Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects

Objective: Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR.

Methods: This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model.

Results: Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime.

Conclusions: This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.     

Opportunities for better use of collective action theory in research and governance for invasive species management

Controlling invasive species presents a public-good dilemma. Although environmental, social, and economic benefits of control accrue to society, costs are borne by only a few individuals and organizations. For decades, policy makers have used incentives and sanctions to encourage or coerce individual actors to contribute to the public good, with limited success. Diverse, subnational efforts to collectively manage invasive plants, insects, and animals provide effective alternatives to traditional command-and-control approaches. Despite this work, there has been little systematic evaluation of collective efforts to determine whether there are consistent principles underpinning success. We reviewed 32 studies to identify the extent to which collective-action theories from related agricultural and environmental fields explain collaborative invasive species management approaches; describe and differentiate emergent invasive species collective-action efforts; and provide guidance on how to enable more collaborative approaches to invasive species management. We identified 4 types of collective action aimed at invasive species—externally led, community led, comanaged, and organizational coalitions—that provide blueprints for future invasive species management. Existing collective-action theories could explain the importance attributed to developing shared knowledge of the social-ecological system and the need for social capital. Yet, collection action on invasive species requires different types of monitoring, sanctions, and boundary definitions. We argue that future government policies can benefit from establishing flexible boundaries that encourage social learning and enable colocated individuals and organizations to identify common goals, pool resources, and coordinate efforts.     

Heavy metals in soils and crops in Southeast Asia

In a reconnaissance soil geochemical and plant survey undertaken to study the heavy metal uptake by major food crops in Malaysia, 241 soils were analysed for cation exchange capacity (CEC), organic carbon (C), pH, electrical conductivity (EC) and available phosphorus (P) using appropriate procedures. These soils were also analysed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) using aqua regia digestion, together with 180 plant samples using nitric acid digestion. Regression analysis between the edible plant part and aqua regia soluble soil As, Cd, Cr, Cu, Hg, Ni, Pb and Zn concentrations sampled throughout Peninsular Malaysia, indicated a positive relationship for Pb in all the plants sampled in the survey (R ² = 0.195, p < 0.001), for Ni in corn (R ² = 0.649, p < 0.005), for Cu in chilli (R ² = 0.344, p < 0.010) and for Zn in chilli (R ² = 0.501, p < 0.001). Principal component analysis of the soil data suggested that concentrations of Co, Ni, Pb and Zn were strongly correlated with concentrations of Al and Fe, which is suggestive of evidence of background variations due to changes in soil mineralogy. Thus the evidence for widespread contamination of soils by these elements through agricultural activities is not strong. Chromium was correlated with soil pH and EC, Na, S, and Ca while Hg was not correlated with any of these components, suggesting diffuse pollution by aerial deposition. However As, Cd, Cu were strongly associated with organic matter and available and aqua regia soluble soil P, which we attribute to inputs in agricultural fertilisers and soil organic amendments (e.g. manures, composts).     

Prenatal detection of structural abnormalities of chromosome 18: associations with interphase fluorescence in situ hybridization (FISH) and maternal serum screening

We describe two cases of prenatally ascertained isochromosome 18. Case 1 included both an isochromosome 18p and an isochromosome 18q, while Case 2 involved only an isochromosome 18q. Both of these cases were associated with a positive maternal serum triple screen trisomy 18 risk (greater than 1 in 100 risk). In addition, fluorescence in situ hybridization (FISH) was performed on uncultured amniotic fluid interphase cells in both cases looking for aneuploidy for chromosomes 13, 18, 21, X and Y. The results of the interphase analyses support the common knowledge that careful interpretation of interphase FISH analysis is necessary and that results should be followed by full cytogenetic analysis. To our knowledge these are the first reported cases of structurally abnormal chromosomes 18 being associated with a positive maternal serum triple screen for trisomy 18. Copyright © 2002 John Wiley & Sons, Ltd.     

Detecting pigments from colourful eggshells of extinct birds

The known chemical basis of diverse avian eggshell coloration is generated by the same two classes of tetrapyrrole pigments in most living birds. We aimed to extend the evolutionary scope of these patterns by detecting pigments from extinct birds’ eggs. In our samples biliverdin was successfully extracted from subfossil shell fragments of the blue-green egg-laying upland moa Megalapteryx didinus, while protoporphyrin was extracted from the beige eggs of two other extinct moa species. Our data on pigment detection from eggshells of other extant paleognath birds, together with published information on other modern lineages, confirm tetrapyrroles as ubiquitous and conserved pigments contributing to diverse eggshell colours throughout avian evolution.     

An econometric model of wastepaper recycling in the USA

A simultaneous model describing the demand for and supply of wastepaper in the USA during 1952-74 has been estimated using the three stage least squares procedure. In our analysis, a low supply elasticity coupled with a zero price elasticity of demand explains the volatile nature of wastepaper prices. The structural estimates indicate that neither the elimination of differential rail freights nor the elimination of preferential tax treatment of stumpage profits will have a significant effect in stimulating the recycling effort.     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.