Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team☆

PubMed Central

Harrison, David A.; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B.; Gwinnutt, Carl; Nolan, Jerry P.; Rowan, Kathryn M.

2014-01-01

Aim The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Methods Risk models for two outcomes—return of spontaneous circulation (ROSC) for greater than 20 min and survival to hospital discharge—were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. Results 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC > 20 min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC > 20 min (c index 0.81 versus 0.72). Conclusions Validated risk models for ROSC > 20 min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. PMID:24830872

Rethinking Validation in Complex High-Stakes Assessment Contexts

ERIC Educational Resources Information Center

Koch, Martha J.; DeLuca, Christopher

2012-01-01

In this article we rethink validation within the complex contexts of high-stakes assessment. We begin by considering the utility of existing models for validation and argue that these models tend to overlook some of the complexities inherent to assessment use, including the multiple interpretations of assessment purposes and the potential…

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Sebok, Angelia; Gore, Brian; Hooey, Becky

2012-01-01

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

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

Smith, Kandler A; Santhanagopalan, Shriram; Yang, Chuanbo

Computer models are helping to accelerate the design and validation of next generation batteries and provide valuable insights not possible through experimental testing alone. Validated 3-D physics-based models exist for predicting electrochemical performance, thermal and mechanical response of cells and packs under normal and abuse scenarios. The talk describes present efforts to make the models better suited for engineering design, including improving their computation speed, developing faster processes for model parameter identification including under aging, and predicting the performance of a proposed electrode material recipe a priori using microstructure models.

Model Validation | Center for Cancer Research

Cancer.gov

Research Investigation and Animal Model Validation This activity is also under development and thus far has included increasing pathology resources, delivering pathology services, as well as using imaging and surgical methods to develop and refine animal models in collaboration with other CCR investigators.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Validating Computational Human Behavior Models: Consistency and Accuracy Issues

DTIC Science & Technology

2004-06-01

includes a discussion of SME demographics, content, and organization of the datasets . This research generalizes data from two pilot studies and two base...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject

Validity of Basic Electronic 1 Module Integrated Character Value Based on Conceptual Change Teaching Model to Increase Students Physics Competency in STKIP PGRI West Sumatera

NASA Astrophysics Data System (ADS)

Hidayati, A.; Rahmi, A.; Yohandri; Ratnawulan

2018-04-01

The importance of teaching materials in accordance with the characteristics of students became the main reason for the development of basic electronics I module integrated character values based on conceptual change teaching model. The module development in this research follows the development procedure of Plomp which includes preliminary research, prototyping phase and assessment phase. In the first year of this research, the module is validated. Content validity is seen from the conformity of the module with the development theory in accordance with the demands of learning model characteristics. The validity of the construct is seen from the linkage and consistency of each module component developed with the characteristic of the integrated learning model of character values obtained through validator assessment. The average validation value assessed by the validator belongs to a very valid category. Based on the validator assessment then revised the basic electronics I module integrated character values based on conceptual change teaching model.

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…

Mathematical multi-scale model of the cardiovascular system including mitral valve dynamics. Application to ischemic mitral insufficiency

PubMed Central

2011-01-01

Background Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions. Methods A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate "open on pressure, close on flow" law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle. Results Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends. Conclusions The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves. PMID:21942971

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Unremarked or Unperformed? Systematic Review on Reporting of Validation Efforts of Health Economic Decision Models in Seasonal Influenza and Early Breast Cancer.

PubMed

de Boer, Pieter T; Frederix, Geert W J; Feenstra, Talitha L; Vemer, Pepijn

2016-09-01

Transparent reporting of validation efforts of health economic models give stakeholders better insight into the credibility of model outcomes. In this study we reviewed recently published studies on seasonal influenza and early breast cancer in order to gain insight into the reporting of model validation efforts in the overall health economic literature. A literature search was performed in Pubmed and Embase to retrieve health economic modelling studies published between 2008 and 2014. Reporting on model validation was evaluated by checking for the word validation, and by using AdViSHE (Assessment of the Validation Status of Health Economic decision models), a tool containing a structured list of relevant items for validation. Additionally, we contacted corresponding authors to ask whether more validation efforts were performed other than those reported in the manuscripts. A total of 53 studies on seasonal influenza and 41 studies on early breast cancer were included in our review. The word validation was used in 16 studies (30 %) on seasonal influenza and 23 studies (56 %) on early breast cancer; however, in a minority of studies, this referred to a model validation technique. Fifty-seven percent of seasonal influenza studies and 71 % of early breast cancer studies reported one or more validation techniques. Cross-validation of study outcomes was found most often. A limited number of studies reported on model validation efforts, although good examples were identified. Author comments indicated that more validation techniques were performed than those reported in the manuscripts. Although validation is deemed important by many researchers, this is not reflected in the reporting habits of health economic modelling studies. Systematic reporting of validation efforts would be desirable to further enhance decision makers' confidence in health economic models and their outcomes.

Derivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality rates.

PubMed

Bray, Benjamin D; Campbell, James; Cloud, Geoffrey C; Hoffman, Alex; James, Martin; Tyrrell, Pippa J; Wolfe, Charles D A; Rudd, Anthony G

2014-11-01

Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data. Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots. Two final models were derived. Model A included age (<60, 60-69, 70-79, 80-89, and ≥90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84-0.89) and 0.86 (95% confidence interval, 0.83-0.89) for models A and B, respectively. We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction. © 2014 American Heart Association, Inc.

Calibration and validation of a spar-type floating offshore wind turbine model using the FAST dynamic simulation tool

DOE PAGES

Browning, J. R.; Jonkman, J.; Robertson, A.; ...

2014-12-16

In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50 th scalemore » in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.« less

Power Plant Model Validation Tool

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

The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool usesmore » PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and The tool automatically generates reports« less

Temporal and external validation of a prediction model for adverse outcomes among inpatients with diabetes.

PubMed

Adderley, N J; Mallett, S; Marshall, T; Ghosh, S; Rayman, G; Bellary, S; Coleman, J; Akiboye, F; Toulis, K A; Nirantharakumar, K

2018-06-01

To temporally and externally validate our previously developed prediction model, which used data from University Hospitals Birmingham to identify inpatients with diabetes at high risk of adverse outcome (mortality or excessive length of stay), in order to demonstrate its applicability to other hospital populations within the UK. Temporal validation was performed using data from University Hospitals Birmingham and external validation was performed using data from both the Heart of England NHS Foundation Trust and Ipswich Hospital. All adult inpatients with diabetes were included. Variables included in the model were age, gender, ethnicity, admission type, intensive therapy unit admission, insulin therapy, albumin, sodium, potassium, haemoglobin, C-reactive protein, estimated GFR and neutrophil count. Adverse outcome was defined as excessive length of stay or death. Model discrimination in the temporal and external validation datasets was good. In temporal validation using data from University Hospitals Birmingham, the area under the curve was 0.797 (95% CI 0.785-0.810), sensitivity was 70% (95% CI 67-72) and specificity was 75% (95% CI 74-76). In external validation using data from Heart of England NHS Foundation Trust, the area under the curve was 0.758 (95% CI 0.747-0.768), sensitivity was 73% (95% CI 71-74) and specificity was 66% (95% CI 65-67). In external validation using data from Ipswich, the area under the curve was 0.736 (95% CI 0.711-0.761), sensitivity was 63% (95% CI 59-68) and specificity was 69% (95% CI 67-72). These results were similar to those for the internally validated model derived from University Hospitals Birmingham. The prediction model to identify patients with diabetes at high risk of developing an adverse event while in hospital performed well in temporal and external validation. The externally validated prediction model is a novel tool that can be used to improve care pathways for inpatients with diabetes. Further research to assess clinical utility is needed. © 2018 Diabetes UK.

Less is more? Assessing the validity of the ICD-11 model of PTSD across multiple trauma samples

PubMed Central

Hansen, Maj; Hyland, Philip; Armour, Cherie; Shevlin, Mark; Elklit, Ask

2015-01-01

Background In the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), the symptom profile of posttraumatic stress disorder (PTSD) was expanded to include 20 symptoms. An alternative model of PTSD is outlined in the proposed 11th edition of the International Classification of Diseases (ICD-11) that includes just six symptoms. Objectives and method The objectives of the current study are: 1) to independently investigate the fit of the ICD-11 model of PTSD, and three DSM-5-based models of PTSD, across seven different trauma samples (N=3,746) using confirmatory factor analysis; 2) to assess the concurrent validity of the ICD-11 model of PTSD; and 3) to determine if there are significant differences in diagnostic rates between the ICD-11 guidelines and the DSM-5 criteria. Results The ICD-11 model of PTSD was found to provide excellent model fit in six of the seven trauma samples, and tests of factorial invariance showed that the model performs equally well for males and females. DSM-5 models provided poor fit of the data. Concurrent validity was established as the ICD-11 PTSD factors were all moderately to strongly correlated with scores of depression, anxiety, dissociation, and aggression. Levels of association were similar for ICD-11 and DSM-5 suggesting that explanatory power is not affected due to the limited number of items included in the ICD-11 model. Diagnostic rates were significantly lower according to ICD-11 guidelines compared to the DSM-5 criteria. Conclusions The proposed factor structure of the ICD-11 model of PTSD appears valid across multiple trauma types, possesses good concurrent validity, and is more stringent in terms of diagnosis compared to the DSM-5 criteria. PMID:26450830

Less is more? Assessing the validity of the ICD-11 model of PTSD across multiple trauma samples.

PubMed

Hansen, Maj; Hyland, Philip; Armour, Cherie; Shevlin, Mark; Elklit, Ask

2015-01-01

In the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), the symptom profile of posttraumatic stress disorder (PTSD) was expanded to include 20 symptoms. An alternative model of PTSD is outlined in the proposed 11th edition of the International Classification of Diseases (ICD-11) that includes just six symptoms. The objectives of the current study are: 1) to independently investigate the fit of the ICD-11 model of PTSD, and three DSM-5-based models of PTSD, across seven different trauma samples (N=3,746) using confirmatory factor analysis; 2) to assess the concurrent validity of the ICD-11 model of PTSD; and 3) to determine if there are significant differences in diagnostic rates between the ICD-11 guidelines and the DSM-5 criteria. The ICD-11 model of PTSD was found to provide excellent model fit in six of the seven trauma samples, and tests of factorial invariance showed that the model performs equally well for males and females. DSM-5 models provided poor fit of the data. Concurrent validity was established as the ICD-11 PTSD factors were all moderately to strongly correlated with scores of depression, anxiety, dissociation, and aggression. Levels of association were similar for ICD-11 and DSM-5 suggesting that explanatory power is not affected due to the limited number of items included in the ICD-11 model. Diagnostic rates were significantly lower according to ICD-11 guidelines compared to the DSM-5 criteria. The proposed factor structure of the ICD-11 model of PTSD appears valid across multiple trauma types, possesses good concurrent validity, and is more stringent in terms of diagnosis compared to the DSM-5 criteria.

A clinical prognostic model compared to the newly adopted UICC staging in an independent validation cohort of P16 negative/positive head and neck cancer patients.

PubMed

Rasmussen, Jacob H; Håkansson, Katrin; Rasmussen, Gregers B; Vogelius, Ivan R; Friborg, Jeppe; Fischer, Barbara M; Bentzen, Søren M; Specht, Lena

2018-06-01

A previously published prognostic model in patients with head and neck squamous cell carcinoma (HNSCC) was validated in both a p16-negative and a p16-positive independent patient cohort and the performance was compared with the newly adopted 8th edition of the UICC staging system. Consecutive patients with HNSCC treated at a single institution from 2005 to 2012 were included. The cohort was divided in three. 1.) Training cohort, patients treated from 2005 to 2009 excluding patients with p16-positive oropharyngeal squamous cell carcinomas (OPSCC); 2.) A p16-negative validation cohort and 3.) A p16-positive validation cohort. A previously published prognostic model (clinical model) with the significant covariates (smoking status, FDG uptake, and tumor volume) was refitted in the training cohort and validated in the two validation cohorts. The clinical model was used to generate four risk groups based on the predicted risk of disease recurrence after 2 years and the performance was compared with UICC staging 8th edition using concordance index. Overall 568 patients were included. Compared to UICC the clinical model had a significantly better concordance index in the p16-negative validation cohort (AUC = 0.63 for UICC and AUC = 0.73 for the clinical model; p = 0.003) and a borderline significantly better concordance index in the p16-positive cohort (AUC = 0.63 for UICC and 0.72 for the clinical model; p = 0.088). The validated clinical model provided a better prognostication of risk of disease recurrence than UICC stage in the p16-negative validation cohort, and similar prognostication as the newly adopted 8th edition of the UICC staging in the p16-positive patient cohort. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

An improved snow scheme for the ECMWF land surface model: Description and offline validation

Treesearch

Emanuel Dutra; Gianpaolo Balsamo; Pedro Viterbo; Pedro M. A. Miranda; Anton Beljaars; Christoph Schar; Kelly Elder

2010-01-01

A new snow scheme for the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model has been tested and validated. The scheme includes a new parameterization of snow density, incorporating a liquid water reservoir, and revised formulations for the subgrid snow cover fraction and snow albedo. Offline validation (covering a wide range of spatial and...

A Framework for Validating Traffic Simulation Models at the Vehicle Trajectory Level

DOT National Transportation Integrated Search

2017-03-01

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

Crash Certification by Analysis - Are We There Yet?

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.; Lyle, Karen H.

2006-01-01

This paper addresses the issue of crash certification by analysis. This broad topic encompasses many ancillary issues including model validation procedures, uncertainty in test data and analysis models, probabilistic techniques for test-analysis correlation, verification of the mathematical formulation, and establishment of appropriate qualification requirements. This paper will focus on certification requirements for crashworthiness of military helicopters; capabilities of the current analysis codes used for crash modeling and simulation, including some examples of simulations from the literature to illustrate the current approach to model validation; and future directions needed to achieve "crash certification by analysis."

Experimental Validation and Combustion Modeling of a JP-8 Surrogate in a Single Cylinder Diesel Engine

DTIC Science & Technology

2014-04-15

SINGLE CYLINDER DIESEL ENGINE Amit Shrestha, Umashankar Joshi, Ziliang Zheng, Tamer Badawy, Naeim A. Henein, Wayne State University, Detroit, MI, USA...13-03-2014 4. TITLE AND SUBTITLE EXPERIMENTAL VALIDATION AND COMBUSTION MODELING OF A JP-8 SURROGATE IN A SINGLE CYLINDER DIESEL ENGINE 5a...INTERNATIONAL UNCLASSIFIED • Validate a two-component JP-8 surrogate in a single cylinder diesel engine. Validation parameters include – Ignition delay

The Development and Validation of a New Land Surface Model for Regional and Global Climate Modeling

NASA Astrophysics Data System (ADS)

Lynch-Stieglitz, Marc

1995-11-01

A new land-surface scheme intended for use in mesoscale and global climate models has been developed and validated. The ground scheme consists of 6 soil layers. Diffusion and a modified tipping bucket model govern heat and water flow respectively. A 3 layer snow model has been incorporated into a modified BEST vegetation scheme. TOPMODEL equations and Digital Elevation Model data are used to generate baseflow which supports lowland saturated zones. Soil moisture heterogeneity represented by saturated lowlands subsequently impacts watershed evapotranspiration, the partitioning of surface fluxes, and the development of the storm hydrograph. Five years of meteorological and hydrological data from the Sleepers river watershed located in the eastern highlands of Vermont where winter snow cover is significant were then used to drive and validate the new scheme. Site validation data were sufficient to evaluate model performance with regard to various aspects of the watershed water balance, including snowpack growth/ablation, the spring snowmelt hydrograph, storm hydrographs, and the seasonal development of watershed evapotranspiration and soil moisture. By including topographic effects, not only are the main spring hydrographs and individual storm hydrographs adequately resolved, but the mechanisms generating runoff are consistent with current views of hydrologic processes. The seasonal movement of the mean water table depth and the saturated area of the watershed are consistent with site data and the overall model hydroclimatology, including the surface fluxes, seems reasonable.

[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

Highlights of Transient Plume Impingement Model Validation and Applications

NASA Technical Reports Server (NTRS)

Woronowicz, Michael

2011-01-01

This paper describes highlights of an ongoing validation effort conducted to assess the viability of applying a set of analytic point source transient free molecule equations to model behavior ranging from molecular effusion to rocket plumes. The validation effort includes encouraging comparisons to both steady and transient studies involving experimental data and direct simulation Monte Carlo results. Finally, this model is applied to describe features of two exotic transient scenarios involving NASA Goddard Space Flight Center satellite programs.

75 FR 53371 - Liquefied Natural Gas Facilities: Obtaining Approval of Alternative Vapor-Gas Dispersion Models

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-31

... factors as the approved models, are validated by experimental test data, and receive the Administrator's... stage of the MEP involves applying the model against a database of experimental test cases including..., particularly the requirement for validation by experimental test data. That guidance is based on the MEP's...

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

PubMed

Willis, Michael; Johansen, Pierre; Nilsson, Andreas; Asseburg, Christian

2017-03-01

The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

Description of a Website Resource for Turbulence Modeling Verification and Validation

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Smith, Brian R.; Huang, George P.

2010-01-01

The activities of the Turbulence Model Benchmarking Working Group - which is a subcommittee of the American Institute of Aeronautics and Astronautics (AIAA) Fluid Dynamics Technical Committee - are described. The group s main purpose is to establish a web-based repository for Reynolds-averaged Navier-Stokes turbulence model documentation, including verification and validation cases. This turbulence modeling resource has been established based on feedback from a survey on what is needed to achieve consistency and repeatability in turbulence model implementation and usage, and to document and disseminate information on new turbulence models or improvements to existing models. The various components of the website are described in detail: description of turbulence models, turbulence model readiness rating system, verification cases, validation cases, validation databases, and turbulence manufactured solutions. An outline of future plans of the working group is also provided.

Proof of Concept for the Trajectory-Level Validation Framework for Traffic Simulation Models

DOT National Transportation Integrated Search

2017-10-30

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

Testing the validity of the International Atomic Energy Agency (IAEA) safety culture model.

PubMed

López de Castro, Borja; Gracia, Francisco J; Peiró, José M; Pietrantoni, Luca; Hernández, Ana

2013-11-01

This paper takes the first steps to empirically validate the widely used model of safety culture of the International Atomic Energy Agency (IAEA), composed of five dimensions, further specified by 37 attributes. To do so, three independent and complementary studies are presented. First, 290 students serve to collect evidence about the face validity of the model. Second, 48 experts in organizational behavior judge its content validity. And third, 468 workers in a Spanish nuclear power plant help to reveal how closely the theoretical five-dimensional model can be replicated. Our findings suggest that several attributes of the model may not be related to their corresponding dimensions. According to our results, a one-dimensional structure fits the data better than the five dimensions proposed by the IAEA. Moreover, the IAEA model, as it stands, seems to have rather moderate content validity and low face validity. Practical implications for researchers and practitioners are included. Copyright © 2013 Elsevier Ltd. All rights reserved.

CFD validation experiments at McDonnell Aircraft Company

NASA Technical Reports Server (NTRS)

Verhoff, August

1987-01-01

Information is given in viewgraph form on computational fluid dynamics (CFD) validation experiments at McDonnell Aircraft Company. Topics covered include a high speed research model, a supersonic persistence fighter model, a generic fighter wing model, surface grids, force and moment predictions, surface pressure predictions, forebody models with 65 degree clipped delta wings, and the low aspect ratio wing/body experiment.

Cross-validation pitfalls when selecting and assessing regression and classification models.

PubMed

Krstajic, Damjan; Buturovic, Ljubomir J; Leahy, David E; Thomas, Simon

2014-03-29

We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error.

Development of Learning Models Based on Problem Solving and Meaningful Learning Standards by Expert Validity for Animal Development Course

NASA Astrophysics Data System (ADS)

Lufri, L.; Fitri, R.; Yogica, R.

2018-04-01

The purpose of this study is to produce a learning model based on problem solving and meaningful learning standards by expert assessment or validation for the course of Animal Development. This research is a development research that produce the product in the form of learning model, which consist of sub product, namely: the syntax of learning model and student worksheets. All of these products are standardized through expert validation. The research data is the level of validity of all sub products obtained using questionnaire, filled by validators from various field of expertise (field of study, learning strategy, Bahasa). Data were analysed using descriptive statistics. The result of the research shows that the problem solving and meaningful learning model has been produced. Sub products declared appropriate by expert include the syntax of learning model and student worksheet.

On the validation of a code and a turbulence model appropriate to circulation control airfoils

NASA Technical Reports Server (NTRS)

Viegas, J. R.; Rubesin, M. W.; Maccormack, R. W.

1988-01-01

A computer code for calculating flow about a circulation control airfoil within a wind tunnel test section has been developed. This code is being validated for eventual use as an aid to design such airfoils. The concept of code validation being used is explained. The initial stages of the process have been accomplished. The present code has been applied to a low-subsonic, 2-D flow about a circulation control airfoil for which extensive data exist. Two basic turbulence models and variants thereof have been successfully introduced into the algorithm, the Baldwin-Lomax algebraic and the Jones-Launder two-equation models of turbulence. The variants include adding a history of the jet development for the algebraic model and adding streamwise curvature effects for both models. Numerical difficulties and difficulties in the validation process are discussed. Turbulence model and code improvements to proceed with the validation process are also discussed.

Phase 1 Validation Testing and Simulation for the WEC-Sim Open Source Code

NASA Astrophysics Data System (ADS)

Ruehl, K.; Michelen, C.; Gunawan, B.; Bosma, B.; Simmons, A.; Lomonaco, P.

2015-12-01

WEC-Sim is an open source code to model wave energy converters performance in operational waves, developed by Sandia and NREL and funded by the US DOE. The code is a time-domain modeling tool developed in MATLAB/SIMULINK using the multibody dynamics solver SimMechanics, and solves the WEC's governing equations of motion using the Cummins time-domain impulse response formulation in 6 degrees of freedom. The WEC-Sim code has undergone verification through code-to-code comparisons; however validation of the code has been limited to publicly available experimental data sets. While these data sets provide preliminary code validation, the experimental tests were not explicitly designed for code validation, and as a result are limited in their ability to validate the full functionality of the WEC-Sim code. Therefore, dedicated physical model tests for WEC-Sim validation have been performed. This presentation provides an overview of the WEC-Sim validation experimental wave tank tests performed at the Oregon State University's Directional Wave Basin at Hinsdale Wave Research Laboratory. Phase 1 of experimental testing was focused on device characterization and completed in Fall 2015. Phase 2 is focused on WEC performance and scheduled for Winter 2015/2016. These experimental tests were designed explicitly to validate the performance of WEC-Sim code, and its new feature additions. Upon completion, the WEC-Sim validation data set will be made publicly available to the wave energy community. For the physical model test, a controllable model of a floating wave energy converter has been designed and constructed. The instrumentation includes state-of-the-art devices to measure pressure fields, motions in 6 DOF, multi-axial load cells, torque transducers, position transducers, and encoders. The model also incorporates a fully programmable Power-Take-Off system which can be used to generate or absorb wave energy. Numerical simulations of the experiments using WEC-Sim will be presented. These simulations highlight the code features included in the latest release of WEC-Sim (v1.2), including: wave directionality, nonlinear hydrostatics and hydrodynamics, user-defined wave elevation time-series, state space radiation, and WEC-Sim compatibility with BEMIO (open source AQWA/WAMI/NEMOH coefficient parser).

Improving the Validity of Activity of Daily Living Dependency Risk Assessment

PubMed Central

Clark, Daniel O.; Stump, Timothy E.; Tu, Wanzhu; Miller, Douglas K.

2015-01-01

Objectives Efforts to prevent activity of daily living (ADL) dependency may be improved through models that assess older adults’ dependency risk. We evaluated whether cognition and gait speed measures improve the predictive validity of interview-based models. Method Participants were 8,095 self-respondents in the 2006 Health and Retirement Survey who were aged 65 years or over and independent in five ADLs. Incident ADL dependency was determined from the 2008 interview. Models were developed using random 2/3rd cohorts and validated in the remaining 1/3rd. Results Compared to a c-statistic of 0.79 in the best interview model, the model including cognitive measures had c-statistics of 0.82 and 0.80 while the best fitting gait speed model had c-statistics of 0.83 and 0.79 in the development and validation cohorts, respectively. Conclusion Two relatively brief models, one that requires an in-person assessment and one that does not, had excellent validity for predicting incident ADL dependency but did not significantly improve the predictive validity of the best fitting interview-based models. PMID:24652867

Independent external validation of predictive models for urinary dysfunction following external beam radiotherapy of the prostate: Issues in model development and reporting.

PubMed

Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; Kennedy, Angel; Joseph, David J; Denham, James W

2016-08-01

Most predictive models are not sufficiently validated for prospective use. We performed independent external validation of published predictive models for urinary dysfunctions following radiotherapy of the prostate. Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed. 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients. Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings.

PubMed

Cowling, Benjamin J; Muller, Matthew P; Wong, Irene O L; Ho, Lai-Ming; Lo, Su-Vui; Tsang, Thomas; Lam, Tai Hing; Louie, Marie; Leung, Gabriel M

2006-07-24

An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.

Validating soil denitrification models based on laboratory N_{2} and N_{2}O fluxes and underlying processes derived by stable isotope approaches

NASA Astrophysics Data System (ADS)

Well, Reinhard; Böttcher, Jürgen; Butterbach-Bahl, Klaus; Dannenmann, Michael; Deppe, Marianna; Dittert, Klaus; Dörsch, Peter; Horn, Marcus; Ippisch, Olaf; Mikutta, Robert; Müller, Carsten; Müller, Christoph; Senbayram, Mehmet; Vogel, Hans-Jörg; Wrage-Mönnig, Nicole

2016-04-01

Robust denitrification data suitable to validate soil N2 fluxes in denitrification models are scarce due to methodical limitations and the extreme spatio-temporal heterogeneity of denitrification in soils. Numerical models have become essential tools to predict denitrification at different scales. Model performance could either be tested for total gaseous flux (NO + N2O + N2), individual denitrification products (e.g. N2O and/or NO) or for the effect of denitrification factors (e.g. C-availability, respiration, diffusivity, anaerobic volume, etc.). While there are numerous examples for validating N2O fluxes, there are neither robust field data of N2 fluxes nor sufficiently resolved measurements of control factors used as state variables in the models. To the best of our knowledge there has been only one published validation of modelled soil N2 flux by now, using a laboratory data set to validate an ecosystem model. Hence there is a need for validation data at both, the mesocosm and the field scale including validation of individual denitrification controls. Here we present the concept for collecting model validation data which is be part of the DFG-research unit "Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM)" starting this year. We will use novel approaches including analysis of stable isotopes, microbial communities, pores structure and organic matter fractions to provide denitrification data sets comprising as much detail on activity and regulation as possible as a basis to validate existing and calibrate new denitrification models that are applied and/or developed by DASIM subprojects. The basic idea is to simulate "field-like" conditions as far as possible in an automated mesocosm system without plants in order to mimic processes in the soil parts not significantly influenced by the rhizosphere (rhizosphere soils are studied by other DASIM projects). Hence, to allow model testing in a wide range of conditions, denitrification control factors will be varied in the initial settings (pore volume, plant residues, mineral N, pH) but also over time, where moisture, temperature, and mineral N will be manipulated according to typical time patterns in the field. This will be realized by including precipitation events, fertilization (via irrigation), drainage (via water potential) and temperature in the course of incubations. Moreover, oxygen concentration will be varied to simulate anaerobic events. These data will be used to calibrate the newly to develop DASIM models as well as existing denitrification models. One goal of DASIM is to create a public data base as a joint basis for model testing by denitrification modellers. Therefore we invite contributions of suitable data-sets from the scientific community. Requirements will be briefly outlined.

Does my patient have chronic Chagas disease? Development and temporal validation of a diagnostic risk score.

PubMed

Brasil, Pedro Emmanuel Alvarenga Americano do; Xavier, Sergio Salles; Holanda, Marcelo Teixeira; Hasslocher-Moreno, Alejandro Marcel; Braga, José Ueleres

2016-01-01

With the globalization of Chagas disease, unexperienced health care providers may have difficulties in identifying which patients should be examined for this condition. This study aimed to develop and validate a diagnostic clinical prediction model for chronic Chagas disease. This diagnostic cohort study included consecutive volunteers suspected to have chronic Chagas disease. The clinical information was blindly compared to serological tests results, and a logistic regression model was fit and validated. The development cohort included 602 patients, and the validation cohort included 138 patients. The Chagas disease prevalence was 19.9%. Sex, age, referral from blood bank, history of living in a rural area, recognizing the kissing bug, systemic hypertension, number of siblings with Chagas disease, number of relatives with a history of stroke, ECG with low voltage, anterosuperior divisional block, pathologic Q wave, right bundle branch block, and any kind of extrasystole were included in the final model. Calibration and discrimination in the development and validation cohorts (ROC AUC 0.904 and 0.912, respectively) were good. Sensitivity and specificity analyses showed that specificity reaches at least 95% above the predicted 43% risk, while sensitivity is at least 95% below the predicted 7% risk. Net benefit decision curves favor the model across all thresholds. A nomogram and an online calculator (available at http://shiny.ipec.fiocruz.br:3838/pedrobrasil/chronic_chagas_disease_prediction/) were developed to aid in individual risk estimation.

Development and validation of P-MODTRAN7 and P-MCScene, 1D and 3D polarimetric radiative transfer models

NASA Astrophysics Data System (ADS)

Hawes, Frederick T.; Berk, Alexander; Richtsmeier, Steven C.

2016-05-01

A validated, polarimetric 3-dimensional simulation capability, P-MCScene, is being developed by generalizing Spectral Sciences' Monte Carlo-based synthetic scene simulation model, MCScene, to include calculation of all 4 Stokes components. P-MCScene polarimetric optical databases will be generated by a new version (MODTRAN7) of the government-standard MODTRAN radiative transfer algorithm. The conversion of MODTRAN6 to a polarimetric model is being accomplished by (1) introducing polarimetric data, by (2) vectorizing the MODTRAN radiation calculations and by (3) integrating the newly revised and validated vector discrete ordinate model VDISORT3. Early results, presented here, demonstrate a clear pathway to the long-term goal of fully validated polarimetric models.

Toward a CFD nose-to-tail capability - Hypersonic unsteady Navier-Stokes code validation

NASA Technical Reports Server (NTRS)

Edwards, Thomas A.; Flores, Jolen

1989-01-01

Computational fluid dynamics (CFD) research for hypersonic flows presents new problems in code validation because of the added complexity of the physical models. This paper surveys code validation procedures applicable to hypersonic flow models that include real gas effects. The current status of hypersonic CFD flow analysis is assessed with the Compressible Navier-Stokes (CNS) code as a case study. The methods of code validation discussed to beyond comparison with experimental data to include comparisons with other codes and formulations, component analyses, and estimation of numerical errors. Current results indicate that predicting hypersonic flows of perfect gases and equilibrium air are well in hand. Pressure, shock location, and integrated quantities are relatively easy to predict accurately, while surface quantities such as heat transfer are more sensitive to the solution procedure. Modeling transition to turbulence needs refinement, though preliminary results are promising.

External validation of the diffuse intrinsic pontine glioma survival prediction model: a collaborative report from the International DIPG Registry and the SIOPE DIPG Registry.

PubMed

Veldhuijzen van Zanten, Sophie E M; Lane, Adam; Heymans, Martijn W; Baugh, Joshua; Chaney, Brooklyn; Hoffman, Lindsey M; Doughman, Renee; Jansen, Marc H A; Sanchez, Esther; Vandertop, William P; Kaspers, Gertjan J L; van Vuurden, Dannis G; Fouladi, Maryam; Jones, Blaise V; Leach, James

2017-08-01

We aimed to perform external validation of the recently developed survival prediction model for diffuse intrinsic pontine glioma (DIPG), and discuss its utility. The DIPG survival prediction model was developed in a cohort of patients from the Netherlands, United Kingdom and Germany, registered in the SIOPE DIPG Registry, and includes age <3 years, longer symptom duration and receipt of chemotherapy as favorable predictors, and presence of ring-enhancement on MRI as unfavorable predictor. Model performance was evaluated by analyzing the discrimination and calibration abilities. External validation was performed using an unselected cohort from the International DIPG Registry, including patients from United States, Canada, Australia and New Zealand. Basic comparison with the results of the original study was performed using descriptive statistics, and univariate- and multivariable regression analyses in the validation cohort. External validation was assessed following a variety of analyses described previously. Baseline patient characteristics and results from the regression analyses were largely comparable. Kaplan-Meier curves of the validation cohort reproduced separated groups of standard (n = 39), intermediate (n = 125), and high-risk (n = 78) patients. This discriminative ability was confirmed by similar values for the hazard ratios across these risk groups. The calibration curve in the validation cohort showed a symmetric underestimation of the predicted survival probabilities. In this external validation study, we demonstrate that the DIPG survival prediction model has acceptable cross-cohort calibration and is able to discriminate patients with short, average, and increased survival. We discuss how this clinico-radiological model may serve a useful role in current clinical practice.

Measuring Children's Environmental Attitudes and Values in Northwest Mexico: Validating a Modified Version of Measures to Test the Model of Ecological Values (2-MEV)

ERIC Educational Resources Information Center

Schneller, A. J.; Johnson, B.; Bogner, F. X.

2015-01-01

This paper describes the validation process of measuring children's attitudes and values toward the environment within a Mexican sample. We applied the Model of Ecological Values (2-MEV), which has been shown to be valid and reliable in 20 countries, including one Spanish speaking culture. Items were initially modified to fit the regional dialect,…

Ground-water models: Validate or invalidate

USGS Publications Warehouse

Bredehoeft, J.D.; Konikow, Leonard F.

1993-01-01

The word validation has a clear meaning to both the scientific community and the general public. Within the scientific community the validation of scientific theory has been the subject of philosophical debate. The philosopher of science, Karl Popper, argued that scientific theory cannot be validated, only invalidated. Popper’s view is not the only opinion in this debate; however, many scientists today agree with Popper (including the authors). To the general public, proclaiming that a ground-water model is validated carries with it an aura of correctness that we do not believe many of us who model would claim. We can place all the caveats we wish, but the public has its own understanding of what the word implies. Using the word valid with respect to models misleads the public; verification carries with it similar connotations as far as the public is concerned. Our point is this: using the terms validation and verification are misleading, at best. These terms should be abandoned by the ground-water community.

A diagnostic model for the detection of sensitization to wheat allergens was developed and validated in bakery workers.

PubMed

Suarthana, Eva; Vergouwe, Yvonne; Moons, Karel G; de Monchy, Jan; Grobbee, Diederick; Heederik, Dick; Meijer, Evert

2010-09-01

To develop and validate a prediction model to detect sensitization to wheat allergens in bakery workers. The prediction model was developed in 867 Dutch bakery workers (development set, prevalence of sensitization 13%) and included questionnaire items (candidate predictors). First, principal component analysis was used to reduce the number of candidate predictors. Then, multivariable logistic regression analysis was used to develop the model. Internal validation and extent of optimism was assessed with bootstrapping. External validation was studied in 390 independent Dutch bakery workers (validation set, prevalence of sensitization 20%). The prediction model contained the predictors nasoconjunctival symptoms, asthma symptoms, shortness of breath and wheeze, work-related upper and lower respiratory symptoms, and traditional bakery. The model showed good discrimination with an area under the receiver operating characteristic (ROC) curve area of 0.76 (and 0.75 after internal validation). Application of the model in the validation set gave a reasonable discrimination (ROC area=0.69) and good calibration after a small adjustment of the model intercept. A simple model with questionnaire items only can be used to stratify bakers according to their risk of sensitization to wheat allergens. Its use may increase the cost-effectiveness of (subsequent) medical surveillance.

Global precipitation measurements for validating climate models

NASA Astrophysics Data System (ADS)

Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

2017-11-01

The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

Using thermochonology to validate a balanced cross section along the Karnali River, far-western Nepal

NASA Astrophysics Data System (ADS)

Battistella, C.; Robinson, D.; McQuarrie, N.; Ghoshal, S.

2017-12-01

Multiple valid balanced cross sections can be produced from mapped surface and subsurface data. By integrating low temperature thermochronologic data, we are better able to predict subsurface geometries. Existing valid balanced cross section for far western Nepal are few (Robinson et al., 2006) and do not incorporate thermochronologic data because the data did not exist. The data published along the Simikot cross section along the Karnali River since then include muscovite Ar, zircon U-Th/He and apatite fission track. We present new mapping and a new valid balanced cross section that takes into account the new field data as well as the limitations that thermochronologic data places on the kinematics of the cross section. Additional constrains include some new geomorphology data acquired since 2006 that indicate areas of increased vertical uplift, which indicate locations of buried ramps in the Main Himalayan thrust and guide the locations of Lesser Himalayan ramps in the balanced cross section. Future work will include flexural modeling, new low temperature thermochronometic data, and 2-D thermokinematic models from a sequentially forward modeled balanced cross sections in far western Nepal.

External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

PubMed

Lamain-de Ruiter, Marije; Kwee, Anneke; Naaktgeboren, Christiana A; de Groot, Inge; Evers, Inge M; Groenendaal, Floris; Hering, Yolanda R; Huisjes, Anjoke J M; Kirpestein, Cornel; Monincx, Wilma M; Siljee, Jacqueline E; Van 't Zelfde, Annewil; van Oirschot, Charlotte M; Vankan-Buitelaar, Simone A; Vonk, Mariska A A W; Wiegers, Therese A; Zwart, Joost J; Franx, Arie; Moons, Karel G M; Koster, Maria P H

2016-08-30

 To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy.  External validation of all published prognostic models in large scale, prospective, multicentre cohort study.  31 independent midwifery practices and six hospitals in the Netherlands.  Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded.  Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots.  3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit.  In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

NASA Astrophysics Data System (ADS)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some validation experiments demonstrated that the models yield accurate estimates at flux measurement sites, the question remains whether they are performing well over the broader landscape. Moreover, a large number of RS_ET products have been released in recent years. Thus, we also pay attention to the cross-validation method of RS_ET derived from multi-source models. "The Multi-scale Observation Experiment on Evapotranspiration over Heterogeneous Land Surfaces: Flux Observation Matrix" campaign is carried out at the middle reaches of the Heihe River Basin, China in 2012. Flux measurements from an observation matrix composed of 22 EC and 4 LAS are acquired to investigate the cross-validation of multi-source models over different landscapes. In this case, six remote sensing models, including the empirical statistical model, the one-source and two-source models, the Penman-Monteith equation based model, the Priestley-Taylor equation based model, and the complementary relationship based model, are used to perform an intercomparison. All the results from the two cases of RS_ET validation showed that the proposed validation methods are reasonable and feasible.

Use of Maple Seeding Canopy Reflectance Dataset for Validation of SART/LEAFMOD Radiative Transfer Model

NASA Technical Reports Server (NTRS)

Bond, Barbara J.; Peterson, David L.

1999-01-01

This project was a collaborative effort by researchers at ARC, OSU and the University of Arizona. The goal was to use a dataset obtained from a previous study to "empirically validate a new canopy radiative-transfer model (SART) which incorporates a recently-developed leaf-level model (LEAFMOD)". The document includes a short research summary.

Development and Validation of an Empiric Tool to Predict Favorable Neurologic Outcomes Among PICU Patients.

PubMed

Gupta, Punkaj; Rettiganti, Mallikarjuna; Gossett, Jeffrey M; Daufeldt, Jennifer; Rice, Tom B; Wetzel, Randall C

2018-01-01

To create a novel tool to predict favorable neurologic outcomes during ICU stay among children with critical illness. Logistic regression models using adaptive lasso methodology were used to identify independent factors associated with favorable neurologic outcomes. A mixed effects logistic regression model was used to create the final prediction model including all predictors selected from the lasso model. Model validation was performed using a 10-fold internal cross-validation approach. Virtual Pediatric Systems (VPS, LLC, Los Angeles, CA) database. Patients less than 18 years old admitted to one of the participating ICUs in the Virtual Pediatric Systems database were included (2009-2015). None. A total of 160,570 patients from 90 hospitals qualified for inclusion. Of these, 1,675 patients (1.04%) were associated with a decline in Pediatric Cerebral Performance Category scale by at least 2 between ICU admission and ICU discharge (unfavorable neurologic outcome). The independent factors associated with unfavorable neurologic outcome included higher weight at ICU admission, higher Pediatric Index of Morality-2 score at ICU admission, cardiac arrest, stroke, seizures, head/nonhead trauma, use of conventional mechanical ventilation and high-frequency oscillatory ventilation, prolonged hospital length of ICU stay, and prolonged use of mechanical ventilation. The presence of chromosomal anomaly, cardiac surgery, and utilization of nitric oxide were associated with favorable neurologic outcome. The final online prediction tool can be accessed at https://soipredictiontool.shinyapps.io/GNOScore/. Our model predicted 139,688 patients with favorable neurologic outcomes in an internal validation sample when the observed number of patients with favorable neurologic outcomes was among 139,591 patients. The area under the receiver operating curve for the validation model was 0.90. This proposed prediction tool encompasses 20 risk factors into one probability to predict favorable neurologic outcome during ICU stay among children with critical illness. Future studies should seek external validation and improved discrimination of this prediction tool.

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Calibration and validation of earthquake catastrophe models. Case study: Impact Forecasting Earthquake Model for Algeria

NASA Astrophysics Data System (ADS)

Trendafiloski, G.; Gaspa Rebull, O.; Ewing, C.; Podlaha, A.; Magee, B.

2012-04-01

Calibration and validation are crucial steps in the production of the catastrophe models for the insurance industry in order to assure the model's reliability and to quantify its uncertainty. Calibration is needed in all components of model development including hazard and vulnerability. Validation is required to ensure that the losses calculated by the model match those observed in past events and which could happen in future. Impact Forecasting, the catastrophe modelling development centre of excellence within Aon Benfield, has recently launched its earthquake model for Algeria as a part of the earthquake model for the Maghreb region. The earthquake model went through a detailed calibration process including: (1) the seismic intensity attenuation model by use of macroseismic observations and maps from past earthquakes in Algeria; (2) calculation of the country-specific vulnerability modifiers by use of past damage observations in the country. The use of Benouar, 1994 ground motion prediction relationship was proven as the most appropriate for our model. Calculation of the regional vulnerability modifiers for the country led to 10% to 40% larger vulnerability indexes for different building types compared to average European indexes. The country specific damage models also included aggregate damage models for residential, commercial and industrial properties considering the description of the buildings stock given by World Housing Encyclopaedia and the local rebuilding cost factors equal to 10% for damage grade 1, 20% for damage grade 2, 35% for damage grade 3, 75% for damage grade 4 and 100% for damage grade 5. The damage grades comply with the European Macroseismic Scale (EMS-1998). The model was validated by use of "as-if" historical scenario simulations of three past earthquake events in Algeria M6.8 2003 Boumerdes, M7.3 1980 El-Asnam and M7.3 1856 Djidjelli earthquake. The calculated return periods of the losses for client market portfolio align with the repeatability of such catastrophe losses in the country. The validation process also included collaboration between Aon Benfield and its client in order to consider the insurance market penetration in Algeria estimated approximately at 5%. Thus, we believe that the applied approach led towards the production of an earthquake model for Algeria that is scientifically sound and reliable from one side and market and client oriented on the other side.

Multivariate statistical assessment of predictors of firefighters' muscular and aerobic work capacity.

PubMed

Lindberg, Ann-Sofie; Oksa, Juha; Antti, Henrik; Malm, Christer

2015-01-01

Physical capacity has previously been deemed important for firefighters physical work capacity, and aerobic fitness, muscular strength, and muscular endurance are the most frequently investigated parameters of importance. Traditionally, bivariate and multivariate linear regression statistics have been used to study relationships between physical capacities and work capacities among firefighters. An alternative way to handle datasets consisting of numerous correlated variables is to use multivariate projection analyses, such as Orthogonal Projection to Latent Structures. The first aim of the present study was to evaluate the prediction and predictive power of field and laboratory tests, respectively, on firefighters' physical work capacity on selected work tasks. Also, to study if valid predictions could be achieved without anthropometric data. The second aim was to externally validate selected models. The third aim was to validate selected models on firefighters' and on civilians'. A total of 38 (26 men and 12 women) + 90 (38 men and 52 women) subjects were included in the models and the external validation, respectively. The best prediction (R2) and predictive power (Q2) of Stairs, Pulling, Demolition, Terrain, and Rescue work capacities included field tests (R2 = 0.73 to 0.84, Q2 = 0.68 to 0.82). The best external validation was for Stairs work capacity (R2 = 0.80) and worst for Demolition work capacity (R2 = 0.40). In conclusion, field and laboratory tests could equally well predict physical work capacities for firefighting work tasks, and models excluding anthropometric data were valid. The predictive power was satisfactory for all included work tasks except Demolition.

Clinical Prediction Models for Patients With Nontraumatic Knee Pain in Primary Care: A Systematic Review and Internal Validation Study.

PubMed

Panken, Guus; Verhagen, Arianne P; Terwee, Caroline B; Heymans, Martijn W

2017-08-01

Study Design Systematic review and validation study. Background Many prognostic models of knee pain outcomes have been developed for use in primary care. Variability among published studies with regard to patient population, outcome measures, and relevant prognostic factors hampers the generalizability and implementation of these models. Objectives To summarize existing prognostic models in patients with knee pain in a primary care setting and to develop and internally validate new summary prognostic models. Methods After a sensitive search strategy, 2 reviewers independently selected prognostic models for patients with nontraumatic knee pain and assessed the methodological quality of the included studies. All predictors of the included studies were evaluated, summarized, and classified. The predictors assessed in multiple studies of sufficient quality are presented in this review. Using data from the Musculoskeletal System Study (BAS) cohort of patients with a new episode of knee pain, recruited consecutively by Dutch general medical practitioners (n = 372), we used predictors with a strong level of evidence to develop new prognostic models for each outcome measure and internally validated these models. Results Sixteen studies were eligible for inclusion. We considered 11 studies to be of sufficient quality. None of these studies validated their models. Five predictors with strong evidence were related to function and 6 to recovery, and were used to compose 2 prognostic models for patients with knee pain at 1 year. Running these new models in another data set showed explained variances (R 2 ) of 0.36 (function) and 0.33 (recovery). The area under the curve of the recovery model was 0.79. After internal validation, the adjusted R 2 values of the models were 0.30 (function) and 0.20 (recovery), and the area under the curve was 0.73. Conclusion We developed 2 valid prognostic models for function and recovery for patients with nontraumatic knee pain, based on predictors with strong evidence. A longer duration of complaints predicted poorer function but did not adequately predict chance of recovery. Level of Evidence Prognosis, levels 1a and 1b. J Orthop Sports Phys Ther 2017;47(8):518-529. Epub 16 Jun 2017. doi:10.2519/jospt.2017.7142.

Development and external validation of new ultrasound-based mathematical models for preoperative prediction of high-risk endometrial cancer.

PubMed

Van Holsbeke, C; Ameye, L; Testa, A C; Mascilini, F; Lindqvist, P; Fischerova, D; Frühauf, F; Fransis, S; de Jonge, E; Timmerman, D; Epstein, E

2014-05-01

To develop and validate strategies, using new ultrasound-based mathematical models, for the prediction of high-risk endometrial cancer and compare them with strategies using previously developed models or the use of preoperative grading only. Women with endometrial cancer were prospectively examined using two-dimensional (2D) and three-dimensional (3D) gray-scale and color Doppler ultrasound imaging. More than 25 ultrasound, demographic and histological variables were analyzed. Two logistic regression models were developed: one 'objective' model using mainly objective variables; and one 'subjective' model including subjective variables (i.e. subjective impression of myometrial and cervical invasion, preoperative grade and demographic variables). The following strategies were validated: a one-step strategy using only preoperative grading and two-step strategies using preoperative grading as the first step and one of the new models, subjective assessment or previously developed models as a second step. One-hundred and twenty-five patients were included in the development set and 211 were included in the validation set. The 'objective' model retained preoperative grade and minimal tumor-free myometrium as variables. The 'subjective' model retained preoperative grade and subjective assessment of myometrial invasion. On external validation, the performance of the new models was similar to that on the development set. Sensitivity for the two-step strategy with the 'objective' model was 78% (95% CI, 69-84%) at a cut-off of 0.50, 82% (95% CI, 74-88%) for the strategy with the 'subjective' model and 83% (95% CI, 75-88%) for that with subjective assessment. Specificity was 68% (95% CI, 58-77%), 72% (95% CI, 62-80%) and 71% (95% CI, 61-79%) respectively. The two-step strategies detected up to twice as many high-risk cases as preoperative grading only. The new models had a significantly higher sensitivity than did previously developed models, at the same specificity. Two-step strategies with 'new' ultrasound-based models predict high-risk endometrial cancers with good accuracy and do this better than do previously developed models. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.

Validation of design procedure and performance modeling of a heat and fluid transport field experiment in the unsaturated zone

NASA Astrophysics Data System (ADS)

Nir, A.; Doughty, C.; Tsang, C. F.

Validation methods which developed in the context of deterministic concepts of past generations often cannot be directly applied to environmental problems, which may be characterized by limited reproducibility of results and highly complex models. Instead, validation is interpreted here as a series of activities, including both theoretical and experimental tests, designed to enhance our confidence in the capability of a proposed model to describe some aspect of reality. We examine the validation process applied to a project concerned with heat and fluid transport in porous media, in which mathematical modeling, simulation, and results of field experiments are evaluated in order to determine the feasibility of a system for seasonal thermal energy storage in shallow unsaturated soils. Technical details of the field experiments are not included, but appear in previous publications. Validation activities are divided into three stages. The first stage, carried out prior to the field experiments, is concerned with modeling the relevant physical processes, optimization of the heat-exchanger configuration and the shape of the storage volume, and multi-year simulation. Subjects requiring further theoretical and experimental study are identified at this stage. The second stage encompasses the planning and evaluation of the initial field experiment. Simulations are made to determine the experimental time scale and optimal sensor locations. Soil thermal parameters and temperature boundary conditions are estimated using an inverse method. Then results of the experiment are compared with model predictions using different parameter values and modeling approximations. In the third stage, results of an experiment performed under different boundary conditions are compared to predictions made by the models developed in the second stage. Various aspects of this theoretical and experimental field study are described as examples of the verification and validation procedure. There is no attempt to validate a specific model, but several models of increasing complexity are compared with experimental results. The outcome is interpreted as a demonstration of the paradigm proposed by van der Heijde, 26 that different constituencies have different objectives for the validation process and therefore their acceptance criteria differ also.

"La Clave Profesional": Validation of a Vocational Guidance Instrument

ERIC Educational Resources Information Center

Mudarra, Maria J.; Lázaro Martínez, Ángel

2014-01-01

Introduction: The current study demonstrates empirical and cultural validity of "La Clave Profesional" (Spanish adaptation of Career Key, Jones's test based Holland's RIASEC model). The process of providing validity evidence also includes a reflection on personal and career development and examines the relationahsips between RIASEC…

Injector Design Tool Improvements: User's manual for FDNS V.4.5

NASA Technical Reports Server (NTRS)

Chen, Yen-Sen; Shang, Huan-Min; Wei, Hong; Liu, Jiwen

1998-01-01

The major emphasis of the current effort is in the development and validation of an efficient parallel machine computational model, based on the FDNS code, to analyze the fluid dynamics of a wide variety of liquid jet configurations for general liquid rocket engine injection system applications. This model includes physical models for droplet atomization, breakup/coalescence, evaporation, turbulence mixing and gas-phase combustion. Benchmark validation cases for liquid rocket engine chamber combustion conditions will be performed for model validation purpose. Test cases may include shear coaxial, swirl coaxial and impinging injection systems with combinations LOXIH2 or LOXISP-1 propellant injector elements used in rocket engine designs. As a final goal of this project, a well tested parallel CFD performance methodology together with a user's operation description in a final technical report will be reported at the end of the proposed research effort.

Estimation of Particulate Mass and Manganese Exposure Levels among Welders

PubMed Central

Hobson, Angela; Seixas, Noah; Sterling, David; Racette, Brad A.

2011-01-01

Background: Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature. Methods: Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models. Results: A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data. Conclusions: This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data. PMID:20870928

Rotary Engine Friction Test Rig Development Report

DTIC Science & Technology

2011-12-01

fundamental research is needed to understand the friction characteristics of the rotary engine that lead to accelerated wear and tear on the seals...that includes a turbocharger . Once the original GT-Suite model is validated, the turbocharger model will be more accurate. This validation will...prepare for turbocharger and fuel-injector testing, which will lead to further development and calibration of the model. Further details are beyond the

A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes.

PubMed

Mushkudiani, Nino A; Hukkelhoven, Chantal W P M; Hernández, Adrián V; Murray, Gordon D; Choi, Sung C; Maas, Andrew I R; Steyerberg, Ewout W

2008-04-01

To describe the modeling techniques used for early prediction of outcome in traumatic brain injury (TBI) and to identify aspects for potential improvements. We reviewed key methodological aspects of studies published between 1970 and 2005 that proposed a prognostic model for the Glasgow Outcome Scale of TBI based on admission data. We included 31 papers. Twenty-four were single-center studies, and 22 reported on fewer than 500 patients. The median of the number of initially considered predictors was eight, and on average five of these were selected for the prognostic model, generally including age, Glasgow Coma Score (or only motor score), and pupillary reactivity. The most common statistical technique was logistic regression with stepwise selection of predictors. Model performance was often quantified by accuracy rate rather than by more appropriate measures such as the area under the receiver-operating characteristic curve. Model validity was addressed in 15 studies, but mostly used a simple split-sample approach, and external validation was performed in only four studies. Although most models agree on the three most important predictors, many were developed on small sample sizes within single centers and hence lack generalizability. Modeling strategies have to be improved, and include external validation.

Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation

NASA Technical Reports Server (NTRS)

Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.

2010-01-01

Dynamic simulations and experimental validation tests were performed on a two-stage, two-speed gearbox as part of the drive system research activities of the NASA Fundamental Aeronautics Subsonics Rotary Wing Project. The gearbox was driven by two electromagnetic motors and had two electromagnetic, multi-disk clutches to control output speed. A dynamic model of the system was created which included a direct current electric motor with proportional-integral-derivative (PID) speed control, a two-speed gearbox with dual electromagnetically actuated clutches, and an eddy current dynamometer. A six degree-of-freedom model of the gearbox accounted for the system torsional dynamics and included gear, clutch, shaft, and load inertias as well as shaft flexibilities and a dry clutch stick-slip friction model. Experimental validation tests were performed on the gearbox in the NASA Glenn gear noise test facility. Gearbox output speed and torque as well as drive motor speed and current were compared to those from the analytical predictions. The experiments correlate very well with the predictions, thus validating the dynamic simulation methodologies.

Fast Running Urban Dispersion Model for Radiological Dispersal Device (RDD) Releases: Model Description and Validation

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

Gowardhan, Akshay; Neuscamman, Stephanie; Donetti, John

Aeolus is an efficient three-dimensional computational fluid dynamics code based on finite volume method developed for predicting transport and dispersion of contaminants in a complex urban area. It solves the time dependent incompressible Navier-Stokes equation on a regular Cartesian staggered grid using a fractional step method. It also solves a scalar transport equation for temperature and using the Boussinesq approximation. The model also includes a Lagrangian dispersion model for predicting the transport and dispersion of atmospheric contaminants. The model can be run in an efficient Reynolds Average Navier-Stokes (RANS) mode with a run time of several minutes, or a moremore » detailed Large Eddy Simulation (LES) mode with run time of hours for a typical simulation. This report describes the model components, including details on the physics models used in the code, as well as several model validation efforts. Aeolus wind and dispersion predictions are compared to field data from the Joint Urban Field Trials 2003 conducted in Oklahoma City (Allwine et al 2004) including both continuous and instantaneous releases. Newly implemented Aeolus capabilities include a decay chain model and an explosive Radiological Dispersal Device (RDD) source term; these capabilities are described. Aeolus predictions using the buoyant explosive RDD source are validated against two experimental data sets: the Green Field explosive cloud rise experiments conducted in Israel (Sharon et al 2012) and the Full-Scale RDD Field Trials conducted in Canada (Green et al 2016).« less

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.

Sonic Boom Modeling Technical Challenge

NASA Technical Reports Server (NTRS)

Sullivan, Brenda M.

2007-01-01

This viewgraph presentation reviews the technical challenges in modeling sonic booms. The goal of this program is to develop knowledge, capabilities and technologies to enable overland supersonic flight. The specific objectives of the modeling are: (1) Develop and validate sonic boom propagation model through realistic atmospheres, including effects of turbulence (2) Develop methods enabling prediction of response of and acoustic transmission into structures impacted by sonic booms (3) Develop and validate psychoacoustic model of human response to sonic booms under both indoor and outdoor listening conditions, using simulators.

Developing and validating risk prediction models in an individual participant data meta-analysis

PubMed Central

2014-01-01

Background Risk prediction models estimate the risk of developing future outcomes for individuals based on one or more underlying characteristics (predictors). We review how researchers develop and validate risk prediction models within an individual participant data (IPD) meta-analysis, in order to assess the feasibility and conduct of the approach. Methods A qualitative review of the aims, methodology, and reporting in 15 articles that developed a risk prediction model using IPD from multiple studies. Results The IPD approach offers many opportunities but methodological challenges exist, including: unavailability of requested IPD, missing patient data and predictors, and between-study heterogeneity in methods of measurement, outcome definitions and predictor effects. Most articles develop their model using IPD from all available studies and perform only an internal validation (on the same set of data). Ten of the 15 articles did not allow for any study differences in baseline risk (intercepts), potentially limiting their model’s applicability and performance in some populations. Only two articles used external validation (on different data), including a novel method which develops the model on all but one of the IPD studies, tests performance in the excluded study, and repeats by rotating the omitted study. Conclusions An IPD meta-analysis offers unique opportunities for risk prediction research. Researchers can make more of this by allowing separate model intercept terms for each study (population) to improve generalisability, and by using ‘internal-external cross-validation’ to simultaneously develop and validate their model. Methodological challenges can be reduced by prospectively planned collaborations that share IPD for risk prediction. PMID:24397587

Assessment of the Value, Impact, and Validity of the Jobs and Economic Development Impacts (JEDI) Suite of Models

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

Billman, L.; Keyser, D.

The Jobs and Economic Development Impacts (JEDI) models, developed by the National Renewable Energy Laboratory (NREL) for the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), use input-output methodology to estimate gross (not net) jobs and economic impacts of building and operating selected types of renewable electricity generation and fuel plants. This analysis provides the DOE with an assessment of the value, impact, and validity of the JEDI suite of models. While the models produce estimates of jobs, earnings, and economic output, this analysis focuses only on jobs estimates. This validation report includes an introductionmore » to JEDI models, an analysis of the value and impact of the JEDI models, and an analysis of the validity of job estimates generated by JEDI model through comparison to other modeled estimates and comparison to empirical, observed jobs data as reported or estimated for a commercial project, a state, or a region.« less

Calibration and Validation of the Checkpoint Model to the Air Force Electronic Systems Center Software Database

DTIC Science & Technology

1997-09-01

Illinois Institute of Technology Research Institute (IITRI) calibrated seven parametric models including SPQR /20, the forerunner of CHECKPOINT. The...a semicolon); thus, SPQR /20 was calibrated using SLOC sizing data (IITRI, 1989: 3-4). The results showed only slight overall improvements in accuracy...even when validating the calibrated models with the same data sets. The IITRI study demonstrated SPQR /20 to be one of two models that were most

Modeling and Simulation Behavior Validation Methodology and Extension Model Validation for the Individual Soldier

DTIC Science & Technology

2015-03-01

domains. Major model functions include: • Ground combat: Light and heavy forces. • Air mobile forces. • Future forces. • Fixed-wing and rotary-wing...Constraints: • Study must be completed no later than 31 December 2014. • Entity behavior limited to select COMBATXXI Mobility , Unmanned Aerial System...and SQL backend , as well as any open application programming interface API. • Allows data transparency and data driven navigation through the model

Testing the Construct Validity of Proposed Criteria for "DSM-5" Autism Spectrum Disorder

ERIC Educational Resources Information Center

Mandy, William P. L.; Charman, Tony; Skuse, David H.

2012-01-01

Objective: To use confirmatory factor analysis to test the construct validity of the proposed "DSM-5" symptom model of autism spectrum disorder (ASD), in comparison to alternative models, including that described in "DSM-IV-TR." Method: Participants were 708 verbal children and young persons (mean age, 9.5 years) with mild to severe autistic…

Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

PubMed

Hwang, Eui Jin; Goo, Jin Mo; Kim, Jihye; Park, Sang Joon; Ahn, Soyeon; Park, Chang Min; Shin, Yeong-Gil

2017-08-01

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth. For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE). SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold. • The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.

Lung Cancer Risk Prediction Model Incorporating Lung Function: Development and Validation in the UK Biobank Prospective Cohort Study.

PubMed

Muller, David C; Johansson, Mattias; Brennan, Paul

2017-03-10

Purpose Several lung cancer risk prediction models have been developed, but none to date have assessed the predictive ability of lung function in a population-based cohort. We sought to develop and internally validate a model incorporating lung function using data from the UK Biobank prospective cohort study. Methods This analysis included 502,321 participants without a previous diagnosis of lung cancer, predominantly between 40 and 70 years of age. We used flexible parametric survival models to estimate the 2-year probability of lung cancer, accounting for the competing risk of death. Models included predictors previously shown to be associated with lung cancer risk, including sex, variables related to smoking history and nicotine addiction, medical history, family history of lung cancer, and lung function (forced expiratory volume in 1 second [FEV1]). Results During accumulated follow-up of 1,469,518 person-years, there were 738 lung cancer diagnoses. A model incorporating all predictors had excellent discrimination (concordance (c)-statistic [95% CI] = 0.85 [0.82 to 0.87]). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected c-statistic = 0.84). The full model, including FEV1, also had modestly superior discriminatory power than one that was designed solely on the basis of questionnaire variables (c-statistic = 0.84 [0.82 to 0.86]; optimism-corrected c-statistic = 0.83; p FEV1 = 3.4 × 10 -13 ). The full model had better discrimination than standard lung cancer screening eligibility criteria (c-statistic = 0.66 [0.64 to 0.69]). Conclusion A risk prediction model that includes lung function has strong predictive ability, which could improve eligibility criteria for lung cancer screening programs.

Containment Sodium Chemistry Models in MELCOR.

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

Louie, David; Humphries, Larry L.; Denman, Matthew R

To meet regulatory needs for sodium fast reactors’ future development, including licensing requirements, Sandia National Laboratories is modernizing MELCOR, a severe accident analysis computer code developed for the U.S. Nuclear Regulatory Commission (NRC). Specifically, Sandia is modernizing MELCOR to include the capability to model sodium reactors. However, Sandia’s modernization effort primarily focuses on the containment response aspects of the sodium reactor accidents. Sandia began modernizing MELCOR in 2013 to allow a sodium coolant, rather than water, for conventional light water reactors. In the past three years, Sandia has been implementing the sodium chemistry containment models in CONTAIN-LMR, a legacy NRCmore » code, into MELCOR. These chemistry models include spray fire, pool fire and atmosphere chemistry models. Only the first two chemistry models have been implemented though it is intended to implement all these models into MELCOR. A new package called “NAC” has been created to manage the sodium chemistry model more efficiently. In 2017 Sandia began validating the implemented models in MELCOR by simulating available experiments. The CONTAIN-LMR sodium models include sodium atmosphere chemistry and sodium-concrete interaction models. This paper presents sodium property models, the implemented models, implementation issues, and a path towards validation against existing experimental data.« less

Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

PubMed

Yoo, Kwangsun; Rosenberg, Monica D; Hsu, Wei-Ting; Zhang, Sheng; Li, Chiang-Shan R; Scheinost, Dustin; Constable, R Todd; Chun, Marvin M

2018-02-15

Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square [PLS] regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with correlations between predicted and observed measures of attention as high as 0.9 for internal validation, and 0.6 for external validation (all p's < 0.05). Models trained on task data outperformed models trained on rest data. Pearson's correlation and accordance features generally showed a small numerical advantage over discordance features, while PLS regression models were usually better than linear regression models. Overall, in addition to correlation features combined with linear models (Rosenberg et al., 2016a), it is useful to consider accordance features and PLS regression for CPM. Copyright © 2017 Elsevier Inc. All rights reserved.

The Construct of the Learning Organization: Dimensions, Measurement, and Validation

ERIC Educational Resources Information Center

Yang, Baiyin; Watkins, Karen E.; Marsick, Victoria J.

2004-01-01

This research describes efforts to develop and validate a multidimensional measure of the learning organization. An instrument was developed based on a critical review of both the conceptualization and practice of this construct. Supporting validity evidence for the instrument was obtained from several sources, including best model-data fit among…

Comparing Posttraumatic Stress Disorder's Symptom Structure between Deployed and Nondeployed Veterans

ERIC Educational Resources Information Center

Engdahl, Ryan M.; Elhai, Jon D.; Richardson, J. Don; Frueh, B. Christopher

2011-01-01

We tested two empirically validated 4-factor models of posttraumatic stress disorder (PTSD) symptoms using the PTSD Checklist: King, Leskin, King, and Weathers' (1998) model including reexperiencing, avoidance, emotional numbing, and hyperarousal factors, and Simms, Watson, and Doebbeling's (2002) model including reexperiencing, avoidance,…

The Professionalism Assessment of Clinical Teachers (PACT): The Reliability and Validity of a Novel Tool to Evaluate Professional and Clinical Teaching Behaviors

ERIC Educational Resources Information Center

Young, Meredith E.; Cruess, Sylvia R.; Cruess, Richard L.; Steinert, Yvonne

2014-01-01

Physicians function as clinicians, teachers, and role models within the clinical environment. Negative learning environments have been shown to be due to many factors, including the presence of unprofessional behaviors among clinical teachers. Reliable and valid assessments of clinical teacher performance, including professional behaviors, may…

Creation of a novel simulator for minimally invasive neurosurgery: fusion of 3D printing and special effects.

PubMed

Weinstock, Peter; Rehder, Roberta; Prabhu, Sanjay P; Forbes, Peter W; Roussin, Christopher J; Cohen, Alan R

2017-07-01

OBJECTIVE Recent advances in optics and miniaturization have enabled the development of a growing number of minimally invasive procedures, yet innovative training methods for the use of these techniques remain lacking. Conventional teaching models, including cadavers and physical trainers as well as virtual reality platforms, are often expensive and ineffective. Newly developed 3D printing technologies can recreate patient-specific anatomy, but the stiffness of the materials limits fidelity to real-life surgical situations. Hollywood special effects techniques can create ultrarealistic features, including lifelike tactile properties, to enhance accuracy and effectiveness of the surgical models. The authors created a highly realistic model of a pediatric patient with hydrocephalus via a unique combination of 3D printing and special effects techniques and validated the use of this model in training neurosurgery fellows and residents to perform endoscopic third ventriculostomy (ETV), an effective minimally invasive method increasingly used in treating hydrocephalus. METHODS A full-scale reproduction of the head of a 14-year-old adolescent patient with hydrocephalus, including external physical details and internal neuroanatomy, was developed via a unique collaboration of neurosurgeons, simulation engineers, and a group of special effects experts. The model contains "plug-and-play" replaceable components for repetitive practice. The appearance of the training model (face validity) and the reproducibility of the ETV training procedure (content validity) were assessed by neurosurgery fellows and residents of different experience levels based on a 14-item Likert-like questionnaire. The usefulness of the training model for evaluating the performance of the trainees at different levels of experience (construct validity) was measured by blinded observers using the Objective Structured Assessment of Technical Skills (OSATS) scale for the performance of ETV. RESULTS A combination of 3D printing technology and casting processes led to the creation of realistic surgical models that include high-fidelity reproductions of the anatomical features of hydrocephalus and allow for the performance of ETV for training purposes. The models reproduced the pulsations of the basilar artery, ventricles, and cerebrospinal fluid (CSF), thus simulating the experience of performing ETV on an actual patient. The results of the 14-item questionnaire showed limited variability among participants' scores, and the neurosurgery fellows and residents gave the models consistently high ratings for face and content validity. The mean score for the content validity questions (4.88) was higher than the mean score for face validity (4.69) (p = 0.03). On construct validity scores, the blinded observers rated performance of fellows significantly higher than that of residents, indicating that the model provided a means to distinguish between novice and expert surgical skills. CONCLUSIONS A plug-and-play lifelike ETV training model was developed through a combination of 3D printing and special effects techniques, providing both anatomical and haptic accuracy. Such simulators offer opportunities to accelerate the development of expertise with respect to new and novel procedures as well as iterate new surgical approaches and innovations, thus allowing novice neurosurgeons to gain valuable experience in surgical techniques without exposing patients to risk of harm.

Development and validation of a cost-utility model for Type 1 diabetes mellitus.

PubMed

Wolowacz, S; Pearson, I; Shannon, P; Chubb, B; Gundgaard, J; Davies, M; Briggs, A

2015-08-01

To develop a health economic model to evaluate the cost-effectiveness of new interventions for Type 1 diabetes mellitus by their effects on long-term complications (measured through mean HbA1c ) while capturing the impact of treatment on hypoglycaemic events. Through a systematic review, we identified complications associated with Type 1 diabetes mellitus and data describing the long-term incidence of these complications. An individual patient simulation model was developed and included the following complications: cardiovascular disease, peripheral neuropathy, microalbuminuria, end-stage renal disease, proliferative retinopathy, ketoacidosis, cataract, hypoglycemia and adverse birth outcomes. Risk equations were developed from published cumulative incidence data and hazard ratios for the effect of HbA1c , age and duration of diabetes. We validated the model by comparing model predictions with observed outcomes from studies used to build the model (internal validation) and from other published data (external validation). We performed illustrative analyses for typical patient cohorts and a hypothetical intervention. Model predictions were within 2% of expected values in the internal validation and within 8% of observed values in the external validation (percentages represent absolute differences in the cumulative incidence). The model utilized high-quality, recent data specific to people with Type 1 diabetes mellitus. In the model validation, results deviated less than 8% from expected values. © 2014 Research Triangle Institute d/b/a RTI Health Solutions. Diabetic Medicine © 2014 Diabetes UK.

Spatio-temporal modeling of chronic PM 10 exposure for the Nurses' Health Study

NASA Astrophysics Data System (ADS)

Yanosky, Jeff D.; Paciorek, Christopher J.; Schwartz, Joel; Laden, Francine; Puett, Robin; Suh, Helen H.

2008-06-01

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or county-wide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM10 concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM10 emissions, elevation, wind speed, and precipitation were found to be important determinants of PM10 concentrations and were included in the final model. Final model performance was strong (cross-validation R2=0.62), with little bias (-0.4 μg m-3) and high precision (6.4 μg m-3). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R2=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R2=0.51) or inverse distance weighted interpolation (cross-validation R2=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM10 exposures for large populations.

The Fruit & Vegetable Screener in the 2000 California Health Interview Survey: Validation Results

Cancer.gov

In this study, multiple 24-hour recalls in conjunction with a measurement error model were used to assess validity. The screeners used in the EATS included additional foods and reported portion sizes.

Earth as an Extrasolar Planet: Earth Model Validation Using EPOXI Earth Observations

NASA Astrophysics Data System (ADS)

Robinson, Tyler D.; Meadows, Victoria S.; Crisp, David; Deming, Drake; A'Hearn, Michael F.; Charbonneau, David; Livengood, Timothy A.; Seager, Sara; Barry, Richard K.; Hearty, Thomas; Hewagama, Tilak; Lisse, Carey M.; McFadden, Lucy A.; Wellnitz, Dennis D.

2011-06-01

The EPOXI Discovery Mission of Opportunity reused the Deep Impact flyby spacecraft to obtain spatially and temporally resolved visible photometric and moderate resolution near-infrared (NIR) spectroscopic observations of Earth. These remote observations provide a rigorous validation of whole-disk Earth model simulations used to better understand remotely detectable extrasolar planet characteristics. We have used these data to upgrade, correct, and validate the NASA Astrobiology Institute's Virtual Planetary Laboratory three-dimensional line-by-line, multiple-scattering spectral Earth model. This comprehensive model now includes specular reflectance from the ocean and explicitly includes atmospheric effects such as Rayleigh scattering, gas absorption, and temperature structure. We have used this model to generate spatially and temporally resolved synthetic spectra and images of Earth for the dates of EPOXI observation. Model parameters were varied to yield an optimum fit to the data. We found that a minimum spatial resolution of ∼100 pixels on the visible disk, and four categories of water clouds, which were defined by using observed cloud positions and optical thicknesses, were needed to yield acceptable fits. The validated model provides a simultaneous fit to Earth's lightcurve, absolute brightness, and spectral data, with a root-mean-square (RMS) error of typically less than 3% for the multiwavelength lightcurves and residuals of ∼10% for the absolute brightness throughout the visible and NIR spectral range. We have extended our validation into the mid-infrared by comparing the model to high spectral resolution observations of Earth from the Atmospheric Infrared Sounder, obtaining a fit with residuals of ∼7% and brightness temperature errors of less than 1 K in the atmospheric window. For the purpose of understanding the observable characteristics of the distant Earth at arbitrary viewing geometry and observing cadence, our validated forward model can be used to simulate Earth's time-dependent brightness and spectral properties for wavelengths from the far ultraviolet to the far infrared.

Earth as an extrasolar planet: Earth model validation using EPOXI earth observations.

PubMed

Robinson, Tyler D; Meadows, Victoria S; Crisp, David; Deming, Drake; A'hearn, Michael F; Charbonneau, David; Livengood, Timothy A; Seager, Sara; Barry, Richard K; Hearty, Thomas; Hewagama, Tilak; Lisse, Carey M; McFadden, Lucy A; Wellnitz, Dennis D

2011-06-01

The EPOXI Discovery Mission of Opportunity reused the Deep Impact flyby spacecraft to obtain spatially and temporally resolved visible photometric and moderate resolution near-infrared (NIR) spectroscopic observations of Earth. These remote observations provide a rigorous validation of whole-disk Earth model simulations used to better understand remotely detectable extrasolar planet characteristics. We have used these data to upgrade, correct, and validate the NASA Astrobiology Institute's Virtual Planetary Laboratory three-dimensional line-by-line, multiple-scattering spectral Earth model. This comprehensive model now includes specular reflectance from the ocean and explicitly includes atmospheric effects such as Rayleigh scattering, gas absorption, and temperature structure. We have used this model to generate spatially and temporally resolved synthetic spectra and images of Earth for the dates of EPOXI observation. Model parameters were varied to yield an optimum fit to the data. We found that a minimum spatial resolution of ∼100 pixels on the visible disk, and four categories of water clouds, which were defined by using observed cloud positions and optical thicknesses, were needed to yield acceptable fits. The validated model provides a simultaneous fit to Earth's lightcurve, absolute brightness, and spectral data, with a root-mean-square (RMS) error of typically less than 3% for the multiwavelength lightcurves and residuals of ∼10% for the absolute brightness throughout the visible and NIR spectral range. We have extended our validation into the mid-infrared by comparing the model to high spectral resolution observations of Earth from the Atmospheric Infrared Sounder, obtaining a fit with residuals of ∼7% and brightness temperature errors of less than 1 K in the atmospheric window. For the purpose of understanding the observable characteristics of the distant Earth at arbitrary viewing geometry and observing cadence, our validated forward model can be used to simulate Earth's time-dependent brightness and spectral properties for wavelengths from the far ultraviolet to the far infrared. Key Words: Astrobiology-Extrasolar terrestrial planets-Habitability-Planetary science-Radiative transfer. Astrobiology 11, 393-408.

Earth as an Extrasolar Planet: Earth Model Validation Using EPOXI Earth Observations

NASA Technical Reports Server (NTRS)

Robinson, Tyler D.; Meadows, Victoria S.; Crisp, David; Deming, Drake; A'Hearn, Michael F.; Charbonneau, David; Livengood, Timothy A.; Seager, Sara; Barry, Richard; Hearty, Thomas;

Analysis procedures and subjective flight results of a simulator validation and cue fidelity experiment

NASA Technical Reports Server (NTRS)

Carr, Peter C.; Mckissick, Burnell T.

1988-01-01

A joint experiment to investigate simulator validation and cue fidelity was conducted by the Dryden Flight Research Facility of NASA Ames Research Center (Ames-Dryden) and NASA Langley Research Center. The primary objective was to validate the use of a closed-loop pilot-vehicle mathematical model as an analytical tool for optimizing the tradeoff between simulator fidelity requirements and simulator cost. The validation process includes comparing model predictions with simulation and flight test results to evaluate various hypotheses for differences in motion and visual cues and information transfer. A group of five pilots flew air-to-air tracking maneuvers in the Langley differential maneuvering simulator and visual motion simulator and in an F-14 aircraft at Ames-Dryden. The simulators used motion and visual cueing devices including a g-seat, a helmet loader, wide field-of-view horizon, and a motion base platform.

Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.

PubMed

Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2018-01-01

An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.

A Survey of Model Evaluation Approaches with a Tutorial on Hierarchical Bayesian Methods

ERIC Educational Resources Information Center

Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan

2008-01-01

This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…

High-fidelity Simulation of Jet Noise from Rectangular Nozzles . [Large Eddy Simulation (LES) Model for Noise Reduction in Advanced Jet Engines and Automobiles

NASA Technical Reports Server (NTRS)

Sinha, Neeraj

2014-01-01

This Phase II project validated a state-of-the-art LES model, coupled with a Ffowcs Williams-Hawkings (FW-H) far-field acoustic solver, to support the development of advanced engine concepts. These concepts include innovative flow control strategies to attenuate jet noise emissions. The end-to-end LES/ FW-H noise prediction model was demonstrated and validated by applying it to rectangular nozzle designs with a high aspect ratio. The model also was validated against acoustic and flow-field data from a realistic jet-pylon experiment, thereby significantly advancing the state of the art for LES.

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

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

Wang, Yuhe; Mazur, Thomas R.; Green, Olga

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expandedmore » to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.« less

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

PubMed Central

Wang, Yuhe; Mazur, Thomas R.; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H. Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H. Harold

2016-01-01

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian’s kmc. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems. PMID:27370123

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model.

PubMed

Wang, Yuhe; Mazur, Thomas R; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H Harold

2016-07-01

The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian's kmc. An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis.

PubMed

Jampathong, Nampet; Laopaiboon, Malinee; Rattanakanokchai, Siwanon; Pattanittum, Porjai

2018-03-09

Prognostic models have been increasingly developed to predict complete recovery in ischemic stroke. However, questions arise about the performance characteristics of these models. The aim of this study was to systematically review and synthesize performance of existing prognostic models for complete recovery in ischemic stroke. We searched journal publications indexed in PUBMED, SCOPUS, CENTRAL, ISI Web of Science and OVID MEDLINE from inception until 4 December, 2017, for studies designed to develop and/or validate prognostic models for predicting complete recovery in ischemic stroke patients. Two reviewers independently examined titles and abstracts, and assessed whether each study met the pre-defined inclusion criteria and also independently extracted information about model development and performance. We evaluated validation of the models by medians of the area under the receiver operating characteristic curve (AUC) or c-statistic and calibration performance. We used a random-effects meta-analysis to pool AUC values. We included 10 studies with 23 models developed from elderly patients with a moderately severe ischemic stroke, mainly in three high income countries. Sample sizes for each study ranged from 75 to 4441. Logistic regression was the only analytical strategy used to develop the models. The number of various predictors varied from one to 11. Internal validation was performed in 12 models with a median AUC of 0.80 (95% CI 0.73 to 0.84). One model reported good calibration. Nine models reported external validation with a median AUC of 0.80 (95% CI 0.76 to 0.82). Four models showed good discrimination and calibration on external validation. The pooled AUC of the two validation models of the same developed model was 0.78 (95% CI 0.71 to 0.85). The performance of the 23 models found in the systematic review varied from fair to good in terms of internal and external validation. Further models should be developed with internal and external validation in low and middle income countries.

Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

PubMed Central

Li, Guowei; Thabane, Lehana; Delate, Thomas; Witt, Daniel M.; Levine, Mitchell A. H.; Cheng, Ji; Holbrook, Anne

2016-01-01

Objectives To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy. Methods Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling. Results We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances. Conclusions In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making PMID:27513986

A Coupled Model System for Southeast Florida: Wave Model Validation Using Radar and In Situ Observations

DTIC Science & Technology

2012-02-24

also included. The “ground truth” for waves validation includes in situ data (ADCP and buoy) and high frequency Wellen Radar (WERA HF) data...which swells are able to pass through islands and shoals to arrive at the in situ data region is highly sensitive to whether currents are included...grid 1: WW3 • ∆x = ∆y = 0.5° ≈ 55 km • Longitude: x = -100° to -0.5° W (260° to 359.5° E), nx =200 • Latitude: y =17° to 59° N, ny =85 • no

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

PubMed

van der Ploeg, Tjeerd; Nieboer, Daan; Steyerberg, Ewout W

2016-10-01

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study.

PubMed

Hippisley-Cox, Julia; Coupland, Carol

2017-11-20

Objectives  To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches. Design  Prospective open cohort study. Setting  Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores. Participants  11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort. Methods  Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measure  Incident type 2 diabetes recorded on the general practice record. Results  In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R 2 ), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index. Conclusions  Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Update on simulation-based surgical training and assessment in ophthalmology: a systematic review.

PubMed

Thomsen, Ann Sofia S; Subhi, Yousif; Kiilgaard, Jens Folke; la Cour, Morten; Konge, Lars

2015-06-01

This study reviews the evidence behind simulation-based surgical training of ophthalmologists to determine (1) the validity of the reported models and (2) the ability to transfer skills to the operating room. Simulation-based training is established widely within ophthalmology, although it often lacks a scientific basis for implementation. We conducted a systematic review of trials involving simulation-based training or assessment of ophthalmic surgical skills among health professionals. The search included 5 databases (PubMed, EMBASE, PsycINFO, Cochrane Library, and Web of Science) and was completed on March 1, 2014. Overall, the included trials were divided into animal, cadaver, inanimate, and virtual-reality models. Risk of bias was assessed using the Cochrane Collaboration's tool. Validity evidence was evaluated using a modern validity framework (Messick's). We screened 1368 reports for eligibility and included 118 trials. The most common surgery simulated was cataract surgery. Most validity trials investigated only 1 or 2 of 5 sources of validity (87%). Only 2 trials (48 participants) investigated transfer of skills to the operating room; 4 trials (65 participants) evaluated the effect of simulation-based training on patient-related outcomes. Because of heterogeneity of the studies, it was not possible to conduct a quantitative analysis. The methodologic rigor of trials investigating simulation-based surgical training in ophthalmology is inadequate. To ensure effective implementation of training models, evidence-based knowledge of validity and efficacy is needed. We provide a useful tool for implementation and evaluation of research in simulation-based training. Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

PubMed

Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi

2017-12-01

Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.

Evaluation of Liquid Fuel Spray Models for Hybrid RANS/LES and DLES Prediction of Turbulent Reactive Flows

NASA Astrophysics Data System (ADS)

Afshar, Ali

An evaluation of Lagrangian-based, discrete-phase models for multi-component liquid sprays encountered in the combustors of gas turbine engines is considered. In particular, the spray modeling capabilities of the commercial software, ANSYS Fluent, was evaluated. Spray modeling was performed for various cold flow validation cases. These validation cases include a liquid jet in a cross-flow, an airblast atomizer, and a high shear fuel nozzle. Droplet properties including velocity and diameter were investigated and compared with previous experimental and numerical results. Different primary and secondary breakup models were evaluated in this thesis. The secondary breakup models investigated include the Taylor analogy breakup (TAB) model, the wave model, the Kelvin-Helmholtz Rayleigh-Taylor model (KHRT), and the Stochastic secondary droplet (SSD) approach. The modeling of fuel sprays requires a proper treatment for the turbulence. Reynolds-averaged Navier-Stokes (RANS), large eddy simulation (LES), hybrid RANS/LES, and dynamic LES (DLES) were also considered for the turbulent flows involving sprays. The spray and turbulence models were evaluated using the available benchmark experimental data.

Towards a model-based patient selection strategy for proton therapy: External validation of photon-derived Normal Tissue Complication Probability models in a head and neck proton therapy cohort

PubMed Central

Blanchard, P; Wong, AJ; Gunn, GB; Garden, AS; Mohamed, ASR; Rosenthal, DI; Crutison, J; Wu, R; Zhang, X; Zhu, XR; Mohan, R; Amin, MV; Fuller, CD; Frank, SJ

2017-01-01

Objective To externally validate head and neck cancer (HNC) photon-derived normal tissue complication probability (NTCP) models in patients treated with proton beam therapy (PBT). Methods This prospective cohort consisted of HNC patients treated with PBT at a single institution. NTCP models were selected based on the availability of data for validation and evaluated using the leave-one-out cross-validated area under the curve (AUC) for the receiver operating characteristics curve. Results 192 patients were included. The most prevalent tumor site was oropharynx (n=86, 45%), followed by sinonasal (n=28), nasopharyngeal (n=27) or parotid (n=27) tumors. Apart from the prediction of acute mucositis (reduction of AUC of 0.17), the models overall performed well. The validation (PBT) AUC and the published AUC were respectively 0.90 versus 0.88 for feeding tube 6 months post-PBT; 0.70 versus 0.80 for physician rated dysphagia 6 months post-PBT; 0.70 versus 0.80 for dry mouth 6 months post-PBT; and 0.73 versus 0.85 for hypothyroidism 12 months post-PBT. Conclusion While the drop in NTCP model performance was expected in PBT patients, the models showed robustness and remained valid. Further work is warranted, but these results support the validity of the model-based approach for treatment selection for HNC patients. PMID:27641784

Validation of the TTM processes of change measure for physical activity in an adult French sample.

PubMed

Bernard, Paquito; Romain, Ahmed-Jérôme; Trouillet, Raphael; Gernigon, Christophe; Nigg, Claudio; Ninot, Gregory

2014-04-01

Processes of change (POC) are constructs from the transtheoretical model that propose to examine how people engage in a behavior. However, there is no consensus about a leading model explaining POC and there is no validated French POC scale in physical activity This study aimed to compare the different existing models to validate a French POC scale. Three studies, with 748 subjects included, were carried out to translate the items and evaluate their clarity (study 1, n = 77), to assess the factorial validity (n = 200) and invariance/equivalence (study 2, n = 471), and to analyze the concurrent validity by stage × process analyses (study 3, n = 671). Two models displayed adequate fit to the data; however, based on the Akaike information criterion, the fully correlated five-factor model appeared as the most appropriate to measure POC in physical activity. The invariance/equivalence was also confirmed across genders and student status. Four of the five existing factors discriminated pre-action and post-action stages. These data support the validation of the POC questionnaire in physical activity among a French sample. More research is needed to explore the longitudinal properties of this scale.

Utilisation of real-scale renewable energy test facility for validation of generic wind turbine and wind power plant controller models

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

Zeni, Lorenzo; Hesselbæk, Bo; Bech, John

This article presents an example of application of a modern test facility conceived for experiments regarding the integration of renewable energy in the power system. The capabilities of the test facility are used to validate dynamic simulation models of wind power plants and their controllers. The models are based on standard and generic blocks. The successful validation of events related to the control of active power (control phenomena in <10 Hz range, including frequency control and power oscillation damping) is described, demonstrating the capabilities of the test facility and drawing the track for future work and improvements.

ASTP ranging system mathematical model

NASA Technical Reports Server (NTRS)

Ellis, M. R.; Robinson, L. H.

1973-01-01

A mathematical model is presented of the VHF ranging system to analyze the performance of the Apollo-Soyuz test project (ASTP). The system was adapted for use in the ASTP. The ranging system mathematical model is presented in block diagram form, and a brief description of the overall model is also included. A procedure for implementing the math model is presented along with a discussion of the validation of the math model and the overall summary and conclusions of the study effort. Detailed appendices of the five study tasks are presented: early late gate model development, unlock probability development, system error model development, probability of acquisition and model development, and math model validation testing.

Generalized Beer-Lambert model for near-infrared light propagation in thick biological tissues

NASA Astrophysics Data System (ADS)

Bhatt, Manish; Ayyalasomayajula, Kalyan R.; Yalavarthy, Phaneendra K.

2016-07-01

The attenuation of near-infrared (NIR) light intensity as it propagates in a turbid medium like biological tissue is described by modified the Beer-Lambert law (MBLL). The MBLL is generally used to quantify the changes in tissue chromophore concentrations for NIR spectroscopic data analysis. Even though MBLL is effective in terms of providing qualitative comparison, it suffers from its applicability across tissue types and tissue dimensions. In this work, we introduce Lambert-W function-based modeling for light propagation in biological tissues, which is a generalized version of the Beer-Lambert model. The proposed modeling provides parametrization of tissue properties, which includes two attenuation coefficients μ0 and η. We validated our model against the Monte Carlo simulation, which is the gold standard for modeling NIR light propagation in biological tissue. We included numerous human and animal tissues to validate the proposed empirical model, including an inhomogeneous adult human head model. The proposed model, which has a closed form (analytical), is first of its kind in providing accurate modeling of NIR light propagation in biological tissues.

Community-wide validation of geospace model local K-index predictions to support model transition to operations

NASA Astrophysics Data System (ADS)

Glocer, A.; Rastätter, L.; Kuznetsova, M.; Pulkkinen, A.; Singer, H. J.; Balch, C.; Weimer, D.; Welling, D.; Wiltberger, M.; Raeder, J.; Weigel, R. S.; McCollough, J.; Wing, S.

2016-07-01

We present the latest result of a community-wide space weather model validation effort coordinated among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), model developers, and the broader science community. Validation of geospace models is a critical activity for both building confidence in the science results produced by the models and in assessing the suitability of the models for transition to operations. Indeed, a primary motivation of this work is supporting NOAA/SWPC's effort to select a model or models to be transitioned into operations. Our validation efforts focus on the ability of the models to reproduce a regional index of geomagnetic disturbance, the local K-index. Our analysis includes six events representing a range of geomagnetic activity conditions and six geomagnetic observatories representing midlatitude and high-latitude locations. Contingency tables, skill scores, and distribution metrics are used for the quantitative analysis of model performance. We consider model performance on an event-by-event basis, aggregated over events, at specific station locations, and separated into high-latitude and midlatitude domains. A summary of results is presented in this report, and an online tool for detailed analysis is available at the CCMC.

Community-Wide Validation of Geospace Model Local K-Index Predictions to Support Model Transition to Operations

NASA Technical Reports Server (NTRS)

Glocer, A.; Rastaetter, L.; Kuznetsova, M.; Pulkkinen, A.; Singer, H. J.; Balch, C.; Weimer, D.; Welling, D.; Wiltberger, M.; Raeder, J.;

GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world.

PubMed

Panayidou, Klea; Gsteiger, Sandro; Egger, Matthias; Kilcher, Gablu; Carreras, Máximo; Efthimiou, Orestis; Debray, Thomas P A; Trelle, Sven; Hummel, Noemi

2016-09-01

The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real-world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi-state models, discrete event simulation models, physiology-based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real-world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

Risk prediction models of breast cancer: a systematic review of model performances.

PubMed

Anothaisintawee, Thunyarat; Teerawattananon, Yot; Wiratkapun, Chollathip; Kasamesup, Vijj; Thakkinstian, Ammarin

2012-05-01

The number of risk prediction models has been increasingly developed, for estimating about breast cancer in individual women. However, those model performances are questionable. We therefore have conducted a study with the aim to systematically review previous risk prediction models. The results from this review help to identify the most reliable model and indicate the strengths and weaknesses of each model for guiding future model development. We searched MEDLINE (PubMed) from 1949 and EMBASE (Ovid) from 1974 until October 2010. Observational studies which constructed models using regression methods were selected. Information about model development and performance were extracted. Twenty-five out of 453 studies were eligible. Of these, 18 developed prediction models and 7 validated existing prediction models. Up to 13 variables were included in the models and sample sizes for each study ranged from 550 to 2,404,636. Internal validation was performed in four models, while five models had external validation. Gail and Rosner and Colditz models were the significant models which were subsequently modified by other scholars. Calibration performance of most models was fair to good (expected/observe ratio: 0.87-1.12), but discriminatory accuracy was poor to fair both in internal validation (concordance statistics: 0.53-0.66) and in external validation (concordance statistics: 0.56-0.63). Most models yielded relatively poor discrimination in both internal and external validation. This poor discriminatory accuracy of existing models might be because of a lack of knowledge about risk factors, heterogeneous subtypes of breast cancer, and different distributions of risk factors across populations. In addition the concordance statistic itself is insensitive to measure the improvement of discrimination. Therefore, the new method such as net reclassification index should be considered to evaluate the improvement of the performance of a new develop model.

Experimental Validation: Subscale Aircraft Ground Facilities and Integrated Test Capability

NASA Technical Reports Server (NTRS)

Bailey, Roger M.; Hostetler, Robert W., Jr.; Barnes, Kevin N.; Belcastro, Celeste M.; Belcastro, Christine M.

2005-01-01

Experimental testing is an important aspect of validating complex integrated safety critical aircraft technologies. The Airborne Subscale Transport Aircraft Research (AirSTAR) Testbed is being developed at NASA Langley to validate technologies under conditions that cannot be flight validated with full-scale vehicles. The AirSTAR capability comprises a series of flying sub-scale models, associated ground-support equipment, and a base research station at NASA Langley. The subscale model capability utilizes a generic 5.5% scaled transport class vehicle known as the Generic Transport Model (GTM). The AirSTAR Ground Facilities encompass the hardware and software infrastructure necessary to provide comprehensive support services for the GTM testbed. The ground facilities support remote piloting of the GTM aircraft, and include all subsystems required for data/video telemetry, experimental flight control algorithm implementation and evaluation, GTM simulation, data recording/archiving, and audio communications. The ground facilities include a self-contained, motorized vehicle serving as a mobile research command/operations center, capable of deployment to remote sites when conducting GTM flight experiments. The ground facilities also include a laboratory based at NASA LaRC providing near identical capabilities as the mobile command/operations center, as well as the capability to receive data/video/audio from, and send data/audio to the mobile command/operations center during GTM flight experiments.

Development and Validation of a Novel Pediatric Appendicitis Risk Calculator (pARC).

PubMed

Kharbanda, Anupam B; Vazquez-Benitez, Gabriela; Ballard, Dustin W; Vinson, David R; Chettipally, Uli K; Kene, Mamata V; Dehmer, Steven P; Bachur, Richard G; Dayan, Peter S; Kuppermann, Nathan; O'Connor, Patrick J; Kharbanda, Elyse O

2018-04-01

We sought to develop and validate a clinical calculator that can be used to quantify risk for appendicitis on a continuous scale for patients with acute abdominal pain. The pediatric appendicitis risk calculator (pARC) was developed and validated through secondary analyses of 3 distinct cohorts. The derivation sample included visits to 9 pediatric emergency departments between March 2009 and April 2010. The validation sample included visits to a single pediatric emergency department from 2003 to 2004 and 2013 to 2015. Variables evaluated were as follows: age, sex, temperature, nausea and/or vomiting, pain duration, pain location, pain with walking, pain migration, guarding, white blood cell count, and absolute neutrophil count. We used stepwise regression to develop and select the best model. Test performance of the pARC was compared with the Pediatric Appendicitis Score (PAS). The derivation sample included 2423 children, 40% of whom had appendicitis. The validation sample included 1426 children, 35% of whom had appendicitis. The final pARC model included the following variables: sex, age, duration of pain, guarding, pain migration, maximal tenderness in the right-lower quadrant, and absolute neutrophil count. In the validation sample, the pARC exhibited near perfect calibration and a high degree of discrimination (area under the curve: 0.85; 95% confidence interval: 0.83 to 0.87) and outperformed the PAS (area under the curve: 0.77; 95% confidence interval: 0.75 to 0.80). By using the pARC, almost half of patients in the validation cohort could be accurately classified as at <15% risk or ≥85% risk for appendicitis, whereas only 23% would be identified as having a comparable PAS of <3 or >8. In our validation cohort of patients with acute abdominal pain, the pARC accurately quantified risk for appendicitis. Copyright © 2018 by the American Academy of Pediatrics.

Mining for Data

NASA Technical Reports Server (NTRS)

1998-01-01

AbTech Corporation used an F-18 HARV (High Alpha Research Vehicle) simulation developed by NASA to create an interactive computer-based prototype of the MQ (Model Quest) SV (System Validator) tool. Dryden Flight Research Center provided support to develop, test, and rapidly reprogram the validation function. AbTech's ModelQuest Enterprises highly automated and outperforms other modeling techniques to quickly discover meaningful relationships, patterns, and trends in databases. Applications include technical and business professionals in finance, marketing, business, banking, retail, healthcare, and aerospace.

Model performance evaluation (validation and calibration) in model-based studies of therapeutic interventions for cardiovascular diseases : a review and suggested reporting framework.

PubMed

Haji Ali Afzali, Hossein; Gray, Jodi; Karnon, Jonathan

2013-04-01

Decision analytic models play an increasingly important role in the economic evaluation of health technologies. Given uncertainties around the assumptions used to develop such models, several guidelines have been published to identify and assess 'best practice' in the model development process, including general modelling approach (e.g., time horizon), model structure, input data and model performance evaluation. This paper focuses on model performance evaluation. In the absence of a sufficient level of detail around model performance evaluation, concerns regarding the accuracy of model outputs, and hence the credibility of such models, are frequently raised. Following presentation of its components, a review of the application and reporting of model performance evaluation is presented. Taking cardiovascular disease as an illustrative example, the review investigates the use of face validity, internal validity, external validity, and cross model validity. As a part of the performance evaluation process, model calibration is also discussed and its use in applied studies investigated. The review found that the application and reporting of model performance evaluation across 81 studies of treatment for cardiovascular disease was variable. Cross-model validation was reported in 55 % of the reviewed studies, though the level of detail provided varied considerably. We found that very few studies documented other types of validity, and only 6 % of the reviewed articles reported a calibration process. Considering the above findings, we propose a comprehensive model performance evaluation framework (checklist), informed by a review of best-practice guidelines. This framework provides a basis for more accurate and consistent documentation of model performance evaluation. This will improve the peer review process and the comparability of modelling studies. Recognising the fundamental role of decision analytic models in informing public funding decisions, the proposed framework should usefully inform guidelines for preparing submissions to reimbursement bodies.

Validity of worksheet-based guided inquiry and mind mapping for training students’ creative thinking skills

NASA Astrophysics Data System (ADS)

Susanti, L. B.; Poedjiastoeti, S.; Taufikurohmah, T.

2018-04-01

The purpose of this study is to explain the validity of guided inquiry and mind mapping-based worksheet that has been developed in this study. The worksheet implemented the phases of guided inquiry teaching models in order to train students’ creative thinking skills. The creative thinking skills which were trained in this study included fluency, flexibility, originality and elaboration. The types of validity used in this study included content and construct validity. The type of this study is development research with Research and Development (R & D) method. The data of this study were collected using review and validation sheets. Sources of the data were chemistry lecturer and teacher. The data is the analyzed descriptively. The results showed that the worksheet is very valid and could be used as a learning media with the percentage of validity ranged from 82.5%-92.5%.

Verification and Validation of COAMPS: Results from a Fully-Coupled Air/Sea/Wave Modeling System

NASA Astrophysics Data System (ADS)

Smith, T.; Allard, R. A.; Campbell, T. J.; Chu, Y. P.; Dykes, J.; Zamudio, L.; Chen, S.; Gabersek, S.

2016-02-01

The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) is a state-of-the art, fully-coupled air/sea/wave modeling system that is currently being validated for operational transition to both the Naval Oceanographic Office (NAVO) and to the Fleet Numerical Meteorology and Oceanography Center (FNMOC). COAMPS is run at the Department of Defense Supercomputing Resource Center (DSRC) operated by the DoD High Performance Computing Modernization Program (HPCMP). A total of four models including the Naval Coastal Ocean Model (NCOM), Simulating Waves Nearshore (SWAN), WaveWatch III, and the COAMPS atmospheric model are coupled through both the Earth System Modeling Framework (ESMF). Results from regions of naval operational interests, including the Western Atlantic (U.S. East Coast), RIMPAC (Hawaii), and DYNAMO (Indian Ocean), will show the advantages of utilizing a coupled modeling system versus an uncoupled or stand alone model. Statistical analyses, which include model/observation comparisons, will be presented in the form of operationally approved scorecards for both the atmospheric and oceanic output. Also, computational logistics involving the HPC resources for the COAMPS simulations will be shown.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

PubMed

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

PubMed

Slavov, Svetoslav H; Stoyanova-Slavova, Iva; Mattes, William; Beger, Richard D; Brüschweiler, Beat J

2018-07-01

A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13 C and 15 N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.

Validation and uncertainty analysis of a pre-treatment 2D dose prediction model

NASA Astrophysics Data System (ADS)

Baeza, Jose A.; Wolfs, Cecile J. A.; Nijsten, Sebastiaan M. J. J. G.; Verhaegen, Frank

2018-02-01

Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

TH-AB-BRA-07: PENELOPE-Based GPU-Accelerated Dose Calculation System Applied to MRI-Guided Radiation Therapy

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

Wang, Y; Mazur, T; Green, O

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: We first translated PENELOPE from FORTRAN to C++ and validated that the translation produced equivalent results. Then we adapted the C++ code to CUDA in a workflow optimized for GPU architecture. We expanded upon the original code to include voxelized transportmore » boosted by Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, we incorporated the vendor-provided MRIdian head model into the code. We performed a set of experimental measurements on MRIdian to examine the accuracy of both the head model and gPENELOPE, and then applied gPENELOPE toward independent validation of patient doses calculated by MRIdian’s KMC. Results: We achieve an average acceleration factor of 152 compared to the original single-thread FORTRAN implementation with the original accuracy preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen (1), mediastinum (1) and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: We developed a Monte Carlo simulation platform based on a GPU-accelerated version of PENELOPE. We validated that both the vendor provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.« less

Progress & Frontiers in PV Performance

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

Deline, Chris; DiOrio, Nick; Jordan, Dirk

2016-09-12

PowerPoint slides for a presentation given at Solar Power International 2016. Presentation includes System Advisor Model (SAM) introduction and battery modeling, bifacial PV modules and modeling, shade modeling and module level power electronics (MLPE), degradation rates, and PVWatts updates and validation.

Glass Transition Temperature- and Specific Volume- Composition Models for Tellurite Glasses

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

Riley, Brian J.; Vienna, John D.

This report provides models for predicting composition-properties for tellurite glasses, namely specific gravity and glass transition temperature. Included are the partial specific coefficients for each model, the component validity ranges, and model fit parameters.

SU-E-J-244: Development and Validation of a Knowledge Based Planning Model for External Beam Radiation Therapy of Locally Advanced Non-Small Cell Lung Cancer

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

Liu, Z; Kennedy, A; Larsen, E

2015-06-15

Purpose: The study aims to develop and validate a knowledge based planning (KBP) model for external beam radiation therapy of locally advanced non-small cell lung cancer (LA-NSCLC). Methods: RapidPlan™ technology was used to develop a lung KBP model. Plans from 65 patients with LA-NSCLC were used to train the model. 25 patients were treated with VMAT, and the other patients were treated with IMRT. Organs-at-risk (OARs) included right lung, left lung, heart, esophagus, and spinal cord. DVH and geometric distribution DVH were extracted from the treated plans. The model was trained using principal component analysis and step-wise multiple regression. Boxmore » plot and regression plot tools were used to identify geometric outliers and dosimetry outliers and help fine-tune the model. The validation was performed by (a) comparing predicted DVH boundaries to actual DVHs of 63 patients and (b) using an independent set of treatment planning data. Results: 63 out of 65 plans were included in the final KBP model with PTV volume ranging from 102.5cc to 1450.2cc. Total treatment dose prescription varied from 50Gy to 70Gy based on institutional guidelines. One patient was excluded due to geometric outlier where 2.18cc of spinal cord was included in PTV. The other patient was excluded due to dosimetric outlier where the dose sparing to spinal cord was heavily enforced in the clinical plan. Target volume, OAR volume, OAR overlap volume percentage to target, and OAR out-of-field volume were included in the trained model. Lungs and heart had two principal component scores of GEDVH, whereas spinal cord and esophagus had three in the final model. Predicted DVH band (mean ±1 standard deviation) represented 66.2±3.6% of all DVHs. Conclusion: A KBP model was developed and validated for radiotherapy of LA-NSCLC in a commercial treatment planning system. The clinical implementation may improve the consistency of IMRT/VMAT planning.« less

Prediction Models for 30-Day Mortality and Complications After Total Knee and Hip Arthroplasties for Veteran Health Administration Patients With Osteoarthritis.

PubMed

Harris, Alex Hs; Kuo, Alfred C; Bowe, Thomas; Gupta, Shalini; Nordin, David; Giori, Nicholas J

2018-05-01

Statistical models to preoperatively predict patients' risk of death and major complications after total joint arthroplasty (TJA) could improve the quality of preoperative management and informed consent. Although risk models for TJA exist, they have limitations including poor transparency and/or unknown or poor performance. Thus, it is currently impossible to know how well currently available models predict short-term complications after TJA, or if newly developed models are more accurate. We sought to develop and conduct cross-validation of predictive risk models, and report details and performance metrics as benchmarks. Over 90 preoperative variables were used as candidate predictors of death and major complications within 30 days for Veterans Health Administration patients with osteoarthritis who underwent TJA. Data were split into 3 samples-for selection of model tuning parameters, model development, and cross-validation. C-indexes (discrimination) and calibration plots were produced. A total of 70,569 patients diagnosed with osteoarthritis who received primary TJA were included. C-statistics and bootstrapped confidence intervals for the cross-validation of the boosted regression models were highest for cardiac complications (0.75; 0.71-0.79) and 30-day mortality (0.73; 0.66-0.79) and lowest for deep vein thrombosis (0.59; 0.55-0.64) and return to the operating room (0.60; 0.57-0.63). Moderately accurate predictive models of 30-day mortality and cardiac complications after TJA in Veterans Health Administration patients were developed and internally cross-validated. By reporting model coefficients and performance metrics, other model developers can test these models on new samples and have a procedure and indication-specific benchmark to surpass. Published by Elsevier Inc.

Temperature and heat flux datasets of a complex object in a fire plume for the validation of fire and thermal response codes.

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

Jernigan, Dann A.; Blanchat, Thomas K.

It is necessary to improve understanding and develop temporally- and spatially-resolved integral scale validation data of the heat flux incident to a complex object in addition to measuring the thermal response of said object located within the fire plume for the validation of the SIERRA/FUEGO/SYRINX fire and SIERRA/CALORE codes. To meet this objective, a complex calorimeter with sufficient instrumentation to allow validation of the coupling between FUEGO/SYRINX/CALORE has been designed, fabricated, and tested in the Fire Laboratory for Accreditation of Models and Experiments (FLAME) facility. Validation experiments are specifically designed for direct comparison with the computational predictions. Making meaningful comparisonmore » between the computational and experimental results requires careful characterization and control of the experimental features or parameters used as inputs into the computational model. Validation experiments must be designed to capture the essential physical phenomena, including all relevant initial and boundary conditions. This report presents the data validation steps and processes, the results of the penlight radiant heat experiments (for the purpose of validating the CALORE heat transfer modeling of the complex calorimeter), and the results of the fire tests in FLAME.« less

User's Manual for Data for Validating Models for PV Module Performance

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

Marion, W.; Anderberg, A.; Deline, C.

2014-04-01

This user's manual describes performance data measured for flat-plate photovoltaic (PV) modules installed in Cocoa, Florida, Eugene, Oregon, and Golden, Colorado. The data include PV module current-voltage curves and associated meteorological data for approximately one-year periods. These publicly available data are intended to facilitate the validation of existing models for predicting the performance of PV modules, and for the development of new and improved models. For comparing different modeling approaches, using these public data will provide transparency and more meaningful comparisons of the relative benefits.

Toward accurate and valid estimates of greenhouse gas reductions from bikeway projects.

DOT National Transportation Integrated Search

2016-07-31

We sought to accurately and validly model emissions generating and activities, including changes in traveler behavior and thus GHG : emissions in the wake of bikeway projects. We wanted the results to be applicable to practice and policy in Californi...

Issues and approach to develop validated analysis tools for hypersonic flows: One perspective

NASA Technical Reports Server (NTRS)

Deiwert, George S.

1993-01-01

Critical issues concerning the modeling of low density hypervelocity flows where thermochemical nonequilibrium effects are pronounced are discussed. Emphasis is on the development of validated analysis tools, and the activity in the NASA Ames Research Center's Aerothermodynamics Branch is described. Inherent in the process is a strong synergism between ground test and real gas computational fluid dynamics (CFD). Approaches to develop and/or enhance phenomenological models and incorporate them into computational flowfield simulation codes are discussed. These models were partially validated with experimental data for flows where the gas temperature is raised (compressive flows). Expanding flows, where temperatures drop, however, exhibit somewhat different behavior. Experimental data for these expanding flow conditions is sparse and reliance must be made on intuition and guidance from computational chemistry to model transport processes under these conditions. Ground based experimental studies used to provide necessary data for model development and validation are described. Included are the performance characteristics of high enthalpy flow facilities, such as shock tubes and ballistic ranges.

Issues and approach to develop validated analysis tools for hypersonic flows: One perspective

NASA Technical Reports Server (NTRS)

Deiwert, George S.

1992-01-01

Critical issues concerning the modeling of low-density hypervelocity flows where thermochemical nonequilibrium effects are pronounced are discussed. Emphasis is on the development of validated analysis tools. A description of the activity in the Ames Research Center's Aerothermodynamics Branch is also given. Inherent in the process is a strong synergism between ground test and real-gas computational fluid dynamics (CFD). Approaches to develop and/or enhance phenomenological models and incorporate them into computational flow-field simulation codes are discussed. These models have been partially validated with experimental data for flows where the gas temperature is raised (compressive flows). Expanding flows, where temperatures drop, however, exhibit somewhat different behavior. Experimental data for these expanding flow conditions are sparse; reliance must be made on intuition and guidance from computational chemistry to model transport processes under these conditions. Ground-based experimental studies used to provide necessary data for model development and validation are described. Included are the performance characteristics of high-enthalpy flow facilities, such as shock tubes and ballistic ranges.

NC truck network model development research.

DOT National Transportation Integrated Search

2008-09-01

This research develops a validated prototype truck traffic network model for North Carolina. The model : includes all counties and metropolitan areas of North Carolina and major economic areas throughout the : U.S. Geographic boundaries, population a...

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...

An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.

PubMed

Bratzler, Dale W; Normand, Sharon-Lise T; Wang, Yun; O'Donnell, Walter J; Metersky, Mark; Han, Lein F; Rapp, Michael T; Krumholz, Harlan M

2011-04-12

Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia. Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032). An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model.

An Administrative Claims Model for Profiling Hospital 30-Day Mortality Rates for Pneumonia Patients

PubMed Central

Bratzler, Dale W.; Normand, Sharon-Lise T.; Wang, Yun; O'Donnell, Walter J.; Metersky, Mark; Han, Lein F.; Rapp, Michael T.; Krumholz, Harlan M.

2011-01-01

Background Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia. Methodology/Principal Findings Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998–2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998–2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25th, 50th, and 75th percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032). Conclusions/Significance An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model. PMID:21532758

A Historical Forcing Ice Sheet Model Validation Framework for Greenland

NASA Astrophysics Data System (ADS)

Price, S. F.; Hoffman, M. J.; Howat, I. M.; Bonin, J. A.; Chambers, D. P.; Kalashnikova, I.; Neumann, T.; Nowicki, S.; Perego, M.; Salinger, A.

2014-12-01

We propose an ice sheet model testing and validation framework for Greenland for the years 2000 to the present. Following Perego et al. (2014), we start with a realistic ice sheet initial condition that is in quasi-equilibrium with climate forcing from the late 1990's. This initial condition is integrated forward in time while simultaneously applying (1) surface mass balance forcing (van Angelen et al., 2013) and (2) outlet glacier flux anomalies, defined using a new dataset of Greenland outlet glacier flux for the past decade (Enderlin et al., 2014). Modeled rates of mass and elevation change are compared directly to remote sensing observations obtained from GRACE and ICESat. Here, we present a detailed description of the proposed validation framework including the ice sheet model and model forcing approach, the model-to-observation comparison process, and initial results comparing model output and observations for the time period 2000-2013.

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

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

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

Twilight reloaded: the peptide experience

PubMed Central

Weichenberger, Christian X.; Pozharski, Edwin; Rupp, Bernhard

2017-01-01

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallo­graphic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein–peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided. PMID:28291756

Twilight reloaded: the peptide experience.

PubMed

Weichenberger, Christian X; Pozharski, Edwin; Rupp, Bernhard

2017-03-01

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallographic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein-peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided.

LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

NASA Astrophysics Data System (ADS)

Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.; Price, Stephen; Hoffman, Matthew; Lipscomb, William H.; Fyke, Jeremy; Vargo, Lauren; Boghozian, Adrianna; Norman, Matthew; Worley, Patrick H.

2017-06-01

To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptops to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Ultimately, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.

Model-based clinical dose optimization for phenobarbital in neonates: An illustration of the importance of data sharing and external validation.

PubMed

Völler, Swantje; Flint, Robert B; Stolk, Leo M; Degraeuwe, Pieter L J; Simons, Sinno H P; Pokorna, Paula; Burger, David M; de Groot, Ronald; Tibboel, Dick; Knibbe, Catherijne A J

2017-11-15

Particularly in the pediatric clinical pharmacology field, data-sharing offers the possibility of making the most of all available data. In this study, we utilize previously collected therapeutic drug monitoring (TDM) data of term and preterm newborns to develop a population pharmacokinetic model for phenobarbital. We externally validate the model using prospective phenobarbital data from an ongoing pharmacokinetic study in preterm neonates. TDM data from 53 neonates (gestational age (GA): 37 (24-42) weeks, bodyweight: 2.7 (0.45-4.5) kg; postnatal age (PNA): 4.5 (0-22) days) contained information on dosage histories, concentration and covariate data (including birth weight, actual weight, post-natal age (PNA), postmenstrual age, GA, sex, liver and kidney function, APGAR-score). Model development was carried out using NONMEM ® 7.3. After assessment of model fit, the model was validated using data of 17 neonates included in the DINO (Drug dosage Improvement in NeOnates)-study. Modelling of 229 plasma concentrations, ranging from 3.2 to 75.2mg/L, resulted in a one compartment model for phenobarbital. Clearance (CL) and volume (V d ) for a child with a birthweight of 2.6kg at PNA day 4.5 was 0.0091L/h (9%) and 2.38L (5%), respectively. Birthweight and PNA were the best predictors for CL maturation, increasing CL by 36.7% per kg birthweight and 5.3% per postnatal day of living, respectively. The best predictor for the increase in V d was actual bodyweight (0.31L/kg). External validation showed that the model can adequately predict the pharmacokinetics in a prospective study. Data-sharing can help to successfully develop and validate population pharmacokinetic models in neonates. From the results it seems that both PNA and bodyweight are required to guide dosing of phenobarbital in term and preterm neonates. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

PubMed

Dehing-Oberije, Cary; Aerts, Hugo; Yu, Shipeng; De Ruysscher, Dirk; Menheere, Paul; Hilvo, Mika; van der Weide, Hiska; Rao, Bharat; Lambin, Philippe

2011-10-01

Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival. Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52). The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively. The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6. Copyright © 2011 Elsevier Inc. All rights reserved.

An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram.

PubMed

Lauer, Michael S; Pothier, Claire E; Magid, David J; Smith, S Scott; Kattan, Michael W

2007-12-18

The exercise treadmill test is recommended for risk stratification among patients with intermediate to high pretest probability of coronary artery disease. Posttest risk stratification is based on the Duke treadmill score, which includes only functional capacity and measures of ischemia. To develop and externally validate a post-treadmill test, multivariable mortality prediction rule for adults with suspected coronary artery disease and normal electrocardiograms. Prospective cohort study conducted from September 1990 to May 2004. Exercise treadmill laboratories in a major medical center (derivation set) and a separate HMO (validation set). 33,268 patients in the derivation set and 5821 in the validation set. All patients had normal electrocardiograms and were referred for evaluation of suspected coronary artery disease. The derivation set patients were followed for a median of 6.2 years. A nomogram-illustrated model was derived on the basis of variables easily obtained in the stress laboratory, including age; sex; history of smoking, hypertension, diabetes, or typical angina; and exercise findings of functional capacity, ST-segment changes, symptoms, heart rate recovery, and frequent ventricular ectopy in recovery. The derivation data set included 1619 deaths. Although both the Duke treadmill score and our nomogram-illustrated model were significantly associated with death (P < 0.001), the nomogram was better at discrimination (concordance index for right-censored data, 0.83 vs. 0.73) and calibration. We reclassified many patients with intermediate- to high-risk Duke treadmill scores as low risk on the basis of the nomogram. The model also predicted 3-year mortality rates well in the validation set: Based on an optimal cut-point for a negative predictive value of 0.97, derivation and validation rates were, respectively, 1.7% and 2.5% below the cut-point and 25% and 29% above the cut-point. Blood test-based measures or left ventricular ejection fraction were not included. The nomogram can be applied only to patients with a normal electrocardiogram. Clinical utility remains to be tested. A simple nomogram based on easily obtained pretest and exercise test variables predicted all-cause mortality in adults with suspected coronary artery disease and normal electrocardiograms.

A scoring system to predict breast cancer mortality at 5 and 10 years.

PubMed

Paredes-Aracil, Esther; Palazón-Bru, Antonio; Folgado-de la Rosa, David Manuel; Ots-Gutiérrez, José Ramón; Compañ-Rosique, Antonio Fernando; Gil-Guillén, Vicente Francisco

2017-03-24

Although predictive models exist for mortality in breast cancer (BC) (generally all cause-mortality), they are not applicable to all patients and their statistical methodology is not the most powerful to develop a predictive model. Consequently, we developed a predictive model specific for BC mortality at 5 and 10 years resolving the above issues. This cohort study included 287 patients diagnosed with BC in a Spanish region in 2003-2016. time-to-BC death. Secondary variables: age, personal history of breast surgery, personal history of any cancer/BC, premenopause, postmenopause, grade, estrogen receptor, progesterone receptor, c-erbB2, TNM stage, multicentricity/multifocality, diagnosis and treatment. A points system was constructed to predict BC mortality at 5 and 10 years. The model was internally validated by bootstrapping. The points system was integrated into a mobile application for Android. Mean follow-up was 8.6 ± 3.5 years and 55 patients died of BC. The points system included age, personal history of BC, grade, TNM stage and multicentricity. Validation was satisfactory, in both discrimination and calibration. In conclusion, we constructed and internally validated a scoring system for predicting BC mortality at 5 and 10 years. External validation studies are needed for its use in other geographical areas.

In silico modeling to predict drug-induced phospholipidosis

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

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

2013-06-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

Development of the Japanese version of the Council on Nutrition Appetite Questionnaire and its simplified versions, and evaluation of their reliability, validity, and reproducibility.

PubMed

Tokudome, Yuko; Okumura, Keiko; Kumagai, Yoshiko; Hirano, Hirohiko; Kim, Hunkyung; Morishita, Shiho; Watanabe, Yutaka

2017-11-01

Because few Japanese questionnaires assess the elderly's appetite, there is an urgent need to develop an appetite questionnaire with verified reliability, validity, and reproducibility. We translated and back-translated the Council on Nutrition Appetite Questionnaire (CNAQ), which has eight items, into Japanese (CNAQ-J), as well as the Simplified Nutritional Appetite Questionnaire (SNAQ-J), which includes four CNAQ-J-derived items. Using structural equation modeling, we examined the CNAQ-J structure based on data of 649 Japanese elderly people in 2013, including individuals having a certain degree of cognitive impairment, and we developed the SNAQ for the Japanese elderly (SNAQ-JE) according to an exploratory factor analysis. Confirmatory factor analyses on the appetite questionnaires were conducted to probe fitting to the model. We computed Cronbach's α coefficients and criterion-referenced/-related validity figures examining associations of the three appetite battery scores with body mass index (BMI) values and with nutrition-related questionnaire values. Test-retest reproducibility of appetite tools was scrutinized over an approximately 2-week interval. An exploratory factor analysis demonstrated that the CNAQ-J was constructed of one factor (appetite), yielding the SNAQ-JE, which includes four questions derived from the CNAQ-J. The three appetite instruments showed almost equivalent fitting to the model and reproducibility. The CNAQ-J and SNAQ-JE demonstrated satisfactory reliability and significant criterion-referenced/-related validity values, including BMIs, but the SNAQ-J included a low factor-loading item, exhibited less satisfactory reliability and had a non-significant relationship to BMI. The CNAQ-J and SNAQ-JE may be applied to assess the appetite of Japanese elderly, including persons with some cognitive impairment. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Toward Supersonic Retropropulsion CFD Validation

NASA Technical Reports Server (NTRS)

Kleb, Bil; Schauerhamer, D. Guy; Trumble, Kerry; Sozer, Emre; Barnhardt, Michael; Carlson, Jan-Renee; Edquist, Karl

2011-01-01

This paper begins the process of verifying and validating computational fluid dynamics (CFD) codes for supersonic retropropulsive flows. Four CFD codes (DPLR, FUN3D, OVERFLOW, and US3D) are used to perform various numerical and physical modeling studies toward the goal of comparing predictions with a wind tunnel experiment specifically designed to support CFD validation. Numerical studies run the gamut in rigor from code-to-code comparisons to observed order-of-accuracy tests. Results indicate that this complex flowfield, involving time-dependent shocks and vortex shedding, design order of accuracy is not clearly evident. Also explored is the extent of physical modeling necessary to predict the salient flowfield features found in high-speed Schlieren images and surface pressure measurements taken during the validation experiment. Physical modeling studies include geometric items such as wind tunnel wall and sting mount interference, as well as turbulence modeling that ranges from a RANS (Reynolds-Averaged Navier-Stokes) 2-equation model to DES (Detached Eddy Simulation) models. These studies indicate that tunnel wall interference is minimal for the cases investigated; model mounting hardware effects are confined to the aft end of the model; and sparse grid resolution and turbulence modeling can damp or entirely dissipate the unsteadiness of this self-excited flow.

Validation of the Continuum of Care Conceptual Model for Athletic Therapy

PubMed Central

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

2015-01-01

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

Monte Carlo simulation of Ray-Scan 64 PET system and performance evaluation using GATE toolkit

NASA Astrophysics Data System (ADS)

Li, Suying; Zhang, Qiushi; Vuletic, Ivan; Xie, Zhaoheng; Yang, Kun; Ren, Qiushi

2017-02-01

In this study, we aimed to develop a GATE model for the simulation of Ray-Scan 64 PET scanner and model its performance characteristics. A detailed implementation of system geometry and physical process were included in the simulation model. Then we modeled the performance characteristics of Ray-Scan 64 PET system for the first time, based on National Electrical Manufacturers Association (NEMA) NU-2 2007 protocols and validated the model against experimental measurement, including spatial resolution, sensitivity, counting rates and noise equivalent count rate (NECR). Moreover, an accurate dead time module was investigated to simulate the counting rate performance. Overall results showed reasonable agreement between simulation and experimental data. The validation results showed the reliability and feasibility of the GATE model to evaluate major performance of Ray-Scan 64 PET system. It provided a useful tool for a wide range of research applications.

Perception of competence in middle school physical education: instrument development and validation.

PubMed

Scrabis-Fletcher, Kristin; Silverman, Stephen

2010-03-01

Perception of Competence (POC) has been studied extensively in physical activity (PA) research with similar instruments adapted for physical education (PE) research. Such instruments do not account for the unique PE learning environment. Therefore, an instrument was developed and the scores validated to measure POC in middle school PE. A multiphase design was used consisting of an intensive theoretical review, elicitation study, prepilot study, pilot study, content validation study, and final validation study (N=1281). Data analysis included a multistep iterative process to identify the best model fit. A three-factor model for POC was tested and resulted in root mean square error of approximation = .09, root mean square residual = .07, goodness offit index = .90, and adjusted goodness offit index = .86 values in the acceptable range (Hu & Bentler, 1999). A two-factor model was also tested and resulted in a good fit (two-factor fit indexes values = .05, .03, .98, .97, respectively). The results of this study suggest that an instrument using a three- or two-factor model provides reliable and valid scores ofPOC measurement in middle school PE.

Earth as an Extrasolar Planet: Earth Model Validation Using EPOXI Earth Observations

PubMed Central

Meadows, Victoria S.; Crisp, David; Deming, Drake; A'Hearn, Michael F.; Charbonneau, David; Livengood, Timothy A.; Seager, Sara; Barry, Richard K.; Hearty, Thomas; Hewagama, Tilak; Lisse, Carey M.; McFadden, Lucy A.; Wellnitz, Dennis D.

2011-01-01

Abstract The EPOXI Discovery Mission of Opportunity reused the Deep Impact flyby spacecraft to obtain spatially and temporally resolved visible photometric and moderate resolution near-infrared (NIR) spectroscopic observations of Earth. These remote observations provide a rigorous validation of whole-disk Earth model simulations used to better understand remotely detectable extrasolar planet characteristics. We have used these data to upgrade, correct, and validate the NASA Astrobiology Institute's Virtual Planetary Laboratory three-dimensional line-by-line, multiple-scattering spectral Earth model. This comprehensive model now includes specular reflectance from the ocean and explicitly includes atmospheric effects such as Rayleigh scattering, gas absorption, and temperature structure. We have used this model to generate spatially and temporally resolved synthetic spectra and images of Earth for the dates of EPOXI observation. Model parameters were varied to yield an optimum fit to the data. We found that a minimum spatial resolution of ∼100 pixels on the visible disk, and four categories of water clouds, which were defined by using observed cloud positions and optical thicknesses, were needed to yield acceptable fits. The validated model provides a simultaneous fit to Earth's lightcurve, absolute brightness, and spectral data, with a root-mean-square (RMS) error of typically less than 3% for the multiwavelength lightcurves and residuals of ∼10% for the absolute brightness throughout the visible and NIR spectral range. We have extended our validation into the mid-infrared by comparing the model to high spectral resolution observations of Earth from the Atmospheric Infrared Sounder, obtaining a fit with residuals of ∼7% and brightness temperature errors of less than 1 K in the atmospheric window. For the purpose of understanding the observable characteristics of the distant Earth at arbitrary viewing geometry and observing cadence, our validated forward model can be used to simulate Earth's time-dependent brightness and spectral properties for wavelengths from the far ultraviolet to the far infrared. Key Words: Astrobiology—Extrasolar terrestrial planets—Habitability—Planetary science—Radiative transfer. Astrobiology 11, 393–408. PMID:21631250

GNSS-Based Space Weather Systems Including COSMIC Ionospheric Measurements

NASA Technical Reports Server (NTRS)

Komjathy, Attila; Mandrake, Lukas; Wilson, Brian; Iijima, Byron; Pi, Xiaoqing; Hajj, George; Mannucci, Anthony J.

2006-01-01

The presentation outline includes University Corporation for Atmospheric Research (UCAR) and Jet Propulsion Laboratory (JPL) product comparisons, assimilating ground-based global positioning satellites (GPS) and COSMIC into JPL/University of Southern California (USC) Global Assimilative Ionospheric Model (GAIM), and JPL/USC GAIM validation. The discussion of comparisons examines Abel profiles and calibrated TEC. The JPL/USC GAIM validation uses Arecibo ISR, Jason-2 VTEC, and Abel profiles.

The Use of Modeling-Based Text to Improve Students' Modeling Competencies

ERIC Educational Resources Information Center

Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

2015-01-01

This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

Molprobity's ultimate rotamer-library distributions for model validation.

PubMed

Hintze, Bradley J; Lewis, Steven M; Richardson, Jane S; Richardson, David C

2016-09-01

Here we describe the updated MolProbity rotamer-library distributions derived from an order-of-magnitude larger and more stringently quality-filtered dataset of about 8000 (vs. 500) protein chains, and we explain the resulting changes and improvements to model validation as seen by users. To include only side-chains with satisfactory justification for their given conformation, we added residue-specific filters for electron-density value and model-to-density fit. The combined new protocol retains a million residues of data, while cleaning up false-positive noise in the multi- χ datapoint distributions. It enables unambiguous characterization of conformational clusters nearly 1000-fold less frequent than the most common ones. We describe examples of local interactions that favor these rare conformations, including the role of authentic covalent bond-angle deviations in enabling presumably strained side-chain conformations. Further, along with favored and outlier, an allowed category (0.3-2.0% occurrence in reference data) has been added, analogous to Ramachandran validation categories. The new rotamer distributions are used for current rotamer validation in MolProbity and PHENIX, and for rotamer choice in PHENIX model-building and refinement. The multi-dimensional χ distributions and Top8000 reference dataset are freely available on GitHub. These rotamers are termed "ultimate" because data sampling and quality are now fully adequate for this task, and also because we believe the future of conformational validation should integrate side-chain with backbone criteria. Proteins 2016; 84:1177-1189. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

MolProbity’s Ultimate Rotamer-Library Distributions for Model Validation

PubMed Central

Hintze, Bradley J.; Lewis, Steven M.; Richardson, Jane S.; Richardson, David C.

2016-01-01

Here we describe the updated MolProbity rotamer-library distributions derived from an order-of-magnitude larger and more stringently quality-filtered dataset of about 8000 (vs. 500) protein chains, and we explain the resulting changes and improvements to model validation as seen by users. To include only sidechains with satisfactory justification for their given conformation, we added residue-specific filters for electron-density value and model-to-density fit. The combined new protocol retains a million residues of data, while cleaning up false-positive noise in the multi-χ datapoint distributions. It enables unambiguous characterization of conformational clusters nearly 1000-fold less frequent than the most common ones. We describe examples of local interactions that favor these rare conformations, including the role of authentic covalent bond-angle deviations in enabling presumably strained sidechain conformations. Further, along with favored and outlier, an allowed category (0.3% to 2.0% occurrence in reference data) has been added, analogous to Ramachandran validation categories. The new rotamer distributions are used for current rotamer validation in Mol-Probity and PHENIX, and for rotamer choice in PHENIX model-building and refinement. The multi-dimensional χ distributions and Top8000 reference dataset are freely available on GitHub. These rotamers are termed “ultimate” because data sampling and quality are now fully adequate for this task, and also because we believe the future of conformational validation should integrate sidechain with backbone criteria. PMID:27018641

Prediction of risk of recurrence of venous thromboembolism following treatment for a first unprovoked venous thromboembolism: systematic review, prognostic model and clinical decision rule, and economic evaluation.

PubMed

Ensor, Joie; Riley, Richard D; Jowett, Sue; Monahan, Mark; Snell, Kym Ie; Bayliss, Susan; Moore, David; Fitzmaurice, David

2016-02-01

Unprovoked first venous thromboembolism (VTE) is defined as VTE in the absence of a temporary provoking factor such as surgery, immobility and other temporary factors. Recurrent VTE in unprovoked patients is highly prevalent, but easily preventable with oral anticoagulant (OAC) therapy. The unprovoked population is highly heterogeneous in terms of risk of recurrent VTE. The first aim of the project is to review existing prognostic models which stratify individuals by their recurrence risk, therefore potentially allowing tailored treatment strategies. The second aim is to enhance the existing research in this field, by developing and externally validating a new prognostic model for individual risk prediction, using a pooled database containing individual patient data (IPD) from several studies. The final aim is to assess the economic cost-effectiveness of the proposed prognostic model if it is used as a decision rule for resuming OAC therapy, compared with current standard treatment strategies. Standard systematic review methodology was used to identify relevant prognostic model development, validation and cost-effectiveness studies. Bibliographic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched using terms relating to the clinical area and prognosis. Reviewing was undertaken by two reviewers independently using pre-defined criteria. Included full-text articles were data extracted and quality assessed. Critical appraisal of included full texts was undertaken and comparisons made of model performance. A prognostic model was developed using IPD from the pooled database of seven trials. A novel internal-external cross-validation (IECV) approach was used to develop and validate a prognostic model, with external validation undertaken in each of the trials iteratively. Given good performance in the IECV approach, a final model was developed using all trials data. A Markov patient-level simulation was used to consider the economic cost-effectiveness of using a decision rule (based on the prognostic model) to decide on resumption of OAC therapy (or not). Three full-text articles were identified by the systematic review. Critical appraisal identified methodological and applicability issues; in particular, all three existing models did not have external validation. To address this, new prognostic models were sought with external validation. Two potential models were considered: one for use at cessation of therapy (pre D-dimer), and one for use after cessation of therapy (post D-dimer). Model performance measured in the external validation trials showed strong calibration performance for both models. The post D-dimer model performed substantially better in terms of discrimination (c = 0.69), better separating high- and low-risk patients. The economic evaluation identified that a decision rule based on the final post D-dimer model may be cost-effective for patients with predicted risk of recurrence of over 8% annually; this suggests continued therapy for patients with predicted risks ≥ 8% and cessation of therapy otherwise. The post D-dimer model performed strongly and could be useful to predict individuals' risk of recurrence at any time up to 2-3 years, thereby aiding patient counselling and treatment decisions. A decision rule using this model may be cost-effective for informing clinical judgement and patient opinion in treatment decisions. Further research may investigate new predictors to enhance model performance and aim to further externally validate to confirm performance in new, non-trial populations. Finally, it is essential that further research is conducted to develop a model predicting bleeding risk on therapy, to manage the balance between the risks of recurrence and bleeding. This study is registered as PROSPERO CRD42013003494. The National Institute for Health Research Health Technology Assessment programme.

Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

NASA Astrophysics Data System (ADS)

Schlup, Jason; Blanquart, Guillaume

2018-03-01

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development.

PubMed

Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin

2018-04-25

Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P < 0.001), and the number of negative sentinel lymph nodes (OR = 0.686, 95% CI 0.575-0.817; P < 0.001) were independent statistically significant predictors of non-sentinel lymph node metastasis. Furthermore, luminal B (OR = 3.311, 95% CI 1.593-6.884; P = 0.001) and HER2 overexpression (OR = 4.308, 95% CI 1.097-16.912; P = 0.036) were independent and statistically significant predictor of non-sentinel lymph node metastasis versus luminal A. A regression model based on the results of multivariate analysis was established to predict the risk of non-sentinel lymph node metastasis, which had an AUC of 0.8188. The model was validated in the validation cohort and showed excellent diagnostic performance. The mathematical prediction model that incorporates five variables including breast cancer molecular subtype demonstrates excellent diagnostic performance in assessing the risk of non-sentinel lymph node metastasis in sentinel lymph node-positive patients. The prediction model could be of help surgeons in evaluating the risk of non-sentinel lymph node involvement for breast cancer patients; however, the model requires further validation in prospective studies.

Validation and Trustworthiness of Multiscale Models of Cardiac Electrophysiology

PubMed Central

Pathmanathan, Pras; Gray, Richard A.

2018-01-01

Computational models of cardiac electrophysiology have a long history in basic science applications and device design and evaluation, but have significant potential for clinical applications in all areas of cardiovascular medicine, including functional imaging and mapping, drug safety evaluation, disease diagnosis, patient selection, and therapy optimisation or personalisation. For all stakeholders to be confident in model-based clinical decisions, cardiac electrophysiological (CEP) models must be demonstrated to be trustworthy and reliable. Credibility, that is, the belief in the predictive capability, of a computational model is primarily established by performing validation, in which model predictions are compared to experimental or clinical data. However, there are numerous challenges to performing validation for highly complex multi-scale physiological models such as CEP models. As a result, credibility of CEP model predictions is usually founded upon a wide range of distinct factors, including various types of validation results, underlying theory, evidence supporting model assumptions, evidence from model calibration, all at a variety of scales from ion channel to cell to organ. Consequently, it is often unclear, or a matter for debate, the extent to which a CEP model can be trusted for a given application. The aim of this article is to clarify potential rationale for the trustworthiness of CEP models by reviewing evidence that has been (or could be) presented to support their credibility. We specifically address the complexity and multi-scale nature of CEP models which makes traditional model evaluation difficult. In addition, we make explicit some of the credibility justification that we believe is implicitly embedded in the CEP modeling literature. Overall, we provide a fresh perspective to CEP model credibility, and build a depiction and categorisation of the wide-ranging body of credibility evidence for CEP models. This paper also represents a step toward the extension of model evaluation methodologies that are currently being developed by the medical device community, to physiological models. PMID:29497385

Development and validation of green eating behaviors, stage of change, decisional balance, and self-efficacy scales in college students.

PubMed

Weller, Kathryn E; Greene, Geoffrey W; Redding, Colleen A; Paiva, Andrea L; Lofgren, Ingrid; Nash, Jessica T; Kobayashi, Hisanori

2014-01-01

To develop and validate an instrument to assess environmentally conscious eating (Green Eating [GE]) behavior (BEH) and GE Transtheoretical Model constructs including Stage of Change (SOC), Decisional Balance (DB), and Self-efficacy (SE). Cross-sectional instrument development survey. Convenience sample (n = 954) of 18- to 24-year-old college students from a northeastern university. The sample was randomly split: (N1) and (N2). N1 was used for exploratory factor analyses using principal components analyses; N2 was used for confirmatory analyses (structural modeling) and reliability analyses (coefficient α). The full sample was used for measurement invariance (multi-group confirmatory analyses) and convergent validity (BEH) and known group validation (DB and SE) by SOC using analysis of variance. Reliable (α > .7), psychometrically sound, and stable measures included 2 correlated 5-item DB subscales (Pros and Cons), 2 correlated SE subscales (school [5 items] and home [3 items]), and a single 6-item BEH scale. Most students (66%) were in Precontemplation and Contemplation SOC. Behavior, DB, and SE scales differed significantly by SOC (P < .001) with moderate to large effect sizes, as predicted by the Transtheoretical Model, which supported the validity of these measures. Successful development and preliminary validation of this 25-item GE instrument provides a basis for assessment as well as development of tailored interventions for college students. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury

PubMed Central

Pannu, Neesh; Hemmelgarn, Brenda R.; Austin, Peter C.; Tan, Zhi; McArthur, Eric; Manns, Braden J.; Tonelli, Marcello; Wald, Ron; Quinn, Robert R.; Ravani, Pietro; Garg, Amit X.

2017-01-01

Importance Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. Objective To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Design, Setting, and Participants Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Exposures Demographic, laboratory, and comorbidity variables measured prior to discharge. Main Outcomes and Measures Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. Results The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). Conclusions and Relevance A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. PMID:29136443

Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury.

PubMed

James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X

2017-11-14

Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research.

Development and validation of the short-form Adolescent Health Promotion Scale.

PubMed

Chen, Mei-Yen; Lai, Li-Ju; Chen, Hsiu-Chih; Gaete, Jorge

2014-10-26

Health-promoting lifestyle choices of adolescents are closely related to current and subsequent health status. However, parsimonious yet reliable and valid screening tools are scarce. The original 40-item adolescent health promotion (AHP) scale was developed by our research team and has been applied to measure adolescent health-promoting behaviors worldwide. The aim of our study was to examine the psychometric properties of a newly developed short-form version of the AHP (AHP-SF) including tests of its reliability and validity. The study was conducted in nine middle and high schools in southern Taiwan. Participants were 814 adolescents randomly divided into two subgroups with equal size and homogeneity of baseline characteristics. The first subsample (calibration sample) was used to modify and shorten the factorial model while the second subsample (validation sample) was utilized to validate the result obtained from the first one. The psychometric testing of the AHP-SF included internal reliability of McDonald's omega and Cronbach's alpha, convergent validity, discriminant validity, and construct validity with confirmatory factor analysis (CFA). The results of the CFA supported a six-factor model and 21 items were retained in the AHP-SF with acceptable model fit. For the discriminant validity test, results indicated that adolescents with lower AHP-SF scores were more likely to be overweight or obese, skip breakfast, and spend more time watching TV and playing computer games. The AHP-SF also showed excellent internal consistency with a McDonald's omega of 0.904 (Cronbach's alpha 0.905) in the calibration group. The current findings suggest that the AHP-SF is a valid and reliable instrument for the evaluation of adolescent health-promoting behaviors. Primary health care providers and clinicians can use the AHP-SF to assess these behaviors and evaluate the outcome of health promotion programs in the adolescent population.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China

PubMed Central

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

Background and Purpose A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. Methods The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson’s correlation coefficient. Results The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79–0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81–0.84). Excellent calibration was reported in the two models with Pearson’s correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). Conclusions The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke. PMID:27846282

Problem behaviours and symptom dimensions of psychiatric disorders in adults with intellectual disabilities: An exploratory and confirmatory factor analysis.

PubMed

Melville, Craig A; Johnson, Paul C D; Smiley, Elita; Simpson, Neill; Purves, David; McConnachie, Alex; Cooper, Sally-Ann

2016-08-01

The limited evidence on the relationship between problem behaviours and symptoms of psychiatric disorders experienced by adults with intellectual disabilities leads to conflict about diagnostic criteria and confused treatment. This study examined the relationship between problem behaviours and other psychopathology, and compared the predictive validity of dimensional and categorical models experienced by adults with intellectual disabilities. Exploratory and confirmatory factor analyses appropriate for non-continuous data were used to derive, and validate, symptom dimensions using two clinical datasets (n=457; n=274). Categorical diagnoses were derived using DC-LD. Severity and 5-year longitudinal outcome was measured using a battery of instruments. Five factors/dimensions were identified and confirmed. Problem behaviours were included in an emotion dysregulation-problem behaviour dimension that was distinct from the depressive, anxiety, organic and psychosis dimensions. The dimensional model had better predictive validity than categorical diagnosis. International classification systems should not include problem behaviours as behavioural equivalents in diagnostic criteria for depression or other psychiatric disorders. Investigating the relevance of emotional regulation to psychopathology may provide an important pathway for development of improved interventions. There is uncertainty whether new onset problem behaviours or a change in longstanding problem behaviours should be considered as symptoms of depression or other types of psychiatric disorders in adults with intellectual disabilities. The validity of previous studies was limited by the use of pre-defined, categorical diagnoses or unreliable statistical methods. This study used robust statistical modelling to examine problem behaviours within a dimensional model of symptoms. We found that problem behaviours were included in an emotional dysregulation dimension and not in the dimension that included symptoms that are typical of depression. The dimensional model of symptoms had greater predictive validity than categorical diagnoses of psychiatric disorders. Our findings suggest that problem behaviours are a final common pathway for emotional distress in adults with intellectual disabilities so clinicians should not use a change in problem behaviours as a diagnostic criterion for depression, or other psychiatric disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

A model of scientific attitudes assessment by observation in physics learning based scientific approach: case study of dynamic fluid topic in high school

NASA Astrophysics Data System (ADS)

Yusliana Ekawati, Elvin

2017-01-01

This study aimed to produce a model of scientific attitude assessment in terms of the observations for physics learning based scientific approach (case study of dynamic fluid topic in high school). Development of instruments in this study adaptation of the Plomp model, the procedure includes the initial investigation, design, construction, testing, evaluation and revision. The test is done in Surakarta, so that the data obtained are analyzed using Aiken formula to determine the validity of the content of the instrument, Cronbach’s alpha to determine the reliability of the instrument, and construct validity using confirmatory factor analysis with LISREL 8.50 program. The results of this research were conceptual models, instruments and guidelines on scientific attitudes assessment by observation. The construct assessment instruments include components of curiosity, objectivity, suspended judgment, open-mindedness, honesty and perseverance. The construct validity of instruments has been qualified (rated load factor > 0.3). The reliability of the model is quite good with the Alpha value 0.899 (> 0.7). The test showed that the model fits the theoretical models are supported by empirical data, namely p-value 0.315 (≥ 0.05), RMSEA 0.027 (≤ 0.08)

SWAT: Model use, calibration, and validation

USDA-ARS?s Scientific Manuscript database

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT including manual calibration procedures...

Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk.

PubMed

Shetty, N; Løvendahl, P; Lund, M S; Buitenhuis, A J

2017-01-01

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R 2 increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R 2 =0.30 and RMSEP=2.91kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R 2 increased to 0.81 and RMSEP decreased to 1.49kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R 2 =0.46 and RMSEP=1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Integrating Model-Based Transmission Reduction into a multi-tier architecture

NASA Astrophysics Data System (ADS)

Straub, J.

A multi-tier architecture consists of numerous craft as part of the system, orbital, aerial, and surface tiers. Each tier is able to collect progressively greater levels of information. Generally, craft from lower-level tiers are deployed to a target of interest based on its identification by a higher-level craft. While the architecture promotes significant amounts of science being performed in parallel, this may overwhelm the computational and transmission capabilities of higher-tier craft and links (particularly the deep space link back to Earth). Because of this, a new paradigm in in-situ data processing is required. Model-based transmission reduction (MBTR) is such a paradigm. Under MBTR, each node (whether a single spacecraft in orbit of the Earth or another planet or a member of a multi-tier network) is given an a priori model of the phenomenon that it is assigned to study. It performs activities to validate this model. If the model is found to be erroneous, corrective changes are identified, assessed to ensure their significance for being passed on, and prioritized for transmission. A limited amount of verification data is sent with each MBTR assertion message to allow those that might rely on the data to validate the correct operation of the spacecraft and MBTR engine onboard. Integrating MBTR with a multi-tier framework creates an MBTR hierarchy. Higher levels of the MBTR hierarchy task lower levels with data collection and assessment tasks that are required to validate or correct elements of its model. A model of the expected conditions is sent to the lower level craft; which then engages its own MBTR engine to validate or correct the model. This may include tasking a yet lower level of craft to perform activities. When the MBTR engine at a given level receives all of its component data (whether directly collected or from delegation), it randomly chooses some to validate (by reprocessing the validation data), performs analysis and sends its own results (v- lidation and/or changes of model elements and supporting validation data) to its upstream node. This constrains data transmission to only significant (either because it includes a change or is validation data critical for assessing overall performance) information and reduces the processing requirements (by not having to process insignificant data) at higher-level nodes. This paper presents a framework for multi-tier MBTR and two demonstration mission concepts: an Earth sensornet and a mission to Mars. These multi-tier MBTR concepts are compared to a traditional mission approach.

The Quality and Validation of Structures from Structural Genomics

PubMed Central

Domagalski, Marcin J.; Zheng, Heping; Zimmerman, Matthew D.; Dauter, Zbigniew; Wlodawer, Alexander; Minor, Wladek

2014-01-01

Quality control of three-dimensional structures of macromolecules is a critical step to ensure the integrity of structural biology data, especially those produced by structural genomics centers. Whereas the Protein Data Bank (PDB) has proven to be a remarkable success overall, the inconsistent quality of structures reveals a lack of universal standards for structure/deposit validation. Here, we review the state-of-the-art methods used in macromolecular structure validation, focusing on validation of structures determined by X-ray crystallography. We describe some general protocols used in the rebuilding and re-refinement of problematic structural models. We also briefly discuss some frontier areas of structure validation, including refinement of protein–ligand complexes, automation of structure redetermination, and the use of NMR structures and computational models to solve X-ray crystal structures by molecular replacement. PMID:24203341

Independent data validation of an in vitro method for ...

EPA Pesticide Factsheets

In vitro bioaccessibility assays (IVBA) estimate arsenic (As) relative bioavailability (RBA) in contaminated soils to improve the accuracy of site-specific human exposure assessments and risk calculations. For an IVBA assay to gain acceptance for use in risk assessment, it must be shown to reliably predict in vivo RBA that is determined in an established animal model. Previous studies correlating soil As IVBA with RBA have been limited by the use of few soil types as the source of As. Furthermore, the predictive value of As IVBA assays has not been validated using an independent set of As-contaminated soils. Therefore, the current study was undertaken to develop a robust linear model to predict As RBA in mice using an IVBA assay and to independently validate the predictive capability of this assay using a unique set of As-contaminated soils. Thirty-six As-contaminated soils varying in soil type, As contaminant source, and As concentration were included in this study, with 27 soils used for initial model development and nine soils used for independent model validation. The initial model reliably predicted As RBA values in the independent data set, with a mean As RBA prediction error of 5.3% (range 2.4 to 8.4%). Following validation, all 36 soils were used for final model development, resulting in a linear model with the equation: RBA = 0.59 * IVBA + 9.8 and R2 of 0.78. The in vivo-in vitro correlation and independent data validation presented here provide

Models of protein–ligand crystal structures: trust, but verify

PubMed Central

Deller, Marc C.

2015-01-01

X-ray crystallography provides the most accurate models of protein–ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein–ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein–ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein–ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein–ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein–ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein–ligand models for their computational and biological studies, and we provide an overview of how this can be achieved. PMID:25665575

Models of protein-ligand crystal structures: trust, but verify.

PubMed

Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

Clinical prediction models for mortality and functional outcome following ischemic stroke: A systematic review and meta-analysis

PubMed Central

Crayton, Elise; Wolfe, Charles; Douiri, Abdel

2018-01-01

Objective We aim to identify and critically appraise clinical prediction models of mortality and function following ischaemic stroke. Methods Electronic databases, reference lists, citations were searched from inception to September 2015. Studies were selected for inclusion, according to pre-specified criteria and critically appraised by independent, blinded reviewers. The discrimination of the prediction models was measured by the area under the curve receiver operating characteristic curve or c-statistic in random effects meta-analysis. Heterogeneity was measured using I2. Appropriate appraisal tools and reporting guidelines were used in this review. Results 31395 references were screened, of which 109 articles were included in the review. These articles described 66 different predictive risk models. Appraisal identified poor methodological quality and a high risk of bias for most models. However, all models precede the development of reporting guidelines for prediction modelling studies. Generalisability of models could be improved, less than half of the included models have been externally validated(n = 27/66). 152 predictors of mortality and 192 predictors and functional outcome were identified. No studies assessing ability to improve patient outcome (model impact studies) were identified. Conclusions Further external validation and model impact studies to confirm the utility of existing models in supporting decision-making is required. Existing models have much potential. Those wishing to predict stroke outcome are advised to build on previous work, to update and adapt validated models to their specific contexts opposed to designing new ones. PMID:29377923

Computational Fluid Dynamics Best Practice Guidelines in the Analysis of Storage Dry Cask

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

Zigh, A.; Solis, J.

2008-07-01

Computational fluid dynamics (CFD) methods are used to evaluate the thermal performance of a dry cask under long term storage conditions in accordance with NUREG-1536 [NUREG-1536, 1997]. A three-dimensional CFD model was developed and validated using data for a ventilated storage cask (VSC-17) collected by Idaho National Laboratory (INL). The developed Fluent CFD model was validated to minimize the modeling and application uncertainties. To address modeling uncertainties, the paper focused on turbulence modeling of buoyancy driven air flow. Similarly, in the application uncertainties, the pressure boundary conditions used to model the air inlet and outlet vents were investigated and validated.more » Different turbulence models were used to reduce the modeling uncertainty in the CFD simulation of the air flow through the annular gap between the overpack and the multi-assembly sealed basket (MSB). Among the chosen turbulence models, the validation showed that the low Reynolds k-{epsilon} and the transitional k-{omega} turbulence models predicted the measured temperatures closely. To assess the impact of pressure boundary conditions used at the air inlet and outlet channels on the application uncertainties, a sensitivity analysis of operating density was undertaken. For convergence purposes, all available commercial CFD codes include the operating density in the pressure gradient term of the momentum equation. The validation showed that the correct operating density corresponds to the density evaluated at the air inlet condition of pressure and temperature. Next, the validated CFD method was used to predict the thermal performance of an existing dry cask storage system. The evaluation uses two distinct models: a three-dimensional and an axisymmetrical representation of the cask. In the 3-D model, porous media was used to model only the volume occupied by the rodded region that is surrounded by the BWR channel box. In the axisymmetric model, porous media was used to model the entire region that encompasses the fuel assemblies as well as the gaps in between. Consequently, a larger volume is represented by porous media in the second model; hence, a higher frictional flow resistance is introduced in the momentum equations. The conservatism and the safety margins of these models were compared to assess the applicability and the realism of these two models. The three-dimensional model included fewer geometry simplifications and is recommended as it predicted less conservative fuel cladding temperature values, while still assuring the existence of adequate safety margins. (authors)« less

Development and Validation of EPH Material Model for Engineered Roadway Soil

DTIC Science & Technology

2014-08-01

MODEL FOR ENGINEERED ROADWAY SOIL Ching Hsieh, PhD Altair Engineering Troy, MI Jianping Sheng, Ph.D. Jai Ramalingam System Engineering...0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing...of information if it does not display a currently valid OMB control number. 1 . REPORT DATE 11 AUG 2014 2. REPORT TYPE Journal Article 3. DATES

VALIDITY OF A TWO-DIMENSIONAL MODEL FOR VARIABLE-DENSITY HYDRODYNAMIC CIRCULATION

EPA Science Inventory

A three-dimensional model of temperatures and currents has been formulated to assist in the analysis and interpretation of the dynamics of stratified lakes. In this model, nonlinear eddy coefficients for viscosity and conductivities are included. A two-dimensional model (one vert...

[Factor structure validity of the social capital scale used at baseline in the ELSA-Brasil study].

PubMed

Souto, Ester Paiva; Vasconcelos, Ana Glória Godoi; Chor, Dora; Reichenheim, Michael E; Griep, Rosane Härter

2016-07-21

This study aims to analyze the factor structure of the Brazilian version of the Resource Generator (RG) scale, using baseline data from the Brazilian Longitudinal Health Study in Adults (ELSA-Brasil). Cross-validation was performed in three random subsamples. Exploratory factor analysis using exploratory structural equation models was conducted in the first two subsamples to diagnose the factor structure, and confirmatory factor analysis was used in the third to corroborate the model defined by the exploratory analyses. Based on the 31 initial items, the model with the best fit included 25 items distributed across three dimensions. They all presented satisfactory convergent validity (values greater than 0.50 for the extracted variance) and precision (values greater than 0.70 for compound reliability). All factor correlations were below 0.85, indicating full discriminative factor validity. The RG scale presents acceptable psychometric properties and can be used in populations with similar characteristics.

[Psychometric properties of the French version of the Effort-Reward Imbalance model].

PubMed

Niedhammer, I; Siegrist, J; Landre, M F; Goldberg, M; Leclerc, A

2000-10-01

Two main models are currently used to evaluate psychosocial factors at work: the Job Strain model developed by Karasek and the Effort-Reward Imbalance model. A French version of the first model has been validated for the dimensions of psychological demands and decision latitude. As regards the second one evaluating three dimensions (extrinsic effort, reward, and intrinsic effort), there are several versions in different languages, but until recently there was no validated French version. The objective of this study was to explore the psychometric properties of the French version of the Effort-Reward Imbalance model in terms of internal consistency, factorial validity, and discriminant validity. The present study was based on the GAZEL cohort and included the 10 174 subjects who were working at the French national electric and gas company (EDF-GDF) and answered the questionnaire in 1998. A French version of Effort-Reward Imbalance was included in this questionnaire. This version was obtained by a standard forward/backward translation procedure. Internal consistency was satisfactory for the three scales of extrinsic effort, reward, and intrinsic effort: Cronbach's Alpha coefficients higher than 0.7 were observed. A one-factor solution was retained for the factor analysis of the scale of extrinsic effort. A three-factor solution was retained for the factor analysis of reward, and these dimensions were interpreted as the factor analysis of intrinsic effort did not support the expected four-dimension structure. The analysis of discriminant validity displayed significant associations between measures of Effort-Reward Imbalance and the variables of sex, age, education level, and occupational grade. This study is the first one supporting satisfactory psychometric properties of the French version of the Effort-Reward Imbalance model. However, the factorial validity of intrinsic effort could be questioned. Furthermore, as most previous studies were based on male samples working in specific occupations, the present one is also one of the first to show strong associations between measures of this model and social class variables in a population of men and women employed in various occupations.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Load Composition Model Workflow (BPA TIP-371 Deliverable 1A)

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

Chassin, David P.; Cezar, Gustavo V.

This project is funded under Bonneville Power Administration (BPA) Strategic Partnership Project (SPP) 17-005 between BPA and SLAC National Accelerator Laboratory. The project in a BPA Technology Improvement Project (TIP) that builds on and validates the Composite Load Model developed by the Western Electric Coordinating Council's (WECC) Load Modeling Task Force (LMTF). The composite load model is used by the WECC Modeling and Validation Work Group to study the stability and security of the western electricity interconnection. The work includes development of load composition data sets, collection of load disturbance data, and model development and validation. This work supports reliablemore » and economic operation of the power system. This report was produced for Deliverable 1A of the BPA TIP-371 Project entitled \\TIP 371: Advancing the Load Composition Model". The deliverable documents the proposed work ow for the Composite Load Model, which provides the basis for the instrumentation, data acquisition, analysis and data dissemination activities addressed by later phases of the project.« less

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Validation of the 2014 European Society of Cardiology Sudden Cardiac Death Risk Prediction Model in Hypertrophic Cardiomyopathy in a Reference Center in South America.

PubMed

Fernández, Adrián; Quiroga, Alejandro; Ochoa, Juan Pablo; Mysuta, Mauricio; Casabé, José Horacio; Biagetti, Marcelo; Guevara, Eduardo; Favaloro, Liliana E; Fava, Agostina M; Galizio, Néstor

2016-07-01

Sudden cardiac death (SCD) is a common cause of death in hypertrophic cardiomyopathy (HC). Our aim was to conduct an external and independent validation in South America of the 2014 European Society of Cardiology (ESC) SCD risk prediction model to identify patients requiring an implantable cardioverter defibrillator. This study included 502 consecutive patients with HC followed from March, 1993 to December, 2014. A combined end point of SCD or appropriate implantable cardioverter defibrillator therapy was assessed. For the quantitative estimation of individual 5-year SCD risk, we used the formula: 1 - 0.998(exp(Prognostic index)). Our database also included the abnormal blood pressure response to exercise as a risk marker. We analyzed the 3 categories of 5-year risk proposed by the ESC: low risk (LR) <4%; intermediate risk (IR) ≥4% to <6%, and high risk (HR) ≥6%. The LR group included 387 patients (77%); the IR group 39 (8%); and the HR group 76 (15%). Fourteen patients (3%) had SCD/appropriate implantable cardioverter defibrillator therapy (LR: 0%; IR: 2 of 39 [5%]; and HR: 12 of 76 [16%]). In a receiver-operating characteristic curve, the new model proved to be an excellent predictor because the area under the curve for the estimated risk is 0.925 (statistical C: 0.925; 95% CI 0.8884 to 0.9539, p <0.0001). In conclusion, the SCD risk prediction model in HC proposed by the 2014 ESC guidelines was validated in our population and represents an improvement compared with previous approaches. A larger multicenter, independent and external validation of the model with long-term follow-up would be advisable. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Results and Validation of MODIS Aerosol Retrievals Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2001-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Results and Validation of MODIS Aerosol Retrievals over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Ichoku, C.; Chu, D. A.; Mattoo, S.; Levy, R.; Martins, J. V.; Li, R.-R.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

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

Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.

To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptopsmore » to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Furthermore, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.« less

LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

DOE PAGES

Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.; ...

2017-03-23

To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptopsmore » to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Furthermore, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.« less

FEMFLOW3D; a finite-element program for the simulation of three-dimensional aquifers; version 1.0

USGS Publications Warehouse

Durbin, Timothy J.; Bond, Linda D.

1998-01-01

This document also includes model validation, source code, and example input and output files. Model validation was performed using four test problems. For each test problem, the results of a model simulation with FEMFLOW3D were compared with either an analytic solution or the results of an independent numerical approach. The source code, written in the ANSI x3.9-1978 FORTRAN standard, and the complete input and output of an example problem are listed in the appendixes.

Microscopic simulation model calibration and validation handbook.

DOT National Transportation Integrated Search

2006-01-01

Microscopic traffic simulation models are widely used in the transportation engineering field. Because of their cost-effectiveness, risk-free nature, and high-speed benefits, areas of use include transportation system design, traffic operations, and ...

[Elaboration and validation of a tool to measure psychological well-being: WBMMS].

PubMed

Massé, R; Poulin, C; Dassa, C; Lambert, J; Bélair, S; Battaglini, M A

1998-01-01

Psychological well-being scales used in epidemiologic surveys usually show high construct validity. The content validation, however, is less convincing since these scales rest on lists of items that reflect the theoretical model of the authors. In this study we present results of the construct and criterion validation of a new Well-Being Manifestations Measure Scale (WBMMS) founded on an initial list of manifestations derived from an original content validation in a general population. It is concluded that national and public health epidemiologic surveys should include both measures of positive and negative mental health.

Development of a Rational Modeling Approach for the Design, and Optimization of the Multifiltration Unit. Volume 1

NASA Technical Reports Server (NTRS)

Hand, David W.; Crittenden, John C.; Ali, Anisa N.; Bulloch, John L.; Hokanson, David R.; Parrem, David L.

1996-01-01

This thesis includes the development and verification of an adsorption model for analysis and optimization of the adsorption processes within the International Space Station multifiltration beds. The fixed bed adsorption model includes multicomponent equilibrium and both external and intraparticle mass transfer resistances. Single solute isotherm parameters were used in the multicomponent equilibrium description to predict the competitive adsorption interactions occurring during the adsorption process. The multicomponent equilibrium description used the Fictive Component Analysis to describe adsorption in unknown background matrices. Multicomponent isotherms were used to validate the multicomponent equilibrium description. Column studies were used to develop and validate external and intraparticle mass transfer parameter correlations for compounds of interest. The fixed bed model was verified using a shower and handwash ersatz water which served as a surrogate to the actual shower and handwash wastewater.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification.

PubMed

Baczyńska, Anna K; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach's alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed.

Confirming the Lanchestrian linear-logarithmic model of attrition

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

Hartley, D.S. III.

1990-12-01

This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and finalmore » force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. 37 refs., 73 figs., 68 tabs.« less

WEC3: Wave Energy Converter Code Comparison Project: Preprint

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

Combourieu, Adrien; Lawson, Michael; Babarit, Aurelien

This paper describes the recently launched Wave Energy Converter Code Comparison (WEC3) project and present preliminary results from this effort. The objectives of WEC3 are to verify and validate numerical modelling tools that have been developed specifically to simulate wave energy conversion devices and to inform the upcoming IEA OES Annex VI Ocean Energy Modelling Verification and Validation project. WEC3 is divided into two phases. Phase 1 consists of a code-to-code verification and Phase II entails code-to-experiment validation. WEC3 focuses on mid-fidelity codes that simulate WECs using time-domain multibody dynamics methods to model device motions and hydrodynamic coefficients to modelmore » hydrodynamic forces. Consequently, high-fidelity numerical modelling tools, such as Navier-Stokes computational fluid dynamics simulation, and simple frequency domain modelling tools were not included in the WEC3 project.« less

Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland

USGS Publications Warehouse

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

2013-01-01

Model adequacy is evaluated with alternative models rated using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and three flows located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may be important to predictions. Analysis of predictions from alternative models is advised. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests to reconsider the utility of model selection criteria, and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to be generally applicable to models of environmental systems.

[Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

PubMed

Wang, X; Xu, Y H; Du, Z Y; Qian, Y J; Xu, Z H; Chen, R; Shi, M H

2018-02-23

Objective: This study aims to analyze the relationship among the clinical features, radiologic characteristics and pathological diagnosis in patients with solitary pulmonary nodules, and establish a prediction model for the probability of malignancy. Methods: Clinical data of 372 patients with solitary pulmonary nodules who underwent surgical resection with definite postoperative pathological diagnosis were retrospectively analyzed. In these cases, we collected clinical and radiologic features including gender, age, smoking history, history of tumor, family history of cancer, the location of lesion, ground-glass opacity, maximum diameter, calcification, vessel convergence sign, vacuole sign, pleural indentation, speculation and lobulation. The cases were divided to modeling group (268 cases) and validation group (104 cases). A new prediction model was established by logistic regression analying the data from modeling group. Then the data of validation group was planned to validate the efficiency of the new model, and was compared with three classical models(Mayo model, VA model and LiYun model). With the calculated probability values for each model from validation group, SPSS 22.0 was used to draw the receiver operating characteristic curve, to assess the predictive value of this new model. Results: 112 benign SPNs and 156 malignant SPNs were included in modeling group. Multivariable logistic regression analysis showed that gender, age, history of tumor, ground -glass opacity, maximum diameter, and speculation were independent predictors of malignancy in patients with SPN( P <0.05). We calculated a prediction model for the probability of malignancy as follow: p =e(x)/(1+ e(x)), x=-4.8029-0.743×gender+ 0.057×age+ 1.306×history of tumor+ 1.305×ground-glass opacity+ 0.051×maximum diameter+ 1.043×speculation. When the data of validation group was added to the four-mathematical prediction model, The area under the curve of our mathematical prediction model was 0.742, which is greater than other models (Mayo 0.696, VA 0.634, LiYun 0.681), while the differences between any two of the four models were not significant ( P >0.05). Conclusions: Age of patient, gender, history of tumor, ground-glass opacity, maximum diameter and speculation are independent predictors of malignancy in patients with solitary pulmonary nodule. This logistic regression prediction mathematic model is not inferior to those classical models in estimating the prognosis of SPNs.

A computational continuum model of poroelastic beds

PubMed Central

Zampogna, G. A.

2017-01-01

Despite the ubiquity of fluid flows interacting with porous and elastic materials, we lack a validated non-empirical macroscale method for characterizing the flow over and through a poroelastic medium. We propose a computational tool to describe such configurations by deriving and validating a continuum model for the poroelastic bed and its interface with the above free fluid. We show that, using stress continuity condition and slip velocity condition at the interface, the effective model captures the effects of small changes in the microstructure anisotropy correctly and predicts the overall behaviour in a physically consistent and controllable manner. Moreover, we show that the performance of the effective model is accurate by validating with fully microscopic resolved simulations. The proposed computational tool can be used in investigations in a wide range of fields, including mechanical engineering, bio-engineering and geophysics. PMID:28413355

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

NASA Astrophysics Data System (ADS)

Skene, Katherine J.; Gent, Janneane F.; McKay, Lisa A.; Belanger, Kathleen; Leaderer, Brian P.; Holford, Theodore R.

2010-12-01

An integrated exposure model was developed that estimates nitrogen dioxide (NO 2) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO 2 taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO 2 measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO 2 levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.

Chemometric and biological validation of a capillary electrophoresis metabolomic experiment of Schistosoma mansoni infection in mice.

PubMed

Garcia-Perez, Isabel; Angulo, Santiago; Utzinger, Jürg; Holmes, Elaine; Legido-Quigley, Cristina; Barbas, Coral

2010-07-01

Metabonomic and metabolomic studies are increasingly utilized for biomarker identification in different fields, including biology of infection. The confluence of improved analytical platforms and the availability of powerful multivariate analysis software have rendered the multiparameter profiles generated by these omics platforms a user-friendly alternative to the established analysis methods where the quality and practice of a procedure is well defined. However, unlike traditional assays, validation methods for these new multivariate profiling tools have yet to be established. We propose a validation for models obtained by CE fingerprinting of urine from mice infected with the blood fluke Schistosoma mansoni. We have analysed urine samples from two sets of mice infected in an inter-laboratory experiment where different infection methods and animal husbandry procedures were employed in order to establish the core biological response to a S. mansoni infection. CE data were analysed using principal component analysis. Validation of the scores consisted of permutation scrambling (100 repetitions) and a manual validation method, using a third of the samples (not included in the model) as a test or prediction set. The validation yielded 100% specificity and 100% sensitivity, demonstrating the robustness of these models with respect to deciphering metabolic perturbations in the mouse due to a S. mansoni infection. A total of 20 metabolites across the two experiments were identified that significantly discriminated between S. mansoni-infected and noninfected control samples. Only one of these metabolites, allantoin, was identified as manifesting different behaviour in the two experiments. This study shows the reproducibility of CE-based metabolic profiling methods for disease characterization and screening and highlights the importance of much needed validation strategies in the emerging field of metabolomics.

Near field interaction of microwave signals with a bounded plasma plume

NASA Technical Reports Server (NTRS)

Ling, Hao; Hallock, Gary A.; Kim, Hyeongdong; Birkner, Bjorn

1991-01-01

The objective was to study the effect of the arcjet thruster plume on the performance of an onboard satellite reflector antenna. A project summary is presented along with sections on plasma and electromagnetic modeling. The plasma modeling section includes the following topics: wave propagation; plasma analysis; plume electron density model; and the proposed experimental program. The section on electromagnetic modeling includes new developments in ray modeling and the validation of three dimensional ray results.

Analytical model for tilting proprotor aircraft dynamics, including blade torsion and coupled bending modes, and conversion mode operation

NASA Technical Reports Server (NTRS)

Johnson, W.

1974-01-01

An analytical model is developed for proprotor aircraft dynamics. The rotor model includes coupled flap-lag bending modes, and blade torsion degrees of freedom. The rotor aerodynamic model is generally valid for high and low inflow, and for axial and nonaxial flight. For the rotor support, a cantilever wing is considered; incorporation of a more general support with this rotor model will be a straight-forward matter.

Modeling and validating HL7 FHIR profiles using semantic web Shape Expressions (ShEx).

PubMed

Solbrig, Harold R; Prud'hommeaux, Eric; Grieve, Grahame; McKenzie, Lloyd; Mandel, Joshua C; Sharma, Deepak K; Jiang, Guoqian

2017-03-01

HL7 Fast Healthcare Interoperability Resources (FHIR) is an emerging open standard for the exchange of electronic healthcare information. FHIR resources are defined in a specialized modeling language. FHIR instances can currently be represented in either XML or JSON. The FHIR and Semantic Web communities are developing a third FHIR instance representation format in Resource Description Framework (RDF). Shape Expressions (ShEx), a formal RDF data constraint language, is a candidate for describing and validating the FHIR RDF representation. Create a FHIR to ShEx model transformation and assess its ability to describe and validate FHIR RDF data. We created the methods and tools that generate the ShEx schemas modeling the FHIR to RDF specification being developed by HL7 ITS/W3C RDF Task Force, and evaluated the applicability of ShEx in the description and validation of FHIR to RDF transformations. The ShEx models contributed significantly to workgroup consensus. Algorithmic transformations from the FHIR model to ShEx schemas and FHIR example data to RDF transformations were incorporated into the FHIR build process. ShEx schemas representing 109 FHIR resources were used to validate 511 FHIR RDF data examples from the Standards for Trial Use (STU 3) Ballot version. We were able to uncover unresolved issues in the FHIR to RDF specification and detect 10 types of errors and root causes in the actual implementation. The FHIR ShEx representations have been included in the official FHIR web pages for the STU 3 Ballot version since September 2016. ShEx can be used to define and validate the syntax of a FHIR resource, which is complementary to the use of RDF Schema (RDFS) and Web Ontology Language (OWL) for semantic validation. ShEx proved useful for describing a standard model of FHIR RDF data. The combination of a formal model and a succinct format enabled comprehensive review and automated validation. Copyright © 2017 Elsevier Inc. All rights reserved.

Are Fearless Dominance Traits Superfluous in Operationalizing Psychopathy? Incremental Validity and Sex Differences

PubMed Central

Murphy, Brett; Lilienfeld, Scott; Skeem, Jennifer; Edens, John

2016-01-01

Researchers are vigorously debating whether psychopathic personality includes seemingly adaptive traits, especially social and physical boldness. In a large sample (N=1565) of adult offenders, we examined the incremental validity of two operationalizations of boldness (Fearless Dominance traits in the Psychopathy Personality Inventory, Lilienfeld & Andrews, 1996; Boldness traits in the Triarchic Model of Psychopathy, Patrick et al, 2009), above and beyond other characteristics of psychopathy, in statistically predicting scores on four psychopathy-related measures, including the Psychopathy Checklist-Revised (PCL-R). The incremental validity added by boldness traits in predicting the PCL-R’s representation of psychopathy was especially pronounced for interpersonal traits (e.g., superficial charm, deceitfulness). Our analyses, however, revealed unexpected sex differences in the relevance of these traits to psychopathy, with boldness traits exhibiting reduced importance for psychopathy in women. We discuss the implications of these findings for measurement models of psychopathy. PMID:26866795

Development and Validation of a Predictive Model to Identify Individuals Likely to Have Undiagnosed Chronic Obstructive Pulmonary Disease Using an Administrative Claims Database.

PubMed

Moretz, Chad; Zhou, Yunping; Dhamane, Amol D; Burslem, Kate; Saverno, Kim; Jain, Gagan; Devercelli, Giovanna; Kaila, Shuchita; Ellis, Jeffrey J; Hernandez, Gemzel; Renda, Andrew

2015-12-01

Despite the importance of early detection, delayed diagnosis of chronic obstructive pulmonary disease (COPD) is relatively common. Approximately 12 million people in the United States have undiagnosed COPD. Diagnosis of COPD is essential for the timely implementation of interventions, such as smoking cessation programs, drug therapies, and pulmonary rehabilitation, which are aimed at improving outcomes and slowing disease progression. To develop and validate a predictive model to identify patients likely to have undiagnosed COPD using administrative claims data. A predictive model was developed and validated utilizing a retro-spective cohort of patients with and without a COPD diagnosis (cases and controls), aged 40-89, with a minimum of 24 months of continuous health plan enrollment (Medicare Advantage Prescription Drug [MAPD] and commercial plans), and identified between January 1, 2009, and December 31, 2012, using Humana's claims database. Stratified random sampling based on plan type (commercial or MAPD) and index year was performed to ensure that cases and controls had a similar distribution of these variables. Cases and controls were compared to identify demographic, clinical, and health care resource utilization (HCRU) characteristics associated with a COPD diagnosis. Stepwise logistic regression (SLR), neural networking, and decision trees were used to develop a series of models. The models were trained, validated, and tested on randomly partitioned subsets of the sample (Training, Validation, and Test data subsets). Measures used to evaluate and compare the models included area under the curve (AUC); index of the receiver operating characteristics (ROC) curve; sensitivity, specificity, positive predictive value (PPV); and negative predictive value (NPV). The optimal model was selected based on AUC index on the Test data subset. A total of 50,880 cases and 50,880 controls were included, with MAPD patients comprising 92% of the study population. Compared with controls, cases had a statistically significantly higher comorbidity burden and HCRU (including hospitalizations, emergency room visits, and medical procedures). The optimal predictive model was generated using SLR, which included 34 variables that were statistically significantly associated with a COPD diagnosis. After adjusting for covariates, anticholinergic bronchodilators (OR = 3.336) and tobacco cessation counseling (OR = 2.871) were found to have a large influence on the model. The final predictive model had an AUC of 0.754, sensitivity of 60%, specificity of 78%, PPV of 73%, and an NPV of 66%. This claims-based predictive model provides an acceptable level of accuracy in identifying patients likely to have undiagnosed COPD in a large national health plan. Identification of patients with undiagnosed COPD may enable timely management and lead to improved health outcomes and reduced COPD-related health care expenditures.

Model development and validation of geometrically complex eddy current coils using finite element methods

NASA Astrophysics Data System (ADS)

Brown, Alexander; Eviston, Connor

2017-02-01

Multiple FEM models of complex eddy current coil geometries were created and validated to calculate the change of impedance due to the presence of a notch. Capable realistic simulations of eddy current inspections are required for model assisted probability of detection (MAPOD) studies, inversion algorithms, experimental verification, and tailored probe design for NDE applications. An FEM solver was chosen to model complex real world situations including varying probe dimensions and orientations along with complex probe geometries. This will also enable creation of a probe model library database with variable parameters. Verification and validation was performed using other commercially available eddy current modeling software as well as experimentally collected benchmark data. Data analysis and comparison showed that the created models were able to correctly model the probe and conductor interactions and accurately calculate the change in impedance of several experimental scenarios with acceptable error. The promising results of the models enabled the start of an eddy current probe model library to give experimenters easy access to powerful parameter based eddy current models for alternate project applications.

Estimation of Unsteady Aerodynamic Models from Dynamic Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick; Klein, Vladislav

2011-01-01

Demanding aerodynamic modelling requirements for military and civilian aircraft have motivated researchers to improve computational and experimental techniques and to pursue closer collaboration in these areas. Model identification and validation techniques are key components for this research. This paper presents mathematical model structures and identification techniques that have been used successfully to model more general aerodynamic behaviours in single-degree-of-freedom dynamic testing. Model parameters, characterizing aerodynamic properties, are estimated using linear and nonlinear regression methods in both time and frequency domains. Steps in identification including model structure determination, parameter estimation, and model validation, are addressed in this paper with examples using data from one-degree-of-freedom dynamic wind tunnel and water tunnel experiments. These techniques offer a methodology for expanding the utility of computational methods in application to flight dynamics, stability, and control problems. Since flight test is not always an option for early model validation, time history comparisons are commonly made between computational and experimental results and model adequacy is inferred by corroborating results. An extension is offered to this conventional approach where more general model parameter estimates and their standard errors are compared.

Validation Evidence for the Elementary School Version of the MUSIC® Model of Academic Motivation Inventory (Pruebas de validación para el Modelo MUSIC® de Inventario de Motivación Educativa para Escuela Primaria)

ERIC Educational Resources Information Center

Jones, Brett D.; Sigmon, Miranda L.

2016-01-01

Introduction: The purpose of our study was to assess whether the Elementary School version of the MUSIC® Model of Academic Motivation Inventory was valid for use with elementary students in classrooms with regular classroom teachers and student teachers enrolled in a university teacher preparation program. Method: The participants included 535…

A Novel Model for Predicting Incident Moderate to Severe Anemia and Iron Deficiency in Patients with Newly Diagnosed Ulcerative Colitis.

PubMed

Khan, Nabeel; Patel, Dhruvan; Shah, Yash; Yang, Yu-Xiao

2017-05-01

Anemia and iron deficiency are common complications of ulcerative colitis (UC). We aimed to develop and internally validate a prediction model for the incidence of moderate to severe anemia and iron deficiency anemia (IDA) in newly diagnosed patients with UC. Multivariable logistic regression was performed among a nationwide cohort of patients who were newly diagnosed with UC in the VA health-care system. Model development was performed in a random two-third of the total cohort and then validated in the remaining one-third of the cohort. As candidate predictors, we examined routinely available data at the time of UC diagnosis including demographics, medications, laboratory results, and endoscopy findings. A total of 789 patients met the inclusion criteria. For the outcome of moderate to severe anemia, age, albumin level and mild anemia at UC diagnosis were predictors selected for the model. The AUC for this model was 0.69 (95% CI 0.64-0.74). For the outcome of moderate to severe anemia with evidence of iron deficiency, the predictors included African-American ethnicity, mild anemia, age, and albumin level at UC diagnosis. The AUC was 0.76, (95% CI 0.69-0.82). Calibration was consistently good in all models (Hosmer-Lemeshow goodness of fit p > 0.05). The models performed similarly in the internal validation cohort. We developed and internally validated a prognostic model for predicting the risk of moderate to severe anemia and IDA among newly diagnosed patients with UC. This will help identify patients at high risk of these complications, who could benefit from surveillance and preventive measures.

Revalidation of the NASA Ames 11-by 11-Foot Transonic Wind Tunnel with a Commercial Airplane Model

NASA Technical Reports Server (NTRS)

Kmak, Frank J.; Hudgins, M.; Hergert, D.; George, Michael W. (Technical Monitor)

2001-01-01

The 11-By 11-Foot Transonic leg of the Unitary Plan Wind Tunnel (UPWT) was modernized to improve tunnel performance, capability, productivity, and reliability. Wind tunnel tests to demonstrate the readiness of the tunnel for a return to production operations included an Integrated Systems Test (IST), calibration tests, and airplane validation tests. One of the two validation tests was a 0.037-scale Boeing 777 model that was previously tested in the 11-By 11-Foot tunnel in 1991. The objective of the validation tests was to compare pre-modernization and post-modernization results from the same airplane model in order to substantiate the operational readiness of the facility. Evaluation of within-test, test-to-test, and tunnel-to-tunnel data repeatability were made to study the effects of the tunnel modifications. Tunnel productivity was also evaluated to determine the readiness of the facility for production operations. The operation of the facility, including model installation, tunnel operations, and the performance of tunnel systems, was observed and facility deficiency findings generated. The data repeatability studies and tunnel-to-tunnel comparisons demonstrated outstanding data repeatability and a high overall level of data quality. Despite some operational and facility problems, the validation test was successful in demonstrating the readiness of the facility to perform production airplane wind tunnel%, tests.

Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

PubMed Central

Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

2016-01-01

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

Comparison of two weighted integration models for the cueing task: linear and likelihood

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2003-01-01

In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.

Validation of a Full-Immersion Simulation Platform for Percutaneous Nephrolithotomy Using Three-Dimensional Printing Technology.

PubMed

Ghazi, Ahmed; Campbell, Timothy; Melnyk, Rachel; Feng, Changyong; Andrusco, Alex; Stone, Jonathan; Erturk, Erdal

2017-12-01

The restriction of resident hours with an increasing focus on patient safety and a reduced caseload has impacted surgical training. A complex and complication prone procedure such as percutaneous nephrolithotomy (PCNL) with a steep learning curve may create an unsafe environment for hands-on resident training. In this study, we validate a high fidelity, inanimate PCNL model within a full-immersion simulation environment. Anatomically correct models of the human pelvicaliceal system, kidney, and relevant adjacent structures were created using polyvinyl alcohol hydrogels and three-dimensional-printed injection molds. All steps of a PCNL were simulated including percutaneous renal access, nephroscopy, and lithotripsy. Five experts (>100 caseload) and 10 novices (<20 caseload) from both urology (full procedure) and interventional radiology (access only) departments completed the simulation. Face and content validity were calculated using model ratings for similarity to the real procedure and usefulness as a training tool. Differences in performance among groups with various levels of experience using clinically relevant procedural metrics were used to calculate construct validity. The model was determined to have an excellent face and content validity with an average score of 4.5/5.0 and 4.6/5.0, respectively. There were significant differences between novice and expert operative metrics including mean fluoroscopy time, the number of percutaneous access attempts, and number of times the needle was repositioned. Experts achieved better stone clearance with fewer procedural complications. We demonstrated the face, content, and construct validity of an inanimate, full task trainer for PCNL. Construct validity between experts and novices was demonstrated using incorporated procedural metrics, which permitted the accurate assessment of performance. While hands-on training under supervision remains an integral part of any residency, this full-immersion simulation provides a comprehensive tool for surgical skills development and evaluation before hands-on exposure.

Claims-based risk model for first severe COPD exacerbation.

PubMed

Stanford, Richard H; Nag, Arpita; Mapel, Douglas W; Lee, Todd A; Rosiello, Richard; Schatz, Michael; Vekeman, Francis; Gauthier-Loiselle, Marjolaine; Merrigan, J F Philip; Duh, Mei Sheng

2018-02-01

To develop and validate a predictive model for first severe chronic obstructive pulmonary disease (COPD) exacerbation using health insurance claims data and to validate the risk measure of controller medication to total COPD treatment (controller and rescue) ratio (CTR). A predictive model was developed and validated in 2 managed care databases: Truven Health MarketScan database and Reliant Medical Group database. This secondary analysis assessed risk factors, including CTR, during the baseline period (Year 1) to predict risk of severe exacerbation in the at-risk period (Year 2). Patients with COPD who were 40 years or older and who had at least 1 COPD medication dispensed during the year following COPD diagnosis were included. Subjects with severe exacerbations in the baseline year were excluded. Risk factors in the baseline period were included as potential predictors in multivariate analysis. Performance was evaluated using C-statistics. The analysis included 223,824 patients. The greatest risk factors for first severe exacerbation were advanced age, chronic oxygen therapy usage, COPD diagnosis type, dispensing of 4 or more canisters of rescue medication, and having 2 or more moderate exacerbations. A CTR of 0.3 or greater was associated with a 14% lower risk of severe exacerbation. The model performed well with C-statistics, ranging from 0.711 to 0.714. This claims-based risk model can predict the likelihood of first severe COPD exacerbation. The CTR could also potentially be used to target populations at greatest risk for severe exacerbations. This could be relevant for providers and payers in approaches to prevent severe exacerbations and reduce costs.

Refining and validating a conceptual model of Clinical Nurse Leader integrated care delivery.

PubMed

Bender, Miriam; Williams, Marjory; Su, Wei; Hites, Lisle

2017-02-01

To empirically validate a conceptual model of Clinical Nurse Leader integrated care delivery. There is limited evidence of frontline care delivery models that consistently achieve quality patient outcomes. Clinical Nurse Leader integrated care delivery is a promising nursing model with a growing record of success. However, theoretical clarity is necessary to generate causal evidence of effectiveness. Sequential mixed methods. A preliminary Clinical Nurse Leader practice model was refined and survey items developed to correspond with model domains, using focus groups and a Delphi process with a multi-professional expert panel. The survey was administered in 2015 to clinicians and administrators involved in Clinical Nurse Leader initiatives. Confirmatory factor analysis and structural equation modelling were used to validate the measurement and model structure. Final sample n = 518. The model incorporates 13 components organized into five conceptual domains: 'Readiness for Clinical Nurse Leader integrated care delivery'; 'Structuring Clinical Nurse Leader integrated care delivery'; 'Clinical Nurse Leader Practice: Continuous Clinical Leadership'; 'Outcomes of Clinical Nurse Leader integrated care delivery'; and 'Value'. Sample data had good fit with specified model and two-level measurement structure. All hypothesized pathways were significant, with strong coefficients suggesting good fit between theorized and observed path relationships. The validated model articulates an explanatory pathway of Clinical Nurse Leader integrated care delivery, including Clinical Nurse Leader practices that result in improved care dynamics and patient outcomes. The validated model provides a basis for testing in practice to generate evidence that can be deployed across the healthcare spectrum. © 2016 John Wiley & Sons Ltd.

Comparison of LIDAR system performance for alternative single-mode receiver architectures: modeling and experimental validation

NASA Astrophysics Data System (ADS)

Toliver, Paul; Ozdur, Ibrahim; Agarwal, Anjali; Woodward, T. K.

2013-05-01

In this paper, we describe a detailed performance comparison of alternative single-pixel, single-mode LIDAR architectures including (i) linear-mode APD-based direct-detection, (ii) optically-preamplified PIN receiver, (iii) PINbased coherent-detection, and (iv) Geiger-mode single-photon-APD counting. Such a comparison is useful when considering next-generation LIDAR on a chip, which would allow one to leverage extensive waveguide-based structures and processing elements developed for telecom and apply them to small form-factor sensing applications. Models of four LIDAR transmit and receive systems are described in detail, which include not only the dominant sources of receiver noise commonly assumed in each of the four detection limits, but also additional noise terms present in realistic implementations. These receiver models are validated through the analysis of detection statistics collected from an experimental LIDAR testbed. The receiver is reconfigurable into four modes of operation, while transmit waveforms and channel characteristics are held constant. The use of a diffuse hard target highlights the importance of including speckle noise terms in the overall system analysis. All measurements are done at 1550 nm, which offers multiple system advantages including less stringent eye safety requirements and compatibility with available telecom components, optical amplification, and photonic integration. Ultimately, the experimentally-validated detection statistics can be used as part of an end-to-end system model for projecting rate, range, and resolution performance limits and tradeoffs of alternative integrated LIDAR architectures.

Theoretical model for a Faraday anomalous dispersion optical filter

NASA Technical Reports Server (NTRS)

Yin, B.; Shay, T. M.

1991-01-01

A model for the Faraday anomalous dispersion optical filter is presented. The model predicts a bandwidth of 0.6 GHz and a transmission peak of 0.98 for a filter operating on the Cs (D2) line. The model includes hyperfine effects and is valid for arbitrary magnetic fields.

Systematic review and retrospective validation of prediction models for weight loss after bariatric surgery.

PubMed

Sharples, Alistair J; Mahawar, Kamal; Cheruvu, Chandra V N

2017-11-01

Patients often have less than realistic expectations of the weight loss they are likely to achieve after bariatric surgery. It would be useful to have a well-validated prediction tool that could give patients a realistic estimate of their expected weight loss. To perform a systematic review of the literature to identify existing prediction models and attempt to validate these models. University hospital, United Kingdom. A systematic review was performed. All English language studies were included if they used data to create a prediction model for postoperative weight loss after bariatric surgery. These models were then tested on patients undergoing bariatric surgery between January 1, 2013 and December 31, 2014 within our unit. An initial literature search produced 446 results, of which only 4 were included in the final review. Our study population included 317 patients. Mean preoperative body mass index was 46.1 ± 7.1. For 257 (81.1%) patients, 12-month follow-up was available, and mean body mass index and percentage excess weight loss at 12 months was 33.0 ± 6.7 and 66.1% ± 23.7%, respectively. All 4 of the prediction models significantly overestimated the amount of weight loss achieved by patients. The best performing prediction model in our series produced a correlation coefficient (R 2 ) of .61 and an area under the curve of .71 on receiver operating curve analysis. All prediction models overestimated weight loss after bariatric surgery in our cohort. There is a need to develop better procedures and patient-specific models for better patient counselling. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Development and validation of a new pediatric resuscitation and trauma outcome (PRESTO) model using the U.S. National Trauma Data Bank.

PubMed

St-Louis, Etienne; Bracco, David; Hanley, James; Razek, Tarek; Baird, Robert

2017-10-12

There is a need for a pediatric trauma outcomes benchmarking model that is adapted for Low-and-Middle-Income Countries (LMICs). We used the National-Trauma-Data-Bank (NTDB) and applied constraints specific to resource-poor environments to develop and validate an LMIC-specific pediatric trauma score. We selected a sample of pediatric trauma patients aged 0-14years in the NTDB from 2007 to 2012. Primary outcome was in-hospital death. Logistic regression was used to create the Pediatric Resuscitation and Trauma Outcome (PRESTO) score, which includes only low-tech predictor variables - those easily obtainable at point-of-care. Internal validation was performed using 10-fold cross-validation. External validation compared PRESTO to TRISS using ROC analyses. Among 651,030 patients, there were 64% males. Median age was 7. In-hospital mortality-rate was 1.2%. Mean TRISS predicted mortality was 0.04% (range 0%-43%). Independent predictors included in PRESTO (p<0.01) were age, blood pressure, neurologic status, need for supplemental oxygen, pulse, and oxygen saturation. The sensitivity and specificity of PRESTO were 95.7% and 94.0%. The resulting model had an AUC of 0.98 compared to 0.89 for TRISS. PRESTO satisfies the requirements of low-resource settings and is inherently adapted to children, allowing for benchmarking and eventual quality improvement initiatives. Further research is necessary for in-situ validation using prospectively collected LMIC data. Level III - Case-Control (Prognostic) Study. Copyright © 2017 Elsevier Inc. All rights reserved.

The pros and cons of code validation

NASA Technical Reports Server (NTRS)

Bobbitt, Percy J.

1988-01-01

Computational and wind tunnel error sources are examined and quantified using specific calculations of experimental data, and a substantial comparison of theoretical and experimental results, or a code validation, is discussed. Wind tunnel error sources considered include wall interference, sting effects, Reynolds number effects, flow quality and transition, and instrumentation such as strain gage balances, electronically scanned pressure systems, hot film gages, hot wire anemometers, and laser velocimeters. Computational error sources include math model equation sets, the solution algorithm, artificial viscosity/dissipation, boundary conditions, the uniqueness of solutions, grid resolution, turbulence modeling, and Reynolds number effects. It is concluded that, although improvements in theory are being made more quickly than in experiments, wind tunnel research has the advantage of the more realistic transition process of a right turbulence model in a free-transition test.

Organizational citizenship behavior in schools: validation of a questionnaire.

PubMed

Neves, Paula C; Paixão, Rui; Alarcão, Madalena; Gomes, A Duarte

2014-01-01

The present study examines the psychometric properties (including factorial validity) of an organizational citizenship behavior (OCB) scale in a school context. A total of 321 middle and high school teachers from 59 schools in urban and rural areas of central Portugal completed the OCB scale at their schools. The confirmatory factor analysis validated a hierarchical model with four latent factors on the first level (altruism, conscientiousness, civic participation and courtesy) and a second order factor (OCB). The revised model fit with the data, χ 2 /gl = 1.97; CFI = .962; GFI = .952, RMSEA = .05. The proposed scale (comportamentos de cidadania organizacional em escolas- Revista CCOE-R)- is a valid instrument to assess teacher's perceptions of OCB in their schools, allowing investigation at the organizational level of analysis.

Time Domain Tool Validation Using ARES I-X Flight Data

NASA Technical Reports Server (NTRS)

Hough, Steven; Compton, James; Hannan, Mike; Brandon, Jay

2011-01-01

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.

A method for landing gear modeling and simulation with experimental validation

NASA Technical Reports Server (NTRS)

Daniels, James N.

1996-01-01

This document presents an approach for modeling and simulating landing gear systems. Specifically, a nonlinear model of an A-6 Intruder Main Gear is developed, simulated, and validated against static and dynamic test data. This model includes nonlinear effects such as a polytropic gas model, velocity squared damping, a geometry governed model for the discharge coefficients, stick-slip friction effects and a nonlinear tire spring and damping model. An Adams-Moulton predictor corrector was used to integrate the equations of motion until a discontinuity caused by a stick-slip friction model was reached, at which point, a Runga-Kutta routine integrated past the discontinuity and returned the problem solution back to the predictor corrector. Run times of this software are around 2 mins. per 1 sec. of simulation under dynamic circumstances. To validate the model, engineers at the Aircraft Landing Dynamics facilities at NASA Langley Research Center installed one A-6 main gear on a drop carriage and used a hydraulic shaker table to provide simulated runway inputs to the gear. Model parameters were tuned to produce excellent agreement for many cases.

Evaluation of Model Fit in Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin

2016-01-01

Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…

Irma 5.1 multisensor signature prediction model

NASA Astrophysics Data System (ADS)

Savage, James; Coker, Charles; Edwards, Dave; Thai, Bea; Aboutalib, Omar; Chow, Anthony; Yamaoka, Neil; Kim, Charles

2006-05-01

The Irma synthetic signature prediction code is being developed to facilitate the research and development of multi-sensor systems. Irma was one of the first high resolution, physics-based Infrared (IR) target and background signature models to be developed for tactical weapon applications. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel, and a Doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Irma is currently used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. In 2005, Irma version 5.1 was released to the community. In addition to upgrading the Ladar channel code to an object oriented language (C++) and providing a new graphical user interface to construct scenes, this new release significantly improves the modeling of the ladar channel and includes polarization effects, time jittering, speckle effect, and atmospheric turbulence. More importantly, the Munitions Directorate has funded three field tests to verify and validate the re-engineered ladar channel. Each of the field tests was comprehensive and included one month of sensor characterization and a week of data collection. After each field test, the analysis included comparisons of Irma predicted signatures with measured signatures, and if necessary, refining the model to produce realistic imagery. This paper will focus on two areas of the Irma 5.1 development effort: report on the analysis results of the validation and verification of the Irma 5.1 ladar channel, and the software development plan and validation efforts of the Irma passive channel. As scheduled, the Irma passive code is being re-engineered using object oriented language (C++), and field data collection is being conducted to validate the re-engineered passive code. This software upgrade will remove many constraints and limitations of the legacy code including limits on image size and facet counts. The field test to validate the passive channel is expected to be complete in the second quarter of 2006.

Critical evaluation of mechanistic two-phase flow pipeline and well simulation models

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

Dhulesia, H.; Lopez, D.

1996-12-31

Mechanistic steady state simulation models, rather than empirical correlations, are used for a design of multiphase production system including well, pipeline and downstream installations. Among the available models, PEPITE, WELLSIM, OLGA, TACITE and TUFFP are widely used for this purpose and consequently, a critical evaluation of these models is needed. An extensive validation methodology is proposed which consists of two distinct steps: first to validate the hydrodynamic point model using the test loop data and, then to validate the over-all simulation model using the real pipelines and wells data. The test loop databank used in this analysis contains about 5952more » data sets originated from four different test loops and a majority of these data are obtained at high pressures (up to 90 bars) with real hydrocarbon fluids. Before performing the model evaluation, physical analysis of the test loops data is required to eliminate non-coherent data. The evaluation of these point models demonstrates that the TACITE and OLGA models can be applied to any configuration of pipes. The TACITE model performs better than the OLGA model because it uses the most appropriate closure laws from the literature validated on a large number of data. The comparison of predicted and measured pressure drop for various real pipelines and wells demonstrates that the TACITE model is a reliable tool.« less

Development and Validation of Personality Disorder Spectra Scales for the MMPI-2-RF.

PubMed

Sellbom, Martin; Waugh, Mark H; Hopwood, Christopher J

2018-01-01

The purpose of this study was to develop and validate a set of MMPI-2-RF (Ben-Porath & Tellegen, 2008/2011) personality disorder (PD) spectra scales. These scales could serve the purpose of assisting with DSM-5 PD diagnosis and help link categorical and dimensional conceptions of personality pathology within the MMPI-2-RF. We developed and provided initial validity results for scales corresponding to the 10 PD constructs listed in the DSM-5 using data from student, community, clinical, and correctional samples. Initial validation efforts indicated good support for criterion validity with an external PD measure as well as with dimensional personality traits included in the DSM-5 alternative model for PDs. Construct validity results using psychosocial history and therapists' ratings in a large clinical sample were generally supportive as well. Overall, these brief scales provide clinicians using MMPI-2-RF data with estimates of DSM-5 PD constructs that can support cross-model connections between categorical and dimensional assessment approaches.

Validity of Students Worksheet Based Problem-Based Learning for 9th Grade Junior High School in living organism Inheritance and Food Biotechnology.

NASA Astrophysics Data System (ADS)

Jefriadi, J.; Ahda, Y.; Sumarmin, R.

2018-04-01

Based on preliminary research of students worksheet used by teachers has several disadvantages such as students worksheet arranged directly drove learners conduct an investigation without preceded by directing learners to a problem or provide stimulation, student's worksheet not provide a concrete imageand presentation activities on the students worksheet not refer to any one learning models curicullum recommended. To address problems Reviews these students then developed a worksheet based on problem-based learning. This is a research development that using Ploom models. The phases are preliminary research, development and assessment. The instruments used in data collection that includes pieces of observation/interviews, instrument self-evaluation, instruments validity. The results of the validation expert on student worksheets get a valid result the average value 80,1%. Validity of students worksheet based problem-based learning for 9th grade junior high school in living organism inheritance and food biotechnology get valid category.

Validity of High School Physic Module With Character Values Using Process Skill Approach In STKIP PGRI West Sumatera

NASA Astrophysics Data System (ADS)

Anaperta, M.; Helendra, H.; Zulva, R.

2018-04-01

This study aims to describe the validity of physics module with Character Oriented Values Using Process Approach Skills at Dynamic Electrical Material in high school physics / MA and SMK. The type of research is development research. The module development model uses the development model proposed by Plomp which consists of (1) preliminary research phase, (2) the prototyping phase, and (3) assessment phase. In this research is done is initial investigation phase and designing. Data collecting technique to know validation is observation and questionnaire. In the initial investigative phase, curriculum analysis, student analysis, and concept analysis were conducted. In the design phase and the realization of module design for SMA / MA and SMK subjects in dynamic electrical materials. After that, the formative evaluation which include self evaluation, prototyping (expert reviews, one-to-one, and small group. At this stage validity is performed. This research data is obtained through the module validation sheet, which then generates a valid module.

Prior Study of Cross-Cultural Validation of McGill Quality-of-Life Questionnaire in Mainland Mandarin Chinese Patients With Cancer.

PubMed

Hu, Liya; Li, Jingwen; Wang, Xu; Payne, Sheila; Chen, Yuan; Mei, Qi

2015-11-01

The validation of McGill quality-of-life questionnaire (MQOLQ) in mainland China, which had already been used in multicultural palliative care background including Hong Kong and Taiwan, remained unknown. Eligible patients completed the translated Chinese version of McGill questionnaires (MQOL-C), which had been examined before the study. Construct validity was preliminarily assessed through exploratory factor analysis extracting 4 factors that construct a new hypothesis model and then the original model was proved to be better confirmed by confirmatory factor analysis. Internal consistency of all the subscales was within 0.582 to 0.917. Furthermore, test-retest reliability ranged from 0.509 to 0.859, which was determined by Spearman rank correlation coefficient. Face validation and feasibility also confirm the good validity of MQOL-C. The MQOL-C has satisfied validation in mainland Chinese patients with cancer, although cultural difference should be considered while using it. © The Author(s) 2014.

Validation of the SunTech Medical Advantage Model 2 Series Automated Blood Pressure Module in Pregnancy.

PubMed

Kuper, Spencer G; Dotson, Kristin N; Anderson, Sarah B; Harris, Stacy L; Harper, Lorie M; Tita, Alan T

2018-06-15

 We sought to validate the SunTech Medical Advantage Model 2 Series with firmware LX 3.40.8 algorithm noninvasive blood pressure module in a pregnant population, including those with preeclampsia.  Validation study of an oscillometric noninvasive blood pressure module using the ANSI/AAMI ISO 81060-2:2013 standard guidelines. Pregnant women were enrolled into three subgroups: normotensive, hypertensive without proteinuria, and preeclampsia (hypertensive with random protein-to-creatinine ratio ≥ 0.3 or a 24-hour urine protein > 300 mg). Two trained research nurses, blinded to each other's measurements, used a mercury sphygmomanometer to validate the module by following the protocol set forth in the ANSI/AAMI ISO 81060-2:2013 standard guidelines.  A total of 45 patients, 15 in each subgroup, were included. The mean systolic and diastolic differences with standard deviations between the module and the mean observers' measurements for all participants were -2.3 ± 7.3 and 0.2 ± 6.5 mm Hg, respectively. The systolic and diastolic standard deviations of the mean of the individual patient's paired module and observers' measurements were 6.27 and 5.98 mm Hg, respectively. The test device, relative to a mercury sphygmomanometer, underestimated the systolic blood pressure in patients with preeclampsia by at least 10 mm Hg in 24% (11/45) of paired measurements.  The SunTech Medical Advantage Model 2 Series with firmware LX 3.40.8 algorithm noninvasive blood pressure module is validated in pregnancy, including patients with preeclampsia; however, it may underestimate systolic blood pressure measurements in patients with preeclampsia. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Predictors of parental discretionary choice provision using the health action process approach framework: Development and validation of a self-reported questionnaire for parents of 4-7-year-olds.

PubMed

Johnson, Brittany J; Zarnowiecki, Dorota; Hendrie, Gilly A; Golley, Rebecca K

2018-02-21

Children's intake of discretionary choices is excessive. This study aimed to develop a questionnaire measuring parents' attitudes and beliefs towards limiting provision of discretionary choices, using the Health Action Process Approach model. The questionnaire items were informed by the Health Action Process Approach model, which extends the Theory of Planned Behaviour to include both motivational (intention) and volitional (post-intention) factors that influence behaviour change. The questionnaire was piloted for content and face validity (expert panel, n = 5; parents, n = 4). Construct and predictive validity were examined in a sample of 178 parents of 4-7-year-old children who completed the questionnaire online. Statistical analyses included exploratory factor analyses, Cronbach's alpha and multiple linear regression. Pilot testing supported content and face validity. Principal component analyses identified constructs that aligned with the eight constructs of the Health Action Process Approach model. Internal consistencies were high for all subscales, in both the motivational (Cronbach's alpha 0.77-0.88) and volitional phase (Cronbach's alpha 0.85-0.92). Initial results from validation tests support the development of a new questionnaire for measuring parent attitudes and beliefs regarding provision of discretionary choices to their 4-7-year-old children within the home. This new questionnaire can be used to gain greater insight into parents' attitudes and beliefs that influence ability to limit discretionary choices provision to children. Further research to expand understanding of the questionnaires' psychometric properties would be valuable, including confirmatory factor analysis and reproducibility. © 2018 Dietitians Association of Australia.

Method validation for chemical composition determination by electron microprobe with wavelength dispersive spectrometer

NASA Astrophysics Data System (ADS)

Herrera-Basurto, R.; Mercader-Trejo, F.; Muñoz-Madrigal, N.; Juárez-García, J. M.; Rodriguez-López, A.; Manzano-Ramírez, A.

2016-07-01

The main goal of method validation is to demonstrate that the method is suitable for its intended purpose. One of the advantages of analytical method validation is translated into a level of confidence about the measurement results reported to satisfy a specific objective. Elemental composition determination by wavelength dispersive spectrometer (WDS) microanalysis has been used over extremely wide areas, mainly in the field of materials science, impurity determinations in geological, biological and food samples. However, little information is reported about the validation of the applied methods. Herein, results of the in-house method validation for elemental composition determination by WDS are shown. SRM 482, a binary alloy Cu-Au of different compositions, was used during the validation protocol following the recommendations for method validation proposed by Eurachem. This paper can be taken as a reference for the evaluation of the validation parameters more frequently requested to get the accreditation under the requirements of the ISO/IEC 17025 standard: selectivity, limit of detection, linear interval, sensitivity, precision, trueness and uncertainty. A model for uncertainty estimation was proposed including systematic and random errors. In addition, parameters evaluated during the validation process were also considered as part of the uncertainty model.

Commercial Supersonics Technology Project - Status of Airport Noise

NASA Technical Reports Server (NTRS)

Bridges, James

2016-01-01

The Commercial Supersonic Technology Project has been developing databases, computational tools, and system models to prepare for a level 1 milestone, the Low Noise Propulsion Tech Challenge, to be delivered Sept 2016. Steps taken to prepare for the final validation test are given, including system analysis, code validation, and risk reduction testing.

PSI-Center Simulations of Validation Platform Experiments

NASA Astrophysics Data System (ADS)

Nelson, B. A.; Akcay, C.; Glasser, A. H.; Hansen, C. J.; Jarboe, T. R.; Marklin, G. J.; Milroy, R. D.; Morgan, K. D.; Norgaard, P. C.; Shumlak, U.; Victor, B. S.; Sovinec, C. R.; O'Bryan, J. B.; Held, E. D.; Ji, J.-Y.; Lukin, V. S.

2013-10-01

The Plasma Science and Innovation Center (PSI-Center - http://www.psicenter.org) supports collaborating validation platform experiments with extended MHD simulations. Collaborators include the Bellan Plasma Group (Caltech), CTH (Auburn U), FRX-L (Los Alamos National Laboratory), HIT-SI (U Wash - UW), LTX (PPPL), MAST (Culham), Pegasus (U Wisc-Madison), PHD/ELF (UW/MSNW), SSX (Swarthmore College), TCSU (UW), and ZaP/ZaP-HD (UW). Modifications have been made to the NIMROD, HiFi, and PSI-Tet codes to specifically model these experiments, including mesh generation/refinement, non-local closures, appropriate boundary conditions (external fields, insulating BCs, etc.), and kinetic and neutral particle interactions. The PSI-Center is exploring application of validation metrics between experimental data and simulations results. Biorthogonal decomposition is proving to be a powerful method to compare global temporal and spatial structures for validation. Results from these simulation and validation studies, as well as an overview of the PSI-Center status will be presented.

External validation of a prediction model for surgical site infection after thoracolumbar spine surgery in a Western European cohort.

PubMed

Janssen, Daniël M C; van Kuijk, Sander M J; d'Aumerie, Boudewijn B; Willems, Paul C

2018-05-16

A prediction model for surgical site infection (SSI) after spine surgery was developed in 2014 by Lee et al. This model was developed to compute an individual estimate of the probability of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Before any prediction model can be validly implemented in daily medical practice, it should be externally validated to assess how the prediction model performs in patients sampled independently from the derivation cohort. We included 898 consecutive patients who underwent instrumented thoracolumbar spine surgery. To quantify overall performance using Nagelkerke's R 2 statistic, the discriminative ability was quantified as the area under the receiver operating characteristic curve (AUC). We computed the calibration slope of the calibration plot, to judge prediction accuracy. Sixty patients developed an SSI. The overall performance of the prediction model in our population was poor: Nagelkerke's R 2 was 0.01. The AUC was 0.61 (95% confidence interval (CI) 0.54-0.68). The estimated slope of the calibration plot was 0.52. The previously published prediction model showed poor performance in our academic external validation cohort. To predict SSI after instrumented thoracolumbar spine surgery for the present population, a better fitting prediction model should be developed.

Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

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

Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com; Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario; Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts

Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogrammore » for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.« less

Validation of mesoscale models

NASA Technical Reports Server (NTRS)

Kuo, Bill; Warner, Tom; Benjamin, Stan; Koch, Steve; Staniforth, Andrew

1993-01-01

The topics discussed include the following: verification of cloud prediction from the PSU/NCAR mesoscale model; results form MAPS/NGM verification comparisons and MAPS observation sensitivity tests to ACARS and profiler data; systematic errors and mesoscale verification for a mesoscale model; and the COMPARE Project and the CME.

A Practical Approach to Governance and Optimization of Structured Data Elements.

PubMed

Collins, Sarah A; Gesner, Emily; Morgan, Steven; Mar, Perry; Maviglia, Saverio; Colburn, Doreen; Tierney, Diana; Rocha, Roberto

2015-01-01

Definition and configuration of clinical content in an enterprise-wide electronic health record (EHR) implementation is highly complex. Sharing of data definitions across applications within an EHR implementation project may be constrained by practical limitations, including time, tools, and expertise. However, maintaining rigor in an approach to data governance is important for sustainability and consistency. With this understanding, we have defined a practical approach for governance of structured data elements to optimize data definitions given limited resources. This approach includes a 10 step process: 1) identification of clinical topics, 2) creation of draft reference models for clinical topics, 3) scoring of downstream data needs for clinical topics, 4) prioritization of clinical topics, 5) validation of reference models for clinical topics, and 6) calculation of gap analyses of EHR compared against reference model, 7) communication of validated reference models across project members, 8) requested revisions to EHR based on gap analysis, 9) evaluation of usage of reference models across project, and 10) Monitoring for new evidence requiring revisions to reference model.

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

Land Ice Verification and Validation Kit

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

2015-07-15

To address a pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice-sheet models is underway. The associated verification and validation process of these models is being coordinated through a new, robust, python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVV). This release provides robust and automated verification and a performance evaluation on LCF platforms. The performance V&V involves a comprehensive comparison of model performance relative to expected behavior on a given computing platform. LIVV operates on a set of benchmark and testmore » data, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-4-bit evaluation, and plots of tests where differences occur.« less

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%.

Development and validation of a risk-prediction nomogram for in-hospital mortality in adults poisoned with drugs and nonpharmaceutical agents

PubMed Central

Lionte, Catalina; Sorodoc, Victorita; Jaba, Elisabeta; Botezat, Alina

2017-01-01

Abstract Acute poisoning with drugs and nonpharmaceutical agents represents an important challenge in the emergency department (ED). The objective is to create and validate a risk-prediction nomogram for use in the ED to predict the risk of in-hospital mortality in adults from acute poisoning with drugs and nonpharmaceutical agents. This was a prospective cohort study involving adults with acute poisoning from drugs and nonpharmaceutical agents admitted to a tertiary referral center for toxicology between January and December 2015 (derivation cohort) and between January and June 2016 (validation cohort). We used a program to generate nomograms based on binary logistic regression predictive models. We included variables that had significant associations with death. Using regression coefficients, we calculated scores for each variable, and estimated the event probability. Model validation was performed using bootstrap to quantify our modeling strategy and using receiver operator characteristic (ROC) analysis. The nomogram was tested on a separate validation cohort using ROC analysis and goodness-of-fit tests. Data from 315 patients aged 18 to 91 years were analyzed (n = 180 in the derivation cohort; n = 135 in the validation cohort). In the final model, the following variables were significantly associated with mortality: age, laboratory test results (lactate, potassium, MB isoenzyme of creatine kinase), electrocardiogram parameters (QTc interval), and echocardiography findings (E wave velocity deceleration time). Sex was also included to use the same model for men and women. The resulting nomogram showed excellent survival/mortality discrimination (area under the curve [AUC] 0.976, 95% confidence interval [CI] 0.954–0.998, P < 0.0001 for the derivation cohort; AUC 0.957, 95% CI 0.892–1, P < 0.0001 for the validation cohort). This nomogram provides more precise, rapid, and simple risk-analysis information for individual patients acutely exposed to drugs and nonpharmaceutical agents, and accurately estimates the probability of in-hospital death, exclusively using the results of objective tests available in the ED. PMID:28328838

Verifying and Validating Proposed Models for FSW Process Optimization

NASA Technical Reports Server (NTRS)

Schneider, Judith

2008-01-01

This slide presentation reviews Friction Stir Welding (FSW) and the attempts to model the process in order to optimize and improve the process. The studies are ongoing to validate and refine the model of metal flow in the FSW process. There are slides showing the conventional FSW process, a couple of weld tool designs and how the design interacts with the metal flow path. The two basic components of the weld tool are shown, along with geometries of the shoulder design. Modeling of the FSW process is reviewed. Other topics include (1) Microstructure features, (2) Flow Streamlines, (3) Steady-state Nature, and (4) Grain Refinement Mechanisms

Development and Validation of a Musculoskeletal Model of the Fully Articulated Thoracolumbar Spine and Rib Cage

PubMed Central

Bruno, Alexander G.; Bouxsein, Mary L.; Anderson, Dennis E.

2015-01-01

We developed and validated a fully articulated model of the thoracolumbar spine in opensim that includes the individual vertebrae, ribs, and sternum. To ensure trunk muscles in the model accurately represent muscles in vivo, we used a novel approach to adjust muscle cross-sectional area (CSA) and position using computed tomography (CT) scans of the trunk sampled from a community-based cohort. Model predictions of vertebral compressive loading and trunk muscle tension were highly correlated to previous in vivo measures of intradiscal pressure (IDP), vertebral loading from telemeterized implants and trunk muscle myoelectric activity recorded by electromyography (EMG). PMID:25901907

A solution to the static frame validation challenge problem using Bayesian model selection

DOE PAGES

Grigoriu, M. D.; Field, R. V.

2007-12-23

Within this paper, we provide a solution to the static frame validation challenge problem (see this issue) in a manner that is consistent with the guidelines provided by the Validation Challenge Workshop tasking document. The static frame problem is constructed such that variability in material properties is known to be the only source of uncertainty in the system description, but there is ignorance on the type of model that best describes this variability. Hence both types of uncertainty, aleatoric and epistemic, are present and must be addressed. Our approach is to consider a collection of competing probabilistic models for themore » material properties, and calibrate these models to the information provided; models of different levels of complexity and numerical efficiency are included in the analysis. A Bayesian formulation is used to select the optimal model from the collection, which is then used for the regulatory assessment. Lastly, bayesian credible intervals are used to provide a measure of confidence to our regulatory assessment.« less

A diagnostic model for chronic hypersensitivity pneumonitis

PubMed Central

Johannson, Kerri A; Elicker, Brett M; Vittinghoff, Eric; Assayag, Deborah; de Boer, Kaïssa; Golden, Jeffrey A; Jones, Kirk D; King, Talmadge E; Koth, Laura L; Lee, Joyce S; Ley, Brett; Wolters, Paul J; Collard, Harold R

2017-01-01

The objective of this study was to develop a diagnostic model that allows for a highly specific diagnosis of chronic hypersensitivity pneumonitis using clinical and radiological variables alone. Chronic hypersensitivity pneumonitis and other interstitial lung disease cases were retrospectively identified from a longitudinal database. High-resolution CT scans were blindly scored for radiographic features (eg, ground-glass opacity, mosaic perfusion) as well as the radiologist’s diagnostic impression. Candidate models were developed then evaluated using clinical and radiographic variables and assessed by the cross-validated C-statistic. Forty-four chronic hypersensitivity pneumonitis and eighty other interstitial lung disease cases were identified. Two models were selected based on their statistical performance, clinical applicability and face validity. Key model variables included age, down feather and/or bird exposure, radiographic presence of ground-glass opacity and mosaic perfusion and moderate or high confidence in the radiographic impression of chronic hypersensitivity pneumonitis. Models were internally validated with good performance, and cut-off values were established that resulted in high specificity for a diagnosis of chronic hypersensitivity pneumonitis. PMID:27245779

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

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

Epiney, A.; Canepa, S.; Zerkak, O.

The STARS project at the Paul Scherrer Institut (PSI) has adopted the TRACE thermal-hydraulic (T-H) code for best-estimate system transient simulations of the Swiss Light Water Reactors (LWRs). For analyses involving interactions between system and core, a coupling of TRACE with the SIMULATE-3K (S3K) LWR core simulator has also been developed. In this configuration, the TRACE code and associated nuclear power reactor simulation models play a central role to achieve a comprehensive safety analysis capability. Thus, efforts have now been undertaken to consolidate the validation strategy by implementing a more rigorous and structured assessment approach for TRACE applications involving eithermore » only system T-H evaluations or requiring interfaces to e.g. detailed core or fuel behavior models. The first part of this paper presents the preliminary concepts of this validation strategy. The principle is to systematically track the evolution of a given set of predicted physical Quantities of Interest (QoIs) over a multidimensional parametric space where each of the dimensions represent the evolution of specific analysis aspects, including e.g. code version, transient specific simulation methodology and model "nodalisation". If properly set up, such environment should provide code developers and code users with persistent (less affected by user effect) and quantified information (sensitivity of QoIs) on the applicability of a simulation scheme (codes, input models, methodology) for steady state and transient analysis of full LWR systems. Through this, for each given transient/accident, critical paths of the validation process can be identified that could then translate into defining reference schemes to be applied for downstream predictive simulations. In order to illustrate this approach, the second part of this paper presents a first application of this validation strategy to an inadvertent blowdown event that occurred in a Swiss BWR/6. The transient was initiated by the spurious actuation of the Automatic Depressurization System (ADS). The validation approach progresses through a number of dimensions here: First, the same BWR system simulation model is assessed for different versions of the TRACE code, up to the most recent one. The second dimension is the "nodalisation" dimension, where changes to the input model are assessed. The third dimension is the "methodology" dimension. In this case imposed power and an updated TRACE core model are investigated. For each step in each validation dimension, a common set of QoIs are investigated. For the steady-state results, these include fuel temperatures distributions. For the transient part of the present study, the evaluated QoIs include the system pressure evolution and water carry-over into the steam line.« less

Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

PubMed

Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

2017-10-01

Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (P<.001). Learning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that distributed learning is the future of sharing data in health care. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

A satellite relative motion model including J_2 and J_3 via Vinti's intermediary

NASA Astrophysics Data System (ADS)

Biria, Ashley D.; Russell, Ryan P.

2018-03-01

Vinti's potential is revisited for analytical propagation of the main satellite problem, this time in the context of relative motion. A particular version of Vinti's spheroidal method is chosen that is valid for arbitrary elliptical orbits, encapsulating J_2, J_3, and generally a partial J_4 in an orbit propagation theory without recourse to perturbation methods. As a child of Vinti's solution, the proposed relative motion model inherits these properties. Furthermore, the problem is solved in oblate spheroidal elements, leading to large regions of validity for the linearization approximation. After offering several enhancements to Vinti's solution, including boosts in accuracy and removal of some singularities, the proposed model is derived and subsequently reformulated so that Vinti's solution is piecewise differentiable. While the model is valid for the critical inclination and nonsingular in the element space, singularities remain in the linear transformation from Earth-centered inertial coordinates to spheroidal elements when the eccentricity is zero or for nearly equatorial orbits. The new state transition matrix is evaluated against numerical solutions including the J_2 through J_5 terms for a wide range of chief orbits and separation distances. The solution is also compared with side-by-side simulations of the original Gim-Alfriend state transition matrix, which considers the J_2 perturbation. Code for computing the resulting state transition matrix and associated reference frame and coordinate transformations is provided online as supplementary material.

An Innovative Software Tool Suite for Power Plant Model Validation and Parameter Calibration using PMU Measurements

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

Li, Yuanyuan; Diao, Ruisheng; Huang, Renke

Maintaining good quality of power plant stability models is of critical importance to ensure the secure and economic operation and planning of today’s power grid with its increasing stochastic and dynamic behavior. According to North American Electric Reliability (NERC) standards, all generators in North America with capacities larger than 10 MVA are required to validate their models every five years. Validation is quite costly and can significantly affect the revenue of generator owners, because the traditional staged testing requires generators to be taken offline. Over the past few years, validating and calibrating parameters using online measurements including phasor measurement unitsmore » (PMUs) and digital fault recorders (DFRs) has been proven to be a cost-effective approach. In this paper, an innovative open-source tool suite is presented for validating power plant models using PPMV tool, identifying bad parameters with trajectory sensitivity analysis, and finally calibrating parameters using an ensemble Kalman filter (EnKF) based algorithm. The architectural design and the detailed procedures to run the tool suite are presented, with results of test on a realistic hydro power plant using PMU measurements for 12 different events. The calibrated parameters of machine, exciter, governor and PSS models demonstrate much better performance than the original models for all the events and show the robustness of the proposed calibration algorithm.« less

Using the split Hopkinson pressure bar to validate material models.

PubMed

Church, Philip; Cornish, Rory; Cullis, Ian; Gould, Peter; Lewtas, Ian

2014-08-28

This paper gives a discussion of the use of the split-Hopkinson bar with particular reference to the requirements of materials modelling at QinetiQ. This is to deploy validated material models for numerical simulations that are physically based and have as little characterization overhead as possible. In order to have confidence that the models have a wide range of applicability, this means, at most, characterizing the models at low rate and then validating them at high rate. The split Hopkinson pressure bar (SHPB) is ideal for this purpose. It is also a very useful tool for analysing material behaviour under non-shock wave loading. This means understanding the output of the test and developing techniques for reliable comparison of simulations with SHPB data. For materials other than metals comparison with an output stress v strain curve is not sufficient as the assumptions built into the classical analysis are generally violated. The method described in this paper compares the simulations with as much validation data as can be derived from deployed instrumentation including the raw strain gauge data on the input and output bars, which avoids any assumptions about stress equilibrium. One has to take into account Pochhammer-Chree oscillations and their effect on the specimen and recognize that this is itself also a valuable validation test of the material model. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation.

PubMed

Zaccardi, Francesco; Webb, David R; Davies, Melanie J; Dhalwani, Nafeesa N; Gray, Laura J; Chatterjee, Sudesna; Housley, Gemma; Shaw, Dominick; Hatton, James W; Khunti, Kamlesh

2017-06-01

Hospital admissions for hypoglycaemia represent a significant burden on individuals with diabetes and have a substantial economic impact on healthcare systems. To date, no prognostic models have been developed to predict outcomes following admission for hypoglycaemia. We aimed to develop and validate prediction models to estimate risk of inpatient death, 24 h discharge and one month readmission in people admitted to hospital for hypoglycaemia. We used the Hospital Episode Statistics database, which includes data on all hospital admission to National Health Service hospital trusts in England, to extract admissions for hypoglycaemia between 2010 and 2014. We developed, internally and temporally validated, and compared two prognostic risk models for each outcome. The first model included age, sex, ethnicity, region, social deprivation and Charlson score ('base' model). In the second model, we added to the 'base' model the 20 most common medical conditions and applied a stepwise backward selection of variables ('disease' model). We used C-index and calibration plots to assess model performance and developed a calculator to estimate probabilities of outcomes according to individual characteristics. In derivation samples, 296 out of 11,136 admissions resulted in inpatient death, 1789/33,825 in one month readmission and 8396/33,803 in 24 h discharge. Corresponding values for validation samples were: 296/10,976, 1207/22,112 and 5363/22,107. The two models had similar discrimination. In derivation samples, C-indices for the base and disease models, respectively, were: 0.77 (95% CI 0.75, 0.80) and 0.78 (0.75, 0.80) for death, 0.57 (0.56, 0.59) and 0.57 (0.56, 0.58) for one month readmission, and 0.68 (0.67, 0.69) and 0.69 (0.68, 0.69) for 24 h discharge. Corresponding values in validation samples were: 0.74 (0.71, 0.76) and 0.74 (0.72, 0.77), 0.55 (0.54, 0.57) and 0.55 (0.53, 0.56), and 0.66 (0.65, 0.67) and 0.67 (0.66, 0.68). In both derivation and validation samples, calibration plots showed good agreement for the three outcomes. We developed a calculator of probabilities for inpatient death and 24 h discharge given the low performance of one month readmission models. This simple and pragmatic tool to predict in-hospital death and 24 h discharge has the potential to reduce mortality and improve discharge in people admitted for hypoglycaemia.

VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilke, Renate A. I.

2015-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. Here, we present the key ingredients of this framework. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

VALUE: A framework to validate downscaling approaches for climate change studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilcke, Renate A. I.

2015-01-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

Experimentally validated finite element model of electrocaloric multilayer ceramic structures

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

Smith, N. A. S., E-mail: nadia.smith@npl.co.uk, E-mail: maciej.rokosz@npl.co.uk, E-mail: tatiana.correia@npl.co.uk; Correia, T. M., E-mail: nadia.smith@npl.co.uk, E-mail: maciej.rokosz@npl.co.uk, E-mail: tatiana.correia@npl.co.uk; Rokosz, M. K., E-mail: nadia.smith@npl.co.uk, E-mail: maciej.rokosz@npl.co.uk, E-mail: tatiana.correia@npl.co.uk

2014-07-28

A novel finite element model to simulate the electrocaloric response of a multilayer ceramic capacitor (MLCC) under real environment and operational conditions has been developed. The two-dimensional transient conductive heat transfer model presented includes the electrocaloric effect as a source term, as well as accounting for radiative and convective effects. The model has been validated with experimental data obtained from the direct imaging of MLCC transient temperature variation under application of an electric field. The good agreement between simulated and experimental data, suggests that the novel experimental direct measurement methodology and the finite element model could be used to supportmore » the design of optimised electrocaloric units and operating conditions.« less

Hybrid Particle-Element Simulation of Impact on Composite Orbital Debris Shields

NASA Technical Reports Server (NTRS)

Fahrenthold, Eric P.

2004-01-01

This report describes the development of new numerical methods and new constitutive models for the simulation of hypervelocity impact effects on spacecraft. The research has included parallel implementation of the numerical methods and material models developed under the project. Validation work has included both one dimensional simulations, for comparison with exact solutions, and three dimensional simulations of published hypervelocity impact experiments. The validated formulations have been applied to simulate impact effects in a velocity and kinetic energy regime outside the capabilities of current experimental methods. The research results presented here allow for the expanded use of numerical simulation, as a complement to experimental work, in future design of spacecraft for hypervelocity impact effects.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

PubMed Central

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

Occupant Protection during Orion Crew Exploration Vehicle Landings

NASA Technical Reports Server (NTRS)

Gernhardt, Michael L.; Jones, J. A.; Granderson, B. K.; Somers, J. T.

2009-01-01

The constellation program is evaluating current vehicle design capabilities for nominal water landings and contingency land landings of the Orion Crew Exploration vehicle. The Orion Landing Strategy tiger team was formed to lead the technical effort for which associated activities include the current vehicle design, susceptibility to roll control and tip over, reviewing methods for assessing occupant injury during ascent / aborts /landings, developing an alternate seat/attenuation design solution which improves occupant protection and operability, and testing the seat/attenuation system designs to ensure valid results. The EVA physiology, systems and Performance (EPSP) project is leading the effort under the authority of the Tiger Team Steering committee to develop, verify, validate and accredit biodynamics models using a variety of crash and injury databases including NASCAR, Indy Car and military aircraft. The validated biodynamics models will be used by the Constellation program to evaluate a variety of vehicle, seat and restraint designs in the context of multiple nominal and off-nominal landing scenarios. The models will be used in conjunction with Acceptable Injury Risk definitions to provide new occupant protection requirements for the Constellation Program.

Development and validation of a predictive risk model for all-cause mortality in type 2 diabetes.

PubMed

Robinson, Tom E; Elley, C Raina; Kenealy, Tim; Drury, Paul L

2015-06-01

Type 2 diabetes is common and is associated with an approximate 80% increase in the rate of mortality. Management decisions may be assisted by an estimate of the patient's absolute risk of adverse outcomes, including death. This study aimed to derive a predictive risk model for all-cause mortality in type 2 diabetes. We used primary care data from a large national multi-ethnic cohort of patients with type 2 diabetes in New Zealand and linked mortality records to develop a predictive risk model for 5-year risk of mortality. We then validated this model using information from a separate cohort of patients with type 2 diabetes. 26,864 people were included in the development cohort with a median follow up time of 9.1 years. We developed three models initially using demographic information and then progressively more clinical detail. The final model, which also included markers of renal disease, proved to give best prediction of all-cause mortality with a C-statistic of 0.80 in the development cohort and 0.79 in the validation cohort (7610 people) and was well calibrated. Ethnicity was a major factor with hazard ratios of 1.37 for indigenous Maori, 0.41 for East Asian and 0.55 for Indo Asian compared with European (P<0.001). We have developed a model using information usually available in primary care that provides good assessment of patient's risk of death. Results are similar to models previously published from smaller cohorts in other countries and apply to a wider range of patient ethnic groups. Copyright © 2015. Published by Elsevier Ireland Ltd.

High-resolution modeling assessment of tidal stream resource in Western Passage of Maine, USA

NASA Astrophysics Data System (ADS)

Yang, Zhaoqing; Wang, Taiping; Feng, Xi; Xue, Huijie; Kilcher, Levi

2017-04-01

Although significant efforts have been taken to assess the maximum potential of tidal stream energy at system-wide scale, accurate assessment of tidal stream energy resource at project design scale requires detailed hydrodynamic simulations using high-resolution three-dimensional (3-D) numerical models. Extended model validation against high quality measured data is essential to minimize the uncertainties of the resource assessment. Western Passage in the State of Maine in U.S. has been identified as one of the top ranking sites for tidal stream energy development in U.S. coastal waters, based on a number of criteria including tidal power density, market value and transmission distance. This study presents an on-going modeling effort for simulating the tidal hydrodynamics in Western Passage using the 3-D unstructured-grid Finite Volume Community Ocean Model (FVCOM). The model domain covers a large region including the entire the Bay of Fundy with grid resolution varies from 20 m in the Western Passage to approximately 1000 m along the open boundary near the mouth of Bay of Fundy. Preliminary model validation was conducted using existing NOAA measurements within the model domain. Spatial distributions of tidal power density were calculated and extractable tidal energy was estimated using a tidal turbine module embedded in FVCOM under different tidal farm scenarios. Additional field measurements to characterize resource and support model validation were discussed. This study provides an example of high resolution resource assessment based on the guidance recommended by the International Electrotechnical Commission Technical Specification.

Irma 5.2 multi-sensor signature prediction model

NASA Astrophysics Data System (ADS)

Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Chow, Anthony; Yamaoka, Neil; Kim, Charles

2007-04-01

The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the validation test results of the Irma passive models and discuss the new features in Irma 5.2.

Numerical evaluation of heating in the human head due to magnetic resonance imaging (MRI)

NASA Astrophysics Data System (ADS)

Nguyen, Uyen; Brown, Steve; Chang, Isaac; Krycia, Joe; Mirotznik, Mark S.

2003-06-01

In this paper we present a numerical model for evaluating tissue heating during magnetic resonance imaging (MRI). Our method, which included a detailed anatomical model of a human head, calculated both the electromagnetic power deposition and the associated temperature elevations during a MRI head examination. Numerical studies were conducted using a realistic birdcage coil excited at frequencies ranging from 63 MHz to 500 MHz. The model was validated both experimentally and analytically. The experimental validation was performed at the MR test facility located at the FDA's Center for Devices and Radiological Health (CDRH).

Predicting the success of IVF: external validation of the van Loendersloot's model.

PubMed

Sarais, Veronica; Reschini, Marco; Busnelli, Andrea; Biancardi, Rossella; Paffoni, Alessio; Somigliana, Edgardo

2016-06-01

Is the predictive model for IVF success proposed by van Loendersloot et al. valid in a different geographical and cultural context? The model discriminates well but was less accurate than in the original context where it was developed. Several independent groups have developed models that combine different variables with the aim of estimating the chance of pregnancy with IVF but only four of them have been externally validated. One of these four, the van Loendersloot's model, deserves particular attention and further investigation for at least three reasons; (i) the reported area under the receiver operating characteristics curve (c-statistics) in the temporal validation setting was the highest reported to date (0.68), (ii) the perspective of the model is clinically wise since it includes variables obtained from previous failed cycles, if any, so it can be applied to any women entering an IVF cycle, (iii) the model lacks external validation in a geographically different center. Retrospective cohort study of women undergoing oocyte retrieval for IVF between January 2013 and December 2013 at the infertility unit of the Fondazione Ca' Granda, Ospedale Maggiore Policlinico of Milan, Italy. Only the first oocyte retrieval cycle performed during the study period was included in the study. Women with previous IVF cycles were excluded if the last one before the study cycle was in another center. The main outcome was the cumulative live birth rate per oocytes retrieval. Seven hundred seventy-two women were selected. Variables included in the van Loendersloot's model and the relative weights (beta) were used. The variable resulting from this combination (Y) was transformed into a probability. The discriminatory capacity was assessed using the c-statistics. Calibration was made using a logistic regression that included Y as the unique variable and live birth as the outcome. Data are presented using both the original and the calibrated models. Performance was evaluated correlating the mean predicted chances of live births in the five quintiles and the observed rates. Two-hundred-eleven live births (27%) were obtained. The c-statistic was 0.64 (95% CI: 0.61-0.67, P < 0.001). The slope of the linear predictor (calibration slope) expressed as an Odds Ratio was 1.81 (95% CI: 1.46-2.24, P < 0.001), corresponding to a beta of 0.630. The calibration intercept was +0.349 (P = 0.13). While a clear discrepancy exists using the original model, data appear properly distributed with the calibrated model. The Pearson coefficient of the correlation between the mean predicted chances of live births in the five quintiles and the observed rates was 0.99 (P = 0.002). Data were collected retrospectively, thus exposing them to potential inaccuracies. The selection criteria for access to IVF adopted in our center might be too stringent, leading to the exclusion of women with a poor, yet acceptable chance of live birth. Therefore, the validity of the model in women with a very low chance of live birth could not be tested. The van Loendersloot's model can be used in other contexts but it is important that it has local calibration. It may help in counseling couples about their chance of success but it cannot be used to exclude treatments. Further research is needed to improve the discriminatory performance of IVF predictive models. None. Not applicable. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation

NASA Astrophysics Data System (ADS)

Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.

2003-12-01

Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.

Validating and determining the weight of items used for evaluating clinical governance implementation based on analytic hierarchy process model.

PubMed

Hooshmand, Elaheh; Tourani, Sogand; Ravaghi, Hamid; Vafaee Najar, Ali; Meraji, Marziye; Ebrahimipour, Hossein

2015-04-08

The purpose of implementing a system such as Clinical Governance (CG) is to integrate, establish and globalize distinct policies in order to improve quality through increasing professional knowledge and the accountability of healthcare professional toward providing clinical excellence. Since CG is related to change, and change requires money and time, CG implementation has to be focused on priority areas that are in more dire need of change. The purpose of the present study was to validate and determine the significance of items used for evaluating CG implementation. The present study was descriptive-quantitative in method and design. Items used for evaluating CG implementation were first validated by the Delphi method and then compared with one another and ranked based on the Analytical Hierarchy Process (AHP) model. The items that were validated for evaluating CG implementation in Iran include performance evaluation, training and development, personnel motivation, clinical audit, clinical effectiveness, risk management, resource allocation, policies and strategies, external audit, information system management, research and development, CG structure, implementation prerequisites, the management of patients' non-medical needs, complaints and patients' participation in the treatment process. The most important items based on their degree of significance were training and development, performance evaluation, and risk management. The least important items included the management of patients' non-medical needs, patients' participation in the treatment process and research and development. The fundamental requirements of CG implementation included having an effective policy at national level, avoiding perfectionism, using the expertise and potentials of the entire country and the coordination of this model with other models of quality improvement such as accreditation and patient safety. © 2015 by Kerman University of Medical Sciences.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification

PubMed Central

Baczyńska, Anna K.; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach’s alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed. PMID:27014111

Nonadiabatic nonradial p-mode frequencies of the standard solar model, with and without helium diffusion

NASA Technical Reports Server (NTRS)

Guenther, D. B.

1994-01-01

The nonadiabatic frequencies of a standard solar model and a solar model that includes helium diffusion are discussed. The nonadiabatic pulsation calculation includes physics that describes the losses and gains due to radiation. Radiative gains and losses are modeled in both the diffusion approximation, which is only valid in optically thick regions, and the Eddington approximation, which is valid in both optically thin and thick regions. The calculated pulsation frequencies for modes with l less than or equal to 1320 are compared to the observed spectrum of the Sun. Compared to a strictly adiabatic calculation, the nonadiabatic calculation of p-mode frequencies improves the agreement between model and observation. When helium diffusion is included in the model the frequencies of the modes that are sensitive to regions near the base of the convection zone are improved (i.e., brought into closer agreement with observation), but the agreement is made worse for other modes. Cyclic variations in the frequency spacings of the Sun as a function of frequency of n are presented as evidence for a discontinuity in the structure of the Sun, possibly located near the base of the convection zone.

Piloted Evaluation of a UH-60 Mixer Equivalent Turbulence Simulation Model

NASA Technical Reports Server (NTRS)

Lusardi, Jeff A.; Blanken, Chris L.; Tischeler, Mark B.

2002-01-01

A simulation study of a recently developed hover/low speed Mixer Equivalent Turbulence Simulation (METS) model for the UH-60 Black Hawk helicopter was conducted in the NASA Ames Research Center Vertical Motion Simulator (VMS). The experiment was a continuation of previous work to develop a simple, but validated, turbulence model for hovering rotorcraft. To validate the METS model, two experienced test pilots replicated precision hover tasks that had been conducted in an instrumented UH-60 helicopter in turbulence. Objective simulation data were collected for comparison with flight test data, and subjective data were collected that included handling qualities ratings and pilot comments for increasing levels of turbulence. Analyses of the simulation results show good analytic agreement between the METS model and flight test data, with favorable pilot perception of the simulated turbulence. Precision hover tasks were also repeated using the more complex rotating-frame SORBET (Simulation Of Rotor Blade Element Turbulence) model to generate turbulence. Comparisons of the empirically derived METS model with the theoretical SORBET model show good agreement providing validation of the more complex blade element method of simulating turbulence.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 2: Wind farm wake models

NASA Astrophysics Data System (ADS)

Moriarty, Patrick; Sanz Rodrigo, Javier; Gancarski, Pawel; Chuchfield, Matthew; Naughton, Jonathan W.; Hansen, Kurt S.; Machefaux, Ewan; Maguire, Eoghan; Castellani, Francesco; Terzi, Ludovico; Breton, Simon-Philippe; Ueda, Yuko

2014-06-01

Researchers within the International Energy Agency (IEA) Task 31: Wakebench have created a framework for the evaluation of wind farm flow models operating at the microscale level. The framework consists of a model evaluation protocol integrated with a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to wind farm wake models, including best practices for the benchmarking and data processing procedures for validation datasets from wind farm SCADA and meteorological databases. A hierarchy of test cases has been proposed for wake model evaluation, from similarity theory of the axisymmetric wake and idealized infinite wind farm, to single-wake wind tunnel (UMN-EPFL) and field experiments (Sexbierum), to wind farm arrays in offshore (Horns Rev, Lillgrund) and complex terrain conditions (San Gregorio). A summary of results from the axisymmetric wake, Sexbierum, Horns Rev and Lillgrund benchmarks are used to discuss the state-of-the-art of wake model validation and highlight the most relevant issues for future development.

CFD methodology and validation for turbomachinery flows

NASA Astrophysics Data System (ADS)

Hirsch, Ch.

1994-05-01

The essential problem today, in the application of 3D Navier-Stokes simulations to the design and analysis of turbomachinery components, is the validation of the numerical approximation and of the physical models, in particular the turbulence modelling. Although most of the complex 3D flow phenomena occurring in turbomachinery bladings can be captured with relatively coarse meshes, many detailed flow features are dependent on mesh size, on the turbulence and transition models. A brief review of the present state of the art of CFD methodology is given with emphasis on quality and accuracy of numerical approximations related to viscous flow computations. Considerations related to the mesh influence on solution accuracy are stressed. The basic problems of turbulence and transition modelling are discussed next, with a short summary of the main turbulence models and their applications to representative turbomachinery flows. Validations of present turbulence models indicate that none of the available turbulence models is able to predict all the detailed flow behavior in complex flow interactions. In order to identify the phenomena that can be captured on coarser meshes a detailed understanding of the complex 3D flow in compressor and turbines is necessary. Examples of global validations for different flow configurations, representative of compressor and turbine aerodynamics are presented, including secondary and tip clearance flows.

A clinical reasoning model focused on clients' behaviour change with reference to physiotherapists: its multiphase development and validation.

PubMed

Elvén, Maria; Hochwälder, Jacek; Dean, Elizabeth; Söderlund, Anne

2015-05-01

A biopsychosocial approach and behaviour change strategies have long been proposed to serve as a basis for addressing current multifaceted health problems. This emphasis has implications for clinical reasoning of health professionals. This study's aim was to develop and validate a conceptual model to guide physiotherapists' clinical reasoning focused on clients' behaviour change. Phase 1 consisted of the exploration of existing research and the research team's experiences and knowledge. Phases 2a and 2b consisted of validation and refinement of the model based on input from physiotherapy students in two focus groups (n = 5 per group) and from experts in behavioural medicine (n = 9). Phase 1 generated theoretical and evidence bases for the first version of a model. Phases 2a and 2b established the validity and value of the model. The final model described clinical reasoning focused on clients' behaviour change as a cognitive, reflective, collaborative and iterative process with multiple interrelated levels that included input from the client and physiotherapist, a functional behavioural analysis of the activity-related target behaviour and the selection of strategies for behaviour change. This unique model, theory- and evidence-informed, has been developed to help physiotherapists to apply clinical reasoning systematically in the process of behaviour change with their clients.

From bedside to bench and back again: research issues in animal models of human disease.

PubMed

Tkacs, Nancy C; Thompson, Hilaire J

2006-07-01

To improve outcomes for patients with many serious clinical problems, multifactorial research approaches by nurse scientists, including the use of animal models, are necessary. Animal models serve as analogies for clinical problems seen in humans and must meet certain criteria, including validity and reliability, to be useful in moving research efforts forward. This article describes research considerations in the development of rodent models. As the standard of diabetes care evolves to emphasize intensive insulin therapy, rates of severe hypoglycemia are increasing among patients with type 1 and type 2 diabetes mellitus. A consequence of this change in clinical practice is an increase in rates of two hypoglycemia-related diabetes complications: hypoglycemia-associated autonomic failure (HAAF) and resulting hypoglycemia unawareness. Work on an animal model of HAAF is in an early developmental stage, with several labs reporting different approaches to model this complication of type 1 diabetes mellitus. This emerging model serves as an example illustrating how evaluation of validity and reliability is critically important at each stage of developing and testing animal models to support inquiry into human disease.

Recent developments of DMI's operational system: Coupled Ecosystem-Circulation-and SPM model.

NASA Astrophysics Data System (ADS)

Murawski, Jens; Tian, Tian; Dobrynin, Mikhail

2010-05-01

ECOOP is a pan- European project with 72 partners from 29 countries around the Baltic Sea, the North Sea, the Iberia-Biscay-Ireland region, the Mediterranean Sea and the Black Sea. The project aims at the development and the integration of the different coastal and regional observation and forecasting systems. The Danish Meteorological Institute DMI coordinates the project and is responsible for the Baltic Sea regional forecasting System. Over the project period, the Baltic Sea system was developed from a purely hydro dynamical model (version V1), running operationally since summer 2009, to a coupled model platform (version V2), including model components for the simulation of suspended particles, data assimilation and ecosystem variables. The ECOOP V2 model is currently tested and validated, and will replace the V1 version soon. The coupled biogeochemical- and circulation model runs operationally since November 2009. The daily forecasts are presented at DMI's homepage http:/ocean.dmi.dk. The presentation includes a short description of the ECOOP forecasting system, discusses the model results and shows the outcome of the model validation.

Goals and Status of the NASA Juncture Flow Experiment

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Morrison, Joseph H.

2016-01-01

The NASA Juncture Flow experiment is a new effort whose focus is attaining validation data in the juncture region of a wing-body configuration. The experiment is designed specifically for the purpose of CFD validation. Current turbulence models routinely employed by Reynolds-averaged Navier-Stokes CFD are inconsistent in their prediction of corner flow separation in aircraft juncture regions, so experimental data in the near-wall region of such a configuration will be useful both for assessment as well as for turbulence model improvement. This paper summarizes the Juncture Flow effort to date, including preliminary risk-reduction experiments already conducted and planned future experiments. The requirements and challenges associated with conducting a quality validation test are discussed.

Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP): a prospective cohort study.

PubMed

Thangaratinam, Shakila; Allotey, John; Marlin, Nadine; Mol, Ben W; Von Dadelszen, Peter; Ganzevoort, Wessel; Akkermans, Joost; Ahmed, Asif; Daniels, Jane; Deeks, Jon; Ismail, Khaled; Barnard, Ann Marie; Dodds, Julie; Kerry, Sally; Moons, Carl; Riley, Richard D; Khan, Khalid S

2017-04-01

The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women. To develop and validate prediction models for outcomes in early-onset pre-eclampsia. Prospective cohort for model development, with validation in two external data sets. Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies. Pregnant women with early-onset pre-eclampsia. Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets. The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey. The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications. We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes ( c -statistic), and the agreement between predicted and observed risk (calibration slope). The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted c -statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c -statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c -statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications. The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation. Current Controlled Trials ISRCTN40384046. The National Institute for Health Research Health Technology Assessment programme.

Construct Validity of Selected Measures of Physical Activity Beliefs and Motives in Fifth and Sixth Grade Boys and Girls

PubMed Central

Saunders, Ruth P.; McIver, Kerry L.; Dowda, Marsha; Pate, Russell R.

2013-01-01

Objective Scales used to measure selected social-cognitive beliefs and motives for physical activity were tested among boys and girls. Methods Covariance modeling was applied to responses obtained from large multi-ethnic samples of students in the fifth and sixth grades. Results Theoretically and statistically sound models were developed, supporting the factorial validity of the scales in all groups. Multi-group longitudinal invariance was confirmed between boys and girls, overweight and normal weight students, and non-Hispanic black and white children. The construct validity of the scales was supported by hypothesized convergent and discriminant relationships within a measurement model that included correlations with physical activity (MET • min/day) measured by an accelerometer. Conclusions Scores from the scales provide valid assessments of selected beliefs and motives that are putative mediators of change in physical activity among boys and girls, as they begin the understudied transition from the fifth grade into middle school, when physical activity naturally declines. PMID:23459310

Construct validity of selected measures of physical activity beliefs and motives in fifth and sixth grade boys and girls.

PubMed

Dishman, Rod K; Saunders, Ruth P; McIver, Kerry L; Dowda, Marsha; Pate, Russell R

2013-06-01

Scales used to measure selected social-cognitive beliefs and motives for physical activity were tested among boys and girls. Covariance modeling was applied to responses obtained from large multi-ethnic samples of students in the fifth and sixth grades. Theoretically and statistically sound models were developed, supporting the factorial validity of the scales in all groups. Multi-group longitudinal invariance was confirmed between boys and girls, overweight and normal weight students, and non-Hispanic black and white children. The construct validity of the scales was supported by hypothesized convergent and discriminant relationships within a measurement model that included correlations with physical activity (MET • min/day) measured by an accelerometer. Scores from the scales provide valid assessments of selected beliefs and motives that are putative mediators of change in physical activity among boys and girls, as they begin the understudied transition from the fifth grade into middle school, when physical activity naturally declines.

Dynamic Simulation of Human Gait Model With Predictive Capability.

PubMed

Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

2018-03-01

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

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

Valencia, Antoni; Prous, Josep; Mora, Oscar

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less

Identification of patients at high risk for Clostridium difficile infection: development and validation of a risk prediction model in hospitalized patients treated with antibiotics.

PubMed

van Werkhoven, C H; van der Tempel, J; Jajou, R; Thijsen, S F T; Diepersloot, R J A; Bonten, M J M; Postma, D F; Oosterheert, J J

2015-08-01

To develop and validate a prediction model for Clostridium difficile infection (CDI) in hospitalized patients treated with systemic antibiotics, we performed a case-cohort study in a tertiary (derivation) and secondary care hospital (validation). Cases had a positive Clostridium test and were treated with systemic antibiotics before suspicion of CDI. Controls were randomly selected from hospitalized patients treated with systemic antibiotics. Potential predictors were selected from the literature. Logistic regression was used to derive the model. Discrimination and calibration of the model were tested in internal and external validation. A total of 180 cases and 330 controls were included for derivation. Age >65 years, recent hospitalization, CDI history, malignancy, chronic renal failure, use of immunosuppressants, receipt of antibiotics before admission, nonsurgical admission, admission to the intensive care unit, gastric tube feeding, treatment with cephalosporins and presence of an underlying infection were independent predictors of CDI. The area under the receiver operating characteristic curve of the model in the derivation cohort was 0.84 (95% confidence interval 0.80-0.87), and was reduced to 0.81 after internal validation. In external validation, consisting of 97 cases and 417 controls, the model area under the curve was 0.81 (95% confidence interval 0.77-0.85) and model calibration was adequate (Brier score 0.004). A simplified risk score was derived. Using a cutoff of 7 points, the positive predictive value, sensitivity and specificity were 1.0%, 72% and 73%, respectively. In conclusion, a risk prediction model was developed and validated, with good discrimination and calibration, that can be used to target preventive interventions in patients with increased risk of CDI. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Analysis of Wave Predictions from the Coastal Model Test Bed using Operationally Estimated Bathymetry

NASA Astrophysics Data System (ADS)

Bak, S.; Smith, J. M.; Hesser, T.; Bryant, M. A.

2016-12-01

Near-coast wave models are generally validated with relatively small data sets that focus on analytical solutions, specialized experiments, or intense storms. Prior studies have compiled testbeds that include a few dozen experiments or storms to validate models (e.g., Ris et al. 2002), but few examples exist that allow for continued model evaluation in the nearshore and surf-zone in near-realtime. The limited nature of these validation sets is driven by a lack of high spatial and temporal resolution in-situ wave measurements and the difficulty in maintaining these instruments on the active profile over long periods of time. The US Army Corps of Engineers Field Research Facility (FRF) has initiated a Coastal Model Test-Bed (CMTB), which is an automated system that continually validates wave models (with morphological and circulation models to follow) utilizing the rich data set of oceanographic and bathymetric measurements collected at the FRF. The FRF's cross-shore wave array provides wave measurements along a cross-shore profile from 26 m of water depth to the shoreline, utilizing various instruments including wave-rider buoys, AWACs, aquadopps, pressure gauges, and a dune-mounted lidar (Brodie et al. 2015). This work uses the CMTB to evaluate the performance of a phase-averaged numerical wave model, STWAVE (Smith 2007, Massey et al. 2011) over the course of a year at the FRF in Duck, NC. Additionally, from the BathyDuck Experiment in October 2015, the CMTB was used to determine the impact of applying the depth boundary condition for the model from monthly acoustic bathymetric surveys in comparison to hourly estimates using a video-based inversion method (e.g., cBathy, Holman et al. 2013). The modeled wave parameters using both bathymetric boundary conditions are evaluated using the FRF's cross-shore wave array and two additional cross-shore arrays of wave measurements in 2 to 4 m water depth from BathyDuck in Fall, 2015.

Predicting long-term survival after coronary artery bypass graft surgery.

PubMed

Karim, Md N; Reid, Christopher M; Huq, Molla; Brilleman, Samuel L; Cochrane, Andrew; Tran, Lavinia; Billah, Baki

2018-02-01

To develop a model for predicting long-term survival following coronary artery bypass graft surgery. This study included 46 573 patients from the Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZCTS) registry, who underwent isolated coronary artery bypass graft surgery between 2001 and 2014. Data were randomly split into development (23 282) and validation (23 291) samples. Cox regression models were fitted separately, using the important preoperative variables, for 4 'time intervals' (31-90 days, 91-365 days, 1-3 years and >3 years), with optimal predictors selected using the bootstrap bagging technique. Model performance was assessed both in validation data and in combined data (development and validation samples). Coefficients of all 4 final models were estimated on the combined data adjusting for hospital-level clustering. The Kaplan-Meier mortality rates estimated in the sample were 1.7% at 90 days, 2.8% at 1 year, 4.4% at 2 years and 6.1% at 3 years. Age, peripheral vascular disease, respiratory disease, reduced ejection fraction, renal dysfunction, arrhythmia, diabetes, hypercholesterolaemia, cerebrovascular disease, hypertension, congestive heart failure, steroid use and smoking were included in all 4 models. However, their magnitude of effect varied across the time intervals. Harrell's C-statistics was 0.83, 0.78, 0.75 and 0.74 for 31-90 days, 91-365 days, 1-3 years and >3 years models, respectively. Models showed excellent discrimination and calibration in validation data. Models were developed for predicting long-term survival at 4 time intervals after isolated coronary artery bypass graft surgery. These models can be used in conjunction with the existing 30-day mortality prediction model. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Frequency Response Function Based Damage Identification for Aerospace Structures

NASA Astrophysics Data System (ADS)

Oliver, Joseph Acton

Structural health monitoring technologies continue to be pursued for aerospace structures in the interests of increased safety and, when combined with health prognosis, efficiency in life-cycle management. The current dissertation develops and validates damage identification technology as a critical component for structural health monitoring of aerospace structures and, in particular, composite unmanned aerial vehicles. The primary innovation is a statistical least-squares damage identification algorithm based in concepts of parameter estimation and model update. The algorithm uses frequency response function based residual force vectors derived from distributed vibration measurements to update a structural finite element model through statistically weighted least-squares minimization producing location and quantification of the damage, estimation uncertainty, and an updated model. Advantages compared to other approaches include robust applicability to systems which are heavily damped, large, and noisy, with a relatively low number of distributed measurement points compared to the number of analytical degrees-of-freedom of an associated analytical structural model (e.g., modal finite element model). Motivation, research objectives, and a dissertation summary are discussed in Chapter 1 followed by a literature review in Chapter 2. Chapter 3 gives background theory and the damage identification algorithm derivation followed by a study of fundamental algorithm behavior on a two degree-of-freedom mass-spring system with generalized damping. Chapter 4 investigates the impact of noise then successfully proves the algorithm against competing methods using an analytical eight degree-of-freedom mass-spring system with non-proportional structural damping. Chapter 5 extends use of the algorithm to finite element models, including solutions for numerical issues, approaches for modeling damping approximately in reduced coordinates, and analytical validation using a composite sandwich plate model. Chapter 6 presents the final extension to experimental systems-including methods for initial baseline correlation and data reduction-and validates the algorithm on an experimental composite plate with impact damage. The final chapter deviates from development and validation of the primary algorithm to discuss development of an experimental scaled-wing test bed as part of a collaborative effort for developing structural health monitoring and prognosis technology. The dissertation concludes with an overview of technical conclusions and recommendations for future work.

Clozapine and GABA transmission in schizophrenia disease models: establishing principles to guide treatments.

PubMed

O'Connor, William T; O'Shea, Sean D

2015-06-01

Schizophrenia disease models are necessary to elucidate underlying changes and to establish new therapeutic strategies towards a stage where drug efficacy in schizophrenia (against all classes of symptoms) can be predicted. Here we summarise the evidence for a GABA dysfunction in schizophrenia and review the functional neuroanatomy of five pathways implicated in schizophrenia, namely the mesocortical, mesolimbic, ventral striopallidal, dorsal striopallidal and perforant pathways including the role of local GABA transmission and we describe the effect of clozapine on local neurotransmitter release. This review also evaluates psychotropic drug-induced, neurodevelopmental and environmental disease models including their compatibility with brain microdialysis. The validity of disease models including face, construct, etiological and predictive validity and how these models constitute theories about this illness is also addressed. A disease model based on the effect of the abrupt withdrawal of clozapine on GABA release is also described. The review concludes that while no single animal model is entirely successful in reproducing schizophreniform symptomatology, a disease model based on an ability to prevent and/or reverse the abrupt clozapine discontinuation-induced changes in GABA release in brain regions implicated in schizophrenia may be useful for hypothesis testing and for in vivo screening of novel ligands not limited to a single pharmacological class. Copyright © 2015 Elsevier Inc. All rights reserved.

Developing a dengue forecast model using machine learning: A case study in China.

PubMed

Guo, Pi; Liu, Tao; Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-10-01

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

A Decision Tree to Identify Children Affected by Prenatal Alcohol Exposure

PubMed Central

Goh, Patrick K.; Doyle, Lauren R.; Glass, Leila; Jones, Kenneth L.; Riley, Edward P.; Coles, Claire D.; Hoyme, H. Eugene; Kable, Julie A.; May, Philip A.; Kalberg, Wendy O.; Elizabeth, R. Sowell; Wozniak, Jeffrey R.; Mattson, Sarah N.

2017-01-01

Objective To develop and validate a hierarchical decision tree model, combining neurobehavioral and physical measures, for identification of children affected by prenatal alcohol exposure even when facial dysmorphology is not present. Study design Data were collected as part of a multisite study across the United States. The model was developed after evaluating over 1000 neurobehavioral and dysmorphology variables collected from 434 children (8–16y) with prenatal alcohol exposure, with and without fetal alcohol syndrome (FAS), and non-exposed controls, with and without other clinically-relevant behavioral or cognitive concerns. The model was subsequently validated in an independent sample of 454 children in two age ranges (5–7y or 10–16y). In all analyses, the discriminatory ability of each model step was tested with logistic regression. Classification accuracies and positive and negative predictive values were calculated. Results The model consisted of variables from 4 measures (2 parent questionnaires, an IQ score, and a physical examination). Overall accuracy rates for both the development and validation samples met or exceeded our goal of 80% overall accuracy. Conclusions The decision tree model distinguished children affected by prenatal alcohol exposure from non-exposed controls, including those with other behavioral concerns or conditions. Improving identification of this population will streamline access to clinical services, including multidisciplinary evaluation and treatment. PMID:27476634

Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.

PubMed

Wieske, Luuk; Witteveen, Esther; Verhamme, Camiel; Dettling-Ihnenfeldt, Daniela S; van der Schaaf, Marike; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2014-01-01

An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters. Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score. Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score. The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation.

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.

Development of the evaluation instrument use CIPP on the implementation of project assessment topic optik

NASA Astrophysics Data System (ADS)

Asfaroh, Jati Aurum; Rosana, Dadan; Supahar

2017-08-01

This research aims to develop an evaluation instrument models CIPP valid and reliable as well as determine the feasibility and practicality of an evaluation instrument models CIPP. An evaluation instrument models CIPP to evaluate the implementation of the project assessment topic optik to measure problem-solving skills of junior high school class VIII in the Yogyakarta region. This research is a model of development that uses 4-D. Subject of product trials are students in class VIII SMP N 1 Galur and SMP N 1 Sleman. Data collection techniques in this research using non-test techniques include interviews, questionnaires and observations. Validity in this research was analyzed using V'Aikens. Reliability analyzed using ICC. This research uses 7 raters are derived from two lecturers expert (expert judgment), two practitioners (science teacher) and three colleagues. The results of this research is the evaluation's instrument model of CIPP is used to evaluate the implementation of the implementation of the project assessment instruments. The validity result of evaluation instrument have V'Aikens values between 0.86 to 1, which means a valid and 0.836 reliability values into categories so well that it has been worth used as an evaluation instrument.

Evaluation of CASL boiling model for DNB performance in full scale 5x5 fuel bundle with spacer grids

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

Kim, Seung Jun

As one of main tasks for FY17 CASL-THM activity, Evaluation study on applicability of the CASL baseline boiling model for 5x5 DNB application is conducted and the predictive capability of the DNB analysis is reported here. While the baseline CASL-boiling model (GEN- 1A) approach has been successfully implemented and validated with a single pipe application in the previous year’s task, the extended DNB validation for realistic sub-channels with detailed spacer grid configurations are tasked in FY17. The focus area of the current study is to demonstrate the robustness and feasibility of the CASL baseline boiling model for DNB performance inmore » a full 5x5 fuel bundle application. A quantitative evaluation of the DNB predictive capability is performed by comparing with corresponding experimental measurements (i.e. reference for the model validation). The reference data are provided from the Westinghouse Electricity Company (WEC). Two different grid configurations tested here include Non-Mixing Vane Grid (NMVG), and Mixing Vane Grid (MVG). Thorough validation studies with two sub-channel configurations are performed at a wide range of realistic PWR operational conditions.« less

Integrated Medical Model Verification, Validation, and Credibility

NASA Technical Reports Server (NTRS)

Walton, Marlei; Kerstman, Eric; Foy, Millennia; Shah, Ronak; Saile, Lynn; Boley, Lynn; Butler, Doug; Myers, Jerry

2014-01-01

The Integrated Medical Model (IMM) was designed to forecast relative changes for a specified set of crew health and mission success risk metrics by using a probabilistic (stochastic process) model based on historical data, cohort data, and subject matter expert opinion. A probabilistic approach is taken since exact (deterministic) results would not appropriately reflect the uncertainty in the IMM inputs. Once the IMM was conceptualized, a plan was needed to rigorously assess input information, framework and code, and output results of the IMM, and ensure that end user requests and requirements were considered during all stages of model development and implementation. METHODS: In 2008, the IMM team developed a comprehensive verification and validation (VV) plan, which specified internal and external review criteria encompassing 1) verification of data and IMM structure to ensure proper implementation of the IMM, 2) several validation techniques to confirm that the simulation capability of the IMM appropriately represents occurrences and consequences of medical conditions during space missions, and 3) credibility processes to develop user confidence in the information derived from the IMM. When the NASA-STD-7009 (7009) was published, the IMM team updated their verification, validation, and credibility (VVC) project plan to meet 7009 requirements and include 7009 tools in reporting VVC status of the IMM. RESULTS: IMM VVC updates are compiled recurrently and include 7009 Compliance and Credibility matrices, IMM VV Plan status, and a synopsis of any changes or updates to the IMM during the reporting period. Reporting tools have evolved over the lifetime of the IMM project to better communicate VVC status. This has included refining original 7009 methodology with augmentation from the NASA-STD-7009 Guidance Document. End user requests and requirements are being satisfied as evidenced by ISS Program acceptance of IMM risk forecasts, transition to an operational model and simulation tool, and completion of service requests from a broad end user consortium including Operations, Science and Technology Planning, and Exploration Planning. CONCLUSIONS: The VVC approach established by the IMM project of combining the IMM VV Plan with 7009 requirements is comprehensive and includes the involvement of end users at every stage in IMM evolution. Methods and techniques used to quantify the VVC status of the IMM have not only received approval from the local NASA community but have also garnered recognition by other federal agencies seeking to develop similar guidelines in the medical modeling community.

Incorporating High-Frequency Physiologic Data Using Computational Dictionary Learning Improves Prediction of Delayed Cerebral Ischemia Compared to Existing Methods.

PubMed

Megjhani, Murad; Terilli, Kalijah; Frey, Hans-Peter; Velazquez, Angela G; Doyle, Kevin William; Connolly, Edward Sander; Roh, David Jinou; Agarwal, Sachin; Claassen, Jan; Elhadad, Noemie; Park, Soojin

2018-01-01

Accurate prediction of delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) can be critical for planning interventions to prevent poor neurological outcome. This paper presents a model using convolution dictionary learning to extract features from physiological data available from bedside monitors. We develop and validate a prediction model for DCI after SAH, demonstrating improved precision over standard methods alone. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Modified Fisher Scale was considered the standard grading scale in clinical use; baseline features also analyzed included age, sex, Hunt-Hess, and Glasgow Coma Scales. An unsupervised approach using convolution dictionary learning was used to extract features from physiological time series (systolic blood pressure and diastolic blood pressure, heart rate, respiratory rate, and oxygen saturation). Classifiers (partial least squares and linear and kernel support vector machines) were trained on feature subsets of the derivation dataset. Models were applied to the validation dataset. The performances of the best classifiers on the validation dataset are reported by feature subset. Standard grading scale (mFS): AUC 0.54. Combined demographics and grading scales (baseline features): AUC 0.63. Kernel derived physiologic features: AUC 0.66. Combined baseline and physiologic features with redundant feature reduction: AUC 0.71 on derivation dataset and 0.78 on validation dataset. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that we could incorporate individual physiologic data to achieve higher classification accuracy.

Conducting field studies for testing pesticide leaching models

USGS Publications Warehouse

Smith, Charles N.; Parrish, Rudolph S.; Brown, David S.

1990-01-01

A variety of predictive models are being applied to evaluate the transport and transformation of pesticides in the environment. These include well known models such as the Pesticide Root Zone Model (PRZM), the Risk of Unsaturated-Saturated Transport and Transformation Interactions for Chemical Concentrations Model (RUSTIC) and the Groundwater Loading Effects of Agricultural Management Systems Model (GLEAMS). The potentially large impacts of using these models as tools for developing pesticide management strategies and regulatory decisions necessitates development of sound model validation protocols. This paper offers guidance on many of the theoretical and practical problems encountered in the design and implementation of field-scale model validation studies. Recommendations are provided for site selection and characterization, test compound selection, data needs, measurement techniques, statistical design considerations and sampling techniques. A strategy is provided for quantitatively testing models using field measurements.

Ablation and Thermal Response Property Model Validation for Phenolic Impregnated Carbon Ablator

NASA Technical Reports Server (NTRS)

Milos, F. S.; Chen, Y.-K.

2009-01-01

Phenolic Impregnated Carbon Ablator was the heatshield material for the Stardust probe and is also a candidate heatshield material for the Orion Crew Module. As part of the heatshield qualification for Orion, physical and thermal properties were measured for newly manufactured material, included emissivity, heat capacity, thermal conductivity, elemental composition, and thermal decomposition rates. Based on these properties, an ablation and thermal-response model was developed for temperatures up to 3500 K and pressures up to 100 kPa. The model includes orthotropic and pressure-dependent thermal conductivity. In this work, model validation is accomplished by comparison of predictions with data from many arcjet tests conducted over a range of stagnation heat flux and pressure from 107 Watts per square centimeter at 2.3 kPa to 1100 Watts per square centimeter at 84 kPa. Over the entire range of test conditions, model predictions compare well with measured recession, maximum surface temperatures, and in depth temperatures.

Creating wavelet-based models for real-time synthesis of perceptually convincing environmental sounds

NASA Astrophysics Data System (ADS)

Miner, Nadine Elizabeth

1998-09-01

This dissertation presents a new wavelet-based method for synthesizing perceptually convincing, dynamic sounds using parameterized sound models. The sound synthesis method is applicable to a variety of applications including Virtual Reality (VR), multi-media, entertainment, and the World Wide Web (WWW). A unique contribution of this research is the modeling of the stochastic, or non-pitched, sound components. This stochastic-based modeling approach leads to perceptually compelling sound synthesis. Two preliminary studies conducted provide data on multi-sensory interaction and audio-visual synchronization timing. These results contributed to the design of the new sound synthesis method. The method uses a four-phase development process, including analysis, parameterization, synthesis and validation, to create the wavelet-based sound models. A patent is pending for this dynamic sound synthesis method, which provides perceptually-realistic, real-time sound generation. This dissertation also presents a battery of perceptual experiments developed to verify the sound synthesis results. These experiments are applicable for validation of any sound synthesis technique.

Development of a diagnosis- and procedure-based risk model for 30-day outcome after pediatric cardiac surgery.

PubMed

Crowe, Sonya; Brown, Kate L; Pagel, Christina; Muthialu, Nagarajan; Cunningham, David; Gibbs, John; Bull, Catherine; Franklin, Rodney; Utley, Martin; Tsang, Victor T

2013-05-01

The study objective was to develop a risk model incorporating diagnostic information to adjust for case-mix severity during routine monitoring of outcomes for pediatric cardiac surgery. Data from the Central Cardiac Audit Database for all pediatric cardiac surgery procedures performed in the United Kingdom between 2000 and 2010 were included: 70% for model development and 30% for validation. Units of analysis were 30-day episodes after the first surgical procedure. We used logistic regression for 30-day mortality. Risk factors considered included procedural information based on Central Cardiac Audit Database "specific procedures," diagnostic information defined by 24 "primary" cardiac diagnoses and "univentricular" status, and other patient characteristics. Of the 27,140 30-day episodes in the development set, 25,613 were survivals, 834 were deaths, and 693 were of unknown status (mortality, 3.2%). The risk model includes procedure, cardiac diagnosis, univentricular status, age band (neonate, infant, child), continuous age, continuous weight, presence of non-Down syndrome comorbidity, bypass, and year of operation 2007 or later (because of decreasing mortality). A risk score was calculated for 95% of cases in the validation set (weight missing in 5%). The model discriminated well; the C-index for validation set was 0.77 (0.81 for post-2007 data). Removal of all but procedural information gave a reduced C-index of 0.72. The model performed well across the spectrum of predicted risk, but there was evidence of underestimation of mortality risk in neonates undergoing operation from 2007. The risk model performs well. Diagnostic information added useful discriminatory power. A future application is risk adjustment during routine monitoring of outcomes in the United Kingdom to assist quality assurance. Copyright © 2013 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

OC5 Project Phase II: Validation of Global Loads of the DeepCwind Floating Semisubmersible Wind Turbine

DOE PAGES

Robertson, Amy N.; Wendt, Fabian; Jonkman, Jason M.; ...

2017-10-01

This paper summarizes the findings from Phase II of the Offshore Code Comparison, Collaboration, Continued, with Correlation project. The project is run under the International Energy Agency Wind Research Task 30, and is focused on validating the tools used for modeling offshore wind systems through the comparison of simulated responses of select system designs to physical test data. Validation activities such as these lead to improvement of offshore wind modeling tools, which will enable the development of more innovative and cost-effective offshore wind designs. For Phase II of the project, numerical models of the DeepCwind floating semisubmersible wind system weremore » validated using measurement data from a 1/50th-scale validation campaign performed at the Maritime Research Institute Netherlands offshore wave basin. Validation of the models was performed by comparing the calculated ultimate and fatigue loads for eight different wave-only and combined wind/wave test cases against the measured data, after calibration was performed using free-decay, wind-only, and wave-only tests. The results show a decent estimation of both the ultimate and fatigue loads for the simulated results, but with a fairly consistent underestimation in the tower and upwind mooring line loads that can be attributed to an underestimation of wave-excitation forces outside the linear wave-excitation region, and the presence of broadband frequency excitation in the experimental measurements from wind. Participant results showed varied agreement with the experimental measurements based on the modeling approach used. Modeling attributes that enabled better agreement included: the use of a dynamic mooring model; wave stretching, or some other hydrodynamic modeling approach that excites frequencies outside the linear wave region; nonlinear wave kinematics models; and unsteady aerodynamics models. Also, it was observed that a Morison-only hydrodynamic modeling approach could create excessive pitch excitation and resulting tower loads in some frequency bands.« less

OC5 Project Phase II: Validation of Global Loads of the DeepCwind Floating Semisubmersible Wind Turbine

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

Robertson, Amy N.; Wendt, Fabian; Jonkman, Jason M.

This paper summarizes the findings from Phase II of the Offshore Code Comparison, Collaboration, Continued, with Correlation project. The project is run under the International Energy Agency Wind Research Task 30, and is focused on validating the tools used for modeling offshore wind systems through the comparison of simulated responses of select system designs to physical test data. Validation activities such as these lead to improvement of offshore wind modeling tools, which will enable the development of more innovative and cost-effective offshore wind designs. For Phase II of the project, numerical models of the DeepCwind floating semisubmersible wind system weremore » validated using measurement data from a 1/50th-scale validation campaign performed at the Maritime Research Institute Netherlands offshore wave basin. Validation of the models was performed by comparing the calculated ultimate and fatigue loads for eight different wave-only and combined wind/wave test cases against the measured data, after calibration was performed using free-decay, wind-only, and wave-only tests. The results show a decent estimation of both the ultimate and fatigue loads for the simulated results, but with a fairly consistent underestimation in the tower and upwind mooring line loads that can be attributed to an underestimation of wave-excitation forces outside the linear wave-excitation region, and the presence of broadband frequency excitation in the experimental measurements from wind. Participant results showed varied agreement with the experimental measurements based on the modeling approach used. Modeling attributes that enabled better agreement included: the use of a dynamic mooring model; wave stretching, or some other hydrodynamic modeling approach that excites frequencies outside the linear wave region; nonlinear wave kinematics models; and unsteady aerodynamics models. Also, it was observed that a Morison-only hydrodynamic modeling approach could create excessive pitch excitation and resulting tower loads in some frequency bands.« less

Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

PubMed

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

2017-05-01

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

Comparison and validation of point spread models for imaging in natural waters.

PubMed

Hou, Weilin; Gray, Deric J; Weidemann, Alan D; Arnone, Robert A

2008-06-23

It is known that scattering by particulates within natural waters is the main cause of the blur in underwater images. Underwater images can be better restored or enhanced with knowledge of the point spread function (PSF) of the water. This will extend the performance range as well as the information retrieval from underwater electro-optical systems, which is critical in many civilian and military applications, including target and especially mine detection, search and rescue, and diver visibility. A better understanding of the physical process involved also helps to predict system performance and simulate it accurately on demand. The presented effort first reviews several PSF models, including the introduction of a semi-analytical PSF given optical properties of the medium, including scattering albedo, mean scattering angles and the optical range. The models under comparison include the empirical model of Duntley, a modified PSF model by Dolin et al, as well as the numerical integration of analytical forms from Wells, as a benchmark of theoretical results. For experimental results, in addition to that of Duntley, we validate the above models with measured point spread functions by applying field measured scattering properties with Monte Carlo simulations. Results from these comparisons suggest it is sufficient but necessary to have the three parameters listed above to model PSFs. The simplified approach introduced also provides adequate accuracy and flexibility for imaging applications, as shown by examples of restored underwater images.

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

NASA Technical Reports Server (NTRS)

Srikishen, Jayanthi; Case, Jonathan L.; Petersen, Walter A.; Iguchi, Takamichi; Tao, Wei-Kuo; Zavodsky, Bradley T.; Molthan, Andrew

2017-01-01

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment -PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates.

PubMed

Focks, Andreas; Belgers, Dick; Boerwinkel, Marie-Claire; Buijse, Laura; Roessink, Ivo; Van den Brink, Paul J

2018-05-01

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

The OncoSim model: development and use for better decision-making in Canadian cancer control.

PubMed

Gauvreau, C L; Fitzgerald, N R; Memon, S; Flanagan, W M; Nadeau, C; Asakawa, K; Garner, R; Miller, A B; Evans, W K; Popadiuk, C M; Wolfson, M; Coldman, A J

2017-12-01

The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada. Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided. OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers. Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

Convergent, discriminant, and criterion validity of DSM-5 traits.

PubMed

Yalch, Matthew M; Hopwood, Christopher J

2016-10-01

Section III of the Diagnostic and Statistical Manual of Mental Disorders (5th edi.; DSM-5; American Psychiatric Association, 2013) contains a system for diagnosing personality disorder based in part on assessing 25 maladaptive traits. Initial research suggests that this aspect of the system improves the validity and clinical utility of the Section II Model. The Computer Adaptive Test of Personality Disorder (CAT-PD; Simms et al., 2011) contains many similar traits as the DSM-5, as well as several additional traits seemingly not covered in the DSM-5. In this study we evaluate the convergent and discriminant validity between the DSM-5 traits, as assessed by the Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012), and CAT-PD in an undergraduate sample, and test whether traits included in the CAT-PD but not the DSM-5 provide incremental validity in association with clinically relevant criterion variables. Results supported the convergent and discriminant validity of the PID-5 and CAT-PD scales in their assessment of 23 out of 25 DSM-5 traits. DSM-5 traits were consistently associated with 11 criterion variables, despite our having intentionally selected clinically relevant criterion constructs not directly assessed by DSM-5 traits. However, the additional CAT-PD traits provided incremental information above and beyond the DSM-5 traits for all criterion variables examined. These findings support the validity of pathological trait models in general and the DSM-5 and CAT-PD models in particular, while also suggesting that the CAT-PD may include additional traits for consideration in future iterations of the DSM-5 system. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

Examining the Relations Among the DSM-5 Alternative Model of Personality, the Five-Factor Model, and Externalizing and Internalizing Behavior.

PubMed

Sleep, Chelsea E; Hyatt, Courtland S; Lamkin, Joanna; Maples-Keller, Jessica L; Miller, Joshua D

2017-01-26

Given long-standing criticisms of the DSM's reliance on categorical models of psychopathology, including the poor reliability and validity of personality-disorder diagnoses, the American Psychiatric Association (APA) published an alternative model (AM) of personality disorders in Section III of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; APA, 2013), which, in part, comprises 5 pathological trait domains based on the 5-factor model (FFM). However, the empirical profiles and discriminant validity of the AM traits remain in question. We recruited a sample of undergraduates (N = 340) for the current study to compare the relations found between a measure of the DSM-5 AM traits (i.e., the Personality Inventory for DSM-5; PID-5; Krueger, Derringer, Markon, Watson, & Skodol, 2012) and a measure of the FFM (i.e., the International Personality Item Pool; IPIP; Goldberg, 1999) in relation to externalizing and internalizing symptoms. In general, the domains from the 2 measures were significantly related and demonstrated similar patterns of relations with these criteria, such that Antagonism/low Agreeableness and Disinhibition/low Conscientiousness were related to externalizing behaviors, whereas Negative Affectivity/Neuroticism was most significantly related to internalizing symptoms. However, the PID-5 demonstrated large interrelations among its domains and poorer discriminant validity than the IPIP. These results provide additional support that the conception of the trait model included in the DSM-5 AM is an extension of the FFM, but highlight some of the issues that arise due to the PID-5's more limited discriminant validity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Continuum Modeling of Inductor Hysteresis and Eddy Current Loss Effects in Resonant Circuits

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

Pries, Jason L.; Tang, Lixin; Burress, Timothy A.

This paper presents experimental validation of a high-fidelity toroid inductor modeling technique. The aim of this research is to accurately model the instantaneous magnetization state and core losses in ferromagnetic materials. Quasi–static hysteresis effects are captured using a Preisach model. Eddy currents are included by coupling the associated quasi-static Everett function to a simple finite element model representing the inductor cross sectional area. The modeling technique is validated against the nonlinear frequency response from two different series RLC resonant circuits using inductors made of electrical steel and soft ferrite. The method is shown to accurately model shifts in resonant frequencymore » and quality factor. The technique also successfully predicts a discontinuity in the frequency response of the ferrite inductor resonant circuit.« less

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning

PubMed Central

Halpern, Yoni; Jernite, Yacine; Shapiro, Nathan I.; Nathanson, Larry A.

2017-01-01

Objective To demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department. Methods This was a retrospective, observational cohort study performed at a tertiary academic teaching hospital. All consecutive ED patient visits between 12/17/08 and 2/17/13 were included. No patients were excluded. The primary outcome measure was infection diagnosed in the emergency department defined as a patient having an infection related ED ICD-9-CM discharge diagnosis. Patients were randomly allocated to train (64%), validate (20%), and test (16%) data sets. After preprocessing the free text using bigram and negation detection, we built four models to predict infection, incrementally adding vital signs, chief complaint, and free text nursing assessment. We used two different methods to represent free text: a bag of words model and a topic model. We then used a support vector machine to build the prediction model. We calculated the area under the receiver operating characteristic curve to compare the discriminatory power of each model. Results A total of 230,936 patient visits were included in the study. Approximately 14% of patients had the primary outcome of diagnosed infection. The area under the ROC curve (AUC) for the vitals model, which used only vital signs and demographic data, was 0.67 for the training data set, 0.67 for the validation data set, and 0.67 (95% CI 0.65–0.69) for the test data set. The AUC for the chief complaint model which also included demographic and vital sign data was 0.84 for the training data set, 0.83 for the validation data set, and 0.83 (95% CI 0.81–0.84) for the test data set. The best performing methods made use of all of the free text. In particular, the AUC for the bag-of-words model was 0.89 for training data set, 0.86 for the validation data set, and 0.86 (95% CI 0.85–0.87) for the test data set. The AUC for the topic model was 0.86 for the training data set, 0.86 for the validation data set, and 0.85 (95% CI 0.84–0.86) for the test data set. Conclusion Compared to previous work that only used structured data such as vital signs and demographic information, utilizing free text drastically improves the discriminatory ability (increase in AUC from 0.67 to 0.86) of identifying infection. PMID:28384212

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning.

PubMed

Horng, Steven; Sontag, David A; Halpern, Yoni; Jernite, Yacine; Shapiro, Nathan I; Nathanson, Larry A

2017-01-01

To demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department. This was a retrospective, observational cohort study performed at a tertiary academic teaching hospital. All consecutive ED patient visits between 12/17/08 and 2/17/13 were included. No patients were excluded. The primary outcome measure was infection diagnosed in the emergency department defined as a patient having an infection related ED ICD-9-CM discharge diagnosis. Patients were randomly allocated to train (64%), validate (20%), and test (16%) data sets. After preprocessing the free text using bigram and negation detection, we built four models to predict infection, incrementally adding vital signs, chief complaint, and free text nursing assessment. We used two different methods to represent free text: a bag of words model and a topic model. We then used a support vector machine to build the prediction model. We calculated the area under the receiver operating characteristic curve to compare the discriminatory power of each model. A total of 230,936 patient visits were included in the study. Approximately 14% of patients had the primary outcome of diagnosed infection. The area under the ROC curve (AUC) for the vitals model, which used only vital signs and demographic data, was 0.67 for the training data set, 0.67 for the validation data set, and 0.67 (95% CI 0.65-0.69) for the test data set. The AUC for the chief complaint model which also included demographic and vital sign data was 0.84 for the training data set, 0.83 for the validation data set, and 0.83 (95% CI 0.81-0.84) for the test data set. The best performing methods made use of all of the free text. In particular, the AUC for the bag-of-words model was 0.89 for training data set, 0.86 for the validation data set, and 0.86 (95% CI 0.85-0.87) for the test data set. The AUC for the topic model was 0.86 for the training data set, 0.86 for the validation data set, and 0.85 (95% CI 0.84-0.86) for the test data set. Compared to previous work that only used structured data such as vital signs and demographic information, utilizing free text drastically improves the discriminatory ability (increase in AUC from 0.67 to 0.86) of identifying infection.

Introducing the Postsecondary Instructional Practices Survey (PIPS): A Concise, Interdisciplinary, and Easy-to-Score Survey

PubMed Central

Walter, Emily M.; Henderson, Charles R.; Beach, Andrea L.; Williams, Cody T.

2016-01-01

Researchers, administrators, and policy makers need valid and reliable information about teaching practices. The Postsecondary Instructional Practices Survey (PIPS) is designed to measure the instructional practices of postsecondary instructors from any discipline. The PIPS has 24 instructional practice statements and nine demographic questions. Users calculate PIPS scores by an intuitive proportion-based scoring convention. Factor analyses from 72 departments at four institutions (N = 891) support a 2- or 5-factor solution for the PIPS; both models include all 24 instructional practice items and have good model fit statistics. Factors in the 2-factor model include (a) instructor-centered practices, nine items; and (b) student-centered practices, 13 items. Factors in the 5-factor model include (a) student–student interactions, six items; (b) content delivery, four items; (c) formative assessment, five items; (d) student-content engagement, five items; and (e) summative assessment, four items. In this article, we describe our development and validation processes, provide scoring conventions and outputs for results, and describe wider applications of the instrument. PMID:27810868

Towards a Consolidated Approach for the Assessment of Evaluation Models of Nuclear Power Reactors

DOE PAGES

Epiney, A.; Canepa, S.; Zerkak, O.; ...

2016-11-02

The STARS project at the Paul Scherrer Institut (PSI) has adopted the TRACE thermal-hydraulic (T-H) code for best-estimate system transient simulations of the Swiss Light Water Reactors (LWRs). For analyses involving interactions between system and core, a coupling of TRACE with the SIMULATE-3K (S3K) LWR core simulator has also been developed. In this configuration, the TRACE code and associated nuclear power reactor simulation models play a central role to achieve a comprehensive safety analysis capability. Thus, efforts have now been undertaken to consolidate the validation strategy by implementing a more rigorous and structured assessment approach for TRACE applications involving eithermore » only system T-H evaluations or requiring interfaces to e.g. detailed core or fuel behavior models. The first part of this paper presents the preliminary concepts of this validation strategy. The principle is to systematically track the evolution of a given set of predicted physical Quantities of Interest (QoIs) over a multidimensional parametric space where each of the dimensions represent the evolution of specific analysis aspects, including e.g. code version, transient specific simulation methodology and model "nodalisation". If properly set up, such environment should provide code developers and code users with persistent (less affected by user effect) and quantified information (sensitivity of QoIs) on the applicability of a simulation scheme (codes, input models, methodology) for steady state and transient analysis of full LWR systems. Through this, for each given transient/accident, critical paths of the validation process can be identified that could then translate into defining reference schemes to be applied for downstream predictive simulations. In order to illustrate this approach, the second part of this paper presents a first application of this validation strategy to an inadvertent blowdown event that occurred in a Swiss BWR/6. The transient was initiated by the spurious actuation of the Automatic Depressurization System (ADS). The validation approach progresses through a number of dimensions here: First, the same BWR system simulation model is assessed for different versions of the TRACE code, up to the most recent one. The second dimension is the "nodalisation" dimension, where changes to the input model are assessed. The third dimension is the "methodology" dimension. In this case imposed power and an updated TRACE core model are investigated. For each step in each validation dimension, a common set of QoIs are investigated. For the steady-state results, these include fuel temperatures distributions. For the transient part of the present study, the evaluated QoIs include the system pressure evolution and water carry-over into the steam line.« less

LIVVkit 2: An extensible land ice verification and validation toolkit for comparing observations and models?

NASA Astrophysics Data System (ADS)

Kennedy, J. H.; Bennett, A. R.; Evans, K. J.; Fyke, J. G.; Vargo, L.; Price, S. F.; Hoffman, M. J.

2016-12-01

Accurate representation of ice sheets and glaciers are essential for robust predictions of arctic climate within Earth System models. Verification and Validation (V&V) is a set of techniques used to quantify the correctness and accuracy of a model, which builds developer/modeler confidence, and can be used to enhance the credibility of the model. Fundamentally, V&V is a continuous process because each model change requires a new round of V&V testing. The Community Ice Sheet Model (CISM) development community is actively developing LIVVkit, the Land Ice Verification and Validation toolkit, which is designed to easily integrate into an ice-sheet model's development workflow (on both personal and high-performance computers) to provide continuous V&V testing.LIVVkit is a robust and extensible python package for V&V, which has components for both software V&V (construction and use) and model V&V (mathematics and physics). The model Verification component is used, for example, to verify model results against community intercomparisons such as ISMIP-HOM. The model validation component is used, for example, to generate a series of diagnostic plots showing the differences between model results against observations for variables such as thickness, surface elevation, basal topography, surface velocity, surface mass balance, etc. Because many different ice-sheet models are under active development, new validation datasets are becoming available, and new methods of analysing these models are actively being researched, LIVVkit includes a framework to easily extend the model V&V analyses by ice-sheet modelers. This allows modelers and developers to develop evaluations of parameters, implement changes, and quickly see how those changes effect the ice-sheet model and earth system model (when coupled). Furthermore, LIVVkit outputs a portable hierarchical website allowing evaluations to be easily shared, published, and analysed throughout the arctic and Earth system communities.

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Fine-particle water and pH in the southeastern United States

EPA Science Inventory

Particle water and pH are predicted using meteorological observations (relative humidity (RH), temperature (T)), gas/particle composition, and thermodynamic modeling (ISORROPIA-II). A comprehensive uncertainty analysis is included, and the model is validated. We investigate mass ...

Knowledge about dietary fibres (KADF): development and validation of an evaluation instrument through structural equation modelling (SEM).

PubMed

Guiné, R P F; Duarte, J; Ferreira, M; Correia, P; Leal, M; Rumbak, I; Barić, I C; Komes, D; Satalić, Z; Sarić, M M; Tarcea, M; Fazakas, Z; Jovanoska, D; Vanevski, D; Vittadini, E; Pellegrini, N; Szűcs, V; Harangozó, J; El-Kenawy, A; El-Shenawy, O; Yalçın, E; Kösemeci, C; Klava, D; Straumite, E

2016-09-01

Because there is scientific evidence that an appropriate intake of dietary fibre should be part of a healthy diet, given its importance in promoting health, the present study aimed to develop and validate an instrument to evaluate the knowledge of the general population about dietary fibres. The present study was a cross sectional study. The methodological study of psychometric validation was conducted with 6010 participants, residing in 10 countries from three continents. The instrument is a questionnaire of self-response, aimed at collecting information on knowledge about food fibres. Exploratory factor analysis (EFA) was chosen as the analysis of the main components using varimax orthogonal rotation and eigenvalues greater than 1. In confirmatory factor analysis by structural equation modelling (SEM) was considered the covariance matrix and adopted the maximum likelihood estimation algorithm for parameter estimation. Exploratory factor analysis retained two factors. The first was called dietary fibre and promotion of health (DFPH) and included seven questions that explained 33.94% of total variance (α = 0.852). The second was named sources of dietary fibre (SDF) and included four questions that explained 22.46% of total variance (α = 0.786). The model was tested by SEM giving a final solution with four questions in each factor. This model showed a very good fit in practically all the indexes considered, except for the ratio χ(2)/df. The values of average variance extracted (0.458 and 0.483) demonstrate the existence of convergent validity; the results also prove the existence of discriminant validity of the factors (r(2) = 0.028) and finally good internal consistency was confirmed by the values of composite reliability (0.854 and 0.787). This study allowed validating the KADF scale, increasing the degree of confidence in the information obtained through this instrument in this and in future studies. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

NASA Technical Reports Server (NTRS)

Lim, Kyong B.

2003-01-01

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.

Validity test and its consistency in the construction of patient loyalty model

NASA Astrophysics Data System (ADS)

Yanuar, Ferra

2016-04-01

The main objective of this present study is to demonstrate the estimation of validity values and its consistency based on structural equation model. The method of estimation was then implemented to an empirical data in case of the construction the patient loyalty model. In the hypothesis model, service quality, patient satisfaction and patient loyalty were determined simultaneously, each factor were measured by any indicator variables. The respondents involved in this study were the patients who ever got healthcare at Puskesmas in Padang, West Sumatera. All 394 respondents who had complete information were included in the analysis. This study found that each construct; service quality, patient satisfaction and patient loyalty were valid. It means that all hypothesized indicator variables were significant to measure their corresponding latent variable. Service quality is the most measured by tangible, patient satisfaction is the most mesured by satisfied on service and patient loyalty is the most measured by good service quality. Meanwhile in structural equation, this study found that patient loyalty was affected by patient satisfaction positively and directly. Service quality affected patient loyalty indirectly with patient satisfaction as mediator variable between both latent variables. Both structural equations were also valid. This study also proved that validity values which obtained here were also consistence based on simulation study using bootstrap approach.

UTCI-Fiala multi-node model of human heat transfer and temperature regulation

NASA Astrophysics Data System (ADS)

Fiala, Dusan; Havenith, George; Bröde, Peter; Kampmann, Bernhard; Jendritzky, Gerd

2012-05-01

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

A multi-site cognitive task analysis for biomedical query mediation.

PubMed

Hruby, Gregory W; Rasmussen, Luke V; Hanauer, David; Patel, Vimla L; Cimino, James J; Weng, Chunhua

2016-09-01

To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: "Identify potential index phenotype," "If needed, request EHR database access rights," and "Perform query and present output to medical researcher", and 8 are invalid. We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Multi-Site Cognitive Task Analysis for Biomedical Query Mediation

PubMed Central

Hruby, Gregory W.; Rasmussen, Luke V.; Hanauer, David; Patel, Vimla; Cimino, James J.; Weng, Chunhua

2016-01-01

Objective To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. Materials and Methods We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. Results The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: “Identify potential index phenotype,” “If needed, request EHR database access rights,” and “Perform query and present output to medical researcher”, and 8 are invalid. Discussion We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. Conclusions We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. PMID:27435950

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

PubMed Central

Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

2016-01-01

Motivation Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. Results In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models. PMID:26812499

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism.

PubMed

Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

2016-01-01

Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models.

WE-H-BRA-03: Development of a Model to Include the Evolution of Resistant Tumor Subpopulations Into the Treatment Optimization Process for Schedules Involving Targeted Agents in Chemoradiation Therapy

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

Grassberger, C; Paganetti, H

Purpose: To develop a model that includes the process of resistance development into the treatment optimization process for schedules that include targeted therapies. Further, to validate the approach using clinical data and to apply the model to assess the optimal induction period with targeted agents before curative treatment with chemo-radiation in stage III lung cancer. Methods: Growth of the tumor and its subpopulations is modeled by Gompertzian growth dynamics, resistance induction as a stochastic process. Chemotherapy induced cell kill is modeled by log-cell kill dynamics, targeted agents similarly but restricted to the sensitive population. Radiation induced cell kill is assumedmore » to follow the linear-quadratic model. The validation patient data consist of a cohort of lung cancer patients treated with tyrosine kinase inhibitors that had longitudinal imaging data available. Results: The resistance induction model was successfully validated using clinical trial data from 49 patients treated with targeted agents. The observed recurrence kinetics, with tumors progressing from 1.4–63 months, result in tumor growth equaling a median volume doubling time of 92 days [34–248] and a median fraction of pre-existing resistance of 0.035 [0–0.22], in agreement with previous clinical studies. The model revealed widely varying optimal time points for the use of curative therapy, reaching from ∼1m to >6m depending on the patient’s growth rate and amount of pre-existing resistance. This demonstrates the importance of patient-specific treatment schedules when targeted agents are incorporated into the treatment. Conclusion: We developed a model including evolutionary dynamics of resistant sub-populations with traditional chemotherapy and radiation cell kill models. Fitting to clinical data yielded patient specific growth rates and resistant fraction in agreement with previous studies. Further application of the model demonstrated how proper timing of chemo-radiation could minimize the probability of resistance, increasing tumor control significantly.« less

Analysis, testing, and evaluation of faulted and unfaulted Wye, Delta, and open Delta connected electromechanical actuators

NASA Technical Reports Server (NTRS)

Nehl, T. W.; Demerdash, N. A.

1983-01-01

Mathematical models capable of simulating the transient, steady state, and faulted performance characteristics of various brushless dc machine-PSA (power switching assembly) configurations were developed. These systems are intended for possible future use as primemovers in EMAs (electromechanical actuators) for flight control applications. These machine-PSA configurations include wye, delta, and open-delta connected systems. The research performed under this contract was initially broken down into the following six tasks: development of mathematical models for various machine-PSA configurations; experimental validation of the model for failure modes; experimental validation of the mathematical model for shorted turn-failure modes; tradeoff study; and documentation of results and methodology.

Preoperative Prediction of Node-Negative Disease After Neoadjuvant Chemotherapy in Patients Presenting with Node-Negative or Node-Positive Breast Cancer.

PubMed

Murphy, Brittany L; L Hoskin, Tanya; Heins, Courtney Day N; Habermann, Elizabeth B; Boughey, Judy C

2017-09-01

Axillary node status after neoadjuvant chemotherapy (NAC) influences the axillary surgical staging procedure as well as recommendations regarding reconstruction and radiation. Our aim was to construct a clinical preoperative prediction model to identify the likelihood of patients being node negative after NAC. Using the National Cancer Database (NCDB) from January 2010 to December 2012, we identified cT1-T4c, N0-N3 breast cancer patients treated with NAC. The effects of patient and tumor factors on pathologic node status were assessed by multivariable logistic regression separately for clinically node negative (cN0) and clinically node positive (cN+) disease, and two models were constructed. Model performance was validated in a cohort of NAC patients treated at our institution (January 2013-July 2016), and model discrimination was assessed by estimating the area under the curve (AUC). Of 16,153 NCDB patients, 6659 (41%) were cN0 and 9494 (59%) were cN+. Factors associated with pathologic nodal status and included in the models were patient age, tumor grade, biologic subtype, histology, clinical tumor category, and, in cN+ patients only, clinical nodal category. The validation dataset included 194 cN0 and 180 cN+ patients. The cN0 model demonstrated good discrimination, with an AUC of 0.73 (95% confidence interval [CI] 0.72-0.74) in the NCDB and 0.77 (95% CI 0.68-0.85) in the external validation, while the cN+ patient model AUC was 0.71 (95% CI 0.70-0.72) in the NCDB and 0.74 (95% CI 0.67-0.82) in the external validation. We constructed two models that showed good discrimination for predicting ypN0 status following NAC in cN0 and cN+ patients. These clinically useful models can guide surgical planning after NAC.

Validity of segmental bioelectrical impedance analysis for estimating fat-free mass in children including overweight individuals.

PubMed

Ohta, Megumi; Midorikawa, Taishi; Hikihara, Yuki; Masuo, Yoshihisa; Sakamoto, Shizuo; Torii, Suguru; Kawakami, Yasuo; Fukunaga, Tetsuo; Kanehisa, Hiroaki

2017-02-01

This study examined the validity of segmental bioelectrical impedance (BI) analysis for predicting the fat-free masses (FFMs) of whole-body and body segments in children including overweight individuals. The FFM and impedance (Z) values of arms, trunk, legs, and whole body were determined using a dual-energy X-ray absorptiometry and segmental BI analyses, respectively, in 149 boys and girls aged 6 to 12 years, who were divided into model-development (n = 74), cross-validation (n = 35), and overweight (n = 40) groups. Simple regression analysis was applied to (length) 2 /Z (BI index) for each of the whole-body and 3 segments to develop the prediction equations of the measured FFM of the related body part. In the model-development group, the BI index of each of the 3 segments and whole body was significantly correlated to the measured FFM (R 2 = 0.867-0.932, standard error of estimation = 0.18-1.44 kg (5.9%-8.7%)). There was no significant difference between the measured and predicted FFM values without systematic error. The application of each equation derived in the model-development group to the cross-validation and overweight groups did not produce significant differences between the measured and predicted FFM values and systematic errors, with an exception that the arm FFM in the overweight group was overestimated. Segmental bioelectrical impedance analysis is useful for predicting the FFM of each of whole-body and body segments in children including overweight individuals, although the application for estimating arm FFM in overweight individuals requires a certain modification.

Model improvements and validation of TerraSAR-X precise orbit determination

NASA Astrophysics Data System (ADS)

Hackel, S.; Montenbruck, O.; Steigenberger, P.; Balss, U.; Gisinger, C.; Eineder, M.

2017-05-01

The radar imaging satellite mission TerraSAR-X requires precisely determined satellite orbits for validating geodetic remote sensing techniques. Since the achieved quality of the operationally derived, reduced-dynamic (RD) orbit solutions limits the capabilities of the synthetic aperture radar (SAR) validation, an effort is made to improve the estimated orbit solutions. This paper discusses the benefits of refined dynamical models on orbit accuracy as well as estimated empirical accelerations and compares different dynamic models in a RD orbit determination. Modeling aspects discussed in the paper include the use of a macro-model for drag and radiation pressure computation, the use of high-quality atmospheric density and wind models as well as the benefit of high-fidelity gravity and ocean tide models. The Sun-synchronous dusk-dawn orbit geometry of TerraSAR-X results in a particular high correlation of solar radiation pressure modeling and estimated normal-direction positions. Furthermore, this mission offers a unique suite of independent sensors for orbit validation. Several parameters serve as quality indicators for the estimated satellite orbit solutions. These include the magnitude of the estimated empirical accelerations, satellite laser ranging (SLR) residuals, and SLR-based orbit corrections. Moreover, the radargrammetric distance measurements of the SAR instrument are selected for assessing the quality of the orbit solutions and compared to the SLR analysis. The use of high-fidelity satellite dynamics models in the RD approach is shown to clearly improve the orbit quality compared to simplified models and loosely constrained empirical accelerations. The estimated empirical accelerations are substantially reduced by 30% in tangential direction when working with the refined dynamical models. Likewise the SLR residuals are reduced from -3 ± 17 to 2 ± 13 mm, and the SLR-derived normal-direction position corrections are reduced from 15 to 6 mm, obtained from the 2012-2014 period. The radar range bias is reduced from -10.3 to -6.1 mm with the updated orbit solutions, which coincides with the reduced standard deviation of the SLR residuals. The improvements are mainly driven by the satellite macro-model for the purpose of solar radiation pressure modeling, improved atmospheric density models, and the use of state-of-the-art gravity field models.

MRI-based modeling for radiocarpal joint mechanics: validation criteria and results for four specimen-specific models.

PubMed

Fischer, Kenneth J; Johnson, Joshua E; Waller, Alexander J; McIff, Terence E; Toby, E Bruce; Bilgen, Mehmet

2011-10-01

The objective of this study was to validate the MRI-based joint contact modeling methodology in the radiocarpal joints by comparison of model results with invasive specimen-specific radiocarpal contact measurements from four cadaver experiments. We used a single validation criterion for multiple outcome measures to characterize the utility and overall validity of the modeling approach. For each experiment, a Pressurex film and a Tekscan sensor were sequentially placed into the radiocarpal joints during simulated grasp. Computer models were constructed based on MRI visualization of the cadaver specimens without load. Images were also acquired during the loaded configuration used with the direct experimental measurements. Geometric surface models of the radius, scaphoid and lunate (including cartilage) were constructed from the images acquired without the load. The carpal bone motions from the unloaded state to the loaded state were determined using a series of 3D image registrations. Cartilage thickness was assumed uniform at 1.0 mm with an effective compressive modulus of 4 MPa. Validation was based on experimental versus model contact area, contact force, average contact pressure and peak contact pressure for the radioscaphoid and radiolunate articulations. Contact area was also measured directly from images acquired under load and compared to the experimental and model data. Qualitatively, there was good correspondence between the MRI-based model data and experimental data, with consistent relative size, shape and location of radioscaphoid and radiolunate contact regions. Quantitative data from the model generally compared well with the experimental data for all specimens. Contact area from the MRI-based model was very similar to the contact area measured directly from the images. For all outcome measures except average and peak pressures, at least two specimen models met the validation criteria with respect to experimental measurements for both articulations. Only the model for one specimen met the validation criteria for average and peak pressure of both articulations; however the experimental measures for peak pressure also exhibited high variability. MRI-based modeling can reliably be used for evaluating the contact area and contact force with similar confidence as in currently available experimental techniques. Average contact pressure, and peak contact pressure were more variable from all measurement techniques, and these measures from MRI-based modeling should be used with some caution.

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

Validation Testing of a Peridynamic Impact Damage Model Using NASA's Micro-Particle Gun

NASA Technical Reports Server (NTRS)

Baber, Forrest E.; Zelinski, Brian J.; Guven, Ibrahim; Gray, Perry

2017-01-01

Through a collaborative effort between the Virginia Commonwealth University and Raytheon, a peridynamic model for sand impact damage has been developed1-3. Model development has focused on simulating impacts of sand particles on ZnS traveling at velocities consistent with aircraft take-off and landing speeds. The model reproduces common features of impact damage including pit and radial cracks, and, under some conditions, lateral cracks. This study focuses on a preliminary validation exercise in which simulation results from the peridynamic model are compared to a limited experimental data set generated by NASA's recently developed micro-particle gun (MPG). The MPG facility measures the dimensions and incoming and rebound velocities of the impact particles. It also links each particle to a specific impact site and its associated damage. In this validation exercise parameters of the peridynamic model are adjusted to fit the experimentally observed pit diameter, average length of radial cracks and rebound velocities for 4 impacts of 300 µm glass beads on ZnS. Results indicate that a reasonable fit of these impact characteristics can be obtained by suitable adjustment of the peridynamic input parameters, demonstrating that the MPG can be used effectively as a validation tool for impact modeling and that the peridynamic sand impact model described herein possesses not only a qualitative but also a quantitative ability to simulate sand impact events.

Acute Kidney Injury Risk Prediction in Patients Undergoing Coronary Angiography in a National Veterans Health Administration Cohort With External Validation.

PubMed

Brown, Jeremiah R; MacKenzie, Todd A; Maddox, Thomas M; Fly, James; Tsai, Thomas T; Plomondon, Mary E; Nielson, Christopher D; Siew, Edward D; Resnic, Frederic S; Baker, Clifton R; Rumsfeld, John S; Matheny, Michael E

2015-12-11

Acute kidney injury (AKI) occurs frequently after cardiac catheterization and percutaneous coronary intervention. Although a clinical risk model exists for percutaneous coronary intervention, no models exist for both procedures, nor do existing models account for risk factors prior to the index admission. We aimed to develop such a model for use in prospective automated surveillance programs in the Veterans Health Administration. We collected data on all patients undergoing cardiac catheterization or percutaneous coronary intervention in the Veterans Health Administration from January 01, 2009 to September 30, 2013, excluding patients with chronic dialysis, end-stage renal disease, renal transplant, and missing pre- and postprocedural creatinine measurement. We used 4 AKI definitions in model development and included risk factors from up to 1 year prior to the procedure and at presentation. We developed our prediction models for postprocedural AKI using the least absolute shrinkage and selection operator (LASSO) and internally validated using bootstrapping. We developed models using 115 633 angiogram procedures and externally validated using 27 905 procedures from a New England cohort. Models had cross-validated C-statistics of 0.74 (95% CI: 0.74-0.75) for AKI, 0.83 (95% CI: 0.82-0.84) for AKIN2, 0.74 (95% CI: 0.74-0.75) for contrast-induced nephropathy, and 0.89 (95% CI: 0.87-0.90) for dialysis. We developed a robust, externally validated clinical prediction model for AKI following cardiac catheterization or percutaneous coronary intervention to automatically identify high-risk patients before and immediately after a procedure in the Veterans Health Administration. Work is ongoing to incorporate these models into routine clinical practice. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Classification and regression tree analysis of acute-on-chronic hepatitis B liver failure: Seeing the forest for the trees.

PubMed

Shi, K-Q; Zhou, Y-Y; Yan, H-D; Li, H; Wu, F-L; Xie, Y-Y; Braddock, M; Lin, X-Y; Zheng, M-H

2017-02-01

At present, there is no ideal model for predicting the short-term outcome of patients with acute-on-chronic hepatitis B liver failure (ACHBLF). This study aimed to establish and validate a prognostic model by using the classification and regression tree (CART) analysis. A total of 1047 patients from two separate medical centres with suspected ACHBLF were screened in the study, which were recognized as derivation cohort and validation cohort, respectively. CART analysis was applied to predict the 3-month mortality of patients with ACHBLF. The accuracy of the CART model was tested using the area under the receiver operating characteristic curve, which was compared with the model for end-stage liver disease (MELD) score and a new logistic regression model. CART analysis identified four variables as prognostic factors of ACHBLF: total bilirubin, age, serum sodium and INR, and three distinct risk groups: low risk (4.2%), intermediate risk (30.2%-53.2%) and high risk (81.4%-96.9%). The new logistic regression model was constructed with four independent factors, including age, total bilirubin, serum sodium and prothrombin activity by multivariate logistic regression analysis. The performances of the CART model (0.896), similar to the logistic regression model (0.914, P=.382), exceeded that of MELD score (0.667, P<.001). The results were confirmed in the validation cohort. We have developed and validated a novel CART model superior to MELD for predicting three-month mortality of patients with ACHBLF. Thus, the CART model could facilitate medical decision-making and provide clinicians with a validated practical bedside tool for ACHBLF risk stratification. © 2016 John Wiley & Sons Ltd.

Combined expectancies: electrophysiological evidence for the adjustment of expectancy effects

PubMed Central

Mattler, Uwe; van der Lugt, Arie; Münte, Thomas F

2006-01-01

Background When subjects use cues to prepare for a likely stimulus or a likely response, reaction times are facilitated by valid cues but prolonged by invalid cues. In studies on combined expectancy effects, two cues can independently give information regarding two dimensions of the forthcoming task. In certain situations, cueing effects on one dimension are reduced when the cue on the other dimension is invalid. According to the Adjusted Expectancy Model, cues affect different processing levels and a mechanism is presumed which is sensitive to the validity of early level cues and leads to online adjustment of expectancy effects at later levels. To examine the predictions of this model cueing of stimulus modality was combined with response cueing. Results Behavioral measures showed the interaction of cueing effects. Electrophysiological measures of the lateralized readiness potential (LRP) and the N200 amplitude confirmed the predictions of the model. The LRP showed larger effects of response cues on response activation when modality cues were valid rather than invalid. N200 amplitude was largest with valid modality cues and invalid response cues, medium with invalid modality cues, and smallest with two valid cues. Conclusion Findings support the view that the validity of early level expectancies modulates the effects of late level expectancies, which included response activation and response conflict in the present study. PMID:16674805

Validation of a predictive model for identifying febrile young infants with altered urinalysis at low risk of invasive bacterial infection.

PubMed

Velasco, R; Gómez, B; Hernández-Bou, S; Olaciregui, I; de la Torre, M; González, A; Rivas, A; Durán, I; Rubio, A

2017-02-01

In 2015, a predictive model for invasive bacterial infection (IBI) in febrile young infants with altered urine dipstick was published. The aim of this study was to externally validate a previously published set of low risk criteria for invasive bacterial infection in febrile young infants with altered urine dipstick. Retrospective multicenter study including nine Spanish hospitals. Febrile infants ≤90 days old with altered urinalysis (presence of leukocyturia and/or nitrituria) were included. According to our predictive model, an infant is classified as low-risk for IBI when meeting all the following: appearing well at arrival to the emergency department, being >21 days old, having a procalcitonin value <0.5 ng/mL and a C-reactive protein value <20 mg/L. IBI was considered as secondary to urinary tract infection if the same pathogen was isolated in the urine culture and in the blood or cerebrospinal fluid culture. A total of 391 patients with altered urine dipstick were included. Thirty (7.7 %) of them developed an IBI, with 26 (86.7 %) of them secondary to UTI. Prevalence of IBI was 2/104 (1.9 %; CI 95% 0.5-6.7) among low-risk patients vs 28/287 (9.7 %; CI 95% 6.8-13.7) among high-risk patients (p < 0.05). Sensitivity of the model was 93.3 % (CI 95% 78.7-98.2) and negative predictive value was 98.1 % (93.3-99.4). Although our predictive model was shown to be less accurate in the validation cohort, it still showed a good discriminatory ability to detect IBI. Larger prospective external validation studies, taking into account fever duration as well as the role of ED observation, should be undertaken before its implementation into clinical practice.

A New Fracture Risk Assessment Tool (FREM) Based on Public Health Registries.

PubMed

Rubin, Katrine Hass; Möller, Sören; Holmberg, Teresa; Bliddal, Mette; Søndergaard, Jens; Abrahamsen, Bo

2018-06-20

Some conditions are already known to be associated with increased risk of osteoporotic fractures. Other conditions may also be significant indicators of increased risk. The aim of the study was to identify conditions for inclusion in a fracture prediction model (FREM - Fracture Risk Evaluation Model) for automated case finding of high-risk individuals of hip or major osteoporotic fractures (MOF). We included the total population in Denmark aged 45+ years (N= 2,495,339). All hospital diagnoses from 1998 to 2012 were used as possible conditions and the primary outcome was MOF during 2013. Our cohort was split randomly 50-50 into a development and a validation dataset for deriving and validating the predictive model. We applied backward selection on ICD-10 codes by logistic regression to develop an age-adjusted and sex-stratified model. FREM for MOF included 38 and 43 risk factors for women and men, respectively. Testing FREM for MOF in the validation cohort showed good accuracy as it produced ROC curves with an AUC of 0.750 (95% CI 0.741, 0.795) and 0.752 (95% CI 0.743, 0.761) for women and men, respectively FREM for hip fractures included 32 risk factors for both genders and showed an even higher accuracy in the validation cohort as AUC of 0.874 (95% CI 0.869, 0.879) and 0.851 (95% CI 0.841, 0.861) for women and men was found. We have developed and tested a prediction model (FREM) for identifying men and women at high risk of MOF or hip fractures by using solely existing administrative data. FREM could be employed either at the point of care integrated into Electronic Patient Record systems to alert physicians or deployed centrally in a national case finding strategy where patients at high fracture risk could be invited to a focused DXA program. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Development and validation of a prediction model for functional decline in older medical inpatients.

PubMed

Takada, Toshihiko; Fukuma, Shingo; Yamamoto, Yosuke; Tsugihashi, Yukio; Nagano, Hiroyuki; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuhara, Shunichi

2018-05-17

To prevent functional decline in older inpatients, identification of high-risk patients is crucial. The aim of this study was to develop and validate a prediction model to assess the risk of functional decline in older medical inpatients. In this retrospective cohort study, patients ≥65 years admitted acutely to medical wards were included. The healthcare database of 246 acute care hospitals (n = 229,913) was used for derivation, and two acute care hospitals (n = 1767 and 5443, respectively) were used for validation. Data were collected using a national administrative claims and discharge database. Functional decline was defined as a decline of the Katz score at discharge compared with on admission. About 6% of patients in the derivation cohort and 9% and 2% in each validation cohort developed functional decline. A model with 7 items, age, body mass index, living in a nursing home, ambulance use, need for assistance in walking, dementia, and bedsore, was developed. On internal validation, it demonstrated a c-statistic of 0.77 (95% confidence interval (CI) = 0.767-0.771) and good fit on the calibration plot. On external validation, the c-statistics were 0.79 (95% CI = 0.77-0.81) and 0.75 (95% CI = 0.73-0.77) for each cohort, respectively. Calibration plots showed good fit in one cohort and overestimation in the other one. A prediction model for functional decline in older medical inpatients was derived and validated. It is expected that use of the model would lead to early identification of high-risk patients and introducing early intervention. Copyright © 2018 Elsevier B.V. All rights reserved.

Development and external validation of a prediction rule for an unfavorable course of late-life depression: A multicenter cohort study.

PubMed

Maarsingh, O R; Heymans, M W; Verhaak, P F; Penninx, B W J H; Comijs, H C

2018-08-01

Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome. Copyright © 2018 Elsevier B.V. All rights reserved.

Extrapolation of a predictive model for growth of a low inoculum size of Salmonella typhimurium DT104 on chicken skin to higher inoculum sizes

USDA-ARS?s Scientific Manuscript database

Validation of model predictions for independent variables not included in model development can save time and money by identifying conditions for which new models are not needed. A single strain of Salmonella Typhimurium DT104 was used to develop a general regression neural network model for growth...

Development of a Stochastically-driven, Forward Predictive Performance Model for PEMFCs

NASA Astrophysics Data System (ADS)

Harvey, David Benjamin Paul

A one-dimensional multi-scale coupled, transient, and mechanistic performance model for a PEMFC membrane electrode assembly has been developed. The model explicitly includes each of the 5 layers within a membrane electrode assembly and solves for the transport of charge, heat, mass, species, dissolved water, and liquid water. Key features of the model include the use of a multi-step implementation of the HOR reaction on the anode, agglomerate catalyst sub-models for both the anode and cathode catalyst layers, a unique approach that links the composition of the catalyst layer to key properties within the agglomerate model and the implementation of a stochastic input-based approach for component material properties. The model employs a new methodology for validation using statistically varying input parameters and statistically-based experimental performance data; this model represents the first stochastic input driven unit cell performance model. The stochastic input driven performance model was used to identify optimal ionomer content within the cathode catalyst layer, demonstrate the role of material variation in potential low performing MEA materials, provide explanation for the performance of low-Pt loaded MEAs, and investigate the validity of transient-sweep experimental diagnostic methods.

How do men and women help? Validation of a multidimensional measure of prosocial behavior.

PubMed

Nielson, Matthew G; Padilla-Walker, Laura; Holmes, Erin K

2017-04-01

The current study sought to address gender differences in prosocial behavior by creating and validating a multidimensional measure of prosocial behavior that more fully captures the ways that men help others. The new measure is directed toward family, friend, and strangers, and has five factors: defending, emotional support, inclusion, physical helping, and sharing. In Study 1, CFA analyses performed on a sample of 463 emerging adults online (mean age 23.42) revealed good model fit and divergent validity for each of the five factors. Study 2 replicated the analyses on a sample of 453 urban adolescents in the Northwest (mean age 18.37). Results established that all factors had good model fit, construct validity, and convergent validity. The discussion focuses on implications of this measure for future prosocial research including an increased diversity in how people (particularly men) help others and developmental differences toward different targets of prosocial behavior. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Developing and upgrading of solar system thermal energy storage simulation models. Technical progress report, March 1, 1979-February 29, 1980

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

Kuhn, J K; von Fuchs, G F; Zob, A P

1980-05-01

Two water tank component simulation models have been selected and upgraded. These models are called the CSU Model and the Extended SOLSYS Model. The models have been standardized and links have been provided for operation in the TRNSYS simulation program. The models are described in analytical terms as well as in computer code. Specific water tank tests were performed for the purpose of model validation. Agreement between model data and test data is excellent. A description of the limitations has also been included. Streamlining results and criteria for the reduction of computer time have also been shown for both watermore » tank computer models. Computer codes for the models and instructions for operating these models in TRNSYS have also been included, making the models readily available for DOE and industry use. Rock bed component simulation models have been reviewed and a model selected and upgraded. This model is a logical extension of the Mumma-Marvin model. Specific rock bed tests have been performed for the purpose of validation. Data have been reviewed for consistency. Details of the test results concerned with rock characteristics and pressure drop through the bed have been explored and are reported.« less

Evidence for the Continuous Latent Structure of Mania in the Epidemiologic Catchment Area from Multiple Latent Structure and Construct Validation Methodologies

PubMed Central

Prisciandaro, James J.; Roberts, John E.

2011-01-01

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

Spacecraft Internal Acoustic Environment Modeling

NASA Technical Reports Server (NTRS)

Chu, Shao-Sheng R.; Allen Christopher S.

2010-01-01

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. This paper describes the implementation of acoustic modeling for design purposes by incrementally increasing model fidelity and validating the accuracy of the model while predicting the noise of sources under various conditions. During FY 07, a simple-geometry Statistical Energy Analysis (SEA) model was developed and validated using a physical mockup and acoustic measurements. A process for modeling the effects of absorptive wall treatments and the resulting reverberation environment were developed. During FY 08, a model with more complex and representative geometry of the Orion Crew Module (CM) interior was built, and noise predictions based on input noise sources were made. A corresponding physical mockup was also built. Measurements were made inside this mockup, and comparisons were made with the model and showed excellent agreement. During FY 09, the fidelity of the mockup and corresponding model were increased incrementally by including a simple ventilation system. The airborne noise contribution of the fans was measured using a sound intensity technique, since the sound power levels were not known beforehand. This is opposed to earlier studies where Reference Sound Sources (RSS) with known sound power level were used. Comparisons of the modeling result with the measurements in the mockup showed excellent results. During FY 10, the fidelity of the mockup and the model were further increased by including an ECLSS (Environmental Control and Life Support System) wall, associated closeout panels, and the gap between ECLSS wall and mockup wall. The effect of sealing the gap and adding sound absorptive treatment to ECLSS wall were also modeled and validated.

External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement-a protocol for a systematic review.

PubMed

Ogurtsova, Katherine; Heise, Thomas L; Linnenkamp, Ute; Dintsios, Charalabos-Markos; Lhachimi, Stefan K; Icks, Andrea

2017-12-29

Type 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM. We will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards. The proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques. PROSPERO CRD42017069983 .

Smouldering (thermal) remediation of soil contaminated with industrial organic liquids: novel insights into heat transfer and kinetics uncovered by integrating experiments and modelling

NASA Astrophysics Data System (ADS)

Gerhard, J.; Zanoni, M. A. B.; Torero, J. L.

2017-12-01

Smouldering (i.e., flameless combustion) underpins the technology Self-sustaining Treatment for Active Remediation (STAR). STAR achieves the in situ destruction of nonaqueous phase liquids (NAPLs) by generating a self-sustained smouldering reaction that propagates through the source zone. This research explores the nature of the travelling reaction and the influence of key in situ and engineered characteristics. A novel one-dimensional numerical model was developed (in COMSOL) to simulate the smouldering remediation of bitumen-contaminated sand. This model was validated against laboratory column experiments. Achieving model validation depended on correctly simulating the energy balance at the reaction front, including properly accounting for heat transfer, smouldering kinetics, and heat losses. Heat transfer between soil and air was demonstrated to be generally not at equilibrium. Moreover, existing heat transfer correlations were found to be inappropriate for the low air flow Reynold's numbers (Re < 30) relevant in this and similar thermal remediation systems. Therefore, a suite of experiments were conducted to generate a new heat transfer correlation, which generated correct simulations of convective heat flow through soil. Moreover, it was found that, for most cases of interest, a simple two-step pyrolysis/oxidation set of kinetic reactions was sufficient. Arrhenius parameters, calculated independently from thermogravimetric experiments, allowed the reaction kinetics to be validated in the smouldering model. Furthermore, a simple heat loss term sufficiently accounted for radial heat losses from the column. Altogether, these advances allow this simple model to reasonably predict the self-sustaining process including the peak reaction temperature, the reaction velocity, and the complete destruction of bitumen behind the front. Simulations with the validated model revealed numerous unique insights, including how the system inherently recycles energy, how air flow rate and NAPL saturation dictate contaminant destruction rates, and the extremes that lead to extinction. Overall, this research provides unique insights into the complex interplay of thermochemical processes that govern the success of smouldering as well as other thermal remediation approaches.

Integrating the Analysis of Mental Operations into Multilevel Models to Validate an Assessment of Higher Education Students' Competency in Business and Economics

ERIC Educational Resources Information Center

Brückner, Sebastian; Pellegrino, James W.

2016-01-01

The Standards for Educational and Psychological Testing indicate that validation of assessments should include analyses of participants' response processes. However, such analyses typically are conducted only to supplement quantitative field studies with qualitative data, and seldom are such data connected to quantitative data on student or item…

A hybrid model for traffic flow and crowd dynamics with random individual properties.

PubMed

Schleper, Veronika

2015-04-01

Based on an established mathematical model for the behavior of large crowds, a new model is derived that is able to take into account the statistical variation of individual maximum walking speeds. The same model is shown to be valid also in traffic flow situations, where for instance the statistical variation of preferred maximum speeds can be considered. The model involves explicit bounds on the state variables, such that a special Riemann solver is derived that is proved to respect the state constraints. Some care is devoted to a valid construction of random initial data, necessary for the use of the new model. The article also includes a numerical method that is shown to respect the bounds on the state variables and illustrative numerical examples, explaining the properties of the new model in comparison with established models.

The clinical effectiveness and cost-effectiveness of testing for cytochrome P450 polymorphisms in patients with schizophrenia treated with antipsychotics: a systematic review and economic evaluation.

PubMed

Fleeman, N; McLeod, C; Bagust, A; Beale, S; Boland, A; Dundar, Y; Jorgensen, A; Payne, K; Pirmohamed, M; Pushpakom, S; Walley, T; de Warren-Penny, P; Dickson, R

2010-01-01

To determine whether testing for cytochrome P450 (CYP) polymorphisms in adults entering antipsychotic treatment for schizophrenia leads to improvement in outcomes, is useful in medical, personal or public health decision-making, and is a cost-effective use of health-care resources. The following electronic databases were searched for relevant published literature: Cochrane Controlled Trials Register, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effectiveness, EMBASE, Health Technology Assessment database, ISI Web of Knowledge, MEDLINE, PsycINFO, NHS Economic Evaluation Database, Health Economic Evaluation Database, Cost-effectiveness Analysis (CEA) Registry and the Centre for Health Economics website. In addition, publicly available information on various genotyping tests was sought from the internet and advisory panel members. A systematic review of analytical validity, clinical validity and clinical utility of CYP testing was undertaken. Data were extracted into structured tables and narratively discussed, and meta-analysis was undertaken when possible. A review of economic evaluations of CYP testing in psychiatry and a review of economic models related to schizophrenia were also carried out. For analytical validity, 46 studies of a range of different genotyping tests for 11 different CYP polymorphisms (most commonly CYP2D6) were included. Sensitivity and specificity were high (99-100%). For clinical validity, 51 studies were found. In patients tested for CYP2D6, an association between genotype and tardive dyskinesia (including Abnormal Involuntary Movement Scale scores) was found. The only other significant finding linked the CYP2D6 genotype to parkinsonism. One small unpublished study met the inclusion criteria for clinical utility. One economic evaluation assessing the costs and benefits of CYP testing for prescribing antidepressants and 28 economic models of schizophrenia were identified; none was suitable for developing a model to examine the cost-effectiveness of CYP testing. Tests for determining genotypes appear to be accurate although not all aspects of analytical validity were reported. Given the absence of convincing evidence from clinical validity studies, the lack of clinical utility and economic studies, and the unsuitability of published schizophrenia models, no model was developed; instead key features and data requirements for economic modelling are presented. Recommendations for future research cover both aspects of research quality and data that will be required to inform the development of future economic models.

Analysis of SSME HPOTP rotordynamics subsynchronous whirl

NASA Technical Reports Server (NTRS)

1984-01-01

The causes and remedies of vibration and subsynchronous whirl problems encountered in the Shuttle Main Engine SSME turbomachinery are analyzed. Because the nonlinear and linearized models of the turbopumps play such an important role in the analysis process, the main emphasis is concentrated on the verification and improvement of these tools. It has been the goal of our work to validate the equations of motion used in the models are validated, including the assumptions upon which they are based. Verification of th SSME rotordynamics simulation and the developed enhancements, are emphasized.

Development of a validation model for the defense meteorological satellite program's special sensor microwave imager

NASA Technical Reports Server (NTRS)

Swift, C. T.; Goodberlet, M. A.; Wilkerson, J. C.

1990-01-01

The Defence Meteorological Space Program's (DMSP) Special Sensor Microwave/Imager (SSM/I), an operational wind speed algorithm was developed. The algorithm is based on the D-matrix approach which seeks a linear relationship between measured SSM/I brightness temperatures and environmental parameters. D-matrix performance was validated by comparing algorithm derived wind speeds with near-simultaneous and co-located measurements made by off-shore ocean buoys. Other topics include error budget modeling, alternate wind speed algorithms, and D-matrix performance with one or more inoperative SSM/I channels.

Methodologies for validating ray-based forward model using finite element method in ultrasonic array data simulation

NASA Astrophysics Data System (ADS)

Zhang, Jie; Nixon, Andrew; Barber, Tom; Budyn, Nicolas; Bevan, Rhodri; Croxford, Anthony; Wilcox, Paul

2018-04-01

In this paper, a methodology of using finite element (FE) model to validate a ray-based model in the simulation of full matrix capture (FMC) ultrasonic array data set is proposed. The overall aim is to separate signal contributions from different interactions in FE results for easier comparing each individual component in the ray-based model results. This is achieved by combining the results from multiple FE models of the system of interest that include progressively more geometrical features while preserving the same mesh structure. It is shown that the proposed techniques allow the interactions from a large number of different ray-paths to be isolated in FE results and compared directly to the results from a ray-based forward model.

Application of a Computer Model to Various Specifications of Fuel Injection System for DI Diesel Engines

NASA Astrophysics Data System (ADS)

Yamanishi, Manabu

A combined experimental and computational investigation was performed in order to evaluate the effects of various design parameters of an in-line injection pump on the nozzle exit characteristics for DI diesel engines. Measurements of the pump chamber pressure and the delivery valve lift were included for validation by using specially designed transducers installed inside the pump. The results confirm that the simulation model is capable of predicting the pump operation for all the different designs investigated pump operating conditions. Following the successful validation of this model, parametric studies were performed which allow for improved fuel injection system design.

Experimental validation of flexible robot arm modeling and control

NASA Technical Reports Server (NTRS)

Ulsoy, A. Galip

1989-01-01

Flexibility is important for high speed, high precision operation of lightweight manipulators. Accurate dynamic modeling of flexible robot arms is needed. Previous work has mostly been based on linear elasticity with prescribed rigid body motions (i.e., no effect of flexible motion on rigid body motion). Little or no experimental validation of dynamic models for flexible arms is available. Experimental results are also limited for flexible arm control. Researchers include the effects of prismatic as well as revolute joints. They investigate the effect of full coupling between the rigid and flexible motions, and of axial shortening, and consider the control of flexible arms using only additional sensors.

Evaluating Nextgen Closely Spaced Parallel Operations Concepts with Validated Human Performance Models: Flight Deck Guidelines

NASA Technical Reports Server (NTRS)

Hooey, Becky Lee; Gore, Brian Francis; Mahlstedt, Eric; Foyle, David C.

2013-01-01

The objectives of the current research were to develop valid human performance models (HPMs) of approach and land operations; use these models to evaluate the impact of NextGen Closely Spaced Parallel Operations (CSPO) on pilot performance; and draw conclusions regarding flight deck display design and pilot-ATC roles and responsibilities for NextGen CSPO concepts. This document presents guidelines and implications for flight deck display designs and candidate roles and responsibilities. A companion document (Gore, Hooey, Mahlstedt, & Foyle, 2013) provides complete scenario descriptions and results including predictions of pilot workload, visual attention and time to detect off-nominal events.

Psychometric testing of the short version of the world health organization quality of life (WHOQOL-BREF) questionnaire among pulmonary tuberculosis patients in Taiwan

PubMed Central

2012-01-01

Background Studies on the effects of tuberculosis on a patient’s quality of life (QOL) are scant. The objective of this study was to evaluate the psychometric properties of the Taiwan short version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire using patients with tuberculosis in Taiwan and healthy referents. Methods The Taiwanese short version of the WHOQOL-BREF was administered to patients with tuberculosis undergoing treatment and healthy referents from March 2007 to July 2007. Patients with tuberculosis (n = 140) and healthy referents (n = 130), matched by age, sex, and ethnicity, agreed to an interview. All participants lived in eastern Taiwan. Reliability assessments included internal consistency, whereas validity assessments included construct validity, convergent validity, and discriminant validity. Results More than half of these patients and referents were men (70.7% and 66.2%, respectively), and their average ages were 50.1 and 47.9 years, respectively. Approximately 60% of patients and referents were aboriginal Taiwanese (60.7% and 61.1%, respectively). The proportion with low socioeconomic status was greater for these patients. The internal consistency reliability coefficients were .92 and .93 for the patients and healthy referents, respectively. Exploratory factor analysis on the healthy referents displayed a 4-domain model, which was compatible with the original WHOQOL-BREF 4-domain model. However, for the TB patient group, after deleting 3 items, both exploratory and confirmatory factor analysis revealed a 6-domain model. Conclusion Psychometric evaluation of the Taiwan short version of the WHOQOL-BREF indicates that it has adequate reliability for use in research with TB patients in Taiwan. However, the factor structure generated from this TB patient sample differed from the WHO’s original 4-factor model, which raised a validity concern to apply the Taiwan short version of the WHOQOL-BREF to Taiwanese TB patients. Future research recruiting another sample to revisit this validity issue must be conducted to determine the validity of the WHOQOL-BREF TW in patients with TB. PMID:22877305

Computational solution verification and validation applied to a thermal model of a ruggedized instrumentation package

DOE PAGES

Scott, Sarah Nicole; Templeton, Jeremy Alan; Hough, Patricia Diane; ...

2014-01-01

This study details a methodology for quantification of errors and uncertainties of a finite element heat transfer model applied to a Ruggedized Instrumentation Package (RIP). The proposed verification and validation (V&V) process includes solution verification to examine errors associated with the code's solution techniques, and model validation to assess the model's predictive capability for quantities of interest. The model was subjected to mesh resolution and numerical parameters sensitivity studies to determine reasonable parameter values and to understand how they change the overall model response and performance criteria. To facilitate quantification of the uncertainty associated with the mesh, automatic meshing andmore » mesh refining/coarsening algorithms were created and implemented on the complex geometry of the RIP. Automated software to vary model inputs was also developed to determine the solution’s sensitivity to numerical and physical parameters. The model was compared with an experiment to demonstrate its accuracy and determine the importance of both modelled and unmodelled physics in quantifying the results' uncertainty. An emphasis is placed on automating the V&V process to enable uncertainty quantification within tight development schedules.« less

Potential serum biomarkers from a metabolomics study of autism

PubMed Central

Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

2016-01-01

Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

Utilization of advanced calibration techniques in stochastic rock fall analysis of quarry slopes

NASA Astrophysics Data System (ADS)

Preh, Alexander; Ahmadabadi, Morteza; Kolenprat, Bernd

2016-04-01

In order to study rock fall dynamics, a research project was conducted by the Vienna University of Technology and the Austrian Central Labour Inspectorate (Federal Ministry of Labour, Social Affairs and Consumer Protection). A part of this project included 277 full-scale drop tests at three different quarries in Austria and recording key parameters of the rock fall trajectories. The tests involved a total of 277 boulders ranging from 0.18 to 1.8 m in diameter and from 0.009 to 8.1 Mg in mass. The geology of these sites included strong rock belonging to igneous, metamorphic and volcanic types. In this paper the results of the tests are used for calibration and validation a new stochastic computer model. It is demonstrated that the error of the model (i.e. the difference between observed and simulated results) has a lognormal distribution. Selecting two parameters, advanced calibration techniques including Markov Chain Monte Carlo Technique, Maximum Likelihood and Root Mean Square Error (RMSE) are utilized to minimize the error. Validation of the model based on the cross validation technique reveals that in general, reasonable stochastic approximations of the rock fall trajectories are obtained in all dimensions, including runout, bounce heights and velocities. The approximations are compared to the measured data in terms of median, 95% and maximum values. The results of the comparisons indicate that approximate first-order predictions, using a single set of input parameters, are possible and can be used to aid practical hazard and risk assessment.

The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.

Documentation and Validation of the Goddard Earth Observing System (GEOS) Data Assimilation System, Version 4

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); daSilva, Arlindo; Dee, Dick; Bloom, Stephen; Bosilovich, Michael; Pawson, Steven; Schubert, Siegfried; Wu, Man-Li; Sienkiewicz, Meta; Stajner, Ivanka

2005-01-01

This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.

Validation of a Simple Score to Determine Risk of Early Rejection After Pediatric Heart Transplantation.

PubMed

Butts, Ryan J; Savage, Andrew J; Atz, Andrew M; Heal, Elisabeth M; Burnette, Ali L; Kavarana, Minoo M; Bradley, Scott M; Chowdhury, Shahryar M

2015-09-01

This study aimed to develop a reliable and feasible score to assess the risk of rejection in pediatric heart transplantation recipients during the first post-transplant year. The first post-transplant year is the most likely time for rejection to occur in pediatric heart transplantation. Rejection during this period is associated with worse outcomes. The United Network for Organ Sharing database was queried for pediatric patients (age <18 years) who underwent isolated orthotopic heart transplantation from January 1, 2000 to December 31, 2012. Transplantations were divided into a derivation cohort (n = 2,686) and a validation (n = 509) cohort. The validation cohort was randomly selected from 20% of transplantations from 2005 to 2012. Covariates found to be associated with rejection (p < 0.2) were included in the initial multivariable logistic regression model. The final model was derived by including only variables independently associated with rejection. A risk score was then developed using relative magnitudes of the covariates' odds ratio. The score was then tested in the validation cohort. A 9-point risk score using 3 variables (age, cardiac diagnosis, and panel reactive antibody) was developed. Mean score in the derivation and validation cohorts were 4.5 ± 2.6 and 4.8 ± 2.7, respectively. A higher score was associated with an increased rate of rejection (score = 0, 10.6% in the validation cohort vs. score = 9, 40%; p < 0.01). In weighted regression analysis, the model-predicted risk of rejection correlated closely with the actual rates of rejection in the validation cohort (R(2) = 0.86; p < 0.01). The rejection score is accurate in determining the risk of early rejection in pediatric heart transplantation recipients. The score has the potential to be used in clinical practice to aid in determining the immunosuppressant regimen and the frequency of rejection surveillance in the first post-transplant year. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Validation of Blockage Interference Corrections in the National Transonic Facility

NASA Technical Reports Server (NTRS)

Walker, Eric L.

2007-01-01

A validation test has recently been constructed for wall interference methods as applied to the National Transonic Facility (NTF). The goal of this study was to begin to address the uncertainty of wall-induced-blockage interference corrections, which will make it possible to address the overall quality of data generated by the facility. The validation test itself is not specific to any particular modeling. For this present effort, the Transonic Wall Interference Correction System (TWICS) as implemented at the NTF is the mathematical model being tested. TWICS uses linear, potential boundary conditions that must first be calibrated. These boundary conditions include three different classical, linear. homogeneous forms that have been historically used to approximate the physical behavior of longitudinally slotted test section walls. Results of the application of the calibrated wall boundary conditions are discussed in the context of the validation test.

Developing workshop module of realistic mathematics education: Follow-up workshop

NASA Astrophysics Data System (ADS)

Palupi, E. L. W.; Khabibah, S.

2018-01-01

Realistic Mathematics Education (RME) is a learning approach which fits the aim of the curriculum. The success of RME in teaching mathematics concepts, triggering students’ interest in mathematics and teaching high order thinking skills to the students will make teachers start to learn RME. Hence, RME workshop is often offered and done. This study applied development model proposed by Plomp. Based on the study by RME team, there are three kinds of RME workshop: start-up workshop, follow-up workshop, and quality boost. However, there is no standardized or validated module which is used in that workshops. This study aims to develop a module of RME follow-up workshop which is valid and can be used. Plopm’s developmental model includes materials analysis, design, realization, implementation, and evaluation. Based on the validation, the developed module is valid. While field test shows that the module can be used effectively.

Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study.

PubMed

Oh, Ein; Yoo, Tae Keun; Park, Eun-Cheol

2013-09-13

Blindness due to diabetic retinopathy (DR) is the major disability in diabetic patients. Although early management has shown to prevent vision loss, diabetic patients have a low rate of routine ophthalmologic examination. Hence, we developed and validated sparse learning models with the aim of identifying the risk of DR in diabetic patients. Health records from the Korea National Health and Nutrition Examination Surveys (KNHANES) V-1 were used. The prediction models for DR were constructed using data from 327 diabetic patients, and were validated internally on 163 patients in the KNHANES V-1. External validation was performed using 562 diabetic patients in the KNHANES V-2. The learning models, including ridge, elastic net, and LASSO, were compared to the traditional indicators of DR. Considering the Bayesian information criterion, LASSO predicted DR most efficiently. In the internal and external validation, LASSO was significantly superior to the traditional indicators by calculating the area under the curve (AUC) of the receiver operating characteristic. LASSO showed an AUC of 0.81 and an accuracy of 73.6% in the internal validation, and an AUC of 0.82 and an accuracy of 75.2% in the external validation. The sparse learning model using LASSO was effective in analyzing the epidemiological underlying patterns of DR. This is the first study to develop a machine learning model to predict DR risk using health records. LASSO can be an excellent choice when both discriminative power and variable selection are important in the analysis of high-dimensional electronic health records.

Challenges in validating model results for first year ice

NASA Astrophysics Data System (ADS)

Melsom, Arne; Eastwood, Steinar; Xie, Jiping; Aaboe, Signe; Bertino, Laurent

2017-04-01

In order to assess the quality of model results for the distribution of first year ice, a comparison with a product based on observations from satellite-borne instruments has been performed. Such a comparison is not straightforward due to the contrasting algorithms that are used in the model product and the remote sensing product. The implementation of the validation is discussed in light of the differences between this set of products, and validation results are presented. The model product is the daily updated 10-day forecast from the Arctic Monitoring and Forecasting Centre in CMEMS. The forecasts are produced with the assimilative ocean prediction system TOPAZ. Presently, observations of sea ice concentration and sea ice drift are introduced in the assimilation step, but data for sea ice thickness and ice age (or roughness) are not included. The model computes the age of the ice by recording and updating the time passed after ice formation as sea ice grows and deteriorates as it is advected inside the model domain. Ice that is younger than 365 days is classified as first year ice. The fraction of first-year ice is recorded as a tracer in each grid cell. The Ocean and Sea Ice Thematic Assembly Centre in CMEMS redistributes a daily product from the EUMETSAT OSI SAF of gridded sea ice conditions which include "ice type", a representation of the separation of regions between those infested by first year ice, and those infested by multi-year ice. The ice type is parameterized based on data for the gradient ratio GR(19,37) from SSMIS observations, and from the ASCAT backscatter parameter. This product also includes information on ambiguity in the processing of the remote sensing data, and the product's confidence level, which have a strong seasonal dependency.

Derivation and Validation of a Renal Risk Score for People With Type 2 Diabetes

PubMed Central

Elley, C. Raina; Robinson, Tom; Moyes, Simon A.; Kenealy, Tim; Collins, John; Robinson, Elizabeth; Orr-Walker, Brandon; Drury, Paul L.

2013-01-01

OBJECTIVE Diabetes has become the leading cause of end-stage renal disease (ESRD). Renal risk stratification could assist in earlier identification and targeted prevention. This study aimed to derive risk models to predict ESRD events in type 2 diabetes in primary care. RESEARCH DESIGN AND METHODS The nationwide derivation cohort included adults with type 2 diabetes from the New Zealand Diabetes Cohort Study initially assessed during 2000–2006 and followed until December 2010, excluding those with pre-existing ESRD. The outcome was fatal or nonfatal ESRD event (peritoneal dialysis or hemodialysis for ESRD, renal transplantation, or death from ESRD). Risk models were developed using Cox proportional hazards models, and their performance was assessed in a separate validation cohort. RESULTS The derivation cohort included 25,736 individuals followed for up to 11 years (180,497 person-years; 86% followed for ≥5 years). At baseline, mean age was 62 years, median diabetes duration 5 years, and median HbA1c 7.2% (55 mmol/mol); 37% had albuminuria; and median estimated glomerular filtration rate (eGFR) was 77 mL/min/1.73 m2. There were 637 ESRD events (2.5%) during follow-up. Models that included sex, ethnicity, age, diabetes duration, albuminuria, serum creatinine, systolic blood pressure, HbA1c, smoking status, and previous cardiovascular disease status performed well with good discrimination and calibration in the derivation cohort and the validation cohort (n = 5,877) (C-statistics 0.89–0.92), improving predictive performance compared with previous models. CONCLUSIONS These 5-year renal risk models performed very well in two large primary care populations with type 2 diabetes. More accurate risk stratification could facilitate earlier intervention than using eGFR and/or albuminuria alone. PMID:23801726

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

Koh, J. H.; Ng, E. Y. K.; Robertson, Amy

As part of a collaboration of the National Renewable Energy Laboratory (NREL) and SWAY AS, NREL installed scientific wind, wave, and motion measurement equipment on the spar-type 1/6.5th-scale prototype SWAY floating offshore wind system. The equipment enhanced SWAY's data collection and allowed SWAY to verify the concept and NREL to validate a FAST model of the SWAY design in an open-water condition. Nanyang Technological University (NTU), in collaboration with NREL, assisted with the validation. This final report gives an overview of the SWAY prototype and NREL and NTU's efforts to validate a model of the system. The report provides amore » summary of the different software tools used in the study, the modeling strategies, and the development of a FAST model of the SWAY prototype wind turbine, including justification of the modeling assumptions. Because of uncertainty in system parameters and modeling assumptions due to the complexity of the design, several system properties were tuned to better represent the system and improve the accuracy of the simulations. Calibration was performed using data from a static equilibrium test and free-decay tests.« less

Integrating technologies for oil spill response in the SW Iberian coast

NASA Astrophysics Data System (ADS)

Janeiro, J.; Neves, A.; Martins, F.; Relvas, P.

2017-09-01

An operational oil spill modelling system developed for the SW Iberia Coast is used to investigate the relative importance of the different components and technologies integrating an oil spill monitoring and response structure. A backtrack of a CleanSeaNet oil detection in the region is used to demonstrate the concept. Taking advantage of regional operational products available, the system provides the necessary resolution to go from regional to coastal scales using a downscalling approach, while a multi-grid methodology allows the based oil spill model to span across model domains taking full advantage of the increasing resolution between the model grids. An extensive validation procedure using a multiplicity of sensors, with good spatial and temporal coverage, strengthens the operational system ability to accurately solve coastal scale processes. The model is validated using available trajectories from satellite-tracked drifters. Finally, a methodology is proposed to identifying potential origins for the CleanSeaNet oil detection, by combining model backtrack results with ship trajectories supplied by AIS was developed, including the error estimations found in the backtrack validation.

SCM-Forcing Data

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

Xie, Shaocheng; Tang, Shuaiqi; Zhang, Yunyan

2016-07-01

Single-Column Model (SCM) Forcing Data are derived from the ARM facility observational data using the constrained variational analysis approach (Zhang and Lin 1997 and Zhang et al., 2001). The resulting products include both the large-scale forcing terms and the evaluation fields, which can be used for driving the SCMs and Cloud Resolving Models (CRMs) and validating model simulations.

A Model for the Education of Gifted Learners in Lebanon

ERIC Educational Resources Information Center

Sarouphim, Ketty M.

2010-01-01

The purpose of this paper is to present a model for developing a comprehensive system of education for gifted learners in Lebanon. The model consists of three phases and includes key elements for establishing gifted education in the country, such as raising community awareness, adopting valid identification measures, and developing effective…

Prediction of Phyllosticta citricarpa using an hourly infection model and validation with prevalence data from South Africa and Australia

USDA-ARS?s Scientific Manuscript database

A simple hourly infection model was used for a risk assessment of citrus black spot (CBS) caused by Phyllosticta citricarpa. The infection model contained a temperature-moisture response function and also included functions to simulate ascospore release and dispersal of pycnidiospores. A validatio...

Design and validation of a model to predict early mortality in haemodialysis patients.

PubMed

Mauri, Joan M; Clèries, Montse; Vela, Emili

2008-05-01

Mortality and morbidity rates are higher in patients receiving haemodialysis therapy than in the general population. Detection of risk factors related to early death in these patients could be of aid for clinical and administrative decision making. Objectives. The aims of this study were (1) to identify risk factors (comorbidity and variables specific to haemodialysis) associated with death in the first year following the start of haemodialysis and (2) to design and validate a prognostic model to quantify the probability of death for each patient. An analysis was carried out on all patients starting haemodialysis treatment in Catalonia during the period 1997-2003 (n = 5738). The data source was the Renal Registry of Catalonia, a mandatory population registry. Patients were randomly divided into two samples: 60% (n = 3455) of the total were used to develop the prognostic model and the remaining 40% (n = 2283) to validate the model. Logistic regression analysis was used to construct the model. One-year mortality in the total study population was 16.5%. The predictive model included the following variables: age, sex, primary renal disease, grade of functional autonomy, chronic obstructive pulmonary disease, malignant processes, chronic liver disease, cardiovascular disease, initial vascular access and malnutrition. The analyses showed adequate calibration for both the sample to develop the model and the validation sample (Hosmer-Lemeshow statistic 0.97 and P = 0.49, respectively) as well as adequate discrimination (ROC curve 0.78 in both cases). Risk factors implicated in mortality at one year following the start of haemodialysis have been determined and a prognostic model designed. The validated, easy-to-apply model quantifies individual patient risk attributable to various factors, some of them amenable to correction by directed interventions.

A design methodology for neutral buoyancy simulation of space operations

NASA Technical Reports Server (NTRS)

Akin, David L.

1988-01-01

Neutral buoyancy has often been used in the past for EVA development activities, but little has been done to provide an analytical understanding of the environment and its correlation with space. This paper covers a set of related research topics at the MIT Space Systems Laboratory, dealing with the modeling of the space and underwater environments, validation of the models through testing in neutral buoyancy, parabolic flight, and space flight experiments, and applications of the models to gain a better design methodology for creating meaningful neutral buoyancy simulations. Examples covered include simulation validation criteria for human body dynamics, and for applied torques in a beam rotation task, which is the pacing crew operation for EVA structural assembly. Extensions of the dynamics models are presented for powered vehicles in the underwater environment, and examples given from the MIT Space Telerobotics Research Program, including the Beam Assembly Teleoperator and the Multimode Proximity Operations Device. Future expansions of the modeling theory are also presented, leading to remote vehicles which behave in neutral buoyancy exactly as the modeled system would in space.

Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

PubMed

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics

NASA Astrophysics Data System (ADS)

Folkert, Michael R.; Setton, Jeremy; Apte, Aditya P.; Grkovski, Milan; Young, Robert J.; Schöder, Heiko; Thorstad, Wade L.; Lee, Nancy Y.; Deasy, Joseph O.; Oh, Jung Hun

2017-07-01

In this study, we investigate the use of imaging feature-based outcomes research (‘radiomics’) combined with machine learning techniques to develop robust predictive models for the risk of all-cause mortality (ACM), local failure (LF), and distant metastasis (DM) following definitive chemoradiation therapy (CRT). One hundred seventy four patients with stage III-IV oropharyngeal cancer (OC) treated at our institution with CRT with retrievable pre- and post-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans were identified. From pre-treatment PET scans, 24 representative imaging features of FDG-avid disease regions were extracted. Using machine learning-based feature selection methods, multiparameter logistic regression models were built incorporating clinical factors and imaging features. All model building methods were tested by cross validation to avoid overfitting, and final outcome models were validated on an independent dataset from a collaborating institution. Multiparameter models were statistically significant on 5 fold cross validation with the area under the receiver operating characteristic curve (AUC)  =  0.65 (p  =  0.004), 0.73 (p  =  0.026), and 0.66 (p  =  0.015) for ACM, LF, and DM, respectively. The model for LF retained significance on the independent validation cohort with AUC  =  0.68 (p  =  0.029) whereas the models for ACM and DM did not reach statistical significance, but resulted in comparable predictive power to the 5 fold cross validation with AUC  =  0.60 (p  =  0.092) and 0.65 (p  =  0.062), respectively. In the largest study of its kind to date, predictive features including increasing metabolic tumor volume, increasing image heterogeneity, and increasing tumor surface irregularity significantly correlated to mortality, LF, and DM on 5 fold cross validation in a relatively uniform single-institution cohort. The LF model also retained significance in an independent population.

Calibration of a rotating accelerometer gravity gradiometer using centrifugal gradients

NASA Astrophysics Data System (ADS)

Yu, Mingbiao; Cai, Tijing

2018-05-01

The purpose of this study is to calibrate scale factors and equivalent zero biases of a rotating accelerometer gravity gradiometer (RAGG). We calibrate scale factors by determining the relationship between the centrifugal gradient excitation and RAGG response. Compared with calibration by changing the gravitational gradient excitation, this method does not need test masses and is easier to implement. The equivalent zero biases are superpositions of self-gradients and the intrinsic zero biases of the RAGG. A self-gradient is the gravitational gradient produced by surrounding masses, and it correlates well with the RAGG attitude angle. We propose a self-gradient model that includes self-gradients and the intrinsic zero biases of the RAGG. The self-gradient model is a function of the RAGG attitude, and it includes parameters related to surrounding masses. The calibration of equivalent zero biases determines the parameters of the self-gradient model. We provide detailed procedures and mathematical formulations for calibrating scale factors and parameters in the self-gradient model. A RAGG physical simulation system substitutes for the actual RAGG in the calibration and validation experiments. Four point masses simulate four types of surrounding masses producing self-gradients. Validation experiments show that the self-gradients predicted by the self-gradient model are consistent with those from the outputs of the RAGG physical simulation system, suggesting that the presented calibration method is valid.

Description and Validation of a Dynamical Systems Model of Presynaptic Serotonin Function: Genetic Variation, Brain Activation and Impulsivity

PubMed Central

Stoltenberg, Scott F.; Nag, Parthasarathi

2010-01-01

Despite more than a decade of empirical work on the role of genetic polymorphisms in the serotonin system on behavior, the details across levels of analysis are not well understood. We describe a mathematical model of the genetic control of presynaptic serotonergic function that is based on control theory, implemented using systems of differential equations, and focused on better characterizing pathways from genes to behavior. We present the results of model validation tests that include the comparison of simulation outcomes with empirical data on genetic effects on brain response to affective stimuli and on impulsivity. Patterns of simulated neural firing were consistent with recent findings of additive effects of serotonin transporter and tryptophan hydroxylase-2 polymorphisms on brain activation. In addition, simulated levels of cerebral spinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA) were negatively correlated with Barratt Impulsiveness Scale (Version 11) Total scores in college students (r = −.22, p = .002, N = 187), which is consistent with the well-established negative correlation between CSF 5-HIAA and impulsivity. The results of the validation tests suggest that the model captures important aspects of the genetic control of presynaptic serotonergic function and behavior via brain activation. The proposed model can be: (1) extended to include other system components, neurotransmitter systems, behaviors and environmental influences; (2) used to generate testable hypotheses. PMID:20111992

Collaborative development of predictive toxicology applications

PubMed Central

2010-01-01

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals. The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation. Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way. PMID:20807436

Collaborative development of predictive toxicology applications.

PubMed

Hardy, Barry; Douglas, Nicki; Helma, Christoph; Rautenberg, Micha; Jeliazkova, Nina; Jeliazkov, Vedrin; Nikolova, Ivelina; Benigni, Romualdo; Tcheremenskaia, Olga; Kramer, Stefan; Girschick, Tobias; Buchwald, Fabian; Wicker, Joerg; Karwath, Andreas; Gütlein, Martin; Maunz, Andreas; Sarimveis, Haralambos; Melagraki, Georgia; Afantitis, Antreas; Sopasakis, Pantelis; Gallagher, David; Poroikov, Vladimir; Filimonov, Dmitry; Zakharov, Alexey; Lagunin, Alexey; Gloriozova, Tatyana; Novikov, Sergey; Skvortsova, Natalia; Druzhilovsky, Dmitry; Chawla, Sunil; Ghosh, Indira; Ray, Surajit; Patel, Hitesh; Escher, Sylvia

2010-08-31

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.

A novel validated model for the prediction of insulin therapy initiation and adverse perinatal outcomes in women with gestational diabetes mellitus.

PubMed

Barnes, Robyn A; Wong, Tang; Ross, Glynis P; Jalaludin, Bin B; Wong, Vincent W; Smart, Carmel E; Collins, Clare E; MacDonald-Wicks, Lesley; Flack, Jeff R

2016-11-01

Identifying women with gestational diabetes mellitus who are more likely to require insulin therapy vs medical nutrition therapy (MNT) alone would allow risk stratification and early triage to be incorporated into risk-based models of care. The aim of this study was to develop and validate a model to predict therapy type (MNT or MNT plus insulin [MNT+I]) for women with gestational diabetes mellitus (GDM). Analysis was performed of de-identified prospectively collected data (1992-2015) from women diagnosed with GDM by criteria in place since 1991 and formally adopted and promulgated as part of the more detailed 1998 Australasian Diabetes in Pregnancy Society management guidelines. Clinically relevant variables predictive of insulin therapy by univariate analysis were dichotomised and included in a multivariable regression model. The model was tested in a separate clinic population. In 3317 women, seven dichotomised significant independent predictors of insulin therapy were maternal age >30 years, family history of diabetes, pre-pregnancy obesity (BMI ≥30 kg/m(2)), prior GDM, early diagnosis of GDM (<24 weeks gestation), fasting venous blood glucose level (≥5.3 mmol/l) and HbA1c at GDM diagnosis ≥5.5% (≥37 mmol/mol). The requirement for MNT+I could be estimated according to the number of predictors present: 85.7-93.1% of women with 6-7 predictors required MNT+I compared with 9.3-14.7% of women with 0-1 predictors. This model predicted the likelihood of several adverse outcomes, including Caesarean delivery, early delivery, large for gestational age and an abnormal postpartum OGTT. The model was validated in a separate clinic population. This validated model has been shown to predict therapy type and the likelihood of several adverse perinatal outcomes in women with GDM.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone App.

PubMed

Choo, Min Soo; Jeong, Seong Jin; Cho, Sung Yong; Yoo, Changwon; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June

2017-04-01

We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

Validation Metrics for Improving Our Understanding of Turbulent Transport - Moving Beyond Proof by Pretty Picture and Loud Assertion

NASA Astrophysics Data System (ADS)

Holland, C.

2013-10-01

Developing validated models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. This tutorial will present an overview of the key guiding principles and practices for state-of-the-art validation studies, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. The primary focus of the talk will be the development of quantiatve validation metrics, which are essential for moving beyond qualitative and subjective assessments of model performance and fidelity. Particular emphasis and discussion is given to (i) the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment, and (ii) the importance of robust uncertainty quantification and its inclusion within the metrics. To illustrate these concepts, we first review the structure and key insights gained from commonly used ``global'' transport model metrics (e.g. predictions of incremental stored energy or radially-averaged temperature), as well as their limitations. Building upon these results, a new form of turbulent transport metrics is then proposed, which focuses upon comparisons of predicted local gradients and fluctuation characteristics against observation. We demonstrate the utility of these metrics by applying them to simulations and modeling of a newly developed ``validation database'' derived from the results of a systematic, multi-year turbulent transport validation campaign on the DIII-D tokamak, in which comprehensive profile and fluctuation measurements have been obtained from a wide variety of heating and confinement scenarios. Finally, we discuss extensions of these metrics and their underlying design concepts to other areas of plasma confinement research, including both magnetohydrodynamic stability and integrated scenario modeling. Supported by the US DOE under DE-FG02-07ER54917 and DE-FC02-08ER54977.

Unsteady Analysis of Separated Aerodynamic Flows Using an Unstructured Multigrid Algorithm

NASA Technical Reports Server (NTRS)

Pelaez, Juan; Mavriplis, Dimitri J.; Kandil, Osama

2001-01-01

An implicit method for the computation of unsteady flows on unstructured grids is presented. The resulting nonlinear system of equations is solved at each time step using an agglomeration multigrid procedure. The method allows for arbitrarily large time steps and is efficient in terms of computational effort and storage. Validation of the code using a one-equation turbulence model is performed for the well-known case of flow over a cylinder. A Detached Eddy Simulation model is also implemented and its performance compared to the one equation Spalart-Allmaras Reynolds Averaged Navier-Stokes (RANS) turbulence model. Validation cases using DES and RANS include flow over a sphere and flow over a NACA 0012 wing including massive stall regimes. The project was driven by the ultimate goal of computing separated flows of aerodynamic interest, such as massive stall or flows over complex non-streamlined geometries.

Calibration and validation of a two-dimensional hydrodynamic model of the Ohio River, Jefferson County, Kentucky

USGS Publications Warehouse

Wagner, C.R.; Mueller, D.S.

2001-01-01

The quantification of current patterns is an essential component of a Water Quality Analysis Simulation Program (WASP) application in a riverine environment. The U.S. Geological Survey (USGS) provided a field validated two-dimensional Resource Management Associates-2 (RMA-2) hydrodynamic model capable of quantifying the steady-flowpatterns in the Ohio River extending from river mile 590 to 630 for the Ohio River Valley Water Sanitation Commission (ORSANCO) water-quality modeling efforts on that reach. Because of the hydrodynamic complexities induced by McAlpine Locks and Dam (Ohio River mile 607), the model was split into two segments: an upstream reach, which extended from the dam upstream to the upper terminus of the study reach at Ohio River mile 590; and a downstream reach, which extended from the dam downstream to a lower terminus at Ohio River mile 636. The model was calibrated to a low-flow hydraulic survey (approximately 35,000 cubic feet per second (ft3/s)) and verified with data collected during a high-flow survey (approximately 390,000 ft3/s). The model calibration and validation process included matching water-surface elevations at 10 locations and velocity profiles at 30 cross sections throughout the study reach. Based on the calibration and validation results, the model is a representative simulation of the Ohio River steady-flow patterns below discharges of approximately 400,000 ft3/s.

6DOF Testing of the SLS Inertial Navigation Unit

NASA Technical Reports Server (NTRS)

Geohagan, Kevin W.; Bernard, William P.; Oliver, T. Emerson; Strickland, Dennis J.; Leggett, Jared O.

2018-01-01

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Assessment of validity with polytrauma Veteran populations.

PubMed

Bush, Shane S; Bass, Carmela

2015-01-01

Veterans with polytrauma have suffered injuries to multiple body parts and organs systems, including the brain. The injuries can generate a triad of physical, neurologic/cognitive, and emotional symptoms. Accurate diagnosis is essential for the treatment of these conditions and for fair allocation of benefits. To accurately diagnose polytrauma disorders and their related problems, clinicians take into account the validity of reported history and symptoms, as well as clinical presentations. The purpose of this article is to describe the assessment of validity with polytrauma Veteran populations. Review of scholarly and other relevant literature and clinical experience are utilized. A multimethod approach to validity assessment that includes objective, standardized measures increases the confidence that can be placed in the accuracy of self-reported symptoms and physical, cognitive, and emotional test results. Due to the multivariate nature of polytrauma and the multiple disciplines that play a role in diagnosis and treatment, an ideal model of validity assessment with polytrauma Veteran populations utilizes neurocognitive, neurological, neuropsychiatric, and behavioral measures of validity. An overview of these validity assessment approaches as applied to polytrauma Veteran populations is presented. Veterans, the VA, and society are best served when accurate diagnoses are made.

Turkish translation and adaptation of Champion's Health Belief Model Scales for breast cancer mammography screening.

PubMed

Yilmaz, Meryem; Sayin, Yazile Yazici

2014-07-01

To examine the translation and adaptation process from English to Turkish and the validity and reliability of the Champion's Health Belief Model Scales for Mammography Screening. Its aim (1) is to provide data about and (2) to assess Turkish women's attitudes and behaviours towards mammography. The proportion of women who have mammography is lower in Turkey. The Champion's Health Belief Model Scales for Mammography Screening-Turkish version can be helpful to determine Turkish women's health beliefs, particularly about mammography. Cross-sectional design was used to collect survey data from Turkish women: classical measurement method. The Champion's Health Belief Model Scales for Mammography Screening was translated from English to Turkish. Again, it was back translated into English. Later, the meaning and clarity of the scale items were evaluated by a bilingual group representing the culture of the target population. Finally, the tool was evaluated by two bilingual professional researchers in terms of content validity, translation validity and psychometric estimates of the validity and reliability. The analysis included a total of 209 Turkish women. The validity of the scale was confirmed by confirmatory factor analysis and criterion-related validity testing. The Champion's Health Belief Model Scales for Mammography Screening aligned to four factors that were coherent and relatively independent of each other. There was a statistically significant relationship among all of the subscale items: the positive and high correlation of the total item test score and high Cronbach's α. The scale has a strong stability over time: the Champion's Health Belief Model Scales for Mammography Screening demonstrated acceptable preliminary values of reliability and validity. The Champion's Health Belief Model Scales for Mammography Screening is both a reliable and valid instrument that can be useful in measuring the health beliefs of Turkish women. It can be used to provide data about healthcare practices required for mammography screening and breast cancer prevention. This scale will show nurses that nursing intervention planning is essential for increasing Turkish women's participation in mammography screening. © 2013 John Wiley & Sons Ltd.

Estimation and Validation of Oceanic Mass Circulation from the GRACE Mission

NASA Technical Reports Server (NTRS)

Boy, J.-P.; Rowlands, D. D.; Sabaka, T. J.; Luthcke, S. B.; Lemoine, F. G.

2011-01-01

Since the launch of the Gravity Recovery And Climate Experiment (GRACE) in March 2002, the Earth's surface mass variations have been monitored with unprecedented accuracy and resolution. Compared to the classical spherical harmonic solutions, global high-resolution mascon solutions allows the retrieval of mass variations with higher spatial and temporal sampling (2 degrees and 10 days). We present here the validation of the GRACE global mascon solutions by comparing mass estimates to a set of about 100 ocean bottom pressure (OSP) records, and show that the forward modelling of continental hydrology prior to the inversion of the K-band range rate data allows better estimates of ocean mass variations. We also validate our GRACE results to OSP variations modelled by different state-of-the-art ocean general circulation models, including ECCO (Estimating the Circulation and Climate of the Ocean) and operational and reanalysis from the MERCATOR project.

Comprehensive preclinical evaluation of a multi-physics model of liver tumor radiofrequency ablation.

PubMed

Audigier, Chloé; Mansi, Tommaso; Delingette, Hervé; Rapaka, Saikiran; Passerini, Tiziano; Mihalef, Viorel; Jolly, Marie-Pierre; Pop, Raoul; Diana, Michele; Soler, Luc; Kamen, Ali; Comaniciu, Dorin; Ayache, Nicholas

2017-09-01

We aim at developing a framework for the validation of a subject-specific multi-physics model of liver tumor radiofrequency ablation (RFA). The RFA computation becomes subject specific after several levels of personalization: geometrical and biophysical (hemodynamics, heat transfer and an extended cellular necrosis model). We present a comprehensive experimental setup combining multimodal, pre- and postoperative anatomical and functional images, as well as the interventional monitoring of intra-operative signals: the temperature and delivered power. To exploit this dataset, an efficient processing pipeline is introduced, which copes with image noise, variable resolution and anisotropy. The validation study includes twelve ablations from five healthy pig livers: a mean point-to-mesh error between predicted and actual ablation extent of 5.3 ± 3.6 mm is achieved. This enables an end-to-end preclinical validation framework that considers the available dataset.

Development and validation of risk models and molecular diagnostics to permit personalized management of cancer.

PubMed

Pu, Xia; Ye, Yuanqing; Wu, Xifeng

2014-01-01

Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.

Prediction of pelvic organ prolapse using an artificial neural network.

PubMed

Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

2008-08-01

The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

A new model of wheezing severity in young children using the validated ISAAC wheezing module: A latent variable approach with validation in independent cohorts.

PubMed

Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V

2018-01-01

The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with asthma morbidity, as demonstrated in two ECHO birth cohort studies, and provides a more statistically powerful method of testing etiologic hypotheses of childhood wheezing illness and asthma.

Direct drive: Simulations and results from the National Ignition Facility

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

Radha, P. B., E-mail: rbah@lle.rochester.edu; Hohenberger, M.; Edgell, D. H.

Direct-drive implosion physics is being investigated at the National Ignition Facility. The primary goal of the experiments is twofold: to validate modeling related to implosion velocity and to estimate the magnitude of hot-electron preheat. Implosion experiments indicate that the energetics is well-modeled when cross-beam energy transfer (CBET) is included in the simulation and an overall multiplier to the CBET gain factor is employed; time-resolved scattered light and scattered-light spectra display the correct trends. Trajectories from backlit images are well modeled, although those from measured self-emission images indicate increased shell thickness and reduced shell density relative to simulations. Sensitivity analyses indicatemore » that the most likely cause for the density reduction is nonuniformity growth seeded by laser imprint and not laser-energy coupling. Hot-electron preheat is at tolerable levels in the ongoing experiments, although it is expected to increase after the mitigation of CBET. Future work will include continued model validation, imprint measurements, and mitigation of CBET and hot-electron preheat.« less

Validation of statistical predictive models meant to select melanoma patients for sentinel lymph node biopsy.

PubMed

Sabel, Michael S; Rice, John D; Griffith, Kent A; Lowe, Lori; Wong, Sandra L; Chang, Alfred E; Johnson, Timothy M; Taylor, Jeremy M G

2012-01-01

To identify melanoma patients at sufficiently low risk of nodal metastases who could avoid sentinel lymph node biopsy (SLNB), several statistical models have been proposed based upon patient/tumor characteristics, including logistic regression, classification trees, random forests, and support vector machines. We sought to validate recently published models meant to predict sentinel node status. We queried our comprehensive, prospectively collected melanoma database for consecutive melanoma patients undergoing SLNB. Prediction values were estimated based upon four published models, calculating the same reported metrics: negative predictive value (NPV), rate of negative predictions (RNP), and false-negative rate (FNR). Logistic regression performed comparably with our data when considering NPV (89.4 versus 93.6%); however, the model's specificity was not high enough to significantly reduce the rate of biopsies (SLN reduction rate of 2.9%). When applied to our data, the classification tree produced NPV and reduction in biopsy rates that were lower (87.7 versus 94.1 and 29.8 versus 14.3, respectively). Two published models could not be applied to our data due to model complexity and the use of proprietary software. Published models meant to reduce the SLNB rate among patients with melanoma either underperformed when applied to our larger dataset, or could not be validated. Differences in selection criteria and histopathologic interpretation likely resulted in underperformance. Statistical predictive models must be developed in a clinically applicable manner to allow for both validation and ultimately clinical utility.

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

PubMed Central

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

2017-01-01

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

Development of Detonation Modeling Capabilities for Rocket Test Facilities: Hydrogen-Oxygen-Nitrogen Mixtures

NASA Technical Reports Server (NTRS)

Allgood, Daniel C.

2016-01-01

The objective of the presented work was to develop validated computational fluid dynamics (CFD) based methodologies for predicting propellant detonations and their associated blast environments. Applications of interest were scenarios relevant to rocket propulsion test and launch facilities. All model development was conducted within the framework of the Loci/CHEM CFD tool due to its reliability and robustness in predicting high-speed combusting flow-fields associated with rocket engines and plumes. During the course of the project, verification and validation studies were completed for hydrogen-fueled detonation phenomena such as shock-induced combustion, confined detonation waves, vapor cloud explosions, and deflagration-to-detonation transition (DDT) processes. The DDT validation cases included predicting flame acceleration mechanisms associated with turbulent flame-jets and flow-obstacles. Excellent comparison between test data and model predictions were observed. The proposed CFD methodology was then successfully applied to model a detonation event that occurred during liquid oxygen/gaseous hydrogen rocket diffuser testing at NASA Stennis Space Center.

Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment

NASA Astrophysics Data System (ADS)

Parkin, G.; O'Donnell, G.; Ewen, J.; Bathurst, J. C.; O'Connell, P. E.; Lavabre, J.

1996-02-01

Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583-594) designed to address these types of application; the method involves making 'blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.

A review of simulation platforms in surgery of the temporal bone.

PubMed

Bhutta, M F

2016-10-01

Surgery of the temporal bone is a high-risk activity in an anatomically complex area. Simulation enables rehearsal of such surgery. The traditional simulation platform is the cadaveric temporal bone, but in recent years other simulation platforms have been created, including plastic and virtual reality platforms. To undertake a review of simulation platforms for temporal bone surgery, specifically assessing their educational value in terms of validity and in enabling transition to surgery. Systematic qualitative review. Search of the Pubmed, CINAHL, BEI and ERIC databases. Assessment of reported outcomes in terms of educational value. A total of 49 articles were included, covering cadaveric, animal, plastic and virtual simulation platforms. Cadaveric simulation is highly rated as an educational tool, but there may be a ceiling effect on educational outcomes after drilling 8-10 temporal bones. Animal models show significant anatomical variation from man. Plastic temporal bone models offer much potential, but at present lack sufficient anatomical or haptic validity. Similarly, virtual reality platforms lack sufficient anatomical or haptic validity, but with technological improvements they are advancing rapidly. At present, cadaveric simulation remains the best platform for training in temporal bone surgery. Technological advances enabling improved materials or modelling mean that in the future plastic or virtual platforms may become comparable to cadaveric platforms, and also offer additional functionality including patient-specific simulation from CT data. © 2015 John Wiley & Sons Ltd.

Examining Factor Structure and Validating the Persian Version of the Pregnancy's Worries and Stress Questionnaire for Pregnant Iranian Women.

PubMed

Navidpour, Fariba; Dolatian, Mahrokh; Yaghmaei, Farideh; Majd, Hamid Alavi; Hashemi, Seyed Saeed

2015-04-23

Pregnant women tend to experience anxiety and stress when faced with the changes to their biology, environment and personal relationships. The identification of these factors and the prevention of their side effects are vital for both mother and fetus. The present study was conducted to validate and to examine the factor structure of the Persian version of the Pregnancy's Worries and Stress Questionnaire. The 25-item PWSQ was first translated by specialists into Persian. The questionnaire's validity was determined using face, content, criterion and construct validity and reliability of questionnaire was examined using Cronbach's alpha. Confirmatory factor analysis was performed in AMOS and SPSS 21. Participants included healthy Iranian pregnant women (8-39 weeks) who refer to selected hospitals for prenatal care. Hospitals included private, social security and university hospitals and selected through the random cluster sampling method. The results of validity and reliability assessments of the questionnaire were acceptable. Cronbach's alpha calculated showed a high internal consistency of 0.89. The confirmatory factor analysis using the c2, CMIN/DF, IFI, CFI, NFI and NNFI indexes showed the 6-factor model to be the best fitted model for explaining the data. The questionnaire was translated into Persian to examine stress and worry specific to Iranian pregnant women. The psychometric results showed that the questionnaire is suitable for identifying Iranian pregnant women with pregnancy-related stress.

Moment method analysis of linearly tapered slot antennas

NASA Technical Reports Server (NTRS)

Koeksal, Adnan

1993-01-01

A method of moments (MOM) model for the analysis of the Linearly Tapered Slot Antenna (LTSA) is developed and implemented. The model employs an unequal size rectangular sectioning for conducting parts of the antenna. Piecewise sinusoidal basis functions are used for the expansion of conductor current. The effect of the dielectric is incorporated in the model by using equivalent volume polarization current density and solving the equivalent problem in free-space. The feed section of the antenna including the microstripline is handled rigorously in the MOM model by including slotline short circuit and microstripline currents among the unknowns. Comparison with measurements is made to demonstrate the validity of the model for both the air case and the dielectric case. Validity of the model is also verified by extending the model to handle the analysis of the skew-plate antenna and comparing the results to those of a skew-segmentation modeling results of the same structure and to available data in the literature. Variation of the radiation pattern for the air LTSA with length, height, and taper angle is investigated, and the results are tabulated. Numerical results for the effect of the dielectric thickness and permittivity are presented.

AQUATOX Model Validation Reports

EPA Pesticide Factsheets

AQUATOX has a myriad of potential applications to water management issues and programs, including water quality criteria and standards, TMDLs (Total Maximum Daily Loads), and ecological risk assessments of aquatic systems.

Review and assessment of turbulence models for hypersonic flows

NASA Astrophysics Data System (ADS)

Roy, Christopher J.; Blottner, Frederick G.

2006-10-01

Accurate aerodynamic prediction is critical for the design and optimization of hypersonic vehicles. Turbulence modeling remains a major source of uncertainty in the computational prediction of aerodynamic forces and heating for these systems. The first goal of this article is to update the previous comprehensive review of hypersonic shock/turbulent boundary-layer interaction experiments published in 1991 by Settles and Dodson (Hypersonic shock/boundary-layer interaction database. NASA CR 177577, 1991). In their review, Settles and Dodson developed a methodology for assessing experiments appropriate for turbulence model validation and critically surveyed the existing hypersonic experiments. We limit the scope of our current effort by considering only two-dimensional (2D)/axisymmetric flows in the hypersonic flow regime where calorically perfect gas models are appropriate. We extend the prior database of recommended hypersonic experiments (on four 2D and two 3D shock-interaction geometries) by adding three new geometries. The first two geometries, the flat plate/cylinder and the sharp cone, are canonical, zero-pressure gradient flows which are amenable to theory-based correlations, and these correlations are discussed in detail. The third geometry added is the 2D shock impinging on a turbulent flat plate boundary layer. The current 2D hypersonic database for shock-interaction flows thus consists of nine experiments on five different geometries. The second goal of this study is to review and assess the validation usage of various turbulence models on the existing experimental database. Here we limit the scope to one- and two-equation turbulence models where integration to the wall is used (i.e., we omit studies involving wall functions). A methodology for validating turbulence models is given, followed by an extensive evaluation of the turbulence models on the current hypersonic experimental database. A total of 18 one- and two-equation turbulence models are reviewed, and results of turbulence model assessments for the six models that have been extensively applied to the hypersonic validation database are compiled and presented in graphical form. While some of the turbulence models do provide reasonable predictions for the surface pressure, the predictions for surface heat flux are generally poor, and often in error by a factor of four or more. In the vast majority of the turbulence model validation studies we review, the authors fail to adequately address the numerical accuracy of the simulations (i.e., discretization and iterative error) and the sensitivities of the model predictions to freestream turbulence quantities or near-wall y+ mesh spacing. We recommend new hypersonic experiments be conducted which (1) measure not only surface quantities but also mean and fluctuating quantities in the interaction region and (2) provide careful estimates of both random experimental uncertainties and correlated bias errors for the measured quantities and freestream conditions. For the turbulence models, we recommend that a wide-range of turbulence models (including newer models) be re-examined on the current hypersonic experimental database, including the more recent experiments. Any future turbulence model validation efforts should carefully assess the numerical accuracy and model sensitivities. In addition, model corrections (e.g., compressibility corrections) should be carefully examined for their effects on a standard, low-speed validation database. Finally, as new experiments or direct numerical simulation data become available with information on mean and fluctuating quantities, they should be used to improve the turbulence models and thus increase their predictive capability.

Development and Validation of an Agency for Healthcare Research and Quality Indicator for Mortality After Congenital Heart Surgery Harmonized With Risk Adjustment for Congenital Heart Surgery (RACHS-1) Methodology.

PubMed

Jenkins, Kathy J; Koch Kupiec, Jennifer; Owens, Pamela L; Romano, Patrick S; Geppert, Jeffrey J; Gauvreau, Kimberlee

2016-05-20

The National Quality Forum previously approved a quality indicator for mortality after congenital heart surgery developed by the Agency for Healthcare Research and Quality (AHRQ). Several parameters of the validated Risk Adjustment for Congenital Heart Surgery (RACHS-1) method were included, but others differed. As part of the National Quality Forum endorsement maintenance process, developers were asked to harmonize the 2 methodologies. Parameters that were identical between the 2 methods were retained. AHRQ's Healthcare Cost and Utilization Project State Inpatient Databases (SID) 2008 were used to select optimal parameters where differences existed, with a goal to maximize model performance and face validity. Inclusion criteria were not changed and included all discharges for patients <18 years with International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes for congenital heart surgery or nonspecific heart surgery combined with congenital heart disease diagnosis codes. The final model includes procedure risk group, age (0-28 days, 29-90 days, 91-364 days, 1-17 years), low birth weight (500-2499 g), other congenital anomalies (Clinical Classifications Software 217, except for 758.xx), multiple procedures, and transfer-in status. Among 17 945 eligible cases in the SID 2008, the c statistic for model performance was 0.82. In the SID 2013 validation data set, the c statistic was 0.82. Risk-adjusted mortality rates by center ranged from 0.9% to 4.1% (5th-95th percentile). Congenital heart surgery programs can now obtain national benchmarking reports by applying AHRQ Quality Indicator software to hospital administrative data, based on the harmonized RACHS-1 method, with high discrimination and face validity. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Copenhagen Psychosocial Questionnaire - A validation study using the Job Demand-Resources model.

PubMed

Berthelsen, Hanne; Hakanen, Jari J; Westerlund, Hugo

2018-01-01

This study aims at investigating the nomological validity of the Copenhagen Psychosocial Questionnaire (COPSOQ II) by using an extension of the Job Demands-Resources (JD-R) model with aspects of work ability as outcome. The study design is cross-sectional. All staff working at public dental organizations in four regions of Sweden were invited to complete an electronic questionnaire (75% response rate, n = 1345). The questionnaire was based on COPSOQ II scales, the Utrecht Work Engagement scale, and the one-item Work Ability Score in combination with a proprietary item. The data was analysed by Structural Equation Modelling. This study contributed to the literature by showing that: A) The scale characteristics were satisfactory and the construct validity of COPSOQ instrument could be integrated in the JD-R framework; B) Job resources arising from leadership may be a driver of the two processes included in the JD-R model; and C) Both the health impairment and motivational processes were associated with WA, and the results suggested that leadership may impact WA, in particularly by securing task resources. In conclusion, the nomological validity of COPSOQ was supported as the JD-R model-can be operationalized by the instrument. This may be helpful for transferral of complex survey results and work life theories to practitioners in the field.

Development and validation of a mortality risk model for pediatric sepsis.

PubMed

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-05-01

Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial.We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities.According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively.The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.

Development and validation of a mortality risk model for pediatric sepsis

PubMed Central

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-01-01

Abstract Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial. We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities. According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively. The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients. PMID:28514310

Full-scale flammability test data for validation of aircraft fire mathematical models

NASA Technical Reports Server (NTRS)

Kuminecz, J. F.; Bricker, R. W.

1982-01-01

Twenty-five large scale aircraft flammability tests were conducted in a Boeing 737 fuselage at the NASA Johnson Space Center (JSC). The objective of this test program was to provide a data base on the propagation of large scale aircraft fires to support the validation of aircraft fire mathematical models. Variables in the test program included cabin volume, amount of fuel, fuel pan area, fire location, airflow rate, and cabin materials. A number of tests were conducted with jet A-1 fuel only, while others were conducted with various Boeing 747 type cabin materials. These included urethane foam seats, passenger service units, stowage bins, and wall and ceiling panels. Two tests were also included using special urethane foam and polyimide foam seats. Tests were conducted with each cabin material individually, with various combinations of these materials, and finally, with all materials in the cabin. The data include information obtained from approximately 160 locations inside the fuselage.

OWL-based reasoning methods for validating archetypes.

PubMed

Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2013-04-01

Some modern Electronic Healthcare Record (EHR) architectures and standards are based on the dual model-based architecture, which defines two conceptual levels: reference model and archetype model. Such architectures represent EHR domain knowledge by means of archetypes, which are considered by many researchers to play a fundamental role for the achievement of semantic interoperability in healthcare. Consequently, formal methods for validating archetypes are necessary. In recent years, there has been an increasing interest in exploring how semantic web technologies in general, and ontologies in particular, can facilitate the representation and management of archetypes, including binding to terminologies, but no solution based on such technologies has been provided to date to validate archetypes. Our approach represents archetypes by means of OWL ontologies. This permits to combine the two levels of the dual model-based architecture in one modeling framework which can also integrate terminologies available in OWL format. The validation method consists of reasoning on those ontologies to find modeling errors in archetypes: incorrect restrictions over the reference model, non-conformant archetype specializations and inconsistent terminological bindings. The archetypes available in the repositories supported by the openEHR Foundation and the NHS Connecting for Health Program, which are the two largest publicly available ones, have been analyzed with our validation method. For such purpose, we have implemented a software tool called Archeck. Our results show that around 1/5 of archetype specializations contain modeling errors, the most common mistakes being related to coded terms and terminological bindings. The analysis of each repository reveals that different patterns of errors are found in both repositories. This result reinforces the need for making serious efforts in improving archetype design processes. Copyright © 2012 Elsevier Inc. All rights reserved.

The Development of a Secondary-Level Solo Wind Instrument Performance Rubric Using the Multifaceted Rasch Partial Credit Measurement Model

ERIC Educational Resources Information Center

Wesolowski, Brian C.; Amend, Ross M.; Barnstead, Thomas S.; Edwards, Andrew S.; Everhart, Matthew; Goins, Quentin R.; Grogan, Robert J., III; Herceg, Amanda M.; Jenkins, S. Ira; Johns, Paul M.; McCarver, Christopher J.; Schaps, Robin E.; Sorrell, Gary W.; Williams, Jonathan D.

2017-01-01

The purpose of this study was to describe the development of a valid and reliable rubric to assess secondary-level solo instrumental music performance based on principles of invariant measurement. The research questions that guided this study included (1) What is the psychometric quality (i.e., validity, reliability, and precision) of a scale…

Trait and state anxiety across academic evaluative contexts: development and validation of the MTEA-12 and MSEA-12 scales.

PubMed

Sotardi, Valerie A

2018-05-01

Educational measures of anxiety focus heavily on students' experiences with tests yet overlook other assessment contexts. In this research, two brief multiscale questionnaires were developed and validated to measure trait evaluation anxiety (MTEA-12) and state evaluation anxiety (MSEA-12) for use in various assessment contexts in non-clinical, educational settings. The research included a cross-sectional analysis of self-report data using authentic assessment settings in which evaluation anxiety was measured. Instruments were tested using a validation sample of 241 first-year university students in New Zealand. Scale development included component structures for state and trait scales based on existing theoretical frameworks. Analyses using confirmatory factor analysis and descriptive statistics indicate that the scales are reliable and structurally valid. Multivariate general linear modeling using subscales from the MTEA-12, MSEA-12, and student grades suggest adequate criterion-related validity. Initial predictive validity in which one relevant MTEA-12 factor explained between 21% and 54% of the variance in three MSEA-12 factors. Results document MTEA-12 and MSEA-12 as reliable measures of trait and state dimensions of evaluation anxiety for test and writing contexts. Initial estimates suggest the scales as having promising validity, and recommendations for further validation are outlined.

Numerical Modelling of Femur Fracture and Experimental Validation Using Bone Simulant.

PubMed

Marco, Miguel; Giner, Eugenio; Larraínzar-Garijo, Ricardo; Caeiro, José Ramón; Miguélez, María Henar

2017-10-01

Bone fracture pattern prediction is still a challenge and an active field of research. The main goal of this article is to present a combined methodology (experimental and numerical) for femur fracture onset analysis. Experimental work includes the characterization of the mechanical properties and fracture testing on a bone simulant. The numerical work focuses on the development of a model whose material properties are provided by the characterization tests. The fracture location and the early stages of the crack propagation are modelled using the extended finite element method and the model is validated by fracture tests developed in the experimental work. It is shown that the accuracy of the numerical results strongly depends on a proper bone behaviour characterization.

Supersonic Combustion Research at NASA

NASA Technical Reports Server (NTRS)

Drummond, J. P.; Danehy, Paul M.; Gaffney, Richard L., Jr.; Tedder, Sarah A.; Cutler, Andrew D.; Bivolaru, Daniel

2007-01-01

This paper discusses the progress of work to model high-speed supersonic reacting flow. The purpose of the work is to improve the state of the art of CFD capabilities for predicting the flow in high-speed propulsion systems, particularly combustor flowpaths. The program has several components including the development of advanced algorithms and models for simulating engine flowpaths as well as a fundamental experimental and diagnostic development effort to support the formulation and validation of the mathematical models. The paper will provide details of current work on experiments that will provide data for the modeling efforts along with the associated nonintrusive diagnostics used to collect the data from the experimental flowfield. Simulation of a recent experiment to partially validate the accuracy of a combustion code is also described.

Physical models for the normal YORP and diurnal Yarkovsky effects

NASA Astrophysics Data System (ADS)

Golubov, O.; Kravets, Y.; Krugly, Yu. N.; Scheeres, D. J.

2016-06-01

We propose an analytic model for the normal Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) and diurnal Yarkovsky effects experienced by a convex asteroid. Both the YORP torque and the Yarkovsky force are expressed as integrals of a universal function over the surface of an asteroid. Although in general this function can only be calculated numerically from the solution of the heat conductivity equation, approximate solutions can be obtained in quadratures for important limiting cases. We consider three such simplified models: Rubincam's approximation (zero heat conductivity), low thermal inertia limit (including the next order correction and thus valid for small heat conductivity), and high thermal inertia limit (valid for large heat conductivity). All three simplified models are compared with the exact solution.

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Modeling Combustion in Supersonic Flows

NASA Technical Reports Server (NTRS)

Drummond, J. Philip; Danehy, Paul M.; Bivolaru, Daniel; Gaffney, Richard L.; Tedder, Sarah A.; Cutler, Andrew D.

2007-01-01

This paper discusses the progress of work to model high-speed supersonic reacting flow. The purpose of the work is to improve the state of the art of CFD capabilities for predicting the flow in high-speed propulsion systems, particularly combustor flow-paths. The program has several components including the development of advanced algorithms and models for simulating engine flowpaths as well as a fundamental experimental and diagnostic development effort to support the formulation and validation of the mathematical models. The paper will provide details of current work on experiments that will provide data for the modeling efforts along with with the associated nonintrusive diagnostics used to collect the data from the experimental flowfield. Simulation of a recent experiment to partially validate the accuracy of a combustion code is also described.

SHERMAN, a shape-based thermophysical model. I. Model description and validation

NASA Astrophysics Data System (ADS)

Magri, Christopher; Howell, Ellen S.; Vervack, Ronald J.; Nolan, Michael C.; Fernández, Yanga R.; Marshall, Sean E.; Crowell, Jenna L.

2018-03-01

SHERMAN, a new thermophysical modeling package designed for analyzing near-infrared spectra of asteroids and other solid bodies, is presented. The model's features, the methods it uses to solve for surface and subsurface temperatures, and the synthetic data it outputs are described. A set of validation tests demonstrates that SHERMAN produces accurate output in a variety of special cases for which correct results can be derived from theory. These cases include a family of solutions to the heat equation for which thermal inertia can have any value and thermophysical properties can vary with depth and with temperature. An appendix describes a new approximation method for estimating surface temperatures within spherical-section craters, more suitable for modeling infrared beaming at short wavelengths than the standard method.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

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

Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.« less

Validation of lumbar spine loading from a musculoskeletal model including the lower limbs and lumbar spine.

PubMed

Actis, Jason A; Honegger, Jasmin D; Gates, Deanna H; Petrella, Anthony J; Nolasco, Luis A; Silverman, Anne K

2018-02-08

Low back mechanics are important to quantify to study injury, pain and disability. As in vivo forces are difficult to measure directly, modeling approaches are commonly used to estimate these forces. Validation of model estimates is critical to gain confidence in modeling results across populations of interest, such as people with lower-limb amputation. Motion capture, ground reaction force and electromyographic data were collected from ten participants without an amputation (five male/five female) and five participants with a unilateral transtibial amputation (four male/one female) during trunk-pelvis range of motion trials in flexion/extension, lateral bending and axial rotation. A musculoskeletal model with a detailed lumbar spine and the legs including 294 muscles was used to predict L4-L5 loading and muscle activations using static optimization. Model estimates of L4-L5 intervertebral joint loading were compared to measured intradiscal pressures from the literature and muscle activations were compared to electromyographic signals. Model loading estimates were only significantly different from experimental measurements during trunk extension for males without an amputation and for people with an amputation, which may suggest a greater portion of L4-L5 axial load transfer through the facet joints, as facet loads are not captured by intradiscal pressure transducers. Pressure estimates between the model and previous work were not significantly different for flexion, lateral bending or axial rotation. Timing of model-estimated muscle activations compared well with electromyographic activity of the lumbar paraspinals and upper erector spinae. Validated estimates of low back loading can increase the applicability of musculoskeletal models to clinical diagnosis and treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

The development of an integrated assessment instrument for measuring analytical thinking and science process skills

NASA Astrophysics Data System (ADS)

Irwanto, Rohaeti, Eli; LFX, Endang Widjajanti; Suyanta

2017-05-01

This research aims to develop instrument and determine the characteristics of an integrated assessment instrument. This research uses 4-D model, which includes define, design, develop, and disseminate. The primary product is validated by expert judgment, tested it's readability by students, and assessed it's feasibility by chemistry teachers. This research involved 246 students of grade XI of four senior high schools in Yogyakarta, Indonesia. Data collection techniques include interview, questionnaire, and test. Data collection instruments include interview guideline, item validation sheet, users' response questionnaire, instrument readability questionnaire, and essay test. The results show that the integrated assessment instrument has Aiken validity value of 0.95. Item reliability was 0.99 and person reliability was 0.69. Teachers' response to the integrated assessment instrument is very good. Therefore, the integrated assessment instrument is feasible to be applied to measure the students' analytical thinking and science process skills.

Computational fluid dynamics modeling of laboratory flames and an industrial flare.

PubMed

Singh, Kanwar Devesh; Gangadharan, Preeti; Chen, Daniel H; Lou, Helen H; Li, Xianchang; Richmond, Peyton

2014-11-01

A computational fluid dynamics (CFD) methodology for simulating the combustion process has been validated with experimental results. Three different types of experimental setups were used to validate the CFD model. These setups include an industrial-scale flare setups and two lab-scale flames. The CFD study also involved three different fuels: C3H6/CH/Air/N2, C2H4/O2/Ar and CH4/Air. In the first setup, flare efficiency data from the Texas Commission on Environmental Quality (TCEQ) 2010 field tests were used to validate the CFD model. In the second setup, a McKenna burner with flat flames was simulated. Temperature and mass fractions of important species were compared with the experimental data. Finally, results of an experimental study done at Sandia National Laboratories to generate a lifted jet flame were used for the purpose of validation. The reduced 50 species mechanism, LU 1.1, the realizable k-epsilon turbulence model, and the EDC turbulence-chemistry interaction model were usedfor this work. Flare efficiency, axial profiles of temperature, and mass fractions of various intermediate species obtained in the simulation were compared with experimental data and a good agreement between the profiles was clearly observed. In particular the simulation match with the TCEQ 2010 flare tests has been significantly improved (within 5% of the data) compared to the results reported by Singh et al. in 2012. Validation of the speciated flat flame data supports the view that flares can be a primary source offormaldehyde emission.

Review of TRMM/GPM Rainfall Algorithm Validation

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

A review is presented concerning current progress on evaluation and validation of standard Tropical Rainfall Measuring Mission (TRMM) precipitation retrieval algorithms and the prospects for implementing an improved validation research program for the next generation Global Precipitation Measurement (GPM) Mission. All standard TRMM algorithms are physical in design, and are thus based on fundamental principles of microwave radiative transfer and its interaction with semi-detailed cloud microphysical constituents. They are evaluated for consistency and degree of equivalence with one another, as well as intercompared to radar-retrieved rainfall at TRMM's four main ground validation sites. Similarities and differences are interpreted in the context of the radiative and microphysical assumptions underpinning the algorithms. Results indicate that the current accuracies of the TRMM Version 6 algorithms are approximately 15% at zonal-averaged / monthly scales with precisions of approximately 25% for full resolution / instantaneous rain rate estimates (i.e., level 2 retrievals). Strengths and weaknesses of the TRMM validation approach are summarized. Because the dew of convergence of level 2 TRMM algorithms is being used as a guide for setting validation requirements for the GPM mission, it is important that the GPM algorithm validation program be improved to ensure concomitant improvement in the standard GPM retrieval algorithms. An overview of the GPM Mission's validation plan is provided including a description of a new type of physical validation model using an analytic 3-dimensional radiative transfer model.

Investigating Mechanisms of Chronic Kidney Disease in Mouse Models

PubMed Central

Eddy, Allison A.; Okamura, Daryl M.; Yamaguchi, Ikuyo; López-Guisa, Jesús M.

2011-01-01

Animal models of chronic kidney disease (CKD) are important experimental tools that are used to investigate novel mechanistic pathways and to validate potential new therapeutic interventions prior to pre-clinical testing in humans. Over the past several years, mouse CKD models have been extensively used for these purposes. Despite significant limitations, the model of unilateral ureteral obstruction (UUO) has essentially become the high throughput in vivo model, as it recapitulates the fundamental pathogenetic mechanisms that typify all forms of CKD in a relatively short time span. In addition, several alternative mouse models are available that can be used to validate new mechanistic paradigms and/or novel therapies. Several models are reviewed – both genetic and experimentally induced – that provide investigators with an opportunity to include renal functional study end-points together with quantitative measures of fibrosis severity, something that is not possible with the UUO model. PMID:21695449

Measuring nursing competencies in the operating theatre: instrument development and psychometric analysis using Item Response Theory.

PubMed

Nicholson, Patricia; Griffin, Patrick; Gillis, Shelley; Wu, Margaret; Dunning, Trisha

2013-09-01

Concern about the process of identifying underlying competencies that contribute to effective nursing performance has been debated with a lack of consensus surrounding an approved measurement instrument for assessing clinical performance. Although a number of methodologies are noted in the development of competency-based assessment measures, these studies are not without criticism. The primary aim of the study was to develop and validate a Performance Based Scoring Rubric, which included both analytical and holistic scales. The aim included examining the validity and reliability of the rubric, which was designed to measure clinical competencies in the operating theatre. The fieldwork observations of 32 nurse educators and preceptors assessing the performance of 95 instrument nurses in the operating theatre were used in the calibration of the rubric. The Rasch model, a particular model among Item Response Models, was used in the calibration of each item in the rubric in an attempt at improving the measurement properties of the scale. This is done by establishing the 'fit' of the data to the conditions demanded by the Rasch model. Acceptable reliability estimates, specifically a high Cronbach's alpha reliability coefficient (0.940), as well as empirical support for construct and criterion validity for the rubric were achieved. Calibration of the Performance Based Scoring Rubric using Rasch model revealed that the fit statistics for most items were acceptable. The use of the Rasch model offers a number of features in developing and refining healthcare competency-based assessments, improving confidence in measuring clinical performance. The Rasch model was shown to be useful in developing and validating a competency-based assessment for measuring the competence of the instrument nurse in the operating theatre with implications for use in other areas of nursing practice. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Derivation and validation of in-hospital mortality prediction models in ischaemic stroke patients using administrative data.

PubMed

Lee, Jason; Morishima, Toshitaka; Kunisawa, Susumu; Sasaki, Noriko; Otsubo, Tetsuya; Ikai, Hiroshi; Imanaka, Yuichi

2013-01-01

Stroke and other cerebrovascular diseases are a major cause of death and disability. Predicting in-hospital mortality in ischaemic stroke patients can help to identify high-risk patients and guide treatment approaches. Chart reviews provide important clinical information for mortality prediction, but are laborious and limiting in sample sizes. Administrative data allow for large-scale multi-institutional analyses but lack the necessary clinical information for outcome research. However, administrative claims data in Japan has seen the recent inclusion of patient consciousness and disability information, which may allow more accurate mortality prediction using administrative data alone. The aim of this study was to derive and validate models to predict in-hospital mortality in patients admitted for ischaemic stroke using administrative data. The sample consisted of 21,445 patients from 176 Japanese hospitals, who were randomly divided into derivation and validation subgroups. Multivariable logistic regression models were developed using 7- and 30-day and overall in-hospital mortality as dependent variables. Independent variables included patient age, sex, comorbidities upon admission, Japan Coma Scale (JCS) score, Barthel Index score, modified Rankin Scale (mRS) score, and admissions after hours and on weekends/public holidays. Models were developed in the derivation subgroup, and coefficients from these models were applied to the validation subgroup. Predictive ability was analysed using C-statistics; calibration was evaluated with Hosmer-Lemeshow χ(2) tests. All three models showed predictive abilities similar or surpassing that of chart review-based models. The C-statistics were highest in the 7-day in-hospital mortality prediction model, at 0.906 and 0.901 in the derivation and validation subgroups, respectively. For the 30-day in-hospital mortality prediction models, the C-statistics for the derivation and validation subgroups were 0.893 and 0.872, respectively; in overall in-hospital mortality prediction these values were 0.883 and 0.876. In this study, we have derived and validated in-hospital mortality prediction models for three different time spans using a large population of ischaemic stroke patients in a multi-institutional analysis. The recent inclusion of JCS, Barthel Index, and mRS scores in Japanese administrative data has allowed the prediction of in-hospital mortality with accuracy comparable to that of chart review analyses. The models developed using administrative data had consistently high predictive abilities for all models in both the derivation and validation subgroups. These results have implications in the role of administrative data in future mortality prediction analyses. Copyright © 2013 S. Karger AG, Basel.

Validation of asphalt mixture pavement skid prediction model and development of skid prediction model for surface treatments.

DOT National Transportation Integrated Search

2017-04-01

Pavement skid resistance is primarily a function of the surface texture, which includes both microtexture and macrotexture. Earlier, under the Texas Department of Transportation (TxDOT) Research Project 0-5627, the researchers developed a method to p...

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.

Ecological validity of cost-effectiveness models of universal HPV vaccination: a protocol for a systematic review.

PubMed

Favato, Giampiero; Noikokyris, Emmanouil; Vecchiato, Riccardo

2017-01-25

Sexually transmitted infection with high-risk, oncogenic strains of human papillomavirus (HPV) still induces a relevant burden of diseases on both men and women. Although vaccines appear to be highly efficacious in preventing the infection of the most common high-risk strains (HPV 6, 11, 16, 18), important questions regarding the appropriate target population for prophylactic vaccination are still debated. Models in the extant literature seem to converge on the cost-effectiveness of high coverage (>80%) of a single cohort of 12-year-old girls. This vaccination strategy should provide an adequate level of indirect protection (herd immunity) to the unvaccinated boys. This argument presupposes the ecological validity of the cost-effectiveness models; the implicit condition that the characteristics of the individuals and the sexual behaviours observed in the models is generalisable to the natural behaviours of the population. The primary aim of this review is to test the ecological validity of the cost-effectiveness models of universal HPV vaccination available in the literature. The ecological validity of each model will be defined by the number of representative characteristics and behaviours taken into consideration. Nine bibliographic databases will be searched: MEDLINE (via PubMed); Scopus; Science Direct; EMBASE via OVID SP, Web of Science, DARE, NHIR EED and HTA (via NHIR CRD); and CINHAL Plus. An additional search for grey literature will be conducted on Google Scholar and Open Grey. A search strategy will be developed for each of the databases. Data will be extracted following a pre-determined spreadsheet and then clustered and prioritised: the main outcomes will report the inputs to the demographic and epidemiological model, while additional outcomes will refer to basic inputs to the cost-effectiveness valuation. Each study included in the review will be scored by the number of representative characteristics and behaviours taken into consideration (yes or no) on both dimensions. Individual study's scores will be plotted in a 2 by 2 matrix: studies included in the upper right quadrant will be defined as ecologically valid, since which both individuals' characteristics and their sexual behaviours are representative. The proposed systematic review will be the first to assess the ecological validity of cost-effectiveness studies. In the context of sexually transmitted diseases, when this condition is violated, an error in predicting the protective impact of herd immunity would occur. Hence, a vaccination policy informed on ecologically invalid models would potentially expose boys to a residual risk of contracting HPV-induced malignancies. PROSPERO CRD42016034145.

An RL10A-3-3A rocket engine model using the rocket engine transient simulator (ROCETS) software

NASA Technical Reports Server (NTRS)

Binder, Michael

1993-01-01

Steady-state and transient computer models of the RL10A-3-3A rocket engine have been created using the Rocket Engine Transient Simulation (ROCETS) code. These models were created for several purposes. The RL10 engine is a critical component of past, present, and future space missions; the model will give NASA an in-house capability to simulate the performance of the engine under various operating conditions and mission profiles. The RL10 simulation activity is also an opportunity to further validate the ROCETS program. The ROCETS code is an important tool for modeling rocket engine systems at NASA Lewis. ROCETS provides a modular and general framework for simulating the steady-state and transient behavior of any desired propulsion system. Although the ROCETS code is being used in a number of different analysis and design projects within NASA, it has not been extensively validated for any system using actual test data. The RL10A-3-3A has a ten year history of test and flight applications; it should provide sufficient data to validate the ROCETS program capability. The ROCETS models of the RL10 system were created using design information provided by Pratt & Whitney, the engine manufacturer. These models are in the process of being validated using test-stand and flight data. This paper includes a brief description of the models and comparison of preliminary simulation output against flight and test-stand data.

[Establishment and validation of normal human L1-L5 lumbar three-dimensional finite element model].

PubMed

Zhu, Zhenqi; Liu, Chenjun; Wang, Jiefu; Wang, Kaifeng; Huang, Zhixin; Wang, Weida; Liu, Haiying

2014-10-14

To create and validate a L1-L5 lumbar three-dimensional finite element model. The L1-L5 lumbar spines of a male healthy volunteer were scanned with computed tomography (CT). And a L1-L5 lumbar three-dimensional finite element model was created with the aid of software packages of Mimics, Geomagic and Ansys. Then border conditions were set, unit type was determined, finite element mesh was divided and a model was established for loading and calculating. Average model stiffness under the conditions of flexion, extension, lateral bending and axial rotation was calculated and compared with the outcomes of former articles for validation. A normal human L1-L5 lumbar three-dimensional finite element model was established to include 459 340 elements and 661 938 nodes. After constraining the inferior endplate of L5 vertebral body, 500 kg × m × s⁻² compressive loading was imposed averagely on the superior endplate of L1 vertebral body. Then 10 kg × m² × s⁻² moment simulating flexion, extension, lateral bending and axial rotation were imposed on the superior endplate of L1 vertebral body. Eventually the average stiffness of all directions was calculated and it was similar to the outcomes of former articles. The L1-L5 lumbar three-dimensional finite element model is validated so that it may used with biomechanical simulation and analysis of normal or surgical models.

Validation of Statistical Predictive Models Meant to Select Melanoma Patients for Sentinel Lymph Node Biopsy

PubMed Central

Sabel, Michael S.; Rice, John D.; Griffith, Kent A.; Lowe, Lori; Wong, Sandra L.; Chang, Alfred E.; Johnson, Timothy M.; Taylor, Jeremy M.G.

2013-01-01

Introduction To identify melanoma patients at sufficiently low risk of nodal metastases who could avoid SLN biopsy (SLNB). Several statistical models have been proposed based upon patient/tumor characteristics, including logistic regression, classification trees, random forests and support vector machines. We sought to validate recently published models meant to predict sentinel node status. Methods We queried our comprehensive, prospectively-collected melanoma database for consecutive melanoma patients undergoing SLNB. Prediction values were estimated based upon 4 published models, calculating the same reported metrics: negative predictive value (NPV), rate of negative predictions (RNP), and false negative rate (FNR). Results Logistic regression performed comparably with our data when considering NPV (89.4% vs. 93.6%); however the model’s specificity was not high enough to significantly reduce the rate of biopsies (SLN reduction rate of 2.9%). When applied to our data, the classification tree produced NPV and reduction in biopsies rates that were lower 87.7% vs. 94.1% and 29.8% vs. 14.3%, respectively. Two published models could not be applied to our data due to model complexity and the use of proprietary software. Conclusions Published models meant to reduce the SLNB rate among patients with melanoma either underperformed when applied to our larger dataset, or could not be validated. Differences in selection criteria and histopathologic interpretation likely resulted in underperformance. Development of statistical predictive models must be created in a clinically applicable manner to allow for both validation and ultimately clinical utility. PMID:21822550

The NETL MFiX Suite of multiphase flow models: A brief review and recent applications of MFiX-TFM to fossil energy technologies

DOE PAGES

Li, Tingwen; Rogers, William A.; Syamlal, Madhava; ...

2016-07-29

Here, the MFiX suite of multiphase computational fluid dynamics (CFD) codes is being developed at U.S. Department of Energy's National Energy Technology Laboratory (NETL). It includes several different approaches to multiphase simulation: MFiX-TFM, a two-fluid (Eulerian–Eulerian) model; MFiX-DEM, an Eulerian fluid model with a Lagrangian Discrete Element Model for the solids phase; and MFiX-PIC, Eulerian fluid model with Lagrangian particle ‘parcels’ representing particle groups. These models are undergoing continuous development and application, with verification, validation, and uncertainty quantification (VV&UQ) as integrated activities. After a brief summary of recent progress in the verification, validation and uncertainty quantification (VV&UQ), this article highlightsmore » two recent accomplishments in the application of MFiX-TFM to fossil energy technology development. First, recent application of MFiX to the pilot-scale KBR TRIG™ Transport Gasifier located at DOE's National Carbon Capture Center (NCCC) is described. Gasifier performance over a range of operating conditions was modeled and compared to NCCC operational data to validate the ability of the model to predict parametric behavior. Second, comparison of code predictions at a detailed fundamental scale is presented studying solid sorbents for the post-combustion capture of CO 2 from flue gas. Specifically designed NETL experiments are being used to validate hydrodynamics and chemical kinetics for the sorbent-based carbon capture process.« less

Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

PubMed

Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

2017-07-15

The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p < 0.0001). The alternative predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA.

PubMed

Chen, Po-Yi; Yang, Chien-Ming; Morin, Charles M

2015-05-01

The purpose of this study is to examine the factor structure of the Insomnia Severity Index (ISI) across samples recruited from different countries. We tried to identify the most appropriate factor model for the ISI and further examined the measurement invariance property of the ISI across samples from different countries. Our analyses included one data set collected from a Taiwanese sample and two data sets obtained from samples in Hong Kong and Canada. The data set collected in Taiwan was analyzed with ordinal exploratory factor analysis (EFA) to obtain the appropriate factor model for the ISI. After that, we conducted a series of confirmatory factor analyses (CFAs), which is a special case of the structural equation model (SEM) that concerns the parameters in the measurement model, to the statistics collected in Canada and Hong Kong. The purposes of these CFA were to cross-validate the result obtained from EFA and further examine the cross-cultural measurement invariance of the ISI. The three-factor model outperforms other models in terms of global fit indices in Taiwan's population. Its external validity is also supported by confirmatory factor analyses. Furthermore, the measurement invariance analyses show that the strong invariance property between the samples from different cultures holds, providing evidence that the ISI results obtained in different cultures are comparable. The factorial validity of the ISI is stable in different populations. More importantly, its invariance property across cultures suggests that the ISI is a valid measure of the insomnia severity construct across countries. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying novel interventional strategies for psychiatric disorders: integrating genomics, 'enviromics' and gene-environment interactions in valid preclinical models.

PubMed

McOmish, Caitlin E; Burrows, Emma L; Hannan, Anthony J

2014-10-01

Psychiatric disorders affect a substantial proportion of the population worldwide. This high prevalence, combined with the chronicity of the disorders and the major social and economic impacts, creates a significant burden. As a result, an important priority is the development of novel and effective interventional strategies for reducing incidence rates and improving outcomes. This review explores the progress that has been made to date in establishing valid animal models of psychiatric disorders, while beginning to unravel the complex factors that may be contributing to the limitations of current methodological approaches. We propose some approaches for optimizing the validity of animal models and developing effective interventions. We use schizophrenia and autism spectrum disorders as examples of disorders for which development of valid preclinical models, and fully effective therapeutics, have proven particularly challenging. However, the conclusions have relevance to various other psychiatric conditions, including depression, anxiety and bipolar disorders. We address the key aspects of construct, face and predictive validity in animal models, incorporating genetic and environmental factors. Our understanding of psychiatric disorders is accelerating exponentially, revealing extraordinary levels of genetic complexity, heterogeneity and pleiotropy. The environmental factors contributing to individual, and multiple, disorders also exhibit breathtaking complexity, requiring systematic analysis to experimentally explore the environmental mediators and modulators which constitute the 'envirome' of each psychiatric disorder. Ultimately, genetic and environmental factors need to be integrated via animal models incorporating the spatiotemporal complexity of gene-environment interactions and experience-dependent plasticity, thus better recapitulating the dynamic nature of brain development, function and dysfunction. © 2014 The British Pharmacological Society.

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

MAVRIC Flutter Model Transonic Limit Cycle Oscillation Test

NASA Technical Reports Server (NTRS)

Edwards, John W.; Schuster, David M.; Spain, Charles V.; Keller, Donald F.; Moses, Robert W.

2001-01-01

The Models for Aeroelastic Validation Research Involving Computation semi-span wind-tunnel model (MAVRIC-I), a business jet wing-fuselage flutter model, was tested in NASA Langley's Transonic Dynamics Tunnel with the goal of obtaining experimental data suitable for Computational Aeroelasticity code validation at transonic separation onset conditions. This research model is notable for its inexpensive construction and instrumentation installation procedures. Unsteady pressures and wing responses were obtained for three wingtip configurations of clean, tipstore, and winglet. Traditional flutter boundaries were measured over the range of M = 0.6 to 0.9 and maps of Limit Cycle Oscillation (LCO) behavior were made in the range of M = 0.85 to 0.95. Effects of dynamic pressure and angle-of-attack were measured. Testing in both R134a heavy gas and air provided unique data on Reynolds number, transition effects, and the effect of speed of sound on LCO behavior. The data set provides excellent code validation test cases for the important class of flow conditions involving shock-induced transonic flow separation onset at low wing angles, including LCO behavior.

Development and Validation of High Precision Thermal, Mechanical, and Optical Models for the Space Interferometry Mission

NASA Technical Reports Server (NTRS)

Lindensmith, Chris A.; Briggs, H. Clark; Beregovski, Yuri; Feria, V. Alfonso; Goullioud, Renaud; Gursel, Yekta; Hahn, Inseob; Kinsella, Gary; Orzewalla, Matthew; Phillips, Charles

2006-01-01

SIM Planetquest (SIM) is a large optical interferometer for making microarcsecond measurements of the positions of stars, and to detect Earth-sized planets around nearby stars. To achieve this precision, SIM requires stability of optical components to tens of picometers per hour. The combination of SIM s large size (9 meter baseline) and the high stability requirement makes it difficult and costly to measure all aspects of system performance on the ground. To reduce risks, costs and to allow for a design with fewer intermediate testing stages, the SIM project is developing an integrated thermal, mechanical and optical modeling process that will allow predictions of the system performance to be made at the required high precision. This modeling process uses commercial, off-the-shelf tools and has been validated against experimental results at the precision of the SIM performance requirements. This paper presents the description of the model development, some of the models, and their validation in the Thermo-Opto-Mechanical (TOM3) testbed which includes full scale brassboard optical components and the metrology to test them at the SIM performance requirement levels.

MAVRIC Flutter Model Transonic Limit Cycle Oscillation Test

NASA Technical Reports Server (NTRS)

Edwards, John W.; Schuster, David M.; Spain, Charles V.; Keller, Donald F.; Moses, Robert W.

2001-01-01

The Models for Aeroelastic Validation Research Involving Computation semi-span wind-tunnel model (MAVRIC-I), a business jet wing-fuselage flutter model, was tested in NASA Langley's Transonic Dynamics Tunnel with the goal of obtaining experimental data suitable for Computational Aeroelasticity code validation at transonic separation onset conditions. This research model is notable for its inexpensive construction and instrumentation installation procedures. Unsteady pressures and wing responses were obtained for three wingtip configurations clean, tipstore, and winglet. Traditional flutter boundaries were measured over the range of M = 0.6 to 0.9 and maps of Limit Cycle Oscillation (LCO) behavior were made in the range of M = 0.85 to 0.95. Effects of dynamic pressure and angle-of-attack were measured. Testing in both R134a heavy gas and air provided unique data on Reynolds number, transition effects, and the effect of speed of sound on LCO behavior. The data set provides excellent code validation test cases for the important class of flow conditions involving shock-induced transonic flow separation onset at low wing angles, including Limit Cycle Oscillation behavior.

Simulation Modeling for Off-Nominal Conditions - Where Are We Today?

NASA Technical Reports Server (NTRS)

Shah, Gautam H.; Foster, John V.; Cunningham, Kevin

2010-01-01

The modeling of aircraft flight characteris4cs in off-nominal or otherwise adverse conditions has become increasingly important for simulation in the loss-of-control arena. Adverse conditions include environmentally-induced upsets such as wind shear or wake vortex encounters; off-nominal flight conditions, such as stall or departure; on-board systems failures; and structural failures or aircraft damage. Spirited discussions in the research community are taking place as to the fidelity and data requirements for adequate representation of vehicle dynamics under such conditions for a host of research areas, including recovery training, flight controls development, trajectory guidance/planning, and envelope limiting. The increasing need for multiple sources of data (empirical, computational, experimental) for modeling across a larger flight envelope leads to challenges in developing methods of appropriately applying or combining such data, particularly in a dynamic flight environment with a physically and/or aerodynamically asymmetric vehicle. Traditional simplifications and symmetry assumptions in current modeling methodology may no longer be valid. Furthermore, once modeled, challenges abound in the validation of flight dynamics characteristics in adverse flight regimes

Finite Element Model of the Knee for Investigation of Injury Mechanisms: Development and Validation

PubMed Central

Kiapour, Ali; Kiapour, Ata M.; Kaul, Vikas; Quatman, Carmen E.; Wordeman, Samuel C.; Hewett, Timothy E.; Demetropoulos, Constantine K.; Goel, Vijay K.

2014-01-01

Multiple computational models have been developed to study knee biomechanics. However, the majority of these models are mainly validated against a limited range of loading conditions and/or do not include sufficient details of the critical anatomical structures within the joint. Due to the multifactorial dynamic nature of knee injuries, anatomic finite element (FE) models validated against multiple factors under a broad range of loading conditions are necessary. This study presents a validated FE model of the lower extremity with an anatomically accurate representation of the knee joint. The model was validated against tibiofemoral kinematics, ligaments strain/force, and articular cartilage pressure data measured directly from static, quasi-static, and dynamic cadaveric experiments. Strong correlations were observed between model predictions and experimental data (r > 0.8 and p < 0.0005 for all comparisons). FE predictions showed low deviations (root-mean-square (RMS) error) from average experimental data under all modes of static and quasi-static loading, falling within 2.5 deg of tibiofemoral rotation, 1% of anterior cruciate ligament (ACL) and medial collateral ligament (MCL) strains, 17 N of ACL load, and 1 mm of tibiofemoral center of pressure. Similarly, the FE model was able to accurately predict tibiofemoral kinematics and ACL and MCL strains during simulated bipedal landings (dynamic loading). In addition to minimal deviation from direct cadaveric measurements, all model predictions fell within 95% confidence intervals of the average experimental data. Agreement between model predictions and experimental data demonstrates the ability of the developed model to predict the kinematics of the human knee joint as well as the complex, nonuniform stress and strain fields that occur in biological soft tissue. Such a model will facilitate the in-depth understanding of a multitude of potential knee injury mechanisms with special emphasis on ACL injury. PMID:24763546

The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

PubMed

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2014-03-01

We present a novel approach to generating fragment-based molecular descriptors. The molecules are represented by labeled undirected chemical graph. Fast Frequent Subgraph Mining (FFSM) is used to find chemical-fragments (subgraphs) that occur in at least a subset of all molecules in a dataset. The collection of frequent subgraphs (FSG) forms a dataset-specific descriptors whose values for each molecule are defined by the number of times each frequent fragment occurs in this molecule. We have employed the FSG descriptors to develop variable selection k Nearest Neighbor (kNN) QSAR models of several datasets with binary target property including Maximum Recommended Therapeutic Dose (MRTD), Salmonella Mutagenicity (Ames Genotoxicity), and P-Glycoprotein (PGP) data. Each dataset was divided into training, test, and validation sets to establish the statistical figures of merit reflecting the model validated predictive power. The classification accuracies of models for both training and test sets for all datasets exceeded 75 %, and the accuracy for the external validation sets exceeded 72 %. The model accuracies were comparable or better than those reported earlier in the literature for the same datasets. Furthermore, the use of fragment-based descriptors affords mechanistic interpretation of validated QSAR models in terms of essential chemical fragments responsible for the compounds' target property. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A model of fluid and solute exchange in the human: validation and implications.

PubMed

Bert, J L; Gyenge, C C; Bowen, B D; Reed, R K; Lund, T

2000-11-01

In order to understand better the complex, dynamic behaviour of the redistribution and exchange of fluid and solutes administered to normal individuals or to those with acute hypovolemia, mathematical models are used in addition to direct experimental investigation. Initial validation of a model developed by our group involved data from animal experiments (Gyenge, C.C., Bowen, B.D., Reed, R.K. & Bert, J.L. 1999b. Am J Physiol 277 (Heart Circ Physiol 46), H1228-H1240). For a first validation involving humans, we compare the results of simulations with a wide range of different types of data from two experimental studies. These studies involved administration of normal saline or hypertonic saline with Dextran to both normal and 10% haemorrhaged subjects. We compared simulations with data including the dynamic changes in plasma and interstitial fluid volumes VPL and VIT respectively, plasma and interstitial colloid osmotic pressures PiPL and PiIT respectively, haematocrit (Hct), plasma solute concentrations and transcapillary flow rates. The model predictions were overall in very good agreement with the wide range of experimental results considered. Based on the conditions investigated, the model was also validated for humans. We used the model both to investigate mechanisms associated with the redistribution and transport of fluid and solutes administered following a mild haemorrhage and to speculate on the relationship between the timing and amount of fluid infusions and subsequent blood volume expansion.

A model for flexi-bar to evaluate intervertebral disc and muscle forces in exercises.

PubMed

Abdollahi, Masoud; Nikkhoo, Mohammad; Ashouri, Sajad; Asghari, Mohsen; Parnianpour, Mohamad; Khalaf, Kinda

2016-10-01

This study developed and validated a lumped parameter model for the FLEXI-BAR, a popular training instrument that provides vibration stimulation. The model which can be used in conjunction with musculoskeletal-modeling software for quantitative biomechanical analyses, consists of 3 rigid segments, 2 torsional springs, and 2 torsional dashpots. Two different sets of experiments were conducted to determine the model's key parameters including the stiffness of the springs and the damping ratio of the dashpots. In the first set of experiments, the free vibration of the FLEXI-BAR with an initial displacement at its end was considered, while in the second set, forced oscillations of the bar were studied. The properties of the mechanical elements in the lumped parameter model were derived utilizing a non-linear optimization algorithm which minimized the difference between the model's prediction and the experimental data. The results showed that the model is valid (8% error) and can be used for simulating exercises with the FLEXI-BAR for excitations in the range of the natural frequency. The model was then validated in combination with AnyBody musculoskeletal modeling software, where various lumbar disc, spinal muscles and hand muscles forces were determined during different FLEXI-BAR exercise simulations. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

A new model for including the effect of fly ash on biochemical methane potential.

PubMed

Gertner, Pablo; Huiliñir, César; Pinto-Villegas, Paula; Castillo, Alejandra; Montalvo, Silvio; Guerrero, Lorna

2017-10-01

The modelling of the effect of trace elements on anaerobic digestion, and specifically the effect of fly ash, has been scarcely studied. Thus, the present work was aimed at the development of a new function that allows accumulated methane models to predict the effect of FA on the volume of methane accumulation. For this, purpose five fly ash concentrations (10, 25, 50, 250 and 500mg/L) using raw and pre-treated sewage sludge were used to calibrate the new function, while three fly ash concentrations were used (40, 150 and 350mg/L) for validation. Three models for accumulated methane volume (the modified Gompertz equation, the logistic function, and the transfer function) were evaluated. The results showed that methane production increased in the presence of FA when the sewage sludge was not pre-treated, while with pretreated sludge there is inhibition of methane production at FA concentrations higher than 50mg/L. In the calibration of the proposed function, it fits well with the experimental data under all the conditions, including the inhibition and stimulating zones, with the values of the parameters of the methane production models falling in the range of those reported in the literature. For validation experiments, the model succeeded in representing the behavior of new experiments in both the stimulating and inhibiting zones, with NRMSE and R 2 ranging from 0.3577 to 0.03714 and 0.2209 to 0.9911, respectively. Thus, the proposed model is robust and valid for the studied conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model assessment using a multi-metric ranking technique

NASA Astrophysics Data System (ADS)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Serum and urine metabolomics study reveals a distinct diagnostic model for cancer cachexia

PubMed Central

Yang, Quan‐Jun; Zhao, Jiang‐Rong; Hao, Juan; Li, Bin; Huo, Yan; Han, Yong‐Long; Wan, Li‐Li; Li, Jie; Huang, Jinlu; Lu, Jin

2017-01-01

Abstract Background Cachexia is a multifactorial metabolic syndrome with high morbidity and mortality in patients with advanced cancer. The diagnosis of cancer cachexia depends on objective measures of clinical symptoms and a history of weight loss, which lag behind disease progression and have limited utility for the early diagnosis of cancer cachexia. In this study, we performed a nuclear magnetic resonance‐based metabolomics analysis to reveal the metabolic profile of cancer cachexia and establish a diagnostic model. Methods Eighty‐four cancer cachexia patients, 33 pre‐cachectic patients, 105 weight‐stable cancer patients, and 74 healthy controls were included in the training and validation sets. Comparative analysis was used to elucidate the distinct metabolites of cancer cachexia, while metabolic pathway analysis was employed to elucidate reprogramming pathways. Random forest, logistic regression, and receiver operating characteristic analyses were used to select and validate the biomarker metabolites and establish a diagnostic model. Results Forty‐six cancer cachexia patients, 22 pre‐cachectic patients, 68 weight‐stable cancer patients, and 48 healthy controls were included in the training set, and 38 cancer cachexia patients, 11 pre‐cachectic patients, 37 weight‐stable cancer patients, and 26 healthy controls were included in the validation set. All four groups were age‐matched and sex‐matched in the training set. Metabolomics analysis showed a clear separation of the four groups. Overall, 45 metabolites and 18 metabolic pathways were associated with cancer cachexia. Using random forest analysis, 15 of these metabolites were identified as highly discriminating between disease states. Logistic regression and receiver operating characteristic analyses were used to create a distinct diagnostic model with an area under the curve of 0.991 based on three metabolites. The diagnostic equation was Logit(P) = −400.53 – 481.88 × log(Carnosine) −239.02 × log(Leucine) + 383.92 × log(Phenyl acetate), and the result showed 94.64% accuracy in the validation set. Conclusions This metabolomics study revealed a distinct metabolic profile of cancer cachexia and established and validated a diagnostic model. This research provided a feasible diagnostic tool for identifying at‐risk populations through the detection of serum metabolites. PMID:29152916

Fixed gain and adaptive techniques for rotorcraft vibration control

NASA Technical Reports Server (NTRS)

Roy, R. H.; Saberi, H. A.; Walker, R. A.

1985-01-01

The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor

NASA Astrophysics Data System (ADS)

Prendergast, Kristine; Adams, Kym; Greenlee, William J.; Nachbar, Robert B.; Patchett, Arthur A.; Underwood, Dennis J.

1994-10-01

A systematic search has been used to derive a hypothesis for the receptor-bound conformation of A-II antagonists at the AT1 receptor. The validity of the pharmacophore hypothesis has been tested using CoMFA, which included 50 diverse A-II antagonists, spanning four orders of magnitude in activity. The resulting cross-validated R2 of 0.64 (conventional R2 of 0.76) is indicative of a good predictive model of activity, and has been used to estimate potency for a variety of non-peptidyl antagonists. The structural model for the non-peptide has been compared with respect to the natural substrate, A-II, by generating peptide to non-peptide overlays.

Aeroservoelastic wind-tunnel investigations using the Active Flexible Wing Model: Status and recent accomplishments

NASA Technical Reports Server (NTRS)

Noll, Thomas E.; Perry, Boyd, III; Tiffany, Sherwood H.; Cole, Stanley R.; Buttrill, Carey S.; Adams, William M., Jr.; Houck, Jacob A.; Srinathkumar, S.; Mukhopadhyay, Vivek; Pototzky, Anthony S.

1989-01-01

The status of the joint NASA/Rockwell Active Flexible Wing Wind-Tunnel Test Program is described. The objectives are to develop and validate the analysis, design, and test methodologies required to apply multifunction active control technology for improving aircraft performance and stability. Major tasks include designing digital multi-input/multi-output flutter-suppression and rolling-maneuver-load alleviation concepts for a flexible full-span wind-tunnel model, obtaining an experimental data base for the basic model and each control concept and providing comparisons between experimental and analytical results to validate the methodologies. The opportunity is provided to improve real-time simulation techniques and to gain practical experience with digital control law implementation procedures.

Numerical Investigations of Interactions between the Knee-Thigh-Hip Complex with Vehicle Interior Structures.

PubMed

Kim, Yong Sun; Choi, Hyeong Ho; Cho, Young Nam; Park, Yong Jae; Lee, Jong B; Yang, King H; King, Albert I

2005-11-01

Although biomechanical studies on the knee-thigh-hip (KTH) complex have been extensive, interactions between the KTH and various vehicular interior design parameters in frontal automotive crashes for newer models have not been reported in the open literature to the best of our knowledge. A 3D finite element (FE) model of a 50(th) percentile male KTH complex, which includes explicit representations of the iliac wing, acetabulum, pubic rami, sacrum, articular cartilage, femoral head, femoral neck, femoral condyles, patella, and patella tendon, has been developed to simulate injuries such as fracture of the patella, femoral neck, acetabulum, and pubic rami of the KTH complex. Model results compared favorably against regional component test data including a three-point bending test of the femur, axial loading of the isolated knee-patella, axial loading of the KTH complex, axial loading of the femoral head, and lateral loading of the isolated pelvis. The model was further integrated into a Wayne State University upper torso model and validated against data obtained from whole body sled tests. The model was validated against these experimental data over a range of impact speeds, impactor masses and boundary conditions. Using Design Of Experiment (DOE) methods based on Taguchi's approach and the developed FE model of the whole body, including the KTH complex, eight vehicular interior design parameters, namely the load limiter force, seat belt elongation, pretensioner inlet amount, knee-knee bolster distance, knee bolster angle, knee bolster stiffness, toe board angle and impact speed, each with either two or three design levels, were simulated to predict their respective effects on the potential of KTH injury in frontal impacts. Simulation results proposed best design levels for vehicular interior design parameters to reduce the injury potential of the KTH complex due to frontal automotive crashes. This study is limited by the fact that prediction of bony fracture was based on an element elimination method available in the LS-DYNA code. No validation study was conducted to determine if this method is suitable when simulating fractures of biological tissues. More work is still needed to further validate the FE model of the KTH complex to increase its reliability in the assessment of various impact loading conditions associated with vehicular crash scenarios.

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

PubMed

Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

2018-05-01

TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P < .001). The model was able to distinguish well among three risk groups based on tertiles of the risk score. Adding treatment modality to the model did not decrease the predictive power. As a post hoc analysis, we tested the added value of comorbidity as scored by American Society of Anesthesiologists score in a subsample, which increased the C statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

A new method for assessing content validity in model-based creation and iteration of eHealth interventions.

PubMed

Kassam-Adams, Nancy; Marsac, Meghan L; Kohser, Kristen L; Kenardy, Justin A; March, Sonja; Winston, Flaura K

2015-04-15

The advent of eHealth interventions to address psychological concerns and health behaviors has created new opportunities, including the ability to optimize the effectiveness of intervention activities and then deliver these activities consistently to a large number of individuals in need. Given that eHealth interventions grounded in a well-delineated theoretical model for change are more likely to be effective and that eHealth interventions can be costly to develop, assuring the match of final intervention content and activities to the underlying model is a key step. We propose to apply the concept of "content validity" as a crucial checkpoint to evaluate the extent to which proposed intervention activities in an eHealth intervention program are valid (eg, relevant and likely to be effective) for the specific mechanism of change that each is intended to target and the intended target population for the intervention. The aims of this paper are to define content validity as it applies to model-based eHealth intervention development, to present a feasible method for assessing content validity in this context, and to describe the implementation of this new method during the development of a Web-based intervention for children. We designed a practical 5-step method for assessing content validity in eHealth interventions that includes defining key intervention targets, delineating intervention activity-target pairings, identifying experts and using a survey tool to gather expert ratings of the relevance of each activity to its intended target, its likely effectiveness in achieving the intended target, and its appropriateness with a specific intended audience, and then using quantitative and qualitative results to identify intervention activities that may need modification. We applied this method during our development of the Coping Coach Web-based intervention for school-age children. In the evaluation of Coping Coach content validity, 15 experts from five countries rated each of 15 intervention activity-target pairings. Based on quantitative indices, content validity was excellent for relevance and good for likely effectiveness and age-appropriateness. Two intervention activities had item-level indicators that suggested the need for further review and potential revision by the development team. This project demonstrated that assessment of content validity can be straightforward and feasible to implement and that results of this assessment provide useful information for ongoing development and iterations of new eHealth interventions, complementing other sources of information (eg, user feedback, effectiveness evaluations). This approach can be utilized at one or more points during the development process to guide ongoing optimization of eHealth interventions.

A validated model for the 22-item Sino-Nasal Outcome Test subdomain structure in chronic rhinosinusitis.

PubMed

Feng, Allen L; Wesely, Nicholas C; Hoehle, Lloyd P; Phillips, Katie M; Yamasaki, Alisa; Campbell, Adam P; Gregorio, Luciano L; Killeen, Thomas E; Caradonna, David S; Meier, Josh C; Gray, Stacey T; Sedaghat, Ahmad R

2017-12-01

Previous studies have identified subdomains of the 22-item Sino-Nasal Outcome Test (SNOT-22), reflecting distinct and largely independent categories of chronic rhinosinusitis (CRS) symptoms. However, no study has validated the subdomain structure of the SNOT-22. This study aims to validate the existence of underlying symptom subdomains of the SNOT-22 using confirmatory factor analysis (CFA) and to develop a subdomain model that practitioners and researchers can use to describe CRS symptomatology. A total of 800 patients with CRS were included into this cross-sectional study (400 CRS patients from Boston, MA, and 400 CRS patients from Reno, NV). Their SNOT-22 responses were analyzed using exploratory factor analysis (EFA) to determine the number of symptom subdomains. A CFA was performed to develop a validated measurement model for the underlying SNOT-22 subdomains along with various tests of validity and goodness of fit. EFA demonstrated 4 distinct factors reflecting: sleep, nasal, otologic/facial pain, and emotional symptoms (Cronbach's alpha, >0.7; Bartlett's test of sphericity, p < 0.001; Kaiser-Meyer-Olkin >0.90), independent of geographic locale. The corresponding CFA measurement model demonstrated excellent measures of fit (root mean square error of approximation, <0.06; standardized root mean square residual, <0.08; comparative fit index, >0.95; Tucker-Lewis index, >0.95) and measures of construct validity (heterotrait-monotrait [HTMT] ratio, <0.85; composite reliability, >0.7), again independent of geographic locale. The use of the 4-subdomain structure for SNOT-22 (reflecting sleep, nasal, otologic/facial pain, and emotional symptoms of CRS) was validated as the most appropriate to calculate SNOT-22 subdomain scores for patients from different geographic regions using CFA. © 2017 ARS-AAOA, LLC.

Measuring maternal satisfaction with maternity care: A systematic integrative review: What is the most appropriate, reliable and valid tool that can be used to measure maternal satisfaction with continuity of maternity care?

PubMed

Perriman, Noelyn; Davis, Deborah

2016-06-01

The objective of this systematic integrative review is to identify, summarise and communicate the findings of research relating to tools that measure maternal satisfaction with continuity of maternity care models. In so doing the most appropriate, reliable and valid tool that can be used to measure maternal satisfaction with continuity of maternity care will be determined. A systematic integrative review of published and unpublished literature was undertaken using selected databases. Research papers were included if they measured maternal satisfaction in a continuity model of maternity care, were published in English after 1999 and if they included (or made available) the instrument used to measure satisfaction. Six hundred and thirty two unique papers were identified and after applying the selection criteria, four papers were included in the review. Three of these originated in Australia and one in Canada. The primary focus of all papers was not on the development of a tool to measure maternal satisfaction but on the comparison of outcomes in different models of care. The instruments developed varied in terms of the degree to which they were tested for validity and reliability. Women's satisfaction with maternity services is an important measure of quality. Most satisfaction surveys in maternity appear to reflect fragmented models of care though continuity of care models are increasing in line with the evidence demonstrating their effectiveness. It is important that robust tools are developed for this context and that there is some consistency in the way this is measured and reported for the purposes of benchmarking and quality improvement. Copyright © 2016 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Policy evaluation in diabetes prevention and treatment using a population-based macro simulation model: the MICADO model.

PubMed

van der Heijden, A A W A; Feenstra, T L; Hoogenveen, R T; Niessen, L W; de Bruijne, M C; Dekker, J M; Baan, C A; Nijpels, G

2015-12-01

To test a simulation model, the MICADO model, for estimating the long-term effects of interventions in people with and without diabetes. The MICADO model includes micro- and macrovascular diseases in relation to their risk factors. The strengths of this model are its population scope and the possibility to assess parameter uncertainty using probabilistic sensitivity analyses. Outcomes include incidence and prevalence of complications, quality of life, costs and cost-effectiveness. We externally validated MICADO's estimates of micro- and macrovascular complications in a Dutch cohort with diabetes (n = 498,400) by comparing these estimates with national and international empirical data. For the annual number of people undergoing amputations, MICADO's estimate was 592 (95% interquantile range 291-842), which compared well with the registered number of people with diabetes-related amputations in the Netherlands (728). The incidence of end-stage renal disease estimated using the MICADO model was 247 people (95% interquartile range 120-363), which was also similar to the registered incidence in the Netherlands (277 people). MICADO performed well in the validation of macrovascular outcomes of population-based cohorts, while it had more difficulty in reflecting a highly selected trial population. Validation by comparison with independent empirical data showed that the MICADO model simulates the natural course of diabetes and its micro- and macrovascular complications well. As a population-based model, MICADO can be applied for projections as well as scenario analyses to evaluate the long-term (cost-)effectiveness of population-level interventions targeting diabetes and its complications in the Netherlands or similar countries. © 2015 The Authors. Diabetic Medicine © 2015 Diabetes UK.

VAVUQ, Python and Matlab freeware for Verification and Validation, Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Courtney, J. E.; Zamani, K.; Bombardelli, F. A.; Fleenor, W. E.

2015-12-01

A package of scripts is presented for automated Verification and Validation (V&V) and Uncertainty Quantification (UQ) for engineering codes that approximate Partial Differential Equations (PDFs). The code post-processes model results to produce V&V and UQ information. This information can be used to assess model performance. Automated information on code performance can allow for a systematic methodology to assess the quality of model approximations. The software implements common and accepted code verification schemes. The software uses the Method of Manufactured Solutions (MMS), the Method of Exact Solution (MES), Cross-Code Verification, and Richardson Extrapolation (RE) for solution (calculation) verification. It also includes common statistical measures that can be used for model skill assessment. Complete RE can be conducted for complex geometries by implementing high-order non-oscillating numerical interpolation schemes within the software. Model approximation uncertainty is quantified by calculating lower and upper bounds of numerical error from the RE results. The software is also able to calculate the Grid Convergence Index (GCI), and to handle adaptive meshes and models that implement mixed order schemes. Four examples are provided to demonstrate the use of the software for code and solution verification, model validation and uncertainty quantification. The software is used for code verification of a mixed-order compact difference heat transport solver; the solution verification of a 2D shallow-water-wave solver for tidal flow modeling in estuaries; the model validation of a two-phase flow computation in a hydraulic jump compared to experimental data; and numerical uncertainty quantification for 3D CFD modeling of the flow patterns in a Gust erosion chamber.

External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland.

PubMed

Harrison, David A; Lone, Nazir I; Haddow, Catriona; MacGillivray, Moranne; Khan, Angela; Cook, Brian; Rowan, Kathryn M

2014-01-01

Risk prediction models are used in critical care for risk stratification, summarising and communicating risk, supporting clinical decision-making and benchmarking performance. However, they require validation before they can be used with confidence, ideally using independently collected data from a different source to that used to develop the model. The aim of this study was to validate the Intensive Care National Audit & Research Centre (ICNARC) model using independently collected data from critical care units in Scotland. Data were extracted from the Scottish Intensive Care Society Audit Group (SICSAG) database for the years 2007 to 2009. Recoding and mapping of variables was performed, as required, to apply the ICNARC model (2009 recalibration) to the SICSAG data using standard computer algorithms. The performance of the ICNARC model was assessed for discrimination, calibration and overall fit and compared with that of the Acute Physiology And Chronic Health Evaluation (APACHE) II model. There were 29,626 admissions to 24 adult, general critical care units in Scotland between 1 January 2007 and 31 December 2009. After exclusions, 23,269 admissions were included in the analysis. The ICNARC model outperformed APACHE II on measures of discrimination (c index 0.848 versus 0.806), calibration (Hosmer-Lemeshow chi-squared statistic 18.8 versus 214) and overall fit (Brier's score 0.140 versus 0.157; Shapiro's R 0.652 versus 0.621). Model performance was consistent across the three years studied. The ICNARC model performed well when validated in an external population to that in which it was developed, using independently collected data.

Risk models for mortality following elective open and endovascular abdominal aortic aneurysm repair: a single institution experience.

PubMed

Choke, E; Lee, K; McCarthy, M; Nasim, A; Naylor, A R; Bown, M; Sayers, R

2012-12-01

To develop and validate an "in house" risk model for predicting perioperative mortality following elective AAA repair and to compare this with other models. Multivariate logistics regression analysis was used to identify risk factors for perioperative-day mortality from one tertiary institution's prospectively maintained database. Consecutive elective open (564) and endovascular (589) AAA repairs (2000-2010) were split randomly into development (810) and validation (343) data sets. The resultant model was compared to Glasgow Aneurysm Score (GAS), Modified Customised Probability Index (m-CPI), CPI, the Vascular Governance North West (VGNW) model and the Medicare model. Variables associated with perioperative mortality included: increasing age (P = 0.034), myocardial infarct within last 10 years (P = 0.0008), raised serum creatinine (P = 0.005) and open surgery (P = 0.0001). The areas under the receiver operating characteristic curve (AUC) for predicted probability of 30-day mortality in development and validation data sets were 0.79 and 0.82 respectively. AUCs for GAS, m-CPI and CPI were poor (0.63, 0.58 and 0.58 respectively), whilst VGNW and Medicare model were fair (0.73 and 0.79 respectively). In this study, an "in-house" developed and validated risk model has the most accurate discriminative value in predicting perioperative mortality after elective AAA repair. For purposes of comparative audit with case mix adjustments, national models such as the VGNW or Medicare models should be used. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

NASA National Combustion Code Simulations

NASA Technical Reports Server (NTRS)

Iannetti, Anthony; Davoudzadeh, Farhad

2001-01-01

A systematic effort is in progress to further validate the National Combustion Code (NCC) that has been developed at NASA Glenn Research Center (GRC) for comprehensive modeling and simulation of aerospace combustion systems. The validation efforts include numerical simulation of the gas-phase combustor experiments conducted at the Center for Turbulence Research (CTR), Stanford University, followed by comparison and evaluation of the computed results with the experimental data. Presently, at GRC, a numerical model of the experimental gaseous combustor is built to simulate the experimental model. The constructed numerical geometry includes the flow development sections for air annulus and fuel pipe, 24 channel air and fuel swirlers, hub, combustor, and tail pipe. Furthermore, a three-dimensional multi-block, multi-grid grid (1.6 million grid points, 3-levels of multi-grid) is generated. Computational simulation of the gaseous combustor flow field operating on methane fuel has started. The computational domain includes the whole flow regime starting from the fuel pipe and the air annulus, through the 12 air and 12 fuel channels, in the combustion region and through the tail pipe.

Modeling of the oxidation of methyl esters—Validation for methyl hexanoate, methyl heptanoate, and methyl decanoate in a jet-stirred reactor

PubMed Central

Glaude, Pierre Alexandre; Herbinet, Olivier; Bax, Sarah; Biet, Joffrey; Warth, Valérie; Battin-Leclerc, Frédérique

2013-01-01

The modeling of the oxidation of methyl esters was investigated and the specific chemistry, which is due to the presence of the ester group in this class of molecules, is described. New reactions and rate parameters were defined and included in the software EXGAS for the automatic generation of kinetic mechanisms. Models generated with EXGAS were successfully validated against data from the literature (oxidation of methyl hexanoate and methyl heptanoate in a jet-stirred reactor) and a new set of experimental results for methyl decanoate. The oxidation of this last species was investigated in a jet-stirred reactor at temperatures from 500 to 1100 K, including the negative temperature coefficient region, under stoichiometric conditions, at a pressure of 1.06 bar and for a residence time of 1.5 s: more than 30 reaction products, including olefins, unsaturated esters, and cyclic ethers, were quantified and successfully simulated. Flow rate analysis showed that reactions pathways for the oxidation of methyl esters in the low-temperature range are similar to that of alkanes. PMID:23710076

Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Investigation of Advanced Counterrotation Blade Configuration Concepts for High Speed Turboprop Systems. Task 8: Cooling Flow/heat Transfer Analysis

NASA Technical Reports Server (NTRS)

Hall, Edward J.; Topp, David A.; Heidegger, Nathan J.; Delaney, Robert A.

1994-01-01

The focus of this task was to validate the ADPAC code for heat transfer calculations. To accomplish this goal, the ADPAC code was modified to allow for a Cartesian coordinate system capability and to add boundary conditions to handle spanwise periodicity and transpiration boundaries. The primary validation case was the film cooled C3X vane. The cooling hole modeling included both a porous region and grid in each discrete hold. Predictions for these models as well as smooth wall compared well with the experimental data.

Reduced and Validated Kinetic Mechanisms for Hydrogen-CO-sir Combustion in Gas Turbines

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

Yiguang Ju; Frederick Dryer

2009-02-07

Rigorous experimental, theoretical, and numerical investigation of various issues relevant to the development of reduced, validated kinetic mechanisms for synthetic gas combustion in gas turbines was carried out - including the construction of new radiation models for combusting flows, improvement of flame speed measurement techniques, measurements and chemical kinetic analysis of H{sub 2}/CO/CO{sub 2}/O{sub 2}/diluent mixtures, revision of the H{sub 2}/O{sub 2} kinetic model to improve flame speed prediction capabilities, and development of a multi-time scale algorithm to improve computational efficiency in reacting flow simulations.

Real-time simulation of an F110/STOVL turbofan engine

NASA Technical Reports Server (NTRS)

Drummond, Colin K.; Ouzts, Peter J.

1989-01-01

A traditional F110-type turbofan engine model was extended to include a ventral nozzle and two thrust-augmenting ejectors for Short Take-Off Vertical Landing (STOVL) aircraft applications. Development of the real-time F110/STOVL simulation required special attention to the modeling approach to component performance maps, the low pressure turbine exit mixing region, and the tailpipe dynamic approximation. Simulation validation derives by comparing output from the ADSIM simulation with the output for a validated F110/STOVL General Electric Aircraft Engines FORTRAN deck. General Electric substantiated basic engine component characteristics through factory testing and full scale ejector data.

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

PubMed Central

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

2015-01-01

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

Validation of the Two-Layer Model for Correcting Clear Sky Reflectance Near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, K. Frank; Vamal, Tamas

2014-01-01

A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.

Numerical Simulation on Hydrodynamics and Combustion in a Circulating Fluidized Bed under O2/CO2 and Air Atmospheres

NASA Astrophysics Data System (ADS)

Zhou, W.; Zhao, C. S.; Duan, L. B.; Qu, C. R.; Lu, J. Y.; Chen, X. P.

Oxy-fuel circulating fluidized bed (CFB) combustion technology is in the stage of initial development for carbon capture and storage (CCS). Numerical simulation is helpful to better understanding the combustion process and will be significant for CFB scale-up. In this paper, a computational fluid dynamics (CFD) model was employed to simulate the hydrodynamics of gas-solid flow in a CFB riser based on the Eulerian-Granular multiphase model. The cold model predicted the main features of the complex gas-solid flow, including the cluster formation of the solid phase along the walls, the flow structure of up-flow in the core and downward flow in the annular region. Furthermore, coal devolatilization, char combustion and heat transfer were considered by coupling semi-empirical sub-models with CFD model to establish a comprehensive model. The gas compositions and temperature profiles were predicted and the outflow gas fractions are validated with the experimental data in air combustion. With the experimentally validated model being applied, the concentration and temperature distributions in O2/CO2 combustion were predicted. The model is useful for the further development of a comprehensive model including more sub-models, such as pollutant emissions, and better understanding the combustion process in furnace.

Factor structure and construct validity of the Generalized Anxiety Disorder 7-item (GAD-7) among Portuguese college students.

PubMed

Bártolo, Ana; Monteiro, Sara; Pereira, Anabela

2017-09-28

: The Generalized Anxiety Disorder 7-item (GAD-7) scale has been presented as a reliable and valid measure to assess generalized anxiety symptoms in several clinical settings and among the general population. However, some researches did not support the original one-dimensional structure of the GAD-7 tool. Our main aim was to examine the factor structure of GAD-7 comparing the one-factor model fit with a two-factor model (3 somatic nature symptoms and 4 cognitive-emotional nature symptoms) in a sample of college students. This validation study with data collected cross-sectionally included 1,031 Portuguese college students attending courses in the six schools of the Polytechnic Institute of Coimbra, Coimbra, Portugal. Measures included the GAD-7, Hospital Anxiety and Depression Scale (HADS) and the University Student Risk Behaviors Questionnaire. Confirmatory factor analysis (CFA) procedures confirmed that neither factor structure was well fitting. Thus, a modified single factor model allowing the error terms of items associated with relaxing difficulties and irritability to covary was an appropriate solution. Additionally, this factor structure revealed configural and metric invariance across gender. A good convergent validity was found by correlating global anxiety and depression. However, this measure showed a weak association with consumption behaviors. Our results are relevant to clinical practice, since the comprehensive approach to GAD-7 contributes to knowing generalized anxiety symptoms trajectory and their correlates within the university setting.

Empirical Measurement and Model Validation of Infrared Spectra of Contaminated Surfaces

NASA Astrophysics Data System (ADS)

Archer, Sean

The goal of this thesis was to validate predicted infrared spectra of liquid contaminated surfaces from a micro-scale bi-directional reflectance distribution function (BRDF) model through the use of empirical measurement. Liquid contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Image and Remote Sensing Image Generation (DIRSIG) model utilizes radiative transfer modeling to generate synthetic imagery for a variety of applications. Aside from DIRSIG, a micro-scale model known as microDIRSIG has been developed as a rigorous ray tracing physics-based model that could predict the BRDF of geometric surfaces that are defined as micron to millimeter resolution facets. The model offers an extension from the conventional BRDF models by allowing contaminants to be added as geometric objects to a micro-facet surface. This model was validated through the use of Fourier transform infrared spectrometer measurements. A total of 18 different substrate and contaminant combinations were measured and compared against modeled outputs. The substrates used in this experiment were wood and aluminum that contained three different paint finishes. The paint finishes included no paint, Krylon ultra-flat black, and Krylon glossy black. A silicon based oil (SF96) was measured out and applied to each surface to create three different contamination cases for each surface. Radiance in the longwave infrared region of the electromagnetic spectrum was measured by a Design and Prototypes (D&P) Fourier transform infrared spectrometer and a Physical Sciences Inc. Adaptive Infrared Imaging Spectroradiometer (AIRIS). The model outputs were compared against the measurements quantitatively in both the emissivity and radiance domains. A temperature emissivity separation (TES) algorithm had to be applied to the measured radiance spectra for comparison with the microDIRSIG predicted emissivity spectra. The model predicted emissivity spectra was also forward modeled through a DIRSIG simulation for comparisons to the radiance measurements. The results showed a promising agreement for homogeneous surfaces with liquid contamination that could be well characterized geometrically. Limitations arose in substrates that were modeled as homogeneous surfaces, but had spatially varying artifacts due to uncertainties with contaminant and surface interactions. There is high desire for accurate physics based modeling of liquid contaminated surfaces and this validation framework may be extended to include a wider array of samples for more realistic natural surfaces that are often found in real world scenarios.

Development of a physically-based planar inductors VHDL-AMS model for integrated power converter design

NASA Astrophysics Data System (ADS)

Ammouri, Aymen; Ben Salah, Walid; Khachroumi, Sofiane; Ben Salah, Tarek; Kourda, Ferid; Morel, Hervé

2014-05-01

Design of integrated power converters needs prototype-less approaches. Specific simulations are required for investigation and validation process. Simulation relies on active and passive device models. Models of planar devices, for instance, are still not available in power simulator tools. There is, thus, a specific limitation during the simulation process of integrated power systems. The paper focuses on the development of a physically-based planar inductor model and its validation inside a power converter during transient switching. The planar inductor model remains a complex device to model, particularly when the skin, the proximity and the parasitic capacitances effects are taken into account. Heterogeneous simulation scheme, including circuit and device models, is successfully implemented in VHDL-AMS language and simulated in Simplorer platform. The mixed simulation results has been favorably tested and compared with practical measurements. It is found that the multi-domain simulation results and measurements data are in close agreement.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

NASA Technical Reports Server (NTRS)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MT3DMS: Model use, calibration, and validation

USGS Publications Warehouse

Zheng, C.; Hill, Mary C.; Cao, G.; Ma, R.

2012-01-01

MT3DMS is a three-dimensional multi-species solute transport model for solving advection, dispersion, and chemical reactions of contaminants in saturated groundwater flow systems. MT3DMS interfaces directly with the U.S. Geological Survey finite-difference groundwater flow model MODFLOW for the flow solution and supports the hydrologic and discretization features of MODFLOW. MT3DMS contains multiple transport solution techniques in one code, which can often be important, including in model calibration. Since its first release in 1990 as MT3D for single-species mass transport modeling, MT3DMS has been widely used in research projects and practical field applications. This article provides a brief introduction to MT3DMS and presents recommendations about calibration and validation procedures for field applications of MT3DMS. The examples presented suggest the need to consider alternative processes as models are calibrated and suggest opportunities and difficulties associated with using groundwater age in transport model calibration.

External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

PubMed

Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud

2018-02-01

End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.