An econometric analysis of the effects of the penalty points system driver's license in Spain

This article seeks to quantify the effects of the penalty points system driver's license during the 18-month period following its coming into force. This is achieved by means of univariate and multivariate unobserved component models set up in a state space framework estimated using maximum likelihood. A detailed intervention analysis is carried out in order to test for the effects and their duration of the introduction of the penalty points system driver's license in Spain. Other variables, mainly indicators of the level of economic activity in Spain, are also considered. Among the main effects, we can mention an average reduction of almost 12.6% in the number of deaths in highway accidents. It would take at least 2 years for that effect to disappear. For the rest of the safety indicator variables (vehicle occupants injured in highway accidents and vehicle occupants injured in accidents built-up areas) the effects disappeared 1 year after the law coming into force.     

Development of planning level transportation safety tools using Geographically Weighted Poisson Regression

A common technique used for the calibration of collision prediction models is the Generalized Linear Modeling (GLM) procedure with the assumption of Negative Binomial or Poisson error distribution. In this technique, fixed coefficients that represent the average relationship between the dependent variable and each explanatory variable are estimated. However, the stationary relationship assumed may hide some important spatial factors of the number of collisions at a particular traffic analysis zone. Consequently, the accuracy of such models for explaining the relationship between the dependent variable and the explanatory variables may be suspected since collision frequency is likely influenced by many spatially defined factors such as land use, demographic characteristics, and traffic volume patterns. The primary objective of this study is to investigate the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression modeling technique. The secondary objective is to build on knowledge comparing the accuracy of Geographically Weighted Poisson Regression models to that of Generalized Linear Models. The results show that the Geographically Weighted Poisson Regression models are useful for capturing spatially dependent relationships and generally perform better than the conventional Generalized Linear Models.     

基于商业模式视角认识代建

在对商业模式理论综述的基础上,提出适用企业实务操作的商业模式概念;站在企业的角度,以商业模式的框架分析了代建的经济逻辑,对代建需求作出了评估,并藉此指出企业通过代建获益的主要方向。     

Investment in new product reliability

Product reliability is of great importance to both manufacturers and customers. Building reliability into a new product is costly, but the consequences of inadequate product reliability can be costlier. This implies that manufacturers need to decide on the optimal investment in new product reliability by achieving a suitable trade-off between the two costs. This paper develops a framework and proposes an approach to help manufacturers decide on the investment in new product reliability.     

Simplified Finite-Element Model for Tissue Regeneration with Angiogenesis

A simplified finite-element model for tissue regeneration is proposed. The model takes into account the sequential steps of angiogenesis (neo-vascularization) and wound closure (the actual healing of a wound). An innovation in the present study is the combination of both partially overlapping processes, yielding novel insights into the process of wound healing, such as geometry related influences, and could be used to investigate the influence of local injection of hormones that stimulate partial processes occurring during wound healing. These insights can be used to improve wound healing treatments. The models consist of nonlinearly coupled diffusion-reaction equations, in which transport of oxygen, growth factors, and epidermal cells and mitosis are taken into account.     

Assessing the Impacts of Nutrient Load Uncertainties on Predicted Truckee River Water Quality

This study examined the effects of uncertain model boundary conditions on dissolved oxygen (DO) predictions for the lower Truckee River, Nevada using an augmented version of the EPA’s Water Quality Analysis Simulation Program Version 5 (WASP5) that included periphyton, or attached algae, in eutrophication kinetics. Uncertainty analyses were performed on selected organic nitrogen (ON) and carbonaceous biochemical oxygen demand boundary conditions using Monte Carlo techniques. The stochastic model was run using boundary concentrations assigned from observed probability distributions. Ranges of simulated values were used to construct confidence intervals, the magnitudes of which indicated the uncertainty associated with model predictions. Uncertainty in agricultural ditch return concentrations had minimal effects on in-stream model predictions, as predicted values of daily minimum and maximum DOs, daily average ON, and periphyton biomass all failed to show significant variability as a result of ditch concentration uncertainty. This result indicates that while ditch return nutrient loads are not trivial, their exact concentrations are not needed to make relatively accurate predictions of in-stream DO. However, uncertainty in the upstream ON boundary did result in significant uncertainty during summer months with regard to in-stream model predictions of ON, periphyton biomass, and DO. The model is clearly more sensitive to changes in this boundary than to changes in agricultural ditch concentrations.     

GEOGRAPHIC INFORMATION SYSTEM TECHNOLOGY AND ITS APPLICATIONS IN CIVIL ENGINEERING

Geographic information system (GIS) technology is attracting interest from a broad range of civil engineering disciplines because of its potential to provide a new environment for problem solving which could lower costs, improve quality, and support multi-discipline analysis for complex projects. This paper reviews the primary components and capabilities of GIS technology and shows how it is used in many civil engineering applications, including infrastructure management, transportation, land use planning, water resources engineering, and environmental engineering.     

Interval timing accuracy and scalar timing in C57BL/6 mice.

In many species, interval timing behavior is accurate—appropriate estimated durations—and scalar—errors vary linearly with estimated durations. Whereas accuracy has been previously examined, scalar timing has not been clearly demonstrated in house mice (Mus musculus), raising concerns about mouse models of human disease. The authors estimated timing accuracy and precision in C57BL/6 mice, the most used background strain for genetic models of human disease, in a peak-interval procedure with multiple intervals. Both when timing 2 intervals (Experiment 1) or 3 intervals (Experiment 2), C57BL/6 mice demonstrated varying degrees of timing accuracy. An important finding was that, both at the individual and group levels, their precision varied linearly with the subjective estimated duration. Further evidence for scalar timing was obtained using an intraclass correlation statistic. This is the first report of consistent, reliable scalar timing in a sizable sample of house mice, thus validating the peak-interval procedure as a valuable technique, the intraclass correlation statistic as a powerful test of the scalar property, and the C57BL/6 strain as a suitable background for behavioral investigations of genetically engineered mice modeling disorders of interval timing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Riparian Vegetation Mapping for Hydraulic Roughness Estimation Using Very High Resolution Remote Sensing Data Fusion

For detailed hydraulic modeling, accurate spatial information of riparian vegetation patterns needs to be derived in automatic fashion. We propose a supervised classification for heterogeneous riparian corridors with a low number of spectrally separate classes using data fusion of a Quickbird image and LIDAR data. The approach considers nine land cover classes including three woody riparian species, brush, cultivated areas, grassland, urban infrastructures, bare soil and water. The classical “stacked vector” approach is adopted for data fusion, while the nonparametric weighted feature-extraction method and the pixel-oriented maximum likelihood algorithm are used for feature-reduction and classification purposes, respectively. We test the approach over a 14-km stretch of the Sieve River (Tuscany Region, Italy). A one-dimensional river modeling is applied over the study reach comparing the results of a classification-derived hydraulic roughness map and a traditional ground-based approach. Despite the complex study reach, the classification method produced encouraging accuracies (OKS = 0.77) and represents a useful tool to delineate application domains of flow resistance models suited to different hydrodynamic patterns (e.g., stiff/flexible vegetation). Hydraulic modeling results showed that the remotely derived floodplain roughness parameterization captures the equivalent Manning coefficient over 20 test cross sections with uncertainty distributions described by low mean and standard deviation values.     

Broadband semi‐parametric estimation of long‐memory time series by fractional exponential models

This article proposes broadband semi‐parametric estimation of a long‐memory parameter by fractional exponential (FEXP) models. We construct the truncated Whittle likelihood based on FEXP models in a semi‐parametric setting to estimate the parameter and show that the proposed estimator is more efficient than the FEXP estimator by Moulines and Soulier (1999) in linear processes. A Monte Carlo simulation suggests that the proposed estimation is more preferable than the existing broadband semi‐parametric estimation.