Objective: This study used medico-legal data to investigate fatal older road user (ORU, aged 65 years and older) crash circumstances and risk factors relating to 4 key components of the Safe System approach (e.g., roads and roadsides, vehicles, road users, and speeds) to identify areas of priority for targeted prevention activity.
Method: The Coroners' Court of Victoria's (CCOV) Surveillance Database was searched to identify and describe the frequency and rate per 100,000 population of fatal ORU crashes in the Australian state of Victoria for 2013–2014. Information relating to the deceased ORU, crash characteristics and circumstances, and risk factors was extracted and analyzed.
Results: One hundred and thirty-eight unintentional fatal ORU crashes were identified in the CCOV Surveillance Database. Of these fatal ORU crashes, most involved older drivers (44%), followed by older pedestrians (32%), older passengers (17%), older pedal cyclists (4%), older motorcyclists (1%), and older mobility scooter users (1%). The average annual rate of fatal ORU crashes per 100,000 population was 8.1 (95% confidence interval [CI], 6.0–10.2). In terms of the crash characteristics and circumstances, most fatal ORU crashes involved a counterpart (98%), of which the majority were passenger cars (50%) or fixed/stationary objects (25%), including trees (46%) or embankments (23%). In addition, most fatal ORU crashes occurred close to home (73%), on-road (87%), on roads that were paved (94%), on roads with light traffic volume (37%), and during low-risk conditions: between 12 p.m. and 6 p.m. (44%), on weekdays (80%), during daylight (75%), and under dry/clear conditions (81%). Road user (RU) error was identified by the police and/or the coroner for the majority of fatal crashes (55%), with a significant proportion of deceased ORUs deemed to have failed to yield (54%) or misjudged (41%).
Conclusions: RU error was the most significant factor identified in fatal ORU crashes, which suggests that there is a limited capacity of the road system to fully accommodate RU errors. Initiatives related to safer roads and roadsides, vehicles, speed zones, as well as behavioral approaches are key areas of priority for targeted activity to prevent fatal ORU crashes in the future. 相似文献
In order to improve the performance and maintain the interconnection components of the subsea pipeline ram blowout preventer system, the idea of importance analysis can be used to solve this problem. This paper uses an extended joint integrated importance measure to effectively analyze the characteristics of component failures of the blowout preventer system. The interaction between two components is considered to improve system performance while the failed component is being repaired. In order to facilitate subsequent maintenance and repair work, the effects of changes in different parameters on the importance value are considered. Finally, the analysis of a numerical example of the submarine pipeline ram blowout preventer system is carried out to verify the proposed method. 相似文献
Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km2, which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models. 相似文献
Metal ions generally share the ability/tendency of interacting with biological material by forming complexes, except possibly for the heavy alkali metals K, Rb and Cs. This is unrelated to the metals being either essential for sustaining life and its reproduction, apparently insignificant for biology, although perhaps undergoing bioconcentration or even being outright toxic, even at low admission levels. Yet, those different kinds of metal-biomass interactions should in some way depend on properties describing coordination chemistries of these very metals. Nevertheless, both ubiquitously essential metals and others sometimes used in biology should share these properties in numeric terms, since it can be anticipated that they will be distinguished from nonessential and/or toxic ones. These features noted above include bioconcentration, the involvement of metal ions such as Zn, Mg, Cu, Fe, etc. in biocatalysis as crucial components of metalloenzymes and the introduction of a certain set of essential metals common to (almost) all living beings (K, Mg, Mo, Mn, Fe, Cu and Zn), which occurred probably very early in biological evolution by ‘natural selection of the chemical elements’ (more exactly speaking, of the metallomes).
Materials and Methods
The approach is semiempirical and consists of three consecutive steps: 1) derivation of a regression equation which links complex stability data of different complexes containing the same metal ion to electrochemical data pertinent to the (replaced) ligands, thus describing properties of metal ions in complexes, 2) a graphical representation of the properties-two typical numbers c and x for each metal ion-in some map across the c/x-space, which additionally contains information about biological functions of these metal ions, i.e. whether they are essential in general (e.g. Mg, Mn, Zn) or, for a few organisms of various kinds (e.g. Cd, V), not essential (e.g. rare earth element ions) or even generally highly toxic (Hg, U). It is hypothesized that, if coordination properties of metals control their biological ‘feasibility’ in some way, this should show up in the mappings (one each for mono and bidentate-bonding ligands). 3) eventually, the regression equation produced in step 1) is inverted to calculate complex stabilities pertinent to biological systems: 3a) complex stabilities are mapped for ligands delivered to soil (-water) by green plants (e.g. citrate, malate) and fungi and, compared to their unlike selectivities and demands of metal use (photosynthesis taking place or not), 3b) the evolution of the metallome during late chemical evolution is reconstructed.
Results
These maps show some ‘window of essentiality’, a small, contrived range/area of c and x parameters in which essential metal ions gather almost exclusively. c and x thus control the possibility of a metal ion becoming essential by their influencing details of metal-substrate or (in cases of catalytic activities) metal-product interactions. Exceptions are not known to be involved in biocatalysis anyhow.
Discussion
Effects of ligands secreted, e.g. from tree roots or agaric mycelia to the soil on the respective modes (selectivities) of metal bioconcentration can be calculated by the equation giving complex stability constants, with obvious ramifications for a thorough, systematic interpretation of biomonitoring data. Eventually, alterations of C, N and P-compounds during chemical evolution are investigated — which converted CH4 or CO2, N2 and other non-ligands to amino acids, etc., for example, with the latter behaving as efficient chelating ligands: Did they cause metal ions to accumulate in what was going to become biological matter and was there a selectivity, a positive bias in favour of nowessential metals (see above) in this process? Though there was no complete selectivity of this kind, neither a RNA world in which early ribozymes effected most of biocatalysis, nor a paleoatmosphere containing substantial amounts of CO could have paved the way to the present biochemistry and metallomes.
Conclusions
This way of reasoning provides a causal account for abundance distributions described earlier in the Biological System of Elements (BSE; Markert 1994, Fränzle &; Markert 2000, 2002). There is a pronounced change from chemical evolution, where but few transformations depended on metal ion catalysis to biology.
Recommendations and Perspectives
The application of this numerical approach can be used for modified, weighted evaluation of biomonitoring analytical data, likewise for the prediction of bioconcentration hazards due to a manifold of metal ions, including organometallic ones. This is relevant in ecotoxicology and biomonitoring. In combining apoproteins or peptides synthesized from scratch for purposes of catalysing certain transformations, the map and numerical approaches might prove useful for the selection of central ions which are even more efficient than the ‘natural’ ones, like for Co2+ in many Zn enzymes.