Development of a cost-effectiveness model for guardrail selection. Executive summary. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Development of a cost-effectiveness model for guardrail selection. Volume I: technical documentation. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Development of a cost-effectiveness model for guardrail selection. Volume II: user's manual. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Development and use of a computer simulation model for the evaluation of design and control alternatives for intersections of minor roads with multi-lane rural highways: selection of the simulation model. Interim report.

Federal Highway Administration, Washington, D.C.

Forecasting stock returns using model-selection criteria

This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay

A phytotoxicity assay based on the ToxY-PAM dual-channel yield analyser has been developed and successfully incorporated into field assessments for the detection of phytotoxicants in water. As a means of further exploring the scope of the assay application and of selecting a model biomaterial to complement the instrument design, nine algal species were exposed to four chemical substances deemed of priority for water quality monitoring purposes (chlorpyrifos, copper, diuron and nonylphenol ethoxylate). Inter-species differences in sensitivity to the four toxicants varied by a factor of 1.9-100. Measurements of photosystem-II quantum yield using these nine single-celled microalgae as biomaterial corroborated previous studies which have shown that the ToxY-PAM dual-channel yield analyser is a highly sensitive method for the detection of PS-II impacting herbicides. Besides Phaeodactylum tricornutum, the previously applied biomaterial, three other species consistently performed well (Nitzschia closterium, Chlorella vulgaris and Dunaliella tertiolecta) and will be used in further test optimisation experiments. In addition to sensitivity, response time was evaluated and revealed a high degree of variation between species and toxicants. While most species displayed relatively weak and slow responses to copper, C. vulgaris demonstrated an IC10 of 51 μ g L-1, with maximum response measured within 25 minutes and inhibition being accompanied by a large decrease in fluorescence yield. The potential for this C vulgaris-based bioassay to be used for the detection of copper is discussed. There was no evidence that the standard ToxY-PAM protocol, using these unicellular algae species, could be used for the detection of chlorpyrifos or nonylphenol ethoxylate at environmentally relevant levels. © 2005 Elsevier B.V. All rights reserved.

Internal versus external R&D:a study of R&D choice with sample selection

This paper extends previous analyses of the choice between internal and external R&D to consider the costs of internal R&D. The Heckman two-stage estimator is used to estimate the determinants of internal R&D unit cost (i.e. cost per product innovation) allowing for sample selection effects. Theory indicates that R&D unit cost will be influenced by scale issues and by the technological opportunities faced by the firm. Transaction costs encountered in research activities are allowed for and, in addition, consideration is given to issues of market structure which influence the choice of R&D mode without affecting the unit cost of internal or external R&D. The model is tested on data from a sample of over 500 UK manufacturing plants which have engaged in product innovation. The key determinants of R&D mode are the scale of plant and R&D input, and market structure conditions. In terms of the R&D cost equation, scale factors are again important and have a non-linear relationship with R&D unit cost. Specificities in physical and human capital also affect unit cost, but have no clear impact on the choice of R&D mode. There is no evidence of technological opportunity affecting either R&D cost or the internal/external decision.

A new DEA model for technology selection in the presence of ordinal data

This paper suggests a data envelopment analysis (DEA) model for selecting the most efficient alternative in advanced manufacturing technology in the presence of both cardinal and ordinal data. The paper explains the problem of using an iterative method for finding the most efficient alternative and proposes a new DEA model without the need of solving a series of LPs. A numerical example illustrates the model, and an application in technology selection with multi-inputs/multi-outputs shows the usefulness of the proposed approach. © 2012 Springer-Verlag London Limited.

Tissue-specific selection of reference genes is required for expression studies in the mouse model of maternal protein undernutrition

Suboptimal maternal nutrition during gestation results in the establishment of long-term phenotypic changes and an increased disease risk in the offspring. To elucidate how such environmental sensitivity results in physiological outcomes, the molecular characterisation of these offspring has become the focus of many studies. However, the likely modification of key cellular processes such as metabolism in response to maternal undernutrition raises the question of whether the genes typically used as reference constants in gene expression studies are suitable controls. Using a mouse model of maternal protein undernutrition, we have investigated the stability of seven commonly used reference genes (18s, Hprt1, Pgk1, Ppib, Sdha, Tbp and Tuba1) in a variety of offspring tissues including liver, kidney, heart, retro-peritoneal and inter-scapular fat, extra-embryonic placenta and yolk sac, as well as in the preimplantation blastocyst and blastocyst-derived embryonic stem cells. We find that although the selected reference genes are all highly stable within this system, they show tissue, treatment and sex-specific variation. Furthermore, software-based selection approaches rank reference genes differently and do not always identify genes which differ between conditions. Therefore, we recommend that reference gene selection for gene expression studies should be thoroughly validated for each tissue of interest. © 2011 Elsevier Inc.

Risk-based model aids selection of pipeline inspection, maintenance strategies

The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

Parametric pattern selection in a reaction-diffusion model

We compare spot patterns generated by Turing mechanisms with those generated by replication cascades, in a model one-dimensional reaction-diffusion system. We determine the stability region of spot solutions in parameter space as a function of a natural control parameter (feed-rate) where degenerate patterns with different numbers of spots coexist for a fixed feed-rate. While it is possible to generate identical patterns via both mechanisms, we show that replication cascades lead to a wider choice of pattern profiles that can be selected through a tuning of the feed-rate, exploiting hysteresis and directionality effects of the different pattern pathways.

Selection and passage of county land preservation voter referendum: The role of government

County jurisdictions in America are increasingly exercising self-government in the provision of public community services through the context of second order federalism. In states exercising this form of contemporary governance, county governments with "reformed" policy-making structures and professional management practices, have begun to rival or surpass municipalities in the delivery of local services with regional implications such as environmental protection (Benton 2002, 2003; Marando and Reeves, 1993). ^ The voter referendum, a form of direct democracy, is an important component of county land preservation and environmental protection governmental policies. The recent growth and success of land preservation voter referendums nationwide reflects an increase in citizen participation in government and their desire to protect vacant land and its natural environment from threats of over-development, urbanization and sprawl, loss of open space and farmland, deterioration of ecosystems, and inadequate park and recreational amenities. ^ The study's design employs a sequential, mixed method. First, a quantitative approach employs the Heckman two-step model. It is fitted with variables for the non-random sample of 227 voter referendum counties and all non-voter referendum counties in the U.S. from 1988 to 2009. Second, the qualitative data collected from the in-depth investigation of three South Florida county case studies with twelve public administrator interviews is transformed for integration with the quantitative findings. The purpose of the qualitative method is to complement, explain and enrich the statistical analysis of county demographic, socio-economic, terrain, regional, governance and government, political preference, environmentalism, and referendum-specific factors. ^ The research finds that government factors are significant in terms of the success of land preservation voter referendums; more specifically, the presence of self-government authority (home rule charter), a reformed structure (county administrator/manager or elected executive), and environmental interest groups. In addition, this study concludes that successful counties are often located coastal, exhibit population and housing growth, and have older and more educated citizens who vote democratic in presidential elections. The analysis of case study documents and public administrator interviews finds that pragmatic considerations of timing, local politics and networking of regional stakeholders are also important features of success. Further research is suggested utilizing additional public participation, local government and public administration factors.^

Optimal selection of autoregressive model coefficients for early damage detectability with an application to wind turbine blades

Piotr Omenzetter and Simon Hoell's work within the Lloyd's Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

Optimal selection of autoregressive model coefficients for early damage detectability with an application to wind turbine blades

Piotr Omenzetter and Simon Hoell's work within the Lloyd's Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.