ability to learn the characteristics of the signal are important advantages of Neural Networks for compatible windspeed and direction predictions compared with measurements.
Effective Affective Design for Distance Education.

ERIC Educational Resources Information Center

Zvacek, Susan M.

1991-01-01

Discusses the importance of affective considerations when designing instruction for distance education. Topics discussed include learner motivation based on Keller's ARCS model (Attention, Relevance, Confidence, and Satisfaction); communication patterns that facilitate interaction between students; and ethics involved with marketing programs,…
Science: A History of Woman's Work

ERIC Educational Resources Information Center

Kadar, Agnes; Shupe, Barbara

1977-01-01

Discussed are significant female contributors to scientific discovery. Fields of inquiry include astronomy, geology, meteorology, physics, chemistry, public health and home economics. The importance of appropriate role models for female students in science as teachers and scientists is stressed. (CS)
Predictive microbiology in food packaging applications

USDA-ARS?s Scientific Manuscript database

Predictive microbiology including growth, inactivation, surface transfer (or cross-contamination), and survival, plays important roles in understanding microbial food safety. Growth models may involve the growth potential of a specified pathogen under different stresses, e.g., temperature, pH, wate...
Studies of the major planet satellite systems

NASA Technical Reports Server (NTRS)

Frey, H.; Lowman, P. D.

1974-01-01

A summary is presented of the available data on the satellites of the major planets, including the currently most plausible models for several observed phenomena, for the planning of spacecraft missions to these objects. Some of the important questions likely to be solved by flyby and/or orbital missions to the giant planets are detailed, the importance of these studies to our understanding of the solar system as a whole is indicated.
Bond Graph Model of Cerebral Circulation: Toward Clinically Feasible Systemic Blood Flow Simulations

PubMed Central

Safaei, Soroush; Blanco, Pablo J.; Müller, Lucas O.; Hellevik, Leif R.; Hunter, Peter J.

2018-01-01

We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data. PMID:29551979
Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; O'Neill, Peter; Ponomarev, Artem; Carra, Claudio; Whalen, Mary; Pluth, Janice M.

2009-01-01

Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.
Assessing NARCCAP climate model effects using spatial confidence regions

PubMed Central

French, Joshua P.; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference. PMID:28936474
Studies of Trace Gas Chemical Cycles Using Inverse Methods and Global Chemical Transport Models

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

2003-01-01

We report progress in the first year, and summarize proposed work for the second year of the three-year dynamical-chemical modeling project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (b) utilization of inverse methods to determine these source/sink strengths using either MATCH (Model for Atmospheric Transport and Chemistry) which is based on analyzed observed wind fields or back-trajectories computed from these wind fields, (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important goals include determination of regional source strengths of methane, nitrous oxide, methyl bromide, and other climatically and chemically important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal protocol and its follow-on agreements and hydrohalocarbons now used as alternatives to the restricted halocarbons.

Intra-Engine Trace Species Chemistry

NASA Technical Reports Server (NTRS)

Waitz, Ian A.; Lukachko, S. P.; Chobot, A.; Miake-Lye, R. C.; Brown, R.

2002-01-01

Prompted by the needs of downstream plume-wake models, the Massachusetts Institute of Technology (MIT) and Aerodyne Research Incorporated (ART) initiated a collaborative effort, with funding from the NASA AEAP, to develop tools that would assist in understanding the fundamental drivers of chemical change within the intra-engine exhaust flow path. Efforts have been focused on the development of a modeling methodology that can adequately investigate the complex intra-engine environment. Over the history of this project, our research has increasingly pointed to the intra-engine environment as a possible site for important trace chemical activity. Modeling studies we initiated for the turbine and exhaust nozzle have contributed several important capabilities to the atmospheric effects of aviation assessment. These include a more complete understanding of aerosol precursor production, improved initial conditions for plume-wake modeling studies, and a more comprehensive analysis of ground-based test cell and in-flight exhaust measurement data. In addition, establishing a physical understanding of important flow and chemical processes through computational investigations may eventually assist in the design of engines to reduce undesirable species.
Antenna design for microwave hepatic ablation using an axisymmetric electromagnetic model

PubMed Central

Bertram, John M; Yang, Deshan; Converse, Mark C; Webster, John G; Mahvi, David M

2006-01-01

Background An axisymmetric finite element method (FEM) model was employed to demonstrate important techniques used in the design of antennas for hepatic microwave ablation (MWA). To effectively treat deep-seated hepatic tumors, these antennas should produce a highly localized specific absorption rate (SAR) pattern and be efficient radiators at approved generator frequencies. Methods and results As an example, a double slot choked antenna for hepatic MWA was designed and implemented using FEMLAB™ 3.0. Discussion This paper emphasizes the importance of factors that can affect simulation accuracy, which include boundary conditions, the dielectric properties of liver tissue, and mesh resolution. PMID:16504153
Visualization of the tire-soil interaction area by means of ObjectARX programming interface

NASA Astrophysics Data System (ADS)

Mueller, W.; Gruszczyński, M.; Raba, B.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.; Boniecki, P.

2014-04-01

The process of data visualization, important for their analysis, becomes problematic when large data sets generated via computer simulations are available. This problem concerns, among others, the models that describe the geometry of tire-soil interaction. For the purpose of a graphical representation of this area and implementation of various geometric calculations the authors have developed a plug-in application for AutoCAD, based on the latest technologies, including ObjectARX, LINQ and the use of Visual Studio platform. Selected programming tools offer a wide variety of IT structures that enable data visualization and data analysis and are important e.g. in model verification.
Advanced X-ray Spectroscopic Methods for Studying Iron-Sulfur-Containing Proteins and Model Complexes.

PubMed

DeBeer, Serena

2018-01-01

In this chapter, a brief overview of X-ray spectroscopic methods that may be utilized to obtain insight into the geometric and electronic structure of iron-sulfur proteins is provided. These methods include conventional methods, such as metal and ligand K-edge X-ray absorption, as well as more advanced methods including nonresonant and resonant X-ray emission. In each section, the basic information content of the spectra is highlighted and important experimental considerations are discussed. Throughout the chapter, recent applications to iron-sulfur-containing models and proteins are highlighted. © 2018 Elsevier Inc. All rights reserved.
Genetic variants associated with neurodegenerative Alzheimer disease in natural models.

PubMed

Salazar, Claudia; Valdivia, Gonzalo; Ardiles, Álvaro O; Ewer, John; Palacios, Adrián G

2016-02-26

The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans.
Modeling of turbulent separated flows for aerodynamic applications

NASA Technical Reports Server (NTRS)

Marvin, J. G.

1983-01-01

Steady, high speed, compressible separated flows modeled through numerical simulations resulting from solutions of the mass-averaged Navier-Stokes equations are reviewed. Emphasis is placed on benchmark flows that represent simplified (but realistic) aerodynamic phenomena. These include impinging shock waves, compression corners, glancing shock waves, trailing edge regions, and supersonic high angle of attack flows. A critical assessment of modeling capabilities is provided by comparing the numerical simulations with experiment. The importance of combining experiment, numerical algorithm, grid, and turbulence model to effectively develop this potentially powerful simulation technique is stressed.
Shape-based approach for the estimation of individual facial mimics in craniofacial surgery planning

NASA Astrophysics Data System (ADS)

Gladilin, Evgeny; Zachow, Stefan; Deuflhard, Peter; Hege, Hans-Christian

2002-05-01

Besides the static soft tissue prediction, the estimation of basic facial emotion expressions is another important criterion for the evaluation of craniofacial surgery planning. For a realistic simulation of facial mimics, an adequate biomechanical model of soft tissue including the mimic musculature is needed. In this work, we present an approach for the modeling of arbitrarily shaped muscles and the estimation of basic individual facial mimics, which is based on the geometrical model derived from the individual tomographic data and the general finite element modeling of soft tissue biomechanics.
Track structure model for damage to mammalian cell cultures during solar proton events

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Wilson, J. W.; Townsend, L. W.; Shinn, J. L.; Katz, R.

1992-01-01

Solar proton events (SPEs) occur infrequently and unpredictably, thus representing a potential hazard to interplanetary space missions. Biological damage from SPEs will be produced principally through secondary electron production in tissue, including important contributions due to delta rays from nuclear reaction products. We review methods for estimating the biological effectiveness of SPEs using a high energy proton model and the parametric cellular track model. Results of the model are presented for several of the historically largest flares using typical levels and body shielding.
Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

PubMed Central

Shao, Yuehjen E.

2014-01-01

Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone's health. Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models. PMID:24723804
The SRI-WEFA Soviet Econometric Model: Phase One Documentation

DTIC Science & Technology

1975-03-01

established prices. We also have an estimated equation for an end-use residual category which conceptually includes state grain reserves, other undis...forecasting. An important virtue of the econometric discipline is that it requires one first to conceptualize and estimate regularities of behavior...any de- scriptive analysis. Within the framwork of an econometric model, the analyst is able to discriminate among these "special events
Models of Financing the Continuing Vocational Training of Employees and Unemployed. Documentation of a LEONARDO-Project in Cooperation with Denmark, Germany, the Netherlands and Norway.

ERIC Educational Resources Information Center

Grunewald, Uwe, Ed.; Moraal, Dick, Ed.

This document contains papers from an international project in which models of financing the continuing vocational training (CVT) in Denmark, Germany, the Netherlands, and Norway were identified and examined. The following are among the papers included: "Important Results of the LEONARDO-Project (contributions by all project-partners)";…
The Role of Dosimetry in High-Quality EMI Risk Assessment

DTIC Science & Technology

2006-09-14

wireless communication usage and exposure to different parts of the body (especially for children and foetuses ), including multiple exposure from...Calculation of induced electric fields in pregnant women and in the foetus is urgently needed. Very little computation has been carried out on...advanced models of the pregnant human and the foetus with appropriate anatomical modelling. It is important to assess possible enhanced induction of
The Impact of College Student Socialization, Social Class, and Race on Need for Cognition

ERIC Educational Resources Information Center

Padgett, Ryan D.; Goodman, Kathleen M.; Johnson, Megan P.; Saichaie, Kem; Umbach, Paul D.; Pascarella, Ernest T.

2010-01-01

John C. Weidman (1989) was one of the first to argue that a socialization model is necessary to fully understand college impact. Weidman also contends that socioeconomic status (SES) is an important part of the socialization process for students. In fact, he placed such emphasis on SES that he included it in two locations within his model: (1)…
Effects of seasonal variation of photosynthetic capacity on the carbon fluxes of a temperate deciduous forest

Treesearch

David Medvigy; Su-Jong Jeong; Kenneth L. Clark; Nicholas S. Skowronski; Karina V. R. Schäfer

2013-01-01

Seasonal variation in photosynthetic capacity is an important part of the overall seasonal variability of temperate deciduous forests. However, it has only recently been introduced in a few terrestrial biosphere models, and many models still do not include it. The biases that result from this omission are not well understood. In this study, we use the Ecosystem...
Selected translated abstracts of Russian-language climate-change publications. 4: General circulation models (in English;Russian)

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

Burtis, M.D.; Razuvaev, V.N.; Sivachok, S.G.

1996-10-01

This report presents English-translated abstracts of important Russian-language literature concerning general circulation models as they relate to climate change. Into addition to the bibliographic citations and abstracts translated into English, this report presents the original citations and abstracts in Russian. Author and title indexes are included to assist the reader in locating abstracts of particular interest.
[Diagnostic rationalism. Views of general practitioners on fibromyalgia].

PubMed

Daehli, B

1993-09-20

Clinical practice is characterized by having to make numerous important decisions, including the diagnosis. In this study, general practitioners were asked to agree or to disagree with statements of fibromyalgia. The main purpose was to test the usefulness of two well-known models for decision-making when studying diagnosis in cases of uncertainty and scepticism. The results show that the models are inadequate to explain the decisions.
Complete Genome Sequence of the Methanococcus maripaludis Type Strain JJ (DSM 2067), a Model for Selenoprotein Synthesis in Archaea.

PubMed

Poehlein, Anja; Heym, Daniel; Quitzke, Vivien; Fersch, Julia; Daniel, Rolf; Rother, Michael

2018-04-05

Methanococcus maripaludis type strain JJ (DSM 2067) is an important organism because it serves as a model for primary energy metabolism and hydrogenotrophic methanogenesis and is amenable to genetic manipulation. The complete genome (1.7 Mb) harbors 1,815 predicted protein-encoding genes, including 9 encoding selenoproteins. Copyright © 2018 Poehlein et al.
Prediction of lake depth across a 17-state region in the United States

USGS Publications Warehouse

Oliver, Samantha K.; Soranno, Patricia A.; Fergus, C. Emi; Wagner, Tyler; Winslow, Luke A.; Scott, Caren E.; Webster, Katherine E.; Downing, John A.; Stanley, Emily H.

2016-01-01

Lake depth is an important characteristic for understanding many lake processes, yet it is unknown for the vast majority of lakes globally. Our objective was to develop a model that predicts lake depth using map-derived metrics of lake and terrestrial geomorphic features. Building on previous models that use local topography to predict lake depth, we hypothesized that regional differences in topography, lake shape, or sedimentation processes could lead to region-specific relationships between lake depth and the mapped features. We therefore used a mixed modeling approach that included region-specific model parameters. We built models using lake and map data from LAGOS, which includes 8164 lakes with maximum depth (Zmax) observations. The model was used to predict depth for all lakes ≥4 ha (n = 42 443) in the study extent. Lake surface area and maximum slope in a 100 m buffer were the best predictors of Zmax. Interactions between surface area and topography occurred at both the local and regional scale; surface area had a larger effect in steep terrain, so large lakes embedded in steep terrain were much deeper than those in flat terrain. Despite a large sample size and inclusion of regional variability, model performance (R2 = 0.29, RMSE = 7.1 m) was similar to other published models. The relative error varied by region, however, highlighting the importance of taking a regional approach to lake depth modeling. Additionally, we provide the largest known collection of observed and predicted lake depth values in the United States.
Numerical simulation of wave-current interaction under strong wind conditions

NASA Astrophysics Data System (ADS)

Larrañaga, Marco; Osuna, Pedro; Ocampo-Torres, Francisco Javier

2017-04-01

Although ocean surface waves are known to play an important role in the momentum and other scalar transfer between the atmosphere and the ocean, most operational numerical models do not explicitly include the terms of wave-current interaction. In this work, a numerical analysis about the relative importance of the processes associated with the wave-current interaction under strong off-shore wind conditions in Gulf of Tehuantepec (the southern Mexican Pacific) was carried out. The numerical system includes the spectral wave model WAM and the 3D hydrodynamic model POLCOMS, with the vertical turbulent mixing parametrized by the kappa-epsilon closure model. The coupling methodology is based on the vortex-force formalism. The hydrodynamic model was forced at the open boundaries using the HYCOM database and the wave model was forced at the open boundaries by remote waves from the southern Pacific. The atmospheric forcing for both models was provided by a local implementation of the WRF model, forced at the open boundaries using the CFSR database. The preliminary analysis of the model results indicates an effect of currents on the propagation of the swell throughout the study area. The Stokes-Coriolis term have an impact on the transient Ekman transport by modifying the Ekman spiral, while the Stokes drift has an effect on the momentum advection and the production of TKE, where the later induces a deepening of the mixing layer. This study is carried out in the framework of the project CONACYT CB-2015-01 255377 and RugDiSMar Project (CONACYT 155793).
Biogeochemical metabolic modeling of methanogenesis by Methanosarcina barkeri

NASA Astrophysics Data System (ADS)

Jensvold, Z. D.; Jin, Q.

2015-12-01

Methanogenesis, the biological process of methane production, is the final step of natural organic matter degradation. In studying natural methanogenesis, important questions include how fast methanogenesis proceeds and how methanogens adapt to the environment. To address these questions, we propose a new approach - biogeochemical reaction modeling - by simulating the metabolic networks of methanogens. Biogeochemical reaction modeling combines geochemical reaction modeling and genome-scale metabolic modeling. Geochemical reaction modeling focuses on the speciation of electron donors and acceptors in the environment, and therefore the energy available to methanogens. Genome-scale metabolic modeling predicts microbial rates and metabolic strategies. Specifically, this approach describes methanogenesis using an enzyme network model, and computes enzyme rates by accounting for both the kinetics and thermodynamics. The network model is simulated numerically to predict enzyme abundances and rates of methanogen metabolism. We applied this new approach to Methanosarcina barkeri strain fusaro, a model methanogen that makes methane by reducing carbon dioxide and oxidizing dihydrogen. The simulation results match well with the results of previous laboratory experiments, including the magnitude of proton motive force and the kinetic parameters of Methanosarcina barkeri. The results also predict that in natural environments, the configuration of methanogenesis network, including the concentrations of enzymes and metabolites, differs significantly from that under laboratory settings.

Dynamic model based on voltage transfer curve for pattern formation in dielectric barrier glow discharge

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

Li, Ben; He, Feng; Ouyang, Jiting, E-mail: jtouyang@bit.edu.cn

2015-12-15

Simulation work is very important for understanding the formation of self-organized discharge patterns. Previous works have witnessed different models derived from other systems for simulation of discharge pattern, but most of these models are complicated and time-consuming. In this paper, we introduce a convenient phenomenological dynamic model based on the basic dynamic process of glow discharge and the voltage transfer curve (VTC) to study the dielectric barrier glow discharge (DBGD) pattern. VTC is an important characteristic of DBGD, which plots the change of wall voltage after a discharge as a function of the initial total gap voltage. In the modeling,more » the combined effect of the discharge conditions is included in VTC, and the activation-inhibition effect is expressed by a spatial interaction term. Besides, the model reduces the dimensionality of the system by just considering the integration effect of current flow. All these greatly facilitate the construction of this model. Numerical simulations turn out to be in good accordance with our previous fluid modeling and experimental result.« less
One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587
Bubble suspension rheology and implications for conduit flow

NASA Astrophysics Data System (ADS)

Llewellin, E. W.; Manga, M.

2005-05-01

Bubbles are ubiquitous in magma during eruption and influence the rheology of the suspension. Despite this, bubble-suspension rheology is routinely ignored in conduit-flow and eruption models, potentially impairing accuracy and resulting in the loss of important phenomenological richness. The omission is due, in part, to a historical confusion in the literature concerning the effect of bubbles on the rheology of a liquid. This confusion has now been largely resolved and recently published studies have identified two viscous regimes: in regime 1, the viscosity of the two-phase (magma-gas) suspension increases as gas volume fraction ϕ increases; in regime 2, the viscosity of the suspension decreases as ϕ increases. The viscous regime for a deforming bubble suspension can be determined by calculating two dimensionless numbers, the capillary number Ca and the dynamic capillary number Cd. We provide a didactic explanation of how to include the effect of bubble-suspension rheology in continuum, conduit-flow models. Bubble-suspension rheology is reviewed and a practical rheological model is presented, followed by an algorithmic, step-by-step guide to including the rheological model in conduit-flow models. Preliminary results from conduit-flow models which have implemented the model presented are discussed and it is concluded that the effect of bubbles on magma rheology may be important in nature and results in a decrease of at least 800 m in calculated fragmentation-depth and an increase of between 40% and 250% in calculated eruption-rate compared with the assumption of Newtonian rheology.
Porphyry Copper Deposits of the World: Database and Grade and Tonnage Models, 2008

USGS Publications Warehouse

Singer, Donald A.; Berger, Vladimir I.; Moring, Barry C.

2008-01-01

This report is an update of earlier publications about porphyry copper deposits (Singer, Berger, and Moring, 2002; Singer, D.A., Berger, V.I., and Moring, B.C., 2005). The update was necessary because of new information about substantial increases in resources in some deposits and because we revised locations of some deposits so that they are consistent with images in GoogleEarth. In this report we have added new porphyry copper deposits and removed a few incorrectly classed deposits. In addition, some errors have been corrected and a number of deposits have had some information, such as grades, tonnages, locations, or ages revised. Colleagues have helped identify places where improvements were needed. Mineral deposit models are important in exploration planning and quantitative resource assessments for a number of reasons including: (1) grades and tonnages among deposit types are significantly different, and (2) many types occur in different geologic settings that can be identified from geologic maps. Mineral deposit models are the keystone in combining the diverse geoscience information on geology, mineral occurrences, geophysics, and geochemistry used in resource assessments and mineral exploration. Too few thoroughly explored mineral deposits are available in most local areas for reliable identification of the important geoscience variables or for robust estimation of undiscovered deposits?thus we need mineral-deposit models. Globally based deposit models allow recognition of important features because the global models demonstrate how common different features are. Well-designed and -constructed deposit models allow geologists to know from observed geologic environments the possible mineral deposit types that might exist, and allow economists to determine the possible economic viability of these resources in the region. Thus, mineral deposit models play the central role in transforming geoscience information to a form useful to policy makers. The foundation of mineral deposit models is information about known deposits. The purpose of this publication is to make this kind of information available in digital form for porphyry copper deposits. The consistently defined deposits in this file provide the foundation for grade and tonnage models included here and for mineral deposit density models (Singer and others, 2005: Singer, 2008).
Complete modeling of rotary ultrasonic motors actuated by traveling flexural waves

NASA Astrophysics Data System (ADS)

Bao, Xiaoqi; Bar-Cohen, Yoseph

2000-06-01

Ultrasonic rotary motors have the potential to meet this NASA need and they are developed as actuators for miniature telerobotic applications. These motors are being adapted for operation at the harsh space environments that include cryogenic temperatures and vacuum and analytical tools for the design of efficient motors are being developed. A hybrid analytical model was developed to address a complete ultrasonic motor as a system. Included in this model is the influence of the rotor dynamics, which was determined experimentally to be important to the motor performance. The analysis employs a 3D finite element model to express the dynamic characteristics of the stator with piezoelectric elements and the rotor. The details of the stator including the teeth, piezoelectric ceramic, geometry, bonding layer, etc. are included to support practical USM designs. A brush model is used for the interface layer and Coulomb's law for the friction between the stator and the rotor. The theoretical predictions were corroborated experimentally for the motor. In parallel, efforts have been made to determine the thermal and vacuum performance of these motors. To explore telerobotic applications for USMs a robotic arm was constructed with such motors.
Modeling of circulating fluised beds for post-combustion carbon capture

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

Lee, A.; Shadle, L.; Miller, D.

2011-01-01

A compartment based model for a circulating fluidized bed reactor has been developed based on experimental observations of riser hydrodynamics. The model uses a cluster based approach to describe the two-phase behavior of circulating fluidized beds. Fundamental mass balance equations have been derived to describe the movement of both gas and solids though the system. Additional work is being performed to develop the correlations required to describe the hydrodynamics of the system. Initial testing of the model with experimental data shows promising results and highlights the importance of including end effects within the model.
Diagnostic techniques in deflagration and detonation studies.

PubMed

Proud, William G; Williamson, David M; Field, John E; Walley, Stephen M

2015-12-01

Advances in experimental, high-speed techniques can be used to explore the processes occurring within energetic materials. This review describes techniques used to study a wide range of processes: hot-spot formation, ignition thresholds, deflagration, sensitivity and finally the detonation process. As this is a wide field the focus will be on small-scale experiments and quantitative studies. It is important that such studies are linked to predictive models, which inform the experimental design process. The stimuli range includes, thermal ignition, drop-weight, Hopkinson Bar and Plate Impact studies. Studies made with inert simulants are also included as these are important in differentiating between reactive response and purely mechanical behaviour.
Modeling and Optimization for Management of Intermittent Water Supply

NASA Astrophysics Data System (ADS)

Lieb, A. M.; Wilkening, J.; Rycroft, C.

2014-12-01

In many urban areas, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at controlling valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Gradient-based optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability at system endpoints.
Towards a portal and search engine to facilitate academic and research collaboration in engineering and education

NASA Astrophysics Data System (ADS)

Bonilla Villarreal, Isaura Nathaly

While international academic and research collaborations are of great importance at this time, it is not easy to find researchers in the engineering field that publish in languages other than English. Because of this disconnect, there exists a need for a portal to find Who's Who in Engineering Education in the Americas. The objective of this thesis is to built an object-oriented architecture for this proposed portal. The Unified Modeling Language (UML) model developed in this thesis incorporates the basic structure of a social network for academic purposes. Reverse engineering of three social networks portals yielded important aspects of their structures that have been incorporated in the proposed UML model. Furthermore, the present work includes a pattern for academic social networks..
Quantum mechanical modeling the emission pattern and polarization of nanoscale light emitting diodes.

PubMed

Wang, Rulin; Zhang, Yu; Bi, Fuzhen; Frauenheim, Thomas; Chen, GuanHua; Yam, ChiYung

2016-07-21

Understanding of the electroluminescence (EL) mechanism in optoelectronic devices is imperative for further optimization of their efficiency and effectiveness. Here, a quantum mechanical approach is formulated for modeling the EL processes in nanoscale light emitting diodes (LED). Based on non-equilibrium Green's function quantum transport equations, interactions with the electromagnetic vacuum environment are included to describe electrically driven light emission in the devices. The presented framework is illustrated by numerical simulations of a silicon nanowire LED device. EL spectra of the nanowire device under different bias voltages are obtained and, more importantly, the radiation pattern and polarization of optical emission can be determined using the current approach. This work is an important step forward towards atomistic quantum mechanical modeling of the electrically induced optical response in nanoscale systems.
Considering direct and indirect habitat influences on stream biota in eco-geomorphology research to better understand, model, and manage riverine ecosystems

NASA Astrophysics Data System (ADS)

Cienciala, P.; Nelson, A. D.

2017-12-01

The field of fluvial eco-geomorphology strives to improve the understanding of interactions between physical and biological processes in running waters. This body of research has greatly contributed to the advancement of integrated river science and management. Arguably, the most popular research themes in eco-geomorphology include hydrogemorphic controls of habitat quality and effects of disturbances such as floods, sediment transport events or sediment accumulation. However, in contrast to the related field of ecology, the distinction between direct and indirect mechanisms which may affect habitat quality and biotic response to disturbance has been poorly explored in eco-geomorphic research. This knowledge gap poses an important challenge for interpretations of field observations and model development. In this research, using the examples of benthic invertebrates and fish, we examine the importance of direct and indirect influences that geomorphic and hydraulic processes may exert on stream biota. We also investigate their implications for modeling of organism-habitat relationships. To achieve our goal, we integrate field and remote sensing data from montane streams in the Pacific Northwest region with habitat models. Preliminary results indicate that indirect hydrogeomorphic influences of stream organisms, such as those mediated by altered availability of food resources, can be as important as direct influences (e.g. physical disturbance). We suggest that these findings may also have important implications for modeling of riverine habitat.
Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants.

PubMed

Hagel, Jillian M; Mandal, Rupasri; Han, Beomsoo; Han, Jun; Dinsmore, Donald R; Borchers, Christoph H; Wishart, David S; Facchini, Peter J

2015-09-15

Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional (1)H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant species.
The generation and use of numerical shape models for irregular Solar System objects

NASA Technical Reports Server (NTRS)

Simonelli, Damon P.; Thomas, Peter C.; Carcich, Brian T.; Veverka, Joseph

1993-01-01

We describe a procedure that allows the efficient generation of numerical shape models for irregular Solar System objects, where a numerical model is simply a table of evenly spaced body-centered latitudes and longitudes and their associated radii. This modeling technique uses a combination of data from limbs, terminators, and control points, and produces shape models that have some important advantages over analytical shape models. Accurate numerical shape models make it feasible to study irregular objects with a wide range of standard scientific analysis techniques. These applications include the determination of moments of inertia and surface gravity, the mapping of surface locations and structural orientations, photometric measurement and analysis, the reprojection and mosaicking of digital images, and the generation of albedo maps. The capabilities of our modeling procedure are illustrated through the development of an accurate numerical shape model for Phobos and the production of a global, high-resolution, high-pass-filtered digital image mosaic of this Martian moon. Other irregular objects that have been modeled, or are being modeled, include the asteroid Gaspra and the satellites Deimos, Amalthea, Epimetheus, Janus, Hyperion, and Proteus.
Development of a hydraulic model of the human systemic circulation

NASA Technical Reports Server (NTRS)

Sharp, M. K.; Dharmalingham, R. K.

1999-01-01

Physical and numeric models of the human circulation are constructed for a number of objectives, including studies and training in physiologic control, interpretation of clinical observations, and testing of prosthetic cardiovascular devices. For many of these purposes it is important to quantitatively validate the dynamic response of the models in terms of the input impedance (Z = oscillatory pressure/oscillatory flow). To address this need, the authors developed an improved physical model. Using a computer study, the authors first identified the configuration of lumped parameter elements in a model of the systemic circulation; the result was a good match with human aortic input impedance with a minimum number of elements. Design, construction, and testing of a hydraulic model analogous to the computer model followed. Numeric results showed that a three element model with two resistors and one compliance produced reasonable matching without undue complication. The subsequent analogous hydraulic model included adjustable resistors incorporating a sliding plate to vary the flow area through a porous material and an adjustable compliance consisting of a variable-volume air chamber. The response of the hydraulic model compared favorably with other circulation models.
Literature Review and Assessment of Plant and Animal Transfer Factors Used in Performance Assessment Modeling

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

Robertson, David E.; Cataldo, Dominic A.; Napier, Bruce A.

2003-07-20

A literature review and assessment was conducted by Pacific Northwest National Laboratory (PNNL) to update information on plant and animal radionuclide transfer factors used in performance-assessment modeling. A group of 15 radionuclides was included in this review and assessment. The review is composed of four main sections, not including the Introduction. Section 2.0 provides a review of the critically important issue of physicochemical speciation and geochemistry of the radionuclides in natural soil-water systems as it relates to the bioavailability of the radionuclides. Section 3.0 provides an updated review of the parameters of importance in the uptake of radionuclides by plants,more » including root uptake via the soil-groundwater system and foliar uptake due to overhead irrigation. Section 3.0 also provides a compilation of concentration ratios (CRs) for soil-to-plant uptake for the 15 selected radionuclides. Section 4.0 provides an updated review on radionuclide uptake data for animal products related to absorption, homeostatic control, approach to equilibration, chemical and physical form, diet, and age. Compiled transfer coefficients are provided for cow’s milk, sheep’s milk, goat’s milk, beef, goat meat, pork, poultry, and eggs. Section 5.0 discusses the use of transfer coefficients in soil, plant, and animal modeling using regulatory models for evaluating radioactive waste disposal or decommissioned sites. Each section makes specific suggestions for future research in its area.« less
Knowledge management systems success in healthcare: Leadership matters.

PubMed

Ali, Nor'ashikin; Tretiakov, Alexei; Whiddett, Dick; Hunter, Inga

2017-01-01

To deliver high-quality healthcare doctors need to access, interpret, and share appropriate and localised medical knowledge. Information technology is widely used to facilitate the management of this knowledge in healthcare organisations. The purpose of this study is to develop a knowledge management systems success model for healthcare organisations. A model was formulated by extending an existing generic knowledge management systems success model by including organisational and system factors relevant to healthcare. It was tested by using data obtained from 263 doctors working within two district health boards in New Zealand. Of the system factors, knowledge content quality was found to be particularly important for knowledge management systems success. Of the organisational factors, leadership was the most important, and more important than incentives. Leadership promoted knowledge management systems success primarily by positively affecting knowledge content quality. Leadership also promoted knowledge management use for retrieval, which should lead to the use of that better quality knowledge by the doctors, ultimately resulting in better outcomes for patients. Copyright Â© 2016 Elsevier Ireland Ltd. All rights reserved.
On the physical Hilbert space of loop quantum cosmology

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

Noui, Karim; Perez, Alejandro; Vandersloot, Kevin

2005-02-15

In this paper we present a model of Riemannian loop quantum cosmology with a self-adjoint quantum scalar constraint. The physical Hilbert space is constructed using refined algebraic quantization. When matter is included in the form of a cosmological constant, the model is exactly solvable and we show explicitly that the physical Hilbert space is separable, consisting of a single physical state. We extend the model to the Lorentzian sector and discuss important implications for standard loop quantum cosmology.
Application of new nuclear de-excitation model of PHITS for prediction of isomer yield and prompt gamma-ray production

NASA Astrophysics Data System (ADS)

Ogawa, Tatsuhiko; Hashimoto, Shintaro; Sato, Tatsuhiko; Niita, Koji

2014-06-01

A new nuclear de-excitation model, intended for accurate simulation of isomeric transition of excited nuclei, was incorporated into PHITS and applied to various situations to clarify the impact of the model. The case studies show that precise treatment of gamma de-excitation and consideration for isomer production are important for various applications such as detector performance prediction, radiation shielding calculations and the estimation of radioactive inventory including isomers.
Constraints on vertical transport near the polar summer mesopause from PMC observations and modelling

NASA Astrophysics Data System (ADS)

Wilms, H.; Rapp, M.; Kirsch, A.

2016-12-01

The comparison of microphysical simulations of polar mesospheric cloud properties with ground based and satellite borne observations suggests that vertical wind variance imposed by gravity waves is an important prerequisite to realistically model PMC properties. This paper reviews the available observational evidence of vertical wind measurements at the polar summer mesopause (including their frequency content). Corresponding results are compared to vertical wind variance from several global models and implications for the transport of trace constituents in this altitude region are discussed.
In silico cancer modeling: is it ready for primetime?

PubMed Central

Deisboeck, Thomas S; Zhang, Le; Yoon, Jeongah; Costa, Jose

2011-01-01

SUMMARY At the dawn of the era of personalized, systems-driven medicine, computational or in silico modeling and the simulation of disease processes is becoming increasingly important for hypothesis generation and data integration in both experiment and clinics alike. Arguably, this is nowhere more visible than in oncology. To illustrate the field’s vast potential as well as its current limitations we briefly review selected works on modeling malignant brain tumors. Implications for clinical practice, including trial design and outcome prediction are also discussed. PMID:18852721

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Sample records for model includes important

Abstract