The diversity of a set of species refers to the joint dissimilarity of the species in the set. This paper discusses the measurement
of diversity from the set of pairwise distances between the species in the set. A measure called the effective number of species
is developed from a non-parametric probability inequality and is shown to have a simple interpretation in terms of comparing
linear experiments. 相似文献
Introduction: Studies thus far have focused on automobile accidents that involve driver distraction. However, it is hard to discern whether distraction played a role if fault designation is missing because an accident could be caused by an unexpected external event over which the driver has no control. This study seeks to determine the effect of distraction in driver-at-fault events. Method: Two generalized linear mixed models, one with at-fault safety critical events (SCE) and the other with all-cause SCEs as the outcomes, were developed to compare the odds associated with common distraction types using data from the SHRP2 naturalistic driving study. Results: Adjusting for environment and driver variation, 6 of 10 common distraction types significantly increased the risk of at-fault SCEs by 20-1330%. The three most hazardous sources of distraction were handling in-cabin objects (OR = 14.3), mobile device use (OR = 2.4), and external distraction (OR = 1.8). Mobile device use and external distraction were also among the most commonly occurring distraction types (10.1% and 11.0%, respectively). Conclusions: Focusing on at-fault events improves our understanding of the role of distraction in potentially avoidable automobile accidents. The in-cabin distraction that requires eye-hand coordination presents the most danger to drivers’ ability in maintaining fault-free, safe driving. Practical Applications: The high risk of at-fault SCEs associated with in-cabin distraction should motivate the smart design of the interior and in-vehicle information system that requires less visual attention and manual effort. 相似文献
Objective: Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs).
Methods: Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes.
Results: The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%.
Conclusions: The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The safety performance model can help better understand the causes of crash occurrences in mid-block bike lanes. 相似文献
Haze in China is primarily caused by high pollution of atmospheric fine particulates (PM2.5). However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor (PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit (R2 = 0.953). The results show that the contribution rates of ammonium sulphate, ammonium nitrate, biomass burning organic aerosol (BBOA), secondary organic aerosol (SOA) and black carbon (BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols (79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected. 相似文献
Estimation of population size has traditionally been viewed from a finite population sampling perspective. Typically, the
objective is to obtain an estimate of the total population count of individuals within some region. Often, some stratification
scheme is used to estimate counts on subregions, whereby the total count is obtained by aggregation with weights, say, proportional
to the areas of the subregions.
We offer an alternative to the finite population sampling approach for estimating population size. The method does not require
that the subregions on which counts are available form a complete partition of the region of interest. In fact, we envision
counts coming from areal units that are small relative to the entire study region and that the total area sampled is a very
small proportion of the total study area. In extrapolating to the entire region, we might benefit from assuming that there
is spatial structure to the counts. We implement this by modeling the intensity surface as a realization from a spatially
correlated random process. In the case of multiple population or species counts, we use the linear model of coregionalization
to specify a multivariate process which provides associated intensity surfaces hence association between counts within and
across areal units.
We illustrate the method of population size estimation with simulated data and with tree counts from a Southwestern pinyon-juniper
woodland data set. 相似文献