Trace elements in sediments,blue spotted tilapia Oreochromis leucostictus (Trewavas, 1933) and its parasite Contracaecum multipapillatum from Lake Naivasha,Kenya, including a comprehensive health risk analysis

This study presents the distribution of 15 major and trace elements in sediments and fish and their pericardial parasites from Lake Naivasha, Kenya. The lake is one of the few freshwater lakes in the Great Rift Valley and is under strong anthropogenic pressure mainly due to agricultural activities. Its fish provide a valuable protein source for approximately 100,000 people in the area. Fish and their parasites have been acknowledged as indicators of environmental quality due to their accumulation potential for both essential and nonessential trace elements. A total of 34 specimens of the blue spotted tilapia Oreochromis leucostictus and pooled samples of their pericardial parasite, the anisakid nematode Contracaecum multipapillatum (larvae 3), were examined. Element concentrations were determined by inductively coupled plasma-optical emission spectroscopy (ICP-OES) and graphite furnace atomic absorption spectrometry (GF-AAS). The concentrations of elements in the sediments reflected the geology of the area and did not point to pollution: none of the investigated trace elements, including Pb, Cd, Cu, and Zn, showed elevated values. In contrast, concentrations in the fish muscle were elevated for Li, Sr, Cd, and Zn, with high target hazard quotients (THQ?>?0.1) indicating a potential health risk to the consumers of this fish. Fish liver showed significantly higher concentrations of the trace elements Fe, Mn, Cd, and Cu compared to the muscle and C. multipapillatum. In the parasite, Zn had the highest concentration, but the worms only minimally accumulated trace elements in relation to their fish host.     

Crash and injury prevention estimates for intersection driver assistance systems in left turn across path/opposite direction crashes in the United States

Abstract

Objective: The objective of this research study was to estimate the number of left turn across path/opposite direction (LTAP/OD) crashes and injuries that could be prevented in the United States if vehicles were equipped with an intersection advanced driver assistance system (I-ADAS).

Methods: This study reconstructed 501 vehicle-to-vehicle LTAP/OD crashes in the United States that were investigated in the NHTSA National Motor Vehicle Crash Causation Survey (NMVCCS). The performance of 30 different I-ADAS system variations was evaluated for each crash. These variations were the combinations of 5 time-to-collision (TTC) activation thresholds, 3 latency times, and 2 different response types (automated braking and driver warning). In addition, 2 sightline assumptions were modeled for each crash: One where the turning vehicle was visible long before the intersection and one where the turning vehicle was only visible within the intersection. For resimulated crashes that were not avoided by I-ADAS, a new crash delta-V was computed for each vehicle. The probability of Abbreviated Injury Scale 2 or higher injury in any body region (Maximum Abbreviated Injury Scale [MAIS] 2+F) to each front-row occupant was computed.

Results: Depending on the system design, sightline assumption, I-ADAS variation, and fleet penetration, an I-ADAS system that automatically applies emergency braking could avoid 18–84% of all LTAP/OD crashes. Only 0–32% of all LTAP/OD crashes could have been avoided using an I-ADAS system that only warns the driver. An I-ADAS system that applies emergency braking could prevent 47–93% of front-row occupants from receiving MAIS 2?+?F injuries. A system that warns the driver in LTAP/OD crashes was able to prevent 0–37% of front-row occupants from receiving MAIS 2?+?F injuries. The effectiveness of I-ADAS in reducing crashes and number of injured persons was higher when both vehicles were equipped with I-ADAS.

Conclusions: This study presents the simulated effectiveness of a hypothetical intersection active safety system on real crashes that occurred in the United States. This work shows that there is a strong potential to reduce crashes and injuries in the United States.     

Interactions between environment, species traits, and human uses describe patterns of plant invasions

Although invasive alien species (IAS) are a major threat to biodiversity, human health, and economy, our understanding of the factors controlling their distribution and abundance is limited. Here, we determine how environmental factors, land use, life-history traits of the invaders, residence time, origin, and human usage interact to shape the spatial pattern of invasive alien plant species in South Africa. Relationships between the environmental factors and the extrinsic and intrinsic attributes of species were investigated using RLQ analysis, a multivariate method for relating a species-attribute table to an environmental table by way of a species presence/absence table. We then clustered species according to their position on the RLQ axes, and tested these groups for phylogenetic independence. The first three axes of the RLQ explained 99% of the variation and were strongly related to the species attributes. The clustering showed that, after accounting for environmental factors, the spatial pattern of IAS in South Africa was driven by human uses, life forms, and reproductive traits. The seven clusters of species strongly reflected geographical distribution, but also intrinsic species attributes and patterns of human use. Two of the clusters, centered on the genera Acacia and Opuntia, were phylogenetically non-independent. The remaining clusters comprised species of diverse taxonomic affinities, but sharing traits facilitating invasion in particular habitats. This information is useful for assessing the extent to which the potential spread of recent introductions can be predicted by considering the interaction of their biological attributes, region of origin, and human use.     

Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study

Objective: Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of driver behavior during lane change events can improve designs of this human–machine interface and increase driver acceptance of FCW. The objective of this study was to aid FCW design by characterizing driver behavior during lane change events using naturalistic driving study data.

Methods: The analysis was based on data from the 100-Car Naturalistic Driving Study, collected by the Virginia Tech Transportation Institute. The 100-Car study contains approximately 1.2 million vehicle miles of driving and 43,000 h of data collected from 108 primary drivers. In order to identify overtaking maneuvers from a large sample of driving data, an algorithm to automatically identify overtaking events was developed. The lead vehicle and minimum time to collision (TTC) at the start of lane change events was identified using radar processing techniques developed in a previous study. The lane change identification algorithm was validated against video analysis, which manually identified 1,425 lane change events from approximately 126 full trips.

Results: Forty-five drivers with valid time series data were selected from the 100-Car study. From the sample of drivers, our algorithm identified 326,238 lane change events. A total of 90,639 lane change events were found to involve a closing lead vehicle. Lane change events were evenly distributed between left side and right side lane changes. The characterization of lane change frequency and minimum TTC was divided into 10 mph speed bins for vehicle travel speeds between 10 and 90 mph. For all lane change events with a closing lead vehicle, the results showed that drivers change lanes most frequently in the 40–50 mph speed range. Minimum TTC was found to increase with travel speed. The variability in minimum TTC between drivers also increased with travel speed.

Conclusions: This study developed and validated an algorithm to detect lane change events in the 100-Car Naturalistic Driving Study and characterized lane change events in the database. The characterization of driver behavior in lane change events showed that driver lane change frequency and minimum TTC vary with travel speed. The characterization of overtaking maneuvers from this study will aid in improving the overall effectiveness of FCW systems by providing active safety system designers with further understanding of driver action in overtaking maneuvers, thereby increasing system warning accuracy, reducing erroneous warnings, and improving driver acceptance.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

Multiparametric approach for assessing environmental quality variations in West African aquatic ecosystems using the black-chinned tilapia (Sarotherodon melanotheron) as a sentinel species

The study highlights the potential of the black-chinned tilapia to be used as a sentinel to assess environmental contaminants based on the use of a set of biomarkers. The usefulness of fish species as sentinels for assessing aquatic environment contamination was tested using a set of biomarkers in Senegalese environments characterized by multi-pollution sources. The black-chinned tilapia (Sarotherodon melanotheron) was selected as a sentinel because of its abundance, wide distribution in all coastal aquatic ecosystems and physiological properties. The potential influence of confounding factors such as salinity on biomarker in the tilapia has been examined. Individuals were sampled during two seasons (dry and wet) in eight sites characterized by various degrees of anthropogenic contamination and different salinities (from 0 to 102?psu). Biomarkers??including growth rate (GR), condition factor (CF), biotransformation enzymes such as 7-ethoxyresorufin-O-deethylase (EROD) and glutathione-S-transferase (GST), lipid peroxidation (TBARS) and acetylcholinesterase (AChE)??were measured. Chemical contaminant [polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs)] levels showed different sources of contamination with relatively high concentrations of PAHs in the Hann Bay and Foundiougne locations. The most sensitive biomarker present in different sites according to the principal component analysis is EROD. Few variations of the AChE activity and TBARS levels were found. No clear relationship was found between biomarker responses and salinity, but GR and CF were lower in hypersaline conditions. Tilapia is responsive to environmental contaminants such as PAHs, OCPs and PCBs. The S. melanotheron multiparametric approach showed a better discrimination of sites.     

Migration of uranium(IV)/(VI) in the presence of humic acids in quartz sand: a laboratory column study

The migration behavior of U(IV) and U(VI) in the presence of humic acid was studied in a quartz sand system. Laboratory column experiments were performed using humic acid, U(VI) in humic acid absence, U(IV) and U(VI) in humic acid presence, and for comparison a conservative tracer. In experiments using humic acid, both redox species of U migrate nearly as fast as the conservative tracer. Humic acid accelerates the U(VI) breakthrough compared to the humic acid-free system. There are strong indications for a similar effect on the U(IV) transport. At the same time, a part of U(IV) and U(VI) associated with the humic acid is immobilized in the quartz sand due to humic colloid filtration thus producing a delaying effect. Tailing at a low concentration level was observed upon tracer elution. The experimental breakthrough curves were described by reactive transport modeling using equations for equilibrium and kinetic reactions. The present study demonstrates that humic acids can play an important role in the migration of actinides. As natural organic matter is ubiquitous in aquifer systems, the humic colloid-borne transport of actinides is of high relevance in performance assessment.     

A novel “Integrated Biomarker Response” calculation based on reference deviation concept

Multi-biomarker approaches are used to assess ecosystem health and identify impacts of environmental stress on organisms. However, exploration of large datasets by environmental managers represents a major challenge for regulatory application of this tool. Several integrative tools were developed to summarize biomarker responses. The aim of the present paper is to update calculation of the “Integrated Biological Response” (IBR) described by Beliaeff and Burgeot (Environ Toxicol Chem 21:1316–1322, 2002) to avoid weaknesses of this integrative tool. In the present paper, a novel index named “Integrated Biological Responses version 2” based on the reference deviation concept is presented. It allows a clear discrimination of sampling sites as for the IBR, but several differences are observed for contaminated sites according to up- and downregulation of biomarker responses. This novel tool could be used to integrate multi-biomarker responses not only in large-scale monitoring but also in upstream/downstream investigations.     

Seasonal dynamics of freshwater pathogens as measured by microarray at Lake Sapanca,a drinking water source in the north-eastern part of Turkey

Monitoring drinking water quality is an important public health issue. Two objectives from the 4 years, six nations, EU Project μAqua were to develop hierarchically specific probes to detect and quantify pathogens in drinking water using a PCR-free microarray platform and to design a standardised water sampling program from different sources in Europe to obtain sufficient material for downstream analysis. Our phylochip contains barcodes (probes) that specifically identify freshwater pathogens that are human health risks in a taxonomic hierarchical fashion such that if species is present, the entire taxonomic hierarchy (genus, family, order, phylum, kingdom) leading to it must also be present, which avoids false positives. Molecular tools are more rapid, accurate and reliable than traditional methods, which means faster mitigation strategies with less harm to humans and the community. We present microarray results for the presence of freshwater pathogens from a Turkish lake used drinking water and inferred cyanobacterial cell equivalents from samples concentrated from 40 into 1 L in 45 min using hollow fibre filters. In two companion studies from the same samples, cyanobacterial toxins were analysed using chemical methods and those dates with highest toxin values also had highest cell equivalents as inferred from this microarray study.