Adsorption of imidazolinone herbicides on ferrihydrite-humic acid associations.

Adsorption of the imidazolinone herbicides imazapyr, imazethapyr and imazaquin was studied on two binary systems (ferrihydrite-humic acid) prepared by treating ferrihydrite (Fh) immediately after its precipitation with a soil humic acid (HA) at different loadings (4% and 8% HA content), and on a blank ferrihydrite sample prepared in the same way, but without HA addition. Imidazolinone adsorption on pure Fh and on the 4% Fh-HA decreased with increasing of the herbicide hydrophobicity (imazaquin相似文献   

Relationship between zooplankton distribution,geographic characteristics and hydrographic patterns off the Catalan coast (Western Mediterranean)

Astract Northern anchovy larvae, Engraulis mordax, were collected on five cruises covering the Southern California Bight, one cruise in April 1984, four cruises in January, February and May 1986. The amounts of triacylglycerol, cholesterol and polar lipid were measured in individual anchovy larvae as indicators of their nutritional condition. There was a significant difference in each of the size-specific lipid components between the stations for four of the five cruises. This indicates that all the ocean habitats within a cruise were not equal in promoting growth (and presumably survival) in the anchovy larvae. There were also differences between cruises, where the percentage of the larvae judged to be in poor condition varied from 8 to 27%. Canonical correlation analyses revealed a significant relationship in most cases between the larval fish parameters and the physical and biological data collected from each occupied station. Cholesterol and triacylglycerol were the most important larval components, and the short-term energy storage component in the copepod Calanus pacificus was the most important station component. The data, however, are not sufficient to identify and characterize stations in the field which produce anchovy larvae in good condition.     

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.