On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

In situ soil water extraction: a review

The knowledge of the composition and fluxes of vadose zone water is essential for a wide range of scientific and practical fields, including water-use management, pesticide registration, fate of xenobiotics, monitoring of disposal from mining and industries, nutrient management of agricultural and forest ecosystems, ecology, and environmental protection. Nowadays, water and solute flow can be monitored using either in situ methods or minimally invasive geophysical measurements. In situ information, however, is necessary to interpret most geophysical data sets and to determine the chemical composition of seepage water. Therefore, we present a comprehensive review of in situ soil water extraction methods to monitor solute concentration, solute transport, and to calculate mass balances in natural soils. We distinguished six different sampling devices: porous cups, porous plates, capillary wicks, pan lysimeters, resin boxes, and lysimeters. For each of the six sampling devices we discuss the basic principles, the advantages and disadvantages, and limits of data acquisition. We also give decision guidance for the selection of the appropriate sampling system. The choice of material is addressed in terms of potential contamination, filtering, and sorption of the target substances. The information provided in this review will support scientists and professionals in optimizing their experimental set-up for meeting their specific goals.     

The contribution of ice cover to sediment resuspension in a shallow temperate lake: possible effects of climate change on internal nutrient loading

The effect of ice cover on sediment resuspension and internal total P (Tot-P) loading was studied in the northern temperate Kirkkoj?rvi basin in Finland. The gross sedimentation and resuspension rates were estimated with sediment traps during ice-cover and ice-free periods. After ice break, the average gross sedimentation rate increased from 1.4 to 30.0 g dw m(-2) d(-1). Resuspension calculations showed clearly higher values after ice break as well. Under ice cover, resuspension ranged from 50 to 78% of the gross sedimentation while during the ice-free period it constituted from 87 to 97% of the gross sedimentation. Consequently, the average resuspension rate increased from 1.0 g dw m(-2) d(-1) under ice-cover to 27.0 g dw m(-2) d(-1) after thaw, indicating the strong effect of ice cover on sediment resuspension. To estimate the potential effect of climate change on internal P loading caused by resuspension we compared the Tot-P loading calculations between the present climate and the climate with doubled atmospheric CO2 concentration relative to the present day values (ice cover reduced from current 165 to 105 d). The annual load increased from 7.4 to 9.4 g m(-2). In conclusion, the annual internal Tot-P loading caused by resuspension will increase by 28% in the Kirkkoj?rvi basin if the 2xCO2 climate scenario comes true.