The extreme toxicity of cyanide and environmental concerns from its continued industrial use continue to generate interest in facile and sensitive methods for cyanide detection. In recent years there is also additional recognition of HCN toxicity from smoke inhalation and potential use of cyanide as a weapon of terrorism. This review summarizes the literature since 2005 on cyanide measurement in different matrices ranging from drinking water and wastewater, to cigarette smoke and exhaled breath to biological fluids like blood, urine and saliva. The dramatic increase in the number of publications on cyanide measurement is indicative of the great interest in this field not only from analytical chemists, but also researchers from diverse environmental, medical, forensic and clinical arena. The recent methods cover both established and emerging analytical disciplines and include naked eye visual detection, spectrophotometry/colorimetry, capillary electrophoresis with optical absorbance detection, fluorometry, chemiluminescence, near-infrared cavity ring down spectroscopy, atomic absorption spectrometry, electrochemical methods (potentiometry/ amperometry/ion chromatography-pulsed amperometry), mass spectrometry (selected ion flow tube mass spectrometry, electrospray ionization mass spectrometry, gas chromatography-mass spectrometry), gas chromatography (nitrogen phosphorus detector, electron capture detector) and quartz crystal mass monitors.

The following paper is a pre-print and the final publication can be found in Accident Analysis and Prevention, 40 (3):964-975, 2008. Presented at the 86 th Annual Meeting of the Transportation Research Board, January 2007 ABSTRACT Numerous efforts have been devoted to investigating crash occurrence as related to roadway design features, environmental and traffic conditions. However, most of the research has relied on univariate count models; that is, traffic crash counts at different levels of severity are estimated separately, which may neglect shared information in unobserved error terms, reduce efficiency in parameter estimates, and lead to potential biases in sample databases. This paper offers a multivariate Poisson-lognormal (MVPLN) specification that simultaneously models injuries by severity. The MVPLN specification allows for a more general correlation structure as well as overdispersion. This approach addresses some questions that are difficult to answer by estimating them separately. With recent advancements in crash modeling and Bayesian statistics, the parameter estimation is done within the Bayesian paradigm, using a Gibbs Sampler and the Metropolis-Hastings (M-H) algorithms for crashes on Washington State rural two-lane highways.The estimation results from the MVPLN approach did show statistically significant correlations between crash counts at different levels of injury severity. The non-zero diagonal elements suggested overdispersion in crash counts at all levels of severity. The results lend themselves to several recommendations for highway safety treatments and design policies. For example, wide lanes and shoulders are key for reducing crash frequencies, as are longer vertical curves. KEY WORDS INTRODUCTIONRoadway safety is a major concern for the general public and public agencies. Roadway crashes claim many lives and cause substantial economic losses each year. In the U.S. traffic crashes bring about more loss of human life (as measured in human-years) than almost any other causefalling behind only cancer and heart disease (NHTSA, 2005). The situation is of particular interest on rural two-lane roadways, which experience significantly higher fatality rates than urban roads. The annual cost of traffic crashes is estimated to be $231 billion, or $820 per capita in 2000(Blincoe et al., 2000. These costs do not include the cost of delays imposed on other travelers, which also are significant, particularly when crashes occur on busy roadways. Schrank and Lomax (2002) estimate that over half of all traffic delays are due to non-recurring events, such as crashes, costing on the order of $1,000 per peak-period driver per year, particularly in urban areas. Thus, while vehicle and roadway design are improving, and growing congestion may be reducing impact speeds, crashes are becoming more critical in many ways, particularly in societies that continue to motorize. Given the importance of roadways safety, there has been considerable crash prediction research (see, e.g., Hauer, 1986Hauer, , 1997Hauer,...

An aging population is bringing new challenges to the management of escape routes and facility design in many countries. This paper investigates pedestrian movement properties of crowd with different age compositions. Three pedestrian groups are considered: young student group, old people group, and mixed group. It is found that traffic jams occur more frequently in mixed group due to the great differences of mobilities and self-adaptive abilities among pedestrians. The jams propagate backward with a velocity 0.4m/s for global density ρ_{g}≈1.75m^{-1} and 0.3m/s for ρ_{g}>2.3m^{-1}. The fundamental diagrams of the three groups are obviously different from each other and cannot be unified into one diagram by direct nondimensionalization. Unlike previous studies, three linear regimes in mixed group but only two regimes in young student group are observed in the headway-velocity relation, which is also verified in the fundamental diagram. Different ages and mobilities of pedestrians in a crowd cause the heterogeneity of system and influence the properties of pedestrian dynamics significantly. It indicates that the density is not the only factor leading to jams in pedestrian traffic. The composition of crowd has to be considered in understanding pedestrian dynamics and facility design.

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