NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

Human exposure model-II : user's guide.

Mode of access: Internet.

Diagnostic motor vehicle inspection demonstration projects, program engineering support. Volume 9 - appendix H: vehicle designs that facilitate or hinder inspection and repair and interchangeability and interface capability of test equipment and vehicles. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

High-resolution dynamical downscaling products for the North Slope of Alaska and surrounding areas, links to model result files

Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic.

A Kinetic Vlasov Model for Plasma Simulation Using Discontinuous Galerkin Method on Many-Core Architectures

Thesis (Ph.D.)--University of Washington, 2016-03

An Electromechanical Coupled Model of the Probe of a Scanning Fiber Imaging System

Thesis (Master's)--University of Washington, 2016-06

Ground water model calibration using pilot points and regularization

Use of nonlinear parameter estimation techniques is now commonplace in ground water model calibration. However, there is still ample room for further development of these techniques in order to enable them to extract more information from calibration datasets, to more thoroughly explore the uncertainty associated with model predictions, and to make them easier to implement in various modeling contexts. This paper describes the use of pilot points as a methodology for spatial hydraulic property characterization. When used in conjunction with nonlinear parameter estimation software that incorporates advanced regularization functionality (such as PEST), use of pilot points can add a great deal of flexibility to the calibration process at the same time as it makes this process easier to implement. Pilot points can be used either as a substitute for zones of piecewise parameter uniformity, or in conjunction with such zones. In either case, they allow the disposition of areas of high and low hydraulic property value to be inferred through the calibration process, without the need for the modeler to guess the geometry of such areas prior to estimating the parameters that pertain to them. Pilot points and regularization can also be used as an adjunct to geostatistically based stochastic parameterization methods. Using the techniques described herein, a series of hydraulic property fields can be generated, all of which recognize the stochastic characterization of an area at the same time that they satisfy the constraints imposed on hydraulic property values by the need to ensure that model outputs match field measurements. Model predictions can then be made using all of these fields as a mechanism for exploring predictive uncertainty.

A framework and tool support for the systematic testing of model-based specifications

Formal specifications can precisely and unambiguously define the required behavior of a software system or component. However, formal specifications are complex artifacts that need to be verified to ensure that they are consistent, complete, and validated against the requirements. Specification testing or animation tools exist to assist with this by allowing the specifier to interpret or execute the specification. However, currently little is known about how to do this effectively. This article presents a framework and tool support for the systematic testing of formal, model-based specifications. Several important generic properties that should be satisfied by model-based specifications are first identified. Following the idea of mutation analysis, we then use variants or mutants of the specification to check that these properties are satisfied. The framework also allows the specifier to test application-specific properties. All properties are tested for a range of states that are defined by the tester in the form of a testgraph, which is a directed graph that partially models the states and transitions of the specification being tested. Tool support is provided for the generation of the mutants, for automatically traversing the testgraph and executing the test cases, and for reporting any errors. The framework is demonstrated on a small specification and its application to three larger specifications is discussed. Experience indicates that the framework can be used effectively to test small to medium-sized specifications and that it can reveal a significant number of problems in these specifications.

Electromagnetic modeling of conformal wideband and multi-band patch antennas by bridging a solid-object modeler with MoM software

The advantages of antennas that can resemble the shape of the body to which they are attached are obvious. However, electromagnetic modeling of such unusually shaped antennas can be difficult. In this paper, the commercially available software SolidWorks(TM) is used for accurately drawing complex shapes in conjunction with the electromagnetic software FEKO(TM) to model the EM behavior of conformal antennas. The application of SolidWorks and custom-written software allows all the required information that forms the analyzed structure to be automatically inserted into FEKO, and gives the user complete control over the antenna being modeled. This approach is illustrated by a number of simulation examples of single, wideband, multi-band planar and curved patch antennas.

An experimental and finite element poroelastic creep response analysis of an intervertebral hydrogel disc model in axial compression

A hydrogel intervertebral disc (lVD) model consisting of an inner nucleus core and an outer anulus ring was manufactured from 30 and 35% by weight Poly(vinyl alcohol) hydrogel (PVA-H) concentrations and subjected to axial compression in between saturated porous endplates at 200 N for 11 h, 30 min. Repeat experiments (n = 4) on different samples (N = 2) show good reproducibility of fluid loss and axial deformation. An axisymmetric nonlinear poroelastic finite element model with variable permeability was developed using commercial finite element software to compare axial deformation and predicted fluid loss with experimental data. The FE predictions indicate differential fluid loss similar to that of biological IVDs, with the nucleus losing more water than the anulus, and there is overall good agreement between experimental and finite element predicted fluid loss. The stress distribution pattern indicates important similarities with the biological lVD that includes stress transference from the nucleus to the anulus upon sustained loading and renders it suitable as a model that can be used in future studies to better understand the role of fluid and stress in biological IVDs. (C) 2005 Springer Science + Business Media, Inc.

Unidirectional inversion of ibuprofen in Caco-2 cells: Developing a suitable model for presystemic chiral inversion study

Intestinal chiral inversion of ibuprofen is still lacking direct evidence. In a preliminary experiment, ibuprofen was found to undergo inversion in Caco-2 cells. This investigation was thus conducted to determine the characteristics and influence of some biochemical factors on the chiral inversion of ibuprofen in Caco-2 cells. The effects of substrate concentration (2.5-40 mu g/ml), cell density (0.5-2 x 10(6) cells/ well), content of serum (0-20%), coexistence of S ibuprofen (corresponding doses), sodium azide (10mm), exogenous Coenzyme A (CoA) (0.1 - 0.4 mm),. and palmitic acid (5-25 mu m) on inversion were examined. A stereoselective HPLC method based on the Chromasil-CHI-TBB column was developed for quantitative analysis of the drug in cell culture medium. The inversion ratio (F-i) and elimination rate constant were calculated as the indexes of inversion extent. Inversion of ibuprofen in Caeo-2 cells was found to be both dose and cell density dependent, indicating saturable characteristics. Addition of serum significantly inhibited the inversion, to an extent of 2.7 fold decrease at 20% content. Preexistence of S enantiomer exerted a significant inhibitory effect (p < 0.01 for all tests). Sodium azide decreased the inversion ratio from 0.43 to 0.32 (p < 0.01). Exogenous CoA and palmitic acid significantly promoted the inversion at all tested doses (p < 0.01 for all tests). This research provided strong evidence to the capacity and capability of intestinal chiral inversion. Although long incubation times up to 120 h were required, Caco-2 cells should be a suitable model for chiral inversion research of 2-APAs considering the human-resourced and well-defined characteristics from the present study.

Modelling of two-stage anaerobic digestion using the IWA Anaerobic Digestion Model No. 1 (ADM1)

The aim of the study presented was to implement a process model to simulate the dynamic behaviour of a pilot-scale process for anaerobic two-stage digestion of sewage sludge. The model implemented was initiated to support experimental investigations of the anaerobic two-stage digestion process. The model concept implemented in the simulation software package MATLAB(TM)/Simulink(R) is a derivative of the IWA Anaerobic Digestion Model No.1 (ADM1) that has been developed by the IWA task group for mathematical modelling of anaerobic processes. In the present study the original model concept has been adapted and applied to replicate a two-stage digestion process. Testing procedures, including balance checks and 'benchmarking' tests were carried out to verify the accuracy of the implementation. These combined measures ensured a faultless model implementation without numerical inconsistencies. Parameters for both, the thermophilic and the mesophilic process stage, have been estimated successfully using data from lab-scale experiments described in literature. Due to the high number of parameters in the structured model, it was necessary to develop a customised procedure that limited the range of parameters to be estimated. The accuracy of the optimised parameter sets has been assessed against experimental data from pilot-scale experiments. Under these conditions, the model predicted reasonably well the dynamic behaviour of a two-stage digestion process in pilot scale. (C) 2004 Elsevier Ltd. All rights reserved.

Development of a quasi-chemical viscosity model for fully liquid slags in the Al2O3-CaO-'FeO'-MgO-SiO2 system. Part 1. Description of the model and its application to the MgO, MgO-SiO2, Al2O3-MgO and CaO-MgO sub-systems

A structurally-based quasi-chemical viscosity model for fully liquid slags in the Al2O3 CaO-'FeO'-MgO-SiO2 system has been developed. The model links the slag viscosities to the internal structures of the melts through the concentrations of various Si0.5O, Me2/nn+O and Me1/nn+Si0.25O viscous flow structural units. The concentrations of these structural units are derived from a quasi-chemical thermodynamic model of the system. The model described in this series of papers enables the viscosities of liquid slags to be predicted within experimental uncertainties over the whole range of temperatures and compositions in the Al2O3 CaOMgO-SiO2 system.

Verifying data refinements using a model checker

In this paper, we consider how refinements between state-based specifications (e.g., written in Z) can be checked by use of a model checker. Specifically, we are interested in the verification of downward and upward simulations which are the standard approach to verifying refinements in state-based notations. We show how downward and upward simulations can be checked using existing temporal logic model checkers. In particular, we show how the branching time temporal logic CTL can be used to encode the standard simulation conditions. We do this for both a blocking, or guarded, interpretation of operations (often used when specifying reactive systems) as well as the more common non-blocking interpretation of operations used in many state-based specification languages (for modelling sequential systems). The approach is general enough to use with any state-based specification language, and we illustrate how refinements between Z specifications can be checked using the SAL CTL model checker using a small example.